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Motivated by the ongoing development of Turbine Based Combined Cyclesystems, special interest was given to the low-speed characteristics of a vehicle designedfor hypersonic operation. More specifically, the subsonic performance of the low-speedinlet for a TBCC vehicle was the primary focus of this study due to its integral role intake-off and landing operation. A wind tunnel model of a hypersonic scramjet inletpreviously tested at hypersonic speeds was characterized for low-speed operation in asubsonic 3’x5’ wind tunnel. This model contained a variable thrust simulator powered byhigh pressure air and was tested over a range of 0-20-degrees angle of attack at twoReynolds numbers, 250k and 500k. Static pressure data was collected along the model’scenterline.The resulting data set was used to assess the validity of a computational fluiddynamic model within ANSYS Fluent setup to match wind tunnel conditions. The modelwas not able to accurately predict the experimental results due to oversimplifications andassumptions made. Despite this shortcoming, the model was still used to analyze theperformance of an inlet optimized for Mach 4 that was integrated into the existinggeometry of the wind tunnel model. This analysis emphasized the importance of subsonicinlet design and provides the framework for future development and design iteration.

The high-speed flight environment entails a wide array of physical phenomena including compressible turbulence, shock-wave boundary layer interactions, and intense aero-thermodynamics. A fundamental understanding of the physics governing these phenomena is of prime relevance to the airframe design, surface material selection, and aerodynamic performance of hypersonic flight vehicles. As such, benchmark datasets which allow for global field analyses of the dynamics of hypersonic turbulence are the subject of a multitude of recent academic studies. The present work leverages modern computational hardware to perform massive-scale direct numerical simulations (DNS) of spatially evolving turbulent boundary layers. The computational approach taken in this work helps to overcome some of the challenges that are faced when experimentally investigating high-speed turbulent boundary layers such as insufficient near-wall resolution, freestream acoustic perturbations, and repeatability. Reynolds-Averaged Navier-Stokes (RANS) simulations are also leveraged to assess the typical assumptions made when developing compressible turbulence models. Modern turbulence models for compressible boundary layers are largely based upon extensions of incompressible models and thus do not uniquely consider the intrinsic hypersonic phenomena outlined above. This discrepancy leads to inaccurate predictions of vital design quantities and overly conservative vehicle designs. Due to its relative affordability, RANS is likely to remain the preferred design tool in real-world applications. It is therefore essential to analyze the predictions made by commonly used RANS models and compare them with high-fidelity data. This manuscript presents two DNS datasets of a Mach 4.9 turbulent boundary layer under cold-wall conditions (T_w/T_r = 0.60). In the first simulation, the zero-pressure-gradient (ZPG) turbulent boundary layer is spatially developed to a friction Reynolds number Re_ ~ 2500, which is the highest Reynolds number achieved via DNS for hypersonic turbulent boundary layers among recent literature. Numerous Reynolds number effects are noted for this simulation, including a modulating effect on the near-wall turbulence from the outer-region eddies and dynamical changes in the turbulent transport budgets.The second simulation subjects the fully-turbulent boundary layer (at Re_ ~ 1135) to a smoothly-varying, forward-facing wall (FFW) curvature, inducing a shock-wave turbulent boundary layer interaction (STBLI) and drastically strengthened bulk dilation. The cold-wall condition gives way to an attached boundary layer throughout the entire interaction, contrary to the report of Nicholson et al., whose quasi-adiabatic simulations of the same wall shape display a large separation bubble. Effects of the cold-wall condition are noted in the Reynolds stress tensor, turbulent kinetic energy budget, and turbulent heat flux budget. A discussion on the flow organization unveils the existence of alternating spanwise periodic regions of velocity and temperature fluctuations, hinting at the existence of Görtler-like structures in the curvature region. In both the ZPG and FFW simulations, corresponding RANS simulations are presented to outline any relevant modeling discrepancies. In particular, the FFW RANS simulations show that, depending on the turbulence model used, the predictions of bulk flow physics and surface quantities are highly variable. The ZPG RANS simulations show a similar level of discrepancy, especially in the lower Reynolds number regime.

In this dissertation, a series of experiments were carried out to investigate the auto-ignition process of transient fuel jets and sprays issuing into high-temperature, environments. Novel high-speed imaging and laser diagnostic techniques were developed and applied to characterize mixing and turbulent flow conditions prior to and at the onset of ignition. In addition, this research examines the topology and dynamics of ignition kernels as they grow and transition into a stable flame. Research was carried out primarily in canonical atmospheric pressure experiments, but a new high-pressure spray test facility is developed in this work with preliminary measurements presented, demonstrating new experimental capabilities. Specific contributions of this dissertation include: (1) characterization of the transient mixing processes of variable-density atmospheric pressure jets both before and after ignition, (2) determination of the most probable mixing and turbulent flow conditions leading to local auto-ignition, (3) statistical evaluation of the dynamic growth and transport of ignition kernels, (4) construction and characterization of a novel high-pressure, high temperature spray and combustion facility, and (5) demonstration of high-speed mixture fraction measurements in non-reacting and reacting sprays at realistic thermodynamic conditions. First, a series of transient gas-phase fuel jets issuing into a high-temperature, vitiated environment at atmospheric pressure was investigated. A well-known jet-into-hot coflow configuration was utilized with the addition of a fast-acting solenoid valves to achieve pulsed fuel injection in an environment with well-defined boundary conditions. Four test conditions were studied to examine the effects of variations in jet Reynolds number, the fuel mixture composition, and coflow temperature. High-speed laser Rayleigh scattering (LRS) was performed at 10 kHz to measure the mixture fraction and temperature fields from fuel injection to auto-ignition. The measurements were facilitated by the high-energy pulse burst laser system (HEPBLS) at OSU which outputted pulse energies > 900 mJ for burst durations ranging from 8-11 ms. The high signal yield and advanced image processing and de-noising techniques yielded results with signal-to-noise ratios (SNR) greater than 200 and spatial resolution sufficient to measure the smallest turbulence spatial scales. Subsequently, highly accurate mixture fraction gradients and scalar dissipation rates are determined in the variable-density, transient jets. High-speed multi-view OH* chemiluminescence (CL) imaging was performed simultaneously to identify the first ignition kernels spatially and temporally and deduce global ignition statistics. Ignition kernels also were determined from the temperature measurements by locating appropriate temperature rises in the LRS images. Finally, simultaneous high-speed particle image velocimetry (PIV) and OH* CL were performed at 20 kHz to determine the most probable turbulent flow conditions leading to auto-ignition. The most probable mixture fraction values at the initial ignition sites were determined for all cases. Probability density functions (PDFs) showed that ignition occurred over a broad range of mixture fraction values, but kernels preferentially form in lean regions in the jet periphery. The mean value of the mixture fraction at ignition, 〈 ξig 〉, for each case closely matches the most reactive mixture fraction (ξMR), which is calculated using a homogeneous reactor as prescribed within the literature. However, the PDF does appear to follow an exponential decay, with a non-negligible number of ignition kernels forming in rich regions. Joint statistics between the mixture fraction and scalar dissipation rate show the tendency for ignition kernels to form in both lean and low scalar dissipation rate regions. These quantitative results corroborate previous qualitative observations from direct numerical simulations (DNS) and experiments. The PIV/OH* results showed that ignition kernels tend to form in regions of low vorticity and strain rate. PDFs of vorticity and strain rate conditioned on ignition kernel location showed a narrowing of the PDF and decrease in the PDF tails (high magnitude vorticity and strain rate), indicating a general trend that the vorticity and strain rate are more likely to decrease at ignition locations compared to non-igniting fluid.A comprehensive characterization of the scalar mixing process was performed within the transient, variable-density jets prior to ignition. The ensemble mean and RMS mixture fraction profiles showed that the jet reaches steady state prior to ignition for the low-temperature coflows, but not necessarily for the high temperature condition. Overall the process can be described as a starting vortex and subsequent shedding, followed by jet contraction and fluid entrainment, and finally reaching a steady state (for lower-temperature conditions) before igniting. Probability density functions of the mixture fraction and scalar dissipation, as well as the mean scalar dissipation rate conditioned on mixture fraction converge to common, single-mode distributions prior to ignition. The mixture fraction and scalar dissipation rate was examined in two separate regions within the jet - the so-called "inner" and "outer" shear layers of the jet. For regions closer to centerline (inner shear layer; 〈 ξ 〉 < 0.5), the scalar dissipation rate PDFs are more symmetric when compared to the PDFs of the scalar dissipation rate in the outer shear layer (0.05 < 〈 ξ 〉 < 0.5), which show clear asymmetry (negative skewness) for low values of χ. Ignition kernel topology and dynamics were tracked from the first ignition kernel through flame stabilization using the high-speed OH* imaging. Kernel areas, growth rates, aspect ratios (defined as the kernel width over the kernel height), sphericity (defined as the ratio of kernel surface area over the squared perimeter), and the convective displacement velocity and angle (measured using the displacement of the kernel centroids) were determined as a function of time. The results showed that the ambient (coflow) temperature has the strongest influence over kernel dynamics, including overall growth rate and stretching. In general ignition kernels tend to stretch in the primary flow direction and move downstream with minimal lateral movement. Under auto-igniting cases, stable flame bases are formed by the merging of multiple expanding kernels.This research also describes the fabrication and testing of a novel optically accessible high-pressure, high-temperature spray and combustion facility (HPTF) for studying the auto-ignition of vaporizing liquid fuels at relevant thermodynamic engine conditions. Facility boundary conditions including the ambient temperature uniformity and fuel injector tip temperature were well characterized and meet the necessary criteria for providing benchmark data to the spray community. The HPTF can operate over a range of oxidizing conditions, consisting of quasi-inert or non-reacting (5% O2) to 21% O2. Initial studies considered n-dodecane (nC12H26) sprays as it is a single-component diesel surrogate and matches the well-known “Spray A” conditions described within the Engine Combustion Network (ECN). In the current dissertation, preliminary measurements are performed under non-reacting conditions with an ambient temperature of 900 K and reacting conditions, where the ambient oxygen content varies from 13 to 15% O2, and ambient temperatures range from 800 to 900 K. Measurement approaches consist of schlieren visualization, diffuse background extinction imaging (DBI), laser Rayleigh scattering, and OH* chemiluminescence. All imaging approaches are performed at a 100-kHz acquisition rate. Schlieren and DBI are used to characterize the liquid length and overall spray/ignition dynamics; OH* CL is used to characterize the ignition delay (ID) times and flame lift-off lengths (FLOL); and LRS is used to simultaneously measure mixture fraction and temperature in the gas-phase regions downstream of the spray. Liquid lengths, and mixture fraction profiles match existing results within the literature in the non-reacting sprays and ignition delay times and flame lift-off lengths match existing results in reacting sprays. The agreement with previous facilities experimental and computational results yield confidence in the boundary conditions, repeatability, and reliability of the HPTF. Finally, preliminary high-speed LRS (mixture fraction) measurements are presented in reacting sprays for the first time.

Temporal and spatial distributions of the electric field in an atmospheric pressure, ns pulse, positive and negative polarity helium plasma jets are measured by ps Electric Field Induced Second Harmonic (EFISH) generation. The measurements have been done in a quasi-two-dimensional plasma jet impinging on liquid water, using a laser sheet and a focused laser beam positioned at different heights above the water surface. Absolute calibration of the electric field is obtained by measuring a known Laplacian electric field distribution for the same geometry and at the same flow conditions. The vertical component of the electric field is determined by isolating the second harmonic signal with the vertical polarization. The measured electric field is averaged over the span of the plasma jet, in the direction of the laser sheet or the focused laser beam. The spatial resolution of the laser sheet measurements is approximately 15 μm across the sheet, with the temporal resolution of 10 ns. The spatial resolution of the focused laser beam measurements is approximately 180 úm across the beam, with the temporal resolution of 2.5 ns. The results show non-monotonous electric field distribution across the jet, with two maxima produced by the surface ionization waves propagating over water. Considerable electric field enhancement is detected near the surface. Residual charge accumulation on the water surface is detected only in the negative polarity pulse discharge. The results provide new insight into the charge species kinetics and transport in atmospheric pressure plasma jets, and produce data for detailed validation of high-fidelity kinetic models.Ionization wave development during ns pulse breakdown in nitrogen between two parallel plate, dielectric-covered electrodes is studied by ps Electric Field Induced Second Harmonic (EFISH) generation and kinetic modeling. The results indicate formation of two well-defined ionization waves in the discharge gap, which requires a relatively high initial electron density. The first, anode-directed, wave is produced by “sweeping” the initial electrons by the applied voltage pulse. The second wave originates between the cathode and the first wave front, due to the field enhancement in this region, generating two wave fronts propagating in opposite directions and observed in plasma emission images. Only the anode-directed front of the second wave is detected by the EFISH measurements, most likely due to the proximity of the cathode-directed front to the wall. Both the measurements and the modeling predictions exhibit a transient electric field overshoot in the center of the gap, caused by the anode-directed front of the second wave. The boundary between the plasma domains formed ahead of the first wave and behind the second wave, observed in the plasma emission images, is detected by the EFISH measurements and predicted by the modeling calculations. The electron density and coupled energy distributions predicted by the model at the end of the discharge pulse are nearly uniform, except near the cathode-adjacent wall, where the applicability of the present model is uncertain and which is not accessible to the EFISH measurements. Vibrational kinetics of O2 is studied during the O atom recombination in an O2-Ar mixture partially dissociated by a burst of ns discharge pulses in a flow reactor, at T=400-800 K. Time-resolved vibrational level populations of molecular oxygen in the ground electronic state, O2(B3Σu-, v' = 8-20), are measured by ps Laser Induced Fluorescence (LIF) on the O2 Schumann-Runge bands, with absolute calibration by NO LIF in a NO-N2-O2-Ar mixture with a known composition. The O atom number density in the same mixture is measured by ps Two-Photon absorption LIF (TALIF), calibrated in xenon. The time-resolved ozone number density is monitored by UV absorption. The ozone number density remains nearly constant after the plasma excitation, indicating that the effect of photolytic dissociation of ozone by the pump laser pulse is negligible. The discharge generates a diffuse volumetric plasma, without well-pronounced filaments. The time-resolved temperature in the plasma is measured by Rayleigh scattering. The experimental results are compared with the predictions of a state-specific kinetic model incorporating the dominant energy transfer processes and chemical reactions in a nonequilibrium O2-O-O3-Ar plasma, including electron impact ionization, dissociation, and electronic excitation; quenching of electronically excited species; vibration-translation (V-T) relaxation and vibration-vibration (V-V) energy transfer; and chemical reactions. The rates of V-T relaxation and dissociation / recombination in O2-O collisions are predicted by the previously published quasiclassical trajectory calculations. The rates of O2-O2 V-V relaxation are based on the experimental data from the literature. The state-specific rates of O + O3 reaction producing two vibrationally excited O2 molecules are predicted based on the modified Treanor-Marrone model. The experimental results indicate a rapid initial decay of O3(v=8-20) populations generated by electron impact in the discharge, on a ∼ 10 μm time scale, primarily due to V-T relaxation. This decay is followed by a much slower decay, on the time scale longer compared to the characteristic time for V-T relaxation and V-V energy exchange, up to several ms. Both O atoms and the O2(v) populations decay on the same time scale, indicating that chemical reactions initiated by the O atom recombination result in the generation of vibrationally excited O2 molecules. These trends are reproduced by the kinetic model, which shows that the reaction of O atoms with ozone is the dominant pathway of O2(v) generation, even at elevated temperatures. Although the predicted relative O2(v) populations are close to the experimental results, their absolute number densities differ from the experimental data. This is likely due to uncertainties in the absolute calibration of LIF measurements and in the spectroscopic model used in the data reduction. The present work demonstrates the capability for the absolute, time-resolved measurements of vibrationally excited O2 during the recombination of O atoms, to quantify the effect of the recombination reaction on the surface heat flux in high-temperature chemically reacting boundary layer flows.

A major challenge in the development of high-speed flight vehicles is understanding, managing, and controlling the impact of an extreme operating environment. Fluid-structural interactions (FSI) are an important and challenging concern due to need for optimal weight and multi-functional structures, juxtaposed with the possibility of catastrophic failure and degradation of vehicle performance.Conditions where strong coupling arises between compliant structures and multi-scale fluid dynamic features characteristic to the flight environment, such as turbulence, shock motions, and flow separation, are not sufficiently understood.This challenges \emph{a priori} model fidelity selection for accurate and efficient prediction of FSI, directly impacting development of high-speed vehicles.This dissertation seeks to address these open questions through studying the interaction between a high-speed, separating turbulent flow field and a compliant cantilever plate.The main features of the flow are separation at the end of the plate and reattachment on the downstream floor, which are modulated by shear layer instabilities and interaction with the cavity underneath the plate.Wall-resolved large eddy simulations (LES) are applied to capture interaction with the multi-scale flow field.Companions predictions are also made with unsteady Reynolds-averaged Navier-Stokes (URANS) and local piston theory (LPT) in order to contextualize the significance of interaction with the inherent flow unsteadiness.The interaction with the flow field is first examined through prescribed oscillations of the cantilever.The flow response to varying amplitude motions in the first bending mode as well as combined bending-torsional motion is explored.Here, the oscillation frequency is set to align with the characteristic low-frequency unsteadiness in the underside recirculation region.Then, the potential for energy transfer between high-frequency structural modes to the shear layer is explored through low-amplitude oscillation at a frequency on the order of the shear layer scales.A key finding from this initial investigation is the reasonable prediction of generalized aerodynamic forces by low-fidelity fluid models relative to LES, indicating their potential suitability for broader study of the aeroelastic behavior of the cantilever.Coupled interactions with the flow field are then studied by first leveraging the reduced computational cost of URANS and LPT.Due to the open cavity underneath the plate, a large-amplitude static aeroelastic response arises as the nondimensional dynamic pressure increases, which is readily predicted by LPT.Structural-induced cavity pressure fluctuations are found to have an important effect on dynamic aeroelastic behavior of the cantilever.Additionally, shock-induced flow separation arises on the top surface of the cantilever due to interaction with the off-body flow field, which gives rise to the post-flutter limit cycle oscillation (LCO) rather than nonlinearity in the structure.Notably, both of these coupling mechanisms are not readily captured within the framework of LPT, indicating its unreliability for prediction of dynamic aeroelastic behavior of the cantilever.Finally, the role of the inherent turbulence within the coupled interaction is explored by applying LES. Notably, an amplified response, modal coalescence, and shock-induced flow separation arise for a condition beyond the URANS-predicted flutter bifurcation point.The importance of capturing dynamic feedback between the turbulence and structural compliance is evaluated through response prediction comparisons with URANS.Here, the URANS wall pressure prediction is superimposed with an LES-informed turbulent load extracted from static states of the cantilever.The overall aeroelastic behavior of the cantilever is predicted reasonably well by URANS in conjunction with an LES-informed turbulent load.However, error is still present in the URANS response prediction relative to LES, which may be due to the neglect of dynamic feedback with the turbulence.

Fluid-Structure Interactions (FSI) are a quintessential multi-disciplinary challenge, where the flowfield is influenced by the structure, and structural deformation is induced by the flow pressure. Computational and experimental research thrusts often seek to answer specific problems for specific configurations, offering observational answers to relatively complex problems. While there is a large body of work on FSI as a whole, the specific coupling mechanisms between the fluid and structural surface in the context of turbulent boundary layers (TBLs) in supersonic flows is an under-explored area of study.This dissertation details progress addressing this gap through cooperative consideration of high-fidelity simulations, classical semi-empirical models, analysis of the governing equations, and data-driven models. Large-Eddy Simulations (LES) of TBLs with static deformations are compared against classical semi-empirical models to characterize applicability to statically deformed surfaces for predicting loads transmitted from the boundary layer to the structure. Additionally, analysis of the governing equations, in conjunction with data-driven modeling, is used to extract a coherent link between structural deformation and the onset of local flow separations. Finally, a parametric study is carried out using Reynolds-Average Navier-Stokes (RANS) and Kriging surrogates to assess the impact of statically deformed surfaces on a downstream ramp.LES indicates that for a variety of deformations sized on the order of the incoming boundary layer, localized flow separation can develop. This leads to important flow modifications that are not readily captured with low-fidelity or semi-empirical models. Motivated by this, a first-order link between local flow separation and structural deformation parameters is established using the Momentum Integral Equation (MIE) combined with data-driven analysis. The curvature of the surface is identified as the dominant structural parameter impacting local skin friction and driving local flow separation. Finally, a parametric analysis using combined RANS and Kriging surrogate models identifies 3 primary characteristics for the impact of deformation on the flow response on a downstream flare: deformation-induced compression and expansion waves, deformation augmented boundary layer stabilization/destabilization, and the direct interaction of deformation with separation corner behavior. Compression and expansion wave propagation from deformed surfaces causes notable reductions in the peak loading in both pressure and heat flux. However, the boundary layer downstream separation tendency and separation characteristics are impacted differently by the type of deformation introduced, and its location relative to the corner.

Understanding thermal performance is essential to optimizing system performance, reducing damage, and enhancing overall reliability and safety, especially in high-powered heat generatingapplications. In the growing eVTOL (electric Vertical Take-Off and Landing) ecosystem, being able to provide a means to quantify and characterize the thermal performance of new propulsion platforms has resorted to complex, numerical solutions via commercial software. One reason for this is how thermal performance is affected by a phenomenon called thermal soak. Thermal soak is the sudden increase of internal component temperature due to terminating any forcedconvective cooling from a heat-producing system (i.e., landing and shutting down after hovering.) A more accessible thermal soak model was developed and explored with the aim of better understanding heat transfer properties of electric/hybrid motors under VTOL power conditions. The purpose of this thesis is to discover if thermal soak as a lumped parameter 2ndorder system can be reliably modeled with defined damping ratios, natural frequencies, and initial conditions that are functions of system thermal parameters. Comparisons between the thermal soak model and experimental data from a multitude of eVTOL motor and propeller configurations at different power and ambient conditions exhibit this. The importance of this model lies in its predictive capability for evaluating thermal soak effects on mechanical components, especially in the initial stages of design or for developing generalized rules-of-thumb for new thermal systems. This contributes to the framework of an eHETR (eVTOL Hybrid Electro-Thermal Rotorcraft) model capable of simulating high-power (>100kW) electric/hybrid rotary-wing propulsion systems and the heat generation experienced duringrotorcraft flight.

This study underlines the impact of the flow structures on the internal flow field through shape-transitioning ducts with global favorable pressure gradients and local adverse pressure gradients, local to the shape-transitioning geometries. Results are evaluated for convergence apropos of acquisition frequency. This thesis presents preliminary results of flow structure measurement by introducing the structures with a cylindrical bluff body in the cross flow. Structure transport through the two duct configurations studied includes the free jet of a convergent nozzle and through a shape-transitioning nozzle. Particle Image Velocimetry (PIV) was employed in data acquisition considering its substantial spatiotemporal resolution necessary. Findings show that the free jet results are characterized by high-velocity jets, detached velocity deficit region at the tailing edge of the cylinder, and strong velocity gradients due to the shear layers formed between the wake, the jets, and the ambient. On the contrary, flow through the shape transitioning or favorable pressure gradient (FPG) nozzle reflects a well-behaved flow with a low-velocity region attached to the cylinder in most cases. The outcome difference primarily stems from the velocity experienced at the cylinder in each case. An examination of convergence, considering the acquiring frequency of the flow field data, unveiled a weighty impact of acquisition frequency on the results of turbulent flow fields. The ensemble average of the results based on the mathematical computation using analytical methods in the time domain revealed an overall comparable trend in results with notable distinctions in the near wake region. Convergence dependence of results on flow essence emerged with a comparison of the running averages at a point within and outside the wake. In conclusion, it was established that a smaller subset of image pairs drawn from a universal set is ample for effectively capturing the physics of the flow field in PIV. The presented results demonstrate the preliminary measurements of the transport of flow structures within ducts with a global favorable pressure gradient, conjoined with localized adverse pressure gradients resulting from shape transitions. These studies shed light on their influence on the flow field dynamics and overall component performance. Additionally, the study delves into the influence of acquisition frequency on the result convergence.Finally, a Flow Conditioning System (FCS) was designed and fabricated to enhance the flow quality through the flow rig, which was initially characterized by significant velocity fluctuations and unsteadiness. Furthermore, a Secondary Flow System (SFS) was developed to introduce these flow structures through ducts as a coaxial flow system with a nozzle head versatile to accommodate flow structure generators.

Thrust vectoring (TV) is the ability to manipulate the directivity of the primary jet to provide a cross-stream force off the primary jet axis. TV can enable desirable flight regimes such as hyper-maneuverability and short/vertical take-off and landing. Modern conventional TV methods utilize a physical mechanism to mechanically deflect the jet flow and change the thrust direction. This method is both heavy and mechanically complex, especially for an axisymmetric jet. A novel approach to TV is explored in this paper by investigating localized arc filament plasma actuators’ (LAFPAs) ability to impart a TV force on a subsonic, axisymmetric jet by attaching the flow to a radially expanding surface (termed “reaction surface”), at the jet exit. LAFPAs will be used to asymmetrically control the entrainment of the jet to provide a deflection of the jet via the conservation of momentum. The deflected jet will then attach to the reaction surface via the Coanda effect. The jet flow was interrogated at baseline and excited cases with a static pressure array located 0.75 jet diameters downstream of the actuators at 70% of the chord of the reaction surface and with cross-stream particle image velocimetry (PIV) located 3 jet diameters downstream of the actuators. Two jet Mach (Mj) values were assessed, Mj = 0.48 and 0.9. The results show that the LAFPAs create a repeatable and significant asymmetric pressure profile trend with respect to excitation frequency. In general, low excitation frequencies provide an asymmetric azimuthal pressure profile that corresponds to a vectored thrust force towards the active actuators, while high excitation frequencies provide an asymmetric azimuthal pressure profile that corresponds to a vectored thrust force away from the active actuators. Cross-stream PIV flow field measurements show that the asymmetry in the azimuthal pressure profile is not as significant as would be desirable for thrust-vectoring applications. However, the PIV results do show the LAFPAs have a strong effect on the azimuthal entrainment of the jet and the directivity, albeit low in magnitude, of the cross-stream velocity, aligning with the results from static pressure measurements.

As manufacturing techniques such as topology optimization and additive manufacturing develop, components with increasing geometric complexity are becoming more common. Thus, it is necessary to develop automated non-destructive evaluation techniques that are adaptable to various surface geometries. This project seeks to leverage robotic simulation software to virtually plan and optimize eddy current inspections of various airplane components to detect flaws while eliminating false positives. The final deliverable will be a Robot Operating System (ROS) software package that generates an optimal tool path plan based on probe output for various scan resolutions.

The role of quartz in gas turbine hot section deposition was investigated by varying both its size and percent concentration in Air Force Research Lab test dust (AFRL-02). The size distributions of quartz tested were 0 – 3 μm, 0 – 10 μm (baseline), and 10 – 20 μm while percent concentration ranged from 0% to 100%. The experiments replicated a gas turbine effusion cooling circuit with a flow temperature of 894K and plate surface temperature of 1144K. Aerosolized AFRL-02 dust was delivered to the test article, and capture efficiency, hole capture efficiency, blockage per gram, normalized deposit height, and effective area were recorded. A quartz size distribution of 0 – 3 μm showed the greatest deposition while 10 – 20 μm consistently deposited the least. Varying percent concentration of quartz had less obvious trends. While at a size distribution of 10 – 20 μm, increasing quartz concentration decreased deposition in all four assessment parameters. For a size distribution of 0 – 3 μm, increasing quartz concentration originally decreased deposition until greatly increasing it past a concentration of 68%. Quartz has been identified as a predominantly erosive mineral to deposits, but results suggest the size distribution contributes to deposition at a rate greater than or equal to percent concentration. The following study elucidates the effects of both size and concentration of quartz in a heterogenous mineral blend.

Various trailing-edge (TE) Coanda active flow control (AFC) actuator configurations were experimentally investigated in a propeller slipstream flow to simulate hover flight. This thesis will provide a comprehensive evaluation of the configuration factors—in terms of spanwise position and geometric parameters—which impact the aerodynamic and control authority performance of TE Coanda AFC actuators in propeller-driven flow with no freestream velocity.Two main types of TE Coanda AFC configuration experiments were conducted. The first type of testing involved varying the spanwise placement and size of TE AFC while maintaining constant internal geometry and circular Coanda profile shape with continuous slot blowing. The spanwise location testing's objectives were to determine the optimal Coanda AFC actuator location relative to the propeller slipstream and compare Coanda flow control effectiveness to that of a traditional deflection control surface. Two trailing-edge Coanda actuator sections of fixed spanwise length were designed, fabricated, and evaluated in terms of lift force and pitching moment generation at varying spanwise locations. Velocity profile measurements for this study for the case of no freestream flow indicated that the propeller slipstream is asymmetric over the NACA 0012 wing and contracts toward the side of the wing on which the propeller blade descends during rotation, where propeller downwash is experienced. This asymmetry indicated that there may be an optimum location for Coanda AFC actuators at the wing trailing edge which couple with momentum from the propeller in regions of peak slipstream velocity.The second type of testing involved varying TE AFC nozzle and surface profiles while maintaining constant spanwise location. These nozzles included both continuous and discrete slot blowing as well as sweeping jets. Surfaces investigated included circular, elliptical, and biconvex profiles. Each configuration was mounted to the trailing edge of a wing on a benchtop setup. A propeller at the leading edge provided a momentum source, and the lift and pitching moment were measured with a six-component load cell. The resulting load data was used to characterize the aerodynamic performance and control authority of each Coanda AFC configuration tested to determine which parameters—such as spanwise placement, Coanda AFC profile shape, slot size and spacing, and discrete vs. continuous slots—yield optimal performance for trailing-edge AFC. The efficiency of the actuators was evaluated using a modified form of momentum coefficient for the hover flight condition.

Uncrewed aerial vehicles (UAVs) have seen an explosion in development over the last decade. Advances in computing and communication technologies have allowed for rapid innovation in remote and autonomous flight controls, leading to development of new aerospace platforms. Without humans on board, vehicles have restrictions removed that can lead to unique configurations; for example, UAVs can be much smaller and more maneuverable than other platforms. An uncrewed platform is not limited by the maximum G-force its pilot can sustain. Relatively low costs further provide opportunities for innovation in UAV design. Thanks to reduced costs per vehicle and autonomous control systems, UAVs could operate with smaller error margins near the regimes of failure. Swept wings are selected in aircraft design for their aerodynamic performance at high Mach number. By reducing the component of freestream velocity incident on the wing in the direction normal to the leading edge, wing sweep increases the critical Mach number where a marked increase in drag is observed. While wing sweep is desirable for flight at high Mach numbers, a swept wing geometry can pose aerodynamic challenges in low speed, high angle of attack flight. The swept geometry develops a spanwise pressure gradient that is not observed on straight wings. The resulting spanwise flow develops a natural boundary layer separation control that is most effective the wing root. As a swept wing’s angle of attack is increased, flow will initially separate near the wingtip and trailing edge. As the angle of attack continues to increase, separation will propagate toward the wing root and leading edge. Taking advantage of these fluid mechanics, a flow control system that interrupts spanwise flow over a swept wing’s suction surface can improve aerodynamic performance at high angles of attack. Because the interruption is not needed for high-speed flight, an active flow control method is desirable. The unsteady aerodynamic effects of pitching and flow control activation are investigated for separating flows over 30ׄ° swept wings of NACA 643-618 airfoil. The wings are not tapered and have cutoff wingtip geometries. The freestream Reynolds and Mach numbers are 105 and 0.05, respectively. Investigations are carried out in wind tunnel experiments and unsteady computational simulations. Conditions varied include the wing’s aspect ratio and angle of attack and the active flow control system’s input level. The unsteady aerodynamics are found to depend heavily on the state of flow separation over the uncontrolled wing in steady flow for a given angle of attack. When the angle of attack is held constant and the flow control is suddenly activated, the time response of aerodynamic loads is significantly faster for cases of trailing-edge separation than for cases of leading-edge separation. The degree of flow control, characterized by the momentum coefficient, is found to strongly influence the magnitude of changes in aerodynamic loads, but not the time required for these changes to take effect. Varying the wings’ aspect ratios reveals evidence that the characteristic time for flow control activation that interrupts spanwise flow is based on the wingspan dimension.

An experimental investigation into the wave sources responsible for the noise generation mechanisms of supersonic jet noise and their mitigation using MVG nozzles is presented. Flow field measurements using PIV revealed that MVGs mitigate noise through two mechanisms; they generate internal oblique shock waves that weakens the shock cell, and they substantially increase the shear layer mixing and its entrainment of ambient fluid which reduces the length scales and velocities of the convecting coherent structures. In addition, time-resolved Schlieren visualizations were spectrally analyzed to decompose and reconstruct the hydrodynamic waves in the flow field and the generation process of the acoustic wave emission directly from the jet providing insights into the noise generation mechanism and their suppression by inducing the peak wave instabilities to shift to larger wavenumber values to reduce their acoustic emission efficiencies, which were confirmed by acoustic measurements. The findings from this investigation show direct visualization of the acoustic wave emission from the sources in the flow field. These waves have downstream components that are emitted from the modulation of the shear layer inducing spatial coherence of the turbulent vortical structures. This modulation is induced by the passing of the upstream acoustic waves along the shear layer from all shock cells synchronized as a phased array with regions of constructive and destructive interference patterns which steers the emitted acoustic radiation beams. The intense acoustic beam perturbs the shear layer and induces the formation of the internal trapped waves with phase velocities propagating upstream of the supersonic jet flow. Based on these findings, new noise generation mechanisms are proposed that cover various aspects of the physical mechanisms of jet noise components for the turbulent mixing noise, the broadband shock associated noise and the screech resonance tone, along with reduction and suppression mechanisms.

The integration of AI in autonomous vehicles has been rapidly expanding and has the potential to raise concerns about non-compliant or malicious actors. Predicting movements or strategies of these actors could provide a substantial advantage in the mitigation of such threats. In a simulated asteroids style game, capture of these actors closely resembles pursuit evasion problems in differential games. In this work, multiple evader control methods are mapped by an adaptable fuzzy modified potential field avoidance method trained via genetic algorithm. Evader routes are integrated and optimal interception points are determined by numerical methods or a fuzzy logic approach. Time delayed mines are then placed at the interception point to eliminate the evader. The fuzzy modified potential field has also been separately trained to produce highly effective avoidance within congested asteroid environments.

An approach for the architecture optimization of emulator embedded neural networks is proposed. While the emulator embedded neural network has been shown to provide accurate predictions with suitable emulators, there is still a challenge regarding how to select the optimal hyperparameters of network architectures, such as, the number of neurons, layers, types of activation functions, etc. The selection of hyperparameters greatly affects the performance of the neural network model training both in terms of accuracy and efficiency. To address this challenge, this study proposes an algorithm that tests a range of hyperparameters and selects the best performing set. The algorithm compares network architectures using average cross-validation error and architecture size. Additionally, the algorithm implements Bayesian optimization to accelerate the hyperparameter selection process and leverages a database of benchmark analytical problems to better define the hyperparameter search space. The proposed method is demonstrated using analytical examples, an aerospace fracture mechanics design study, and a representative aerospace vehicle design study. It was found that the proposed algorithm was able to successfully select well-performing architectures from within the chosen search spaces. In comparison to the popular grid search algorithm, it found architectures of similar sizes and performance while testing less than half of the total number of architectures. The proposed algorithm was able to successfully avoid large architectures when the accuracy benefits were minimal compared to smaller architectures, saving both time and computational efficiency. The potential benefits of the algorithm when applied to aerospace design application are an increased confidence in the selected architecture, identification of best fit architectures with less dependence on experts' knowledge and experience, and reduction in time and computational efficiency when selecting an architecture.

Semi-supervised multi-class classification with novelty detection consists of one tool that can accurately define what class an instance belongs to from a set group of known classes while simultaneously detecting instances that do not belong to any of the classes. This field of machine learning has been studied for a decade or more, with many different algorithms and solutions tested. In this thesis, an algorithm built using One-Class Support Vector Machines (OCSVM) and Linear Discriminant Analysis (LDA) will be explored and demonstrated on data from simulated missile trajectories. Not only is this algorithm novel to the aerospace industry, but also to the computer science and machine learning industries as well. Its strengths and limitations will be explored, as well as techniques to increase accuracy and ideas for future work and other uses for this tool. The data used is produced by the Auburn University Solid Rocket Code (AUSRC), a validated code which simulates the flight of a missile given its design parameters. The output data from the AUSRC is preprocessed using common techniques such as standardization, to eliminate the influence of units of measurement, and principal component analysis (PCA) as a method of data reduction. The data is then fed into an iterative OCSVM, during which necessary data is recorded to extract any outlier points. An objective threshold is used to differentiate between instances that are outliers of a known clean class and instances that are true novelties from an unknown class. The instances deemed 'true' novelties by the threshold are added to the training data to fit the LDA to. The data is then run through the LDA, which provides a higher classification accuracy than the OCSVM, cleaning up inter-class misclassifications as well as tracking the outliers back to their known class. Since the LDA was trained on the 'true' novelty class data, it acts as a novelty detector by extracting any other points the OCSVM missed. This method works accurately (>90\% overall accuracy) on simulated missile trajectories across 3 different data sets and robustness tests. The data set features used are comprised of performance parameters, trajectory data, or derived features. The tests comprise of reduced time frames and random missing data. The OCSVM provides high accuracy novelty detection while the LDA provides high accuracy classification, exploiting the strengths of each machine learning algorithm. Further work should be done to improve the hybrid method and to investigate ways to eliminate the LDA's underlying assumption of the data set to have a multivariate Gaussian distribution.

In the constant search for more efficient engines, one approach to gain performance is to reduce the weight of the low pressure turbine (LPT) module. This module can account for up to 30% of the total engine weight [1], and a reduction in LPT weight results in clear gains to engine performance and a reduction in engine cost. High lift airfoils accomplish this weight reduction by each blade extracting a larger amount of work from the flow and thus requiring fewer blades to drive the compressor when compared to conventional blades. However, high lift LPT blades, quantified by a high Zweifel loading coefficient Zw>1.15, encounter increasing loss at low Reynolds numbers. Named Reynolds lapse, this effect is problematic if the engine must operate at high altitude cruise conditions such as the case with unmanned air vehicles. The two airfoils of this study, the L2FHW and the L3FHW, were designed to be front loaded and to demonstrate favorable low Reynolds number loss characteristics. Both airfoils were tested in the Transonic Turbine Cascade (TTC) at the Air Force Research Laboratory Building 18 Test Cell 21. The TTC is capable of high Mach number and low Reynolds number flow via independent control of each. Each airfoil was tested across a broad range of Mach numbers: exit Mach 0.78 down to 0.2 and exit Reynolds numbers from 23,000 to 201,000. Across each condition an exit total pressure traverse yielded the loss coefficient of the cascade at that condition. It was found that across all design exit Mach conditions, 0.78, both airfoils experience fully attached flow and nearly flat loss behavior. This strongly aligns with the design level predictions made. At conditions beyond expected operating conditions, the L2FHW displayed resistance to un-reattaching separations at all conditions down to exit Mach 0.2 Reynolds number 23,300. The L3FHW showed un-reattaching separations at only the most extreme condition tested, exit Mach 0.2 and Reynolds number 25,300. Both airfoils showed smooth gradually increasing levels of loss rather than sharp discontinuous jumps that are present in other highly loaded airfoils. The results show that both airfoils may operate across a broad operating range without fear of suddenly incurring a significant reduction in performance. Such increases in loss would negate any performance benefits made from a reduction in engine weight. The success of the airfoils in this Tech Readiness Level 3 test shows the promise in highly loaded LPT blades. The performance of the airfoils in future higher fidelity tests, such as annular cascades and rotating stages, is the source of much interest in the turbomachinery industry.

Traditional conceptual-level aerodynamic analysis is limited to empirical and/or inviscidmodels due to considerations of computational cost and complexity. There is a distinctdesire to incorporate higher-fidelity analysis into the conceptual-design process as early aspossible. This work seeks to enable the use of high-fidelity data by developing and applyingmulti-fidelity surrogate models that can efficiently predict the underlying response of asystem with high accuracy. To that end, a novel form of the multi-fidelity polynomial chaosexpansion (PCE) method is introduced, extending the surrogate modeling technique toaccept three distinct fidelities of input. The PCE implementation is evaluated for a seriesof analytical test functions, showing excellent accuracy in creating multi-fidelity surrogatemodels. Aerodynamic analysis of a generic hypersonic vehicle (GHV) is performed using threecodes of increasing fidelity: CBAERO (panel code), Cart3D (Euler), and FUN3D (RANS).The multi-fidelity PCE technique is used to model the aerodynamic responses of the GHVover a broad, five-dimensional input domain defined by Mach number, dynamic pressure,angle of attack, and left and right control surface settings. Mono-, bi-, and tri-fidelityPCE surrogates are generated and evaluated against a high-fidelity “truth” database toassess the global error of the surrogates focusing on the prediction of lift, drag, and pitchingmoment coefficients. Both monofidelity and multi-fidelity surrogates show excellent predictivecapabilities. Multi-fidelity PCE models show significant promise, generating aerodynamicdatabases anchored to RANS fidelity at a fraction of the cost of direct evaluation.

The miniaturization of satellites has led to a new era of miniaturized spacecraft technology, which includes propulsion systems. The full potential of CubeSats will be realized once they are equipped with miniaturized thrusters. One option being developed at the University of Tennessee Space Institute (UTSI) is a miniature electrospray device, Micro Scalable Thrusters for Adaptive Mission Profiles in Space (µSTAMPS). This device operates via electrospray principles and utilizes an ionic liquid (IL) propellant. µSTAMPS aims to provide CubeSats with maneuvering capabilities, including rapid deorbiting, station-keeping, and collision avoidance maneuvers (CAMs). An internal propellant reservoir can deliver enough propellant for CAMs; however, to achieve additional applications, an external propellant feed system is required. The focus of this thesis is to initiate the development of such a system. The first prototype employs a FEP bladder tank, a peristaltic pump, and an MSLA 3P printed (3DP) millifluidic propellant routing manifold (PRM). Primary goals were to develop a leak-free bladder tank to deliver 100 grams of IL and fabricate a 3DP millifluidic PRM to simultaneously distribute propellant to four thrusters. Seal strength tests (ASTM F88) were performed to determine the required tank thickness, which ended up being 0.1 in. However, the assembled prototype failed before any pressurization tests could commence. It was concluded that the current tank design was not ideal. The fabrication of the PRMs began with a comparison of print accuracy between Elegoo’s Mars 2 Pro (M2P) and Mars 4 Ultra (M4U). Test prints were performed with various support strategies; it was found that the PRMs should be printed with lightweight supports at a support density of 80%. PRMs were then fabricated on both printers with differing orientations and channel designs. These iterations were subjected to several flow tests; the ideal orientation was to print the wide face of the PRM perpendicular to the bed with an inlet on the wide face. However, the current method of fabrication does not allow simultaneous flow through each channel due to internal deformations. Overall, while the initial prototype faced challenges, the project lays a foundation for future improvements which will ensure the success of µSTAMPS.

Wire electrical discharge machining (WEDM) enables production of complex parts with tight tolerances, although maintaining dimensional accuracy in corners and tapers remains challenging due to wire deflection and vibration. This study optimizes WEDM parameters for achieving high-accuracy in machining complex geometrical parts and taper cuts in 6061 Aluminum alloy using Excetek W350G WEDM machine with a copper wire electrode. Parameters including Wire Tension, Pulse On-Time, Pulse Off-Time, Wire Feed Rate, Open Circuit Voltage, and Flashing Pressure were varied using L18 Taguchi Orthogonal Array and response graph method to identify optimal cutting conditions. Results indicated feature-specific optimization is crucial, as different geometrical features (rectangular fins, triangular fins, gears) exhibited varying critical parameters. Key findings highlighted the importance of Wire Tension and Pulse On-Time in maintaining cutting accuracy, although at varying levels for specific features. Response graphs demonstrated effects of major WEDM parameters on corner and profile accuracies, whereas Taguchi analysis provided optimum settings of parameters for each feature and taper cutting. Validation experiments for rectangular fins showed significant improvement in the dimensional error for the fin length and taper angle. These advancements will enhance precision, efficiency, and versatility of WEDM processes in machining complex profiles, and corners, contributing to precision manufacturing.

This manuscript is divided into three parts, each associated with three of the main projects I undertook throughout my doctoral journey. In particular, this dissertation focuses on the topics of anomaly resilience, detection, and reaction in astrodynamics problems, which are crucial aspects to consider for ensuring mission success, especially when dealing with the harsh space environment. In this manuscript, resilience, detection and reaction are investigated in two selected domains: trajectory design in cislunar regime and satellite constellations, both susceptible to the possibility of unexpected events. Therefore, effective identification capabilities and swift reaction to unforeseen phenomena become vital to support mission integrity. Resilience to off-nominal behaviors is investigated for the trajectory design problem in the first part of this manuscript. In particular, we explore the convergence and dynamical structure of the trajectory design space associated with lunar landing and ascent abort scenarios for a crewed module departing from and returning to the Deep Space Gateway. Numerical methods for the identification of abort trajectory solutions are employed within a two-step optimization pipeline, through which we discover the existence of regions of stiff convergence where traditional pipelines may fail. Hence, we present an extensive analysis of problem parameters, demonstrating how the presence of such regions can be traced to the formulation of employed correction algorithms, problem dynamics sensitivity, and transfers geometry. To reduce the computational cost, we introduce a three-step optimization pipeline relying on surrogate models trained via adaptive sampling for the fast generation of initial guesses, which are then corrected for the recovery of abort trajectories within the defined scenario. Results obtained from the application of the optimization pipeline on the two scenarios underscore the complexity of the solution space, while providing useful information to inform the trajectory design process. Anomaly detection and reaction in the context of Proliferated Low Earth Orbit (P-LEO) satellite constellations are then explored in the remaining two parts of this manuscript, with a focus on anomalous behaviors originating from adversarial actions against a constellation. For the detection problem, we present a transformer neural network- based pipeline for the identification of anomalous connections between satellites, modeling a P-LEO as a dynamic graph, which is capable of capturing spatial-temporal correlations characterizing a temporal network. Our analyses demonstrate how temporal and spatial signals alone are insufficient for effectively discriminating anomalous connections, requiring additional features to enrich the information extracted from the network dynamics. Notably, we discover how the introduction of edge-frequency information positively impacts our algorithm performance, reaching up to 95% in AUC score, here used as quality metric. Additionally, extensive analyses on variations of problem parameters demonstrate the robustness of the method over a wide range of scenarios, and highlight the existence of interesting couplings between satellite dynamics, spatial ground node distribution, and algorithm performance. For the reaction component, a combination of competitive coevolutionary algorithms and genetic programming is employed to evolve reactive strategies to respond to adversarial actions against a constellation system. In particular, genetic programming trees are employed for the representation of reactive policies to respond to presented and different, unseen scenarios. The analysis demonstrates how the utilized approach provides effective solutions, beating both minimally complex strategies and human-developed ones, and showing adaptability to the introduction of multiple constraints. In both the detection and reaction problems, the proposed methodologies display the potential to reduce the cognitive load on operators of large constellation systems, and to possibly enable resolution of critical situations in a timely manner.

Oak trees are of great ecological and economic importance in the southeastern United States. These trees are being replaced through the mesophication process, presenting a major risk to regional ecosystems. This study applies an established method to measure the burning characteristics of longleaf pine ($Pinus$ $palustris$), southern red oak ($Quercus$ $falcata$) and sweetgum ($Liquidambar$ $styraciflua$ L.). The combustion fraction, the mass loss rate, the temperature at multiple heights and the propagation rate were measured for each individual species and mixtures with 30\% oak mass and variable pine and sweetgum mass. Pine was found to be the most consistently flammable species with the highest median measurements for all measured burning characteristics. Conversely, sweetgum had the lowest median values for all burning characteristics. The results for oak were bimodal. The low flammability mode had results similar to those of sweetgum, whereas the high flammability mode had lower temperatures than that of pine but higher mass loss and propagation rates. Burning characteristics generally decreased as the sweetgum content increased; however, using principal component and cluster analysis, five clusters were identified. In the first cluster, the test had higher mass loss and propagation rates than any of its constituent species. In the second cluster, the propagation rate and flame height decreased, but the temperature along the fuel bed was greater than that of its constituent species. In the third cluster, the temperature decreased to expected values. The fourth cluster contained tests with combustion fractions lower than that found for any of the individual species. However, in the fifth cluster the combustion fraction approached the values found for sweetgum. It was concluded that there exist distinct pine-oak and oak-sweetgum interactions, which lead to competing changes in the overall fuel-bed burning characteristics. These results contribute to the current discussion on how the progression of mesophication impacts the forest floor flammability; and can be used to improve prescribed burning to suppress mesophication.

In this dissertation, a stereo-photogrammetry technique for obtaining non-intrusive, full-domain measurements of Plume-Surface Interaction (PSI) crater evolution was developed. Using this technique, crater formation was studied at multiple static nozzle heights above the surface, multiple nozzle mass flow rates, and at both Earth atmospheric and sub-atmospheric ambient pressure conditions. From the stereo-photogrammetry data, time-resolved 3-D reconstructions of the crater geometry were generated, and crater depth, radius, and volume evolutions were extracted. Results show that the stereo-photogrammetry technique is able to accurately measure the crater formation process. Under Earth atmospheric ambient pressures, the crater depth was observed to grow logarithmically with time at high nozzle heights but more rapidly at low nozzle heights. Craters formed under Earth atmospheric ambient pressure had an axisymmetric parabolic geometry. Crater geometry changed significantly across ambient pressure conditions. Craters formed under Earth atmospheric pressure had an axisymmetric parabolic geometry while craters formed at some nozzle heights under sub-atmospheric pressures had a lobed geometry characterized by azimuthal depth variations. The data were used to investigate crater formation scaling laws and a new physics-informed scaling law for the crater depth evolution was proposed.

Thermoacoustic instabilities pose significant challenges to the development of modern combustors. These instabilities arise from the interaction between heat and sound in propulsion systems, potentially leading to limit cycle pressure oscillations or, in extreme cases, engine failure. Thus, it is crucial to study and quantify the acoustic waveforms in realistic combustion devices. One effective approach is to investigate simplified models, such as one-dimensional wave propagation in a Rijke tube. A three-pronged approach is introduced, which comprises of theoretical and numerical investigations that leverage experimentally available data in order to explore the time-dependent field within a Rijke tube. A perturbation expansion method is presented, which uses a naturally occurring small parameter within the context of a one-dimensional tube, both with and without a spatially variable heat source. This approach yields accurate predictions for the pressure and velocity modal shapes and frequencies for any specified temperature distribution, along with other acoustic properties. Furthermore, this method results in a set of linear partial differential equations that can be solved using a Green’s function to describe thermoacoustic pressure, velocity, heat oscillations, temperature, density, acoustic intensity, energy density, entropy, boundary-layer heat flux, and velocity under arbitrary endpoint conditions. Our findings highlight the significant axial dependence of the waveforms and nodal locations on the thermal profile and respective thermal gradient. The analysis further reveals that the peak value of the energy-flux vector modulus—representing the product of acoustic velocity and pressure—occurs at the heat source location and increases with the heat power input. Moreover, for a finite heat source, we derive the acoustic frequencies analytically. These frequencies are shown to increase monotonically with successive increases in temperature gain across the heat source, retraction of the heat source, reductions in heat source length, and smoothing of the temperature gain profile. Lastly, we introduce the dual reciprocity boundary element method to extend our formulation to two-dimensional (and three-dimensional) thermoacoustic wave propagation. Results for the 2-D Rijke tube and a cyclonic rocket engine are presented, demonstrating the applicability of our approach to more complex systems.

This paper presents a computational finite element analysis (FEA) focused on the utilization of shape memory alloy (SMA) interfaces as thermal expansion compensators for ductile positive coefficient of thermal expansion (CTE) materials such as Aluminum 6061-T6. The investigation delves into the efficacy of superelastic, one-way, and two-way shape memory effects in mitigating thermal expansion-induced stresses within engineering structures utilizing beam components. The research examines critical structural factors in a fixed beam system such as thermally induced internal stresses and buckling resilience at varying thermal loads.Computational simulation software from ANSYS Mechanical was calibrated to fit previous data from the literature on commercially available NiTi-based SMA properties. Comparing noninterface and SMA-interfaced beam structures, this study demonstrates the potential of SMAs to mitigate thermally induced stresses, thereby enhancing the structural integrity and longevity of engineering structures in thermal gradient environments. Furthermore, this paper proposes potential industries where the implementation of SMA interfaces could prove advantageous over current thermal compensating practices, including aerospace, optical, and civil engineering.This paper also introduces employing two-way shape memory alloys (TWSMAs) in thermal compensation by using computational and numerical analysis to showcase that TWSMAs response can be trained to perform similarly to materials with a negative thermal coefficient. By leveraging the unique property of trained TSMAs of the bidirectional shape memory effect, the aim was to demonstrate a second stress-free thermal state at an elevated temperature to increase the structure’s buckling resilience. This research underscores the practical feasibility and performance of SMA interfaces as thermal expansion compensators, setting the stage for further exploration of advanced SMA technologies.

Nonlinear hereditary inelastic deformation behavior can occur in manymaterials utilized at elevated service temperatures. This behavior can includecreep, rate sensitivity, and plasticity. Accurate assessments of nonlinear stress anddeformation behavior are important in predicting the operational life and overallperformance of critical engineering systems. Inelastic constitutive models havebeen developed and deployed to meet these assessment needs. The models mustpredict nonlinear behavior under complex thermomechanical load paths. Thisincludes capturing phenomena such as Bauschinger’s effect, cyclic softening andhardening, stress relaxation, and ratcheting when present in high-temperatureapplications.This dissertation provides a literature review that details the developmentof inelastic constitutive modeling as it relates to polycrystalline materials. Thisreview distinguishes between inelastic constitutive models that account fornonlinear behavior at the microstructural level, time independent classic plasticitymodels, and time-dependent unified models. Emphasis is placed on understandingthe underlying theoretical framework for unified viscoplasticity models wherecreep and classical plasticity behavior are considered the result of appliedboundary conditions instead of separable rates representing distinct physicalmechanisms.This review also discusses recent topics in constitutive modeling that offernew techniques that bridge the gap between the microstructure and the continuum.Focus has been given to material science models that physically explain nonlinearbehavior at the microstructural level. An understanding of material microstructureis always necessary in developing accurate multiaxial continuum-levelconstitutive models that characterize the responses of engineering componentsmodeled with continuum-level perspective.Many forms of inelastic constitutive models are presented that includedifferential formulations as well as integral forms. Focus is drawn to the salientfeatures of Robinson’s potential function-based unified theory. The viscoplasticmodel developed from this theory is expressed in its first rendition andmodifications are defined that are intended to capture the unique behavior ofgraphite. Including the kinematic hardening and isotropic effects using a statevariable approach.Care is taken to introduce the effects of irradiation on the graphite materialvia the dependence of the isotropic hardening variable on neutron dose or fluence.Thus, with this implementation, the current form of Robinson’s potential function-based unified viscoplastic theory one predicts the behavior of graphite material inhigh temperature applications including irradiation.

Continuous control and monitoring of the gas turbine combustor wall is essential for preventing combustor liner from overheating which may significantly damage structural integrity and reduce overall lifespan. In the past half century combustor outlet temperature has risen from 1100 to 1850 K. The continuous increase of severity of operating conditions inside combustor demands for a temperature determination method whose operation and accuracy are not affected by ever rising temperature. Conventional methods such as thermocouples and thermographic phosphor are not only intrusive, but their operation is also either restricted by an upper temperature limit (thermocouple) or measurement accuracy significantly decreases with increasing temperature beyond a certain threshold (thermographic phosphor). In this paper a multi-wavelength pyrometry system is developed which provides a fast, minimally intrusive temperature determination of the combustor wall. This method does not require any prior knowledge of exact emissivity but of the functional relationship between emissivity and wavelength over the spectral region of interest. One of major problems of wall temperature measurement using a pyrometry in combustor is that the emission from the combustor wall is interfered by the emissions from molecular radicals existing in the flame such as CH* (~431nm), OH* (~308nm), CO2* (400-600 nm) in the visible range and major species such as H2O (1.4,1.9,2.7,6.3 um) and CO2 (2.7,4.3,15 um) in the infrared region. In this report, a combustor that is made of stainless steel and runs on natural gas and the spectrum of flame emission is measured to identify a proper wavelength range (650-800 nm) over which there exists minimal or no interference from flame emission with thermal radiation. Thermal radiation is measured within the mentioned spectral range with a spectrometer and camera assembly from the target spot on the combustor wall with temperatures ranging from 1000 to 1300K. Thermal radiation spectra from both bare stainless steel and YSZ thermal barrier-coated steel were measured for temperature determination. Measured spectra were transformed into a straight line and corresponding temperatures were measured from the slope of those lines. The slope method is only valid when reflected radiation from the target spot is minimal or non-existent and spectral emissivity of target spot is inversely proportional to the wavelength. A separate algorithm was formulated to compensate for reflected radiation when it constitutes a good portion of the total (thermal and reflected) measured radiation. It was found that the addition of YSZ TBC thickness increased the hot gas side temperature although it reduced the temperature of the base metal underneath. A steep temperature gradient was found to exist across the thickness of the non-isothermal thermal barrier coating. Measured temperatures are found to be in good agreement with temperatures measured with thermocouple with absolute error being always within 5% or less.

Real world operational environments for uncrewed aerial systems are inherently dynamic and full of uncertainties. This presents significant challenges to the safety and reliability of autonomous precision landing systems for UAVs. This study focused on evaluating and improving upon the existing ArduPilot precision landing system. ATARI testing identified brittle areas within the precision landing architecture. The precision landing failsafe interacts with other failsafes, including the critical battery failsafe, which created a state where the ground station could not land the UAV. Motion capture testing demonstrated a testing method to obtain a measure of ground truth and assess UAV performance. Analysis showed precision landing performed within requirements and much better than GPS. Results also identified room for improvement in the relative position estimation. In response to the identified brittle behavior, new flight modes were created to successfully decouple precision landing from the LAND and RTL flight modes. Now there is the option to normal RTL or LAND while precision landing is enabled, preserving precision landing strictness. GCS can force the UAV to land in the event of precision landing failsafe. A fuzzy logic based risk assessment algorithm was developed and successfully tested with logged data from a real precision landing flight. This will be valuable in future integration with a new failsafe which to make real time go/no-go decisions to continue precision landing. This research not only underscores the high performance of ArduPilot's precision landing system, but added critical safety improvements and laid the foundation for further enhancements to UAV precision landing and operational reliability.

Aerial Vehicle (UAS) remote and autonomous operation is a growing industry with applications in defense and the commercial space. UAS's can use the Global Positioning System (GPS) to determine their position when signals are available. Operational environments like urban canyons, forested areas, and indoors can block the UAS from receiving GPS signals and prevent the receiver from determining a position, which can hinder the vehicle's ability to successfully complete the mission. Unreliable positioning from GPS data requires UAS's to have an alternative means of localization, which can be accomplished by utilizing ultra-wideband ranging to landmarks and other aerial systems. Machine learning can be used to train models to utilize raw data from intervehicle distance sensors on the agent and anchors to determine the location of the agent without access to GPS data. This work will explore using machine learning as an adaptable localization system using neural networks and gradient descent methods. Fully trained neural networks will be capable of learning specific noise models and performing cooperative localization using unfiltered intervehicle ranges and anchor positions.

In icing conditions, ice accretes on aircraft components which impacts performance and stability. Researchers simulate icing in wind tunnels to understand icing physics and to develop methods of mitigating its effects. This research investigates the capabilities of the Adaptive Icing Tunnel (AIT), a small-scale tunnel designed to conduct economical and quicker tests. A test plan is developed to characterize the temperature in the AIT including objectives, instrumentation, methodology, and test matrices. Four drop sizing methods are developed that use scaling physics, LEWICE, a cloud droplet probe (CDP), and a rotating multi-cylinder. For specified ice shapes, the scaling and LEWICE methods result in average differences between the calculated and actual MVDs of 24.5% and 71.9% respectively. Methodologies and test plans are developed to use the CDP and the rotating multi-cylinder. The test plans designed will be used during the initial aerothermal and icing cloud characterizations of the AIT.

As deep space missions expand in scope and distance, the efficiency of propulsion systems becomes paramount. This thesis analyzes the impact of small measurement errors in the thrust profiles of Hall-Effect Thrusters, a common type of electric propulsor, known for increased efficiency compared to traditional chemical propulsion despite lower thrust. Due to their prolonged operational times, these errors compound, affecting trajectory and mission success. Through analyzing the AEPS Hall-Effect Thruster prototype, designed for NASA’s Artemis Program’s Gateway space station, using curve fitting and a Monte Carlo simulation, we assess the effects of these errors on an example mission to Alpha Centauri. Results show plasma dynamics cause the majority of error, but cause minimal trajectory deviation and propellant loss. This reinforces electric propulsion’s suitability for long-distance space travel. This work informs spacecraft mission design, providing valuable insights into fuel efficiency and system selection, as well as building upon NASA Glenn Research Center’s Electric Propulsion and Power Laboratory’s prior research.

The Adaptive Icing Tunnel is a new refrigerated, closed-loop, vertical icing wind tunnel designed to achieve a test section airspeed of 215 knots and a temperature of 20 °C. Test section airspeed, liquid water content, and icing cloud uniformity will be tested for both spatial and temporal uniformity. The methods of these initial characterizations are developed, and analysis is conducted to determine the theoretical capabilities of the icing cloud based on data collected at a similar wind tunnel with known nozzle characteristics. It was approximated that a single Mod1 nozzle could produce an icing cloud with an LWC of 0.15 g/m3. A redesigned nozzle was created to allow for the use of multiple nozzles while maintaining a low LWC. The results of these characterization efforts will be used to provide crucial insights into the tunnel’s performance and future research opportunities.

A significant challenge to engine design is the development of combustion systems that meet increasingly strict efficiency, performance, and emissions demands. This pursuit often prompts using conditions at the limits of capability, dictating the need to expand the envelope of robust and reliable operation. The use of nanosecond-pulsed high-frequency discharges (NPHFDs) for ignition has attracted considerable attention because of their ability to produce active radicals and excited species, ultrafast gas heating effects, and unique hydrodynamic behavior. These characteristics are why NPHFDs have proven effective in extending ignition limits and reducing ignition times in quiescent, low-speed, and high-speed turbulent environments. Despite these observations, the community will benefit from additional research on NPHFDs to better understand their kinetics, hydrodynamics, and operational strengths and weaknesses compared to conventional exciter systems. The work within this dissertation provides insight into these topics, starting with results from a two-photon laser-induced fluorescence campaign that reports the spatio-temporal evolution of oxygen atom fluorescence produced from a nanosecond discharge. Results indicated that the evolution of the oxygen atom (O-atom) signal was heavily influenced by the discharge-induced flow field. This work was followed by an exploration of the unique hydrodynamics related to a train of nanosecond discharges, namely, discharge-induced jetting motion and the experimental conditions that maximize/minimize its influence. Overall, the jetting motion was bolstered by larger inter-electrode distances, higher pulse repetition frequencies (shorter inter-pulse times), and larger bursts of pulses. Increasing the bulk flow velocity did not eliminate the jetting motion but reoriented it in the bulk flow direction such that its spanwise magnitude decreased. With the unique attributes of NPHFDs known, a comparison between an NPHFD exciter system and a conventional exciter system was then conducted in terms of ignition kernel size, growth rate, and ignition probability. Results showed that the NPHFD exciter has benefits in terms of ignition kernel size and growth rate compared to the conventional system, as long as the equivalence ratio ensures a 100% ignition probability or the average power is sufficiently high. This dissertation concludes with an investigation of the application of lower-voltage nanosecond discharges to a high-speed turbulent environment, with the conclusion that low-voltage bursts can successfully ignite a cavity flameholder. Overall, the collection of works within this dissertation documents the characteristics of NPHFDs, beginning with their fundamental kinetic and hydrodynamic qualities observed in controlled, low-speed, non-reacting environments.

The development of next generation aircraft is trending towards more interconnected and highly multidisciplinary systems. To better support the design of these systems, an alternative approach to design is needed beyond traditional methods. An automated design approach by means of multidisciplinary design, analysis, and optimization (MDAO) offers the potential to enable aircraft concepts traditional designers may not have considered. However, the selection of objective function for optimization remains an ambiguous choice by the designer. To remove ambiguity from the choice of objective function, a universal measure of performance in the form of exergy and its destruction can be used. Through the quantity of exergy, typically disparate systems such as the force-based approach of aerodynamics can be compared in a one-to-one fashion to the energetic-based approach of a thermal or propulsion system.In this thesis, a high-fidelity approach for aerodynamic and thermo-mechanical exergy destruction evaluation and sensitivity analysis is provided to enable gradient-based design optimization. To arrive at the exergy destruction equations, a formal development of the entropy balance equation from the concavity property of entropy is presented. From the balance equations, the exergy destruction equations can be derived for arbitrary thermal and fluid processes. The aerodynamic exergy destruction functional is implemented in FUN3D and a rigorous verification effort is conducted demonstrating good functional agreement with test cases. Additionally, the discrete adjoint is implemented and demonstrates discrete agreement with complex-step derivatives. A series of trade studies are then conducted on the Generic Hypersonic Vehicle (GHV) to identify performance metrics of the vehicle. The thermal exergy destruction functional is implemented in MAST along with a series of verification cases for the functional and discrete adjoint demonstrating discrete agreement. A series of thermal exergy destruction trade studies are performed on the GHV and some modeling and design perspectives are discussed. Finally, a series of optimization cases are presented demonstrating the use of exergy destruction as an objective function. A series of inverse design problems are conducted as well as inviscid aerodynamic exergy destruction optimizations of the GHV. These contributions demonstrate the utility of the exergy quantity as a universal measure of performance and push the state of the art in the area of exergy-based analysis and optimization.

With the increasing interest in electric vertical takeoff and landing air vehicles and small-scale Unmanned Air Vehicles, many novel design concepts favor the fixed-pitch-propeller as the primary propulsion system due to its simplicity and reliability. This expands the application scenario of the fixed-pitch propeller from axial forward flight to edgewise flight conditions. The current study investigated the changes in its performance when operating at higher incidence angle conditions as well as the proximity effects of the propellers in these conditions. It is hypothesized that the propeller performance under various conditions and proximities can be reasonably predicted by modeling the changes in the inflow angle of the propeller. This hypothesis was tested using three major steps. First, a relationship between inflow angle, propeller inclination angle, and advance ratio was established using a series of experimental investigations. Second, this relationship was used to predict the performance of two propellers in tandem configuration with various horizontal and vertical offset distances. Third, the same model was used to predict the ceiling effect of the propeller at different incidence angles and advance ratios. All experiments were conducted at the University of Dayton Low-Speed Wind Tunnel (UD-LSWT) Laboratory under its open jet configuration. Force-based experiments, flow visualization as well as phase-locked Particle Image Velocimetry (PIV) experiments were conducted for all investigations. The changes in propeller performance at various flight conditions were quantified and several normalization methods were successfully employed indicating the predictability of various propeller forces and moments. A novel propeller axial thrust prediction model was proposed considering the propeller performance as a summation of propeller-like components and wing-like component, with an overall error of less than 8.3%. Flow visualization and PIV results confirmed the changes in propeller performance were strongly related to the propeller inflow angle. A model relating the propeller advance ratio, incidence angle, and inflow angle was developed, which can be applied to predict the propeller performance in proximity to another propeller and in proximity to the ceiling. The investigation of the changes in propeller performance in the negatively staggered configuration, where the rear propeller was placed above the plane of the front propeller, and in the positively staggered configuration, where the rear propeller was placed beneath the plane of the front propeller, was then conducted. The changes in propeller performance at different propeller vertical and horizontal spacings, incidence angles, and advance ratios were quantified. A reduction in the back propeller thrust generation was measured, resulting in a lower overall efficiency of the tandem propeller system. Flow visualization and PIV experiment confirmed a reduction of the back propeller inflow angle due to the interaction with the front propeller, resulting in the reduction of its thrust generation. The linear superposition model developed from the standalone propeller flowfield showed good agreement with the PIV results from the tandem propeller configuration, indicating the linear superposition model can be applied to predict the trend of the changes in propeller performance in tandem.The investigation continued with the changes in propeller performance in ceiling effect in forward flight. In general, an increment in propeller thrust generation and a reduction in power consumption are found in the ceiling effect. For propellers operating in edgewise flight, a higher ceiling effect benefit was observed when compared to propellers operating at lower incidence angles. Performance similarity in propeller ceiling effect at different distances to the ceiling is found. An in-ceiling-effect performance prediction method is proposed, which combines the ceiling-effect hovering prediction model and the propeller forward flight prediction model. Phase-locked PIV confirmed an increase in the propeller inflow angle in the ceiling effect, resulting in higher thrust generation. Additionally, PIV and surface flow visualization reveal the presence of a nodal point on the ceiling plate indicating the propeller flowfield in the ceiling effect is highly three-dimensional.The current study established a strong connection between the changes in propeller performance in forward flight and its inflow angle. The proposed prediction model provides a quick estimation of the propeller axial thrust in edgewise flight conditions using only the axial flight performance data. The validation of the propeller inflow linear superposition model presents the potential of using a single propeller performance and flowfield to estimate the performance of a multi-propeller vehicle system. This provides a design guideline for multi-rotor systems at the initial design stage. Meanwhile, the current study also reveals the changes in propeller performance and flowfield in ceiling effect forward flight and provides a performance estimation method when designing a vehicle operating in the ceiling effect.

Event-based pixel sensors asynchronously report changes in log-intensity in microsecond-order resolution. Its exceptional speed, cost effectiveness, and sparse event stream makes it an attractive imaging modality for particle tracking velocimetry. In this work, we propose a causal Kalman filter-based particle event velocimetry (KF-PEV). Using the Kalman filter model to track the events generated by the particles seeded in the flow medium, KF-PEV yields the linear least squares estimate of the particle track velocities corresponding to the flow vector field. KF-PEV processes events in a computationally efficient and streaming manner (i.e.~causal and iteratively updating). Our simulation-based benchmarking study with synthetic particle event data confirms that the proposed KF-PEV outperforms the conventional frame-based (FB) particle image/tracking velocimetry (PIV/PTV) as well as the state-of-the-art event-based (EB) particle velocimetry methods. In a real-world water tunnel event-based sensor data experiment performed on what we believe to be the widest field view ever reported, KF-PEV accurately predicted the expected flow field of the SD7003 wing, including details such as the lower velocity in the wake and the flow separation around the underside of an angled wing.

Recent advancements in battery technology have led to an increase in the development of electric Vertical Takeoff and Landing (eVTOL) vehicles, typically using electrically-powered propellers to generate both lift and thrust. These vehicles typically operate in low-altitude, and limited-space conditions in urban environments. Unsteady flows from building wakes or atmospheric boundary layer effects raise concern to the stability of eVTOL-capable aircraft under normal operating conditions and during transition from vertical to forward flight and vice-versa in population dense areas. Although all types of unsteady flows have been studied for decades, little has been published on the influence of unsteady flow on a propeller-wing system. Understanding of this system is crucial to ensuring the safety of not only the passengers of these VTOL aircraft, but also the safety of the public.Investigation into powered wing response to streamwise gust encounters was conducted through various propeller locations, angles of attack, reduced frequencies, and thrust levels. All experiments were run at the University of Dayton Low Speed Wind Tunnel (UD-LSWT) in its open-jet configuration. The shuttering system downstream of the test section consists of a set of rotating louvers that change angle to effectively change the blockage ratio of the wind tunnel. Different louver angles and actuation frequencies provide different velocities and reduced frequencies. Particle Image Velocimetry (PIV) was conducted on the freestream flow during actuation of the louvers to spatially characterize the angle of attack variation throughout the test section. The results from PIV were used to determine the optimal testing location and wing size for the test article. The wing was designed to be modular, accepting a number of different propellerDistribution Statement A: Approved for Public Release; Distribution is Unlimited. PA# AFRL-2024-20834locations. Four total configurations were considered – unpowered, midspan, semi-midspan, and wingtip. Each configuration was tested through the entire reduced frequency regime, from steady and quasi-steady to high unsteady flow. Extended analysis provided interesting conclusions about the interconnected effects of each parameter varied through the experiments. Angle of attack and thrust had significant impact in the lift response of the wing in addition to the various trends that occur at the different reduced frequencies. The addition of a propeller lowered the threshold for unsteady behavior, especially at high angles of attack and high thrust. The steady state thrust affects the peak achieved in unsteady flow in a linear fashion. Strategic propeller placement at the midspan, where the unpowered wing is prone to flow separation, can completely eliminate stall and achieve a higher peak compared to other configurations. Various transitional flight profiles with discrete streamwise gusts were designed and implemented on the configurations mentioned previously.

Modeling and simulation is widely used within the aerospace industry to inform technology development, acquisition, and operations and sustainment decisions. Accurate simulation of a system's performance is critical for ensuring operationally relevant solutions are delivered on time and within budget constraints. High-fidelity five or six degree-of-freedom representations of platforms of interest are often required, resulting in significant effort to generate the aerodynamic databases for flight simulation. Missile Data Compendium (DATCOM) is a commonly used tool for building aerodynamic databases, but the tool loses accuracy for novel vehicle configurations and high angle of attack flight conditions. Computational Fluid Dynamics (CFD) tools address many of these issues. However, the computational burden imposed by CFD prevents this approach from generating full envelope aerodynamic databases for most applications without access to high performance computing resources.Surrogate models are gaining use within the engineering community as a way to meet the demands for higher-fidelity analyses while balancing limitations imposed by available computational resources. Multi-fidelity surrogate aerodynamic models provide a means to bring together Missile DATCOM and CFD to improve the aerodynamic database with a manageable computational burden. The goal of this research was to study the improvement of CFD compared to Missile DATCOM for several reference geometries, generate multi-fidelity surrogate aerodynamics models, and explore the impact of the improved aerodynamics models in the context of missile flight simulation. Multi-fidelity surrogate aerodynamic models of the axial force, normal force, and pitching moment coefficients for a range of Mach numbers, angles of attack, and deflections were successfully generated. Closed-loop missile responses to step acceleration commands highlighted potential limitations of the approach when used with a traditional three-loop autopilot. The multi-fidelity surrogates were usedwith a robust control autopilot formulation to ensure a stable system response at three flight conditions.

This research introduces an Origami-inspired dynamic spacecraft radiator,capable of adjusting heat rejection in response to orbital variations and extremetemperature fluctuations in lunar environments. The research centers around thesquare twist origami tessellation, an adaptable geometric structure withsignificant potential for revolutionizing radiative heat control in space.The investigative involves simulations of square twist origami tessellation panelsusing vector math and algebra. This study examines both a two-dimensional (2-D), infinitely thin tessellation, and a three-dimensional (3-D), rigidly-foldabletessellation, each characterized by an adjustable closure or actuation angle “φ”.Meticulously analyzed the heat loss characteristics of both the 2D and 3Dradiators over a 180-degree range of actuation.Utilizing Monte Carlo Ray Tracing and the concept of “view factors”, the studyquantifies radiative heat loss, exploring the interplay of emitted, interrupted, andescaped rays as the geometry adapts to various positions. This method allowedfor an in-depth understanding of the changing radiative heat loss behavior asthe tessellation actuates from fully closed to fully deployed. The findings reveal asignificant divergence between the 2D and 3D square twist origami radiators.With an emissivity of 1, the 3D model demonstrated a slower decrease in theratio of escaped to emitted rays (Ψ) as the closure/actuation angle increased,while the 2D model exhibited a more linear decline. This divergence underscoresthe superior radiative heat loss control capabilities of the 2D square twist origamigeometry, offering a promising turndown ratio of 4.42, validating the model’sefficiency and practicality for radiative heat loss control.Further exploration involved both non-rigidly and rigidly foldable radiator models.The non-rigidly foldable geometry, initially a theoretical concept, is realizedthrough 3D modeling and physical prototyping, demonstrating effective foldabilityand radiative heat loss control. The rigidly foldable model, enhanced withsophisticated techniques for increasing 3D height, showed full actuationcapabilities in a physical prototype, confirming its practical application potential.The research also extends to derivative geometries such as “Star Twist”,“Sloped-Edge Twist”, “Octa Twist”, and “Min-core Square Twist”. Extensivesimulations for these geometries are conducted, exploring their potential foradvanced thermal management systems.In conclusion, this research significantly advances the understanding of squaretwist origami geometry in radiative heat loss control. The study highlights thedistinct behavior and advantages of origami-based designs over conventionalradiators, demonstrating efficient thermal management capabilities andadaptability for space exploration. These findings illuminate the path towarddynamic heat rejection in future space missions, powered by origami radiatortechnology, and open avenues for further optimization and enhanced thermalefficiency.

A novel class of alumina-reinforced, pre-ceramic resin matrix ablative composites was developed, manufactured, characterized, and modeled for use as a thermal protection system (TPS) material for extreme aerothermal environments. High alumina paper and twill-woven mullite fiber were investigated as reinforcements for a Techneglas Ultra High Temperature Resin (UHTR) pre-ceramic polysiloxane matrix composite. These 2D laminate alumina/UHTR (A/U) composites minimize peak back face temperature primarily through rapid melt advection and low through-thickness thermal conductivity. A loading study was performed for boron carbide (B₄C) as an additive and identified an optimal 7.5 wt% loading in UHTR, and the resulting changes to decomposition chemistry mechanisms were identified using analytical chemistry techniques. The bulk formation of networked Silicon Boron Oxycarbide (SiBOC) and precipitation of Highly Oriented Pyrolytic Graphite (HOPG) was identified in pyrolyzed and annealed UHTR with boron carbide. Four variants of A/U with and without boron carbide underwent aerothermal testing using an oxyacetylene test bed (OTB), whose flow field was characterized using Schlieren imaging and a low-cost enthalpy probe. Alumina Paper/UHTR with 7.5 wt% B4C (AP/UBC) was down selected to be the primary focus of thermal characterization and ablation material response (MR) modeling efforts in CMA, FIAT, and ITRAC, three industry standard one-dimensional ablation modeling codes. Ablative software outputs were compared against OTB experimental results to validate the AP/UBC material response model for use in preliminary design estimates for AP/UBC thicknesses of 0.100 inches or less.

Plume-surface interaction experiments were conducted in a 4.27 m tall drop tower facility to achieve 0g conditions, where g is Earth gravity at 9.81 m/s^2. Following the drop tower experiments, Martian (0.38g) and Lunar (0.16g) gravity conditions were simulated via parabolic flight. A stereo photogrammetry technique was used to capture crater formation under these gravity conditions, allowing for the quantification of the effect of gravity on crater depth and volume evolution. Three nozzle heights of 25D, 40D, and 50D, where D is the nozzle exit diameter, and three nozzle pressures of 5, 10, and 15 psig were investigated using the drop tower at both 0g and 1g. Results from the 0g experiments were compared to the results obtained using the same nozzle heights and pressures under 1g. The results indicated that crater evolution occurred more rapidly during 0g conditions, resulting in deeper and wider craters compared to those formed under 1g. During the parabolic flight, five nozzle heights between 25D and 60D at 15 psig were tested. It was found that the trend of more rapid crater evolution with decreasing gravity followed for Lunar and Martian gravity.

Laminar flow airfoils represent a possible method of greatly increasing the efficiency and thus flight time of small civilian aircraft and drones. This is theoretically accomplished by allowing the boundary layer to remain laminar and attached over a wing, thus reducing the effects of drag over the wing. Unfortunately, laminar flow boundary layers are easily disturbed by a variety of outside effects, including particles, rainfall, transient pressure changes, and other phenomena. Disruptions to flow are able to cause transient or lasting disturbances, both of these scenarios working to prematurely trigger transition over a surface. For this reason it is important to understand the impact these conditions have on boundary layers, and to discover possible methods of mitigation. The focus of these studies lies in examining the differences of behavior and interactions between spots and wedges created by a variety of scenarios.These scenarios may be divided into the ricochet and the adhesion scenarios. The difference being that within the ricochet scenario the droplet rebounds from the surface while in the adhesion scenario some amount of the droplet volume remains attached. The ricochet scenario serves as comparison to a spot initiated by an impulsive disturbance, with the aim to investigate the importance of methodology to the disturbance creation. The adhesion scenarios investigate the interaction between the initial disturbance and the lasting disturbance that follows, and has three subcategories in which the droplet:1) retains sufficient mass to instigate a turbulent wedge.2) loses sufficient mass to only form a low-speed streak.3) retains sufficient mass to create an unstable low speed streak, capable of turning into a wedge. Raindrops will be abstracted into time-evolving body forces moving through channel flow making use of an in-house direct numerical simulation code. This code solves the Navier Stokes equations without utilizing any turbulencemodels by resolving the relevant length and time scales using a pseudo spectral algorithm based on the channel code algorithm of Kim Moin and Moser. The simulations will be examined through a turbulence and vorticity field of view, analysis of both large turbulent structures and smaller phenomena.

Precision finishing of hard/brittle materials is of ever-increasing relevance in industry today. Silicon nitride is such a material that has been used increasingly in demanding applications such as bearing rolling elements and in microelectronics. Silicon nitride is considered a difficult-to-grind material due to its high hardness, requiring the use of superabrasives. Several studies have documented the grinding or scratching of silicon nitride and the resulting mechanism of material removal. In general, those studies do not include abrasives typical in grinding process or were not conducted at typical grinding speeds. It is important to understand the interaction between the abrasive grain and the workpiece at grinding speed to better design manufacturing processes of silicon nitride material. A main objective of this research was to create a multi-grit scratch machine capable of producing speeds in the range of actual grinding processes for fast data generation. This machine utilizes a partially electroplated arbor to enable fast generation of individual scratches. In addition, the second objective of the research was to investigate the influence of various factors - wheel speed, depth of cut, workspeed – on grinding outcomes.

In this work, a novel neural implicit representation tomography algorithm based on Neural Radiance Fields is developed and demonstrated for 3D flow diagnostics. Neural Radiance Fields (NeRF) originate from the computer vision community that uses a machine learning approach to approximate a scene of interest as a continuous function using a neural network. The NeRF machine learning concept provides some advantages over traditional tomography methods, including i) a continuous approximation of the volume that removes the inherent limitation on volume resolution that is present in discretized representations, ii) a reduction in memory requirements for the volume prediction, and iii) an adaptable tomography framework that can include additional inputs, outputs, imaging models, and constraints. The method developed in this work, FluidNeRF, predicts the intensity per unit volume as a continuous function of 3D spatial (static) or 4D spatial-temporal (time-resolved) coordinates. FluidNeRF trains similarly to other algebraic reconstruction techniques, where the volume approximation is updated by comparing predicted and captured images of the volume. The image rendering technique of FluidNeRF employs an emission-based imaging model. Static and time-resolved FluidNeRF was evaluated using both i) a DNS-generated turbulent mixing jet and ii) an experimental dataset of a low-speed, smoke-entrained jet flow. The synthetic datasets systematically investigated the hyperparameters, camera configuration, and image noise regarding reconstruction quality. Static FluidNeRF was also compared to a traditional ART-based tomography model. The results show that i) FluidNeRF is a viable technique for tomography of flow diagnostics, ii) FluidNeRF produces comparable or superior reconstruction accuracy and is more robust to noise than traditional tomography methods, and iii) the method can scale to larger problems. Additionally, the results proved the FluidNeRF can be expanded to time-resolved reconstructions, which further compresses the volume representation and implicitly constrains the problem in time.

Future challenges in aerospace problems, spanning space exploration and military aircraft, demand advancements in several areas, including in-space 3D printing, high-performance missile technology, and rapid structural failure modeling for aircraft and rockets. However, materials used in these applications, such as additively manufactured (AM) materials and Energetic Materials (EM), exhibit defects at atomistic and microstructural scales, impacting their structural integrity and failure behavior. Addressing these challenges requires improved computational models for material characterization and dynamic failure simulation. Machine learning (ML) methods offer a promising approach to develop such models and enhance data processing efficiency. In this study, we propose various ML frameworks and techniques to aid in the development of efficient computational models for characterizing and simulating failure response in heterogeneous 3D printed materials and EMs. The first framework proposed is an autonomous ML model for fast characterization of pores, particles, grains and grain boundaries (GBs) from microstructural images of additively manufactured (AM) materials. To automate the process, the first ML model involves a classifier Convolutional Neural Network (CNN) to detect microstructures of pores or powder particles, versus GBs. For microstructures of pores or particles, a Convolutional Encoder-Decoder Network (CEDN) is used for generating binary segmentation images. Using an object detection ML network (YOLOv5), the particles’ or pores’ number, size and location are predicted with high accuracy. For GBs, Red-Green-Blue (RGB) segmentations are generated using an additional optimized CEDN. The Deep Emulator Network SEarch (DENSE) method (which employs the Covariance Matrix Adaptation - Evolution Strategy (CMA-ES)) is implemented to optimize the RGB CEDN in terms of computational speed. The characterization framework showed a significant improvement in analysis time when compared to conventional methods. The extracted defects can be used to rapidly estimate material properties in new unique heterogeneous AM material configurations. Lastly, the predicted defects and estimated material properties can be used as input to computational models to simulate their failure dynamics. Towards this effort, moving to simulation models of material failure, we then develop a Graph Neural Network (GNN) framework for simulating the failure response of brittle materials with multiple initial microcracks (5 to 19 microcracks) subjected to tension. First, a conventional eXtended Finite Element Model (XFEM-based) fracture model was used to generate training, validation, and test datasets. The number of cracks (5 to 19), their initial positions and orientations (0o, 60o, and 120o) were varied. The graph representation involved vertices placed at each crack-tip and edges connecting each crack-tip to its neighboring crack-tips within a 750mm radius. To achieve high prediction accuracy, the framework architecture is established using a sequence of physics-informed GNN-based predictions. The first prediction stage determines Mode-I and Mode-II stress intensity factors (stress distribution), the second stage predicts which microcracks will propagate (quasi-statics), and the final stage propagates crack-tip positions to the next time instant. The trained GNN framework is capable of simulating crack propagation, coalescence and corresponding stress distribution with speed-ups 6x–25x faster compared to an XFEM-based simulator. Next, while Microcrack-GNN was able to emulate crack propagation in problems involving multiple cracks with length of 300mm, orientations of 0o, 60o, and 120o, in a 2000mm × 3000mm domain under tensile load, the framework did not consider other problem-specific inputs. For instance, problems involving shear loadings, arbitrary crack orientations, arbitrary crack lengths, and different domain sizes were not predicted. An important challenge in supervised ML applications is the need for large training datasets. Extending Microcrack-GNN to handle these varying problem-specific inputs using traditional approaches would require generating large datasets for each parameter change. Therefore, to circumvent the issue of needing large training datasets for new initial conditions and loading cases, we use Transfer Learning (TL) approaches from ML theory to extend Microcrack-GNN’s capability. The new framework, ACCelerated Universal fRAcTure Emulator (ACCURATE), is generalized to a variety of crack problems using a sequence of TL update steps. The TL update steps are defined by sequentially training on significantly smaller datasets for: (i) arbitrary crack lengths, (ii) arbitrary crack orientations, (iii) square domains, (iv) horizontal domains, and (v) shear loadings. Using significantly small training datasets (20 simulations for each TL update step), ACCURATE achieves high prediction accuracy in Mode-I and Mode-II stress intensity factors, and crack paths for these problems. A key addition of ACCURATE is its ability to predict crack growth and stress evolution with high accuracy for unseen cases involving the combination of new boundary sizes with arbitrary crack lengths and crack orientations, for both tensile and shear loading. Additionally, we demonstrate a significant acceleration in simulation time of up to 2 orders of magnitude faster (200x) compared to the XFEM-based fracture model. The ACCURATE framework provides a universal computational fracture mechanics model that can be easily modified or extended in future work. Following this GNN framework along with TL, where the graph representation is formulated using vertices at each crack-tip, we then considered a mesh-based fracture simulator for phase field (PF) fracture models. As such, we develop a mesh-based GNN framework for emulating PF simulations of crack propagation. A key addition of this work is the introduction of Adaptive Mesh Refinement (AMR) to the graph representation itself. The framework (ADAPT-GNN) exploits the benefits of both ML methods and AMR by describing the graph representation at each time-step as the refined mesh itself. ADAPT-GNN is able to add nodes and edges dynamically as the mesh is refined. We predict the evolution of displacement fields (u,ν) and scalar damage field (or crack field, ϕ) with good accuracy compared to a conventional PF fracture model. The stress field (σ) is as also computed using the predicted displacements and PF parameter. In terms of computational efficiency improvement, ADAPT-GNN is 15-36x faster compared to serial execution of the PF model. While ADAPT-GNN showed significant speed-up and overall good prediction accuracy, the framework involved limitations. Mesh-based GNNs such as ADAPT-GNN require a large number of message-passing (MP) steps and suffer from over-smoothing for problems involving very fine mesh. To mitigate challenges with conventional mesh-based GNNs such as ADAPTGNN, we develop a multiscale mesh-based GNN framework mimicking a conventional iterative multigrid solver, coupled with adaptive mesh refinement (AMR). We use the framework to accelerate PF fracture problems involving coupled partial differential equations with a near singular operator due to near-zero modulus inside the crack. We define the initial graph representation using all mesh resolution levels. We perform a series of downsampling steps using Transformer MP GNNs to reach the coarsest graph followed by upsampling steps to reach the original graph. We use skip connectors from the generated embedding during coarsening to prevent over-smoothing. We use Transfer Learning (TL) to significantly reduce the size of training datasets needed to simulate different crack configurations and loading conditions. The trained framework showed accelerated simulation times, while maintaining high accuracy for all cases compared to physics-based PF fracture model. This work provides a new approach to accelerate a variety of mesh-based engineering multiphysics problems. In future efforts, the microstructure characterization framework can be used in conjunction with the developed mesh-based GNNs to accelerate computational failure models for heterogeneous AM materials with defects such as pores, particles, grains and GBs. Lastly, in an effort to aid in the development of new high-performance missiles we also integrate ML methods for Heterogeneous Energetic Materials (HEM). In the realm of HEMs, where structural defects like pores are prevalent, predicting initiation metrics such as pressure, temperature, and particle velocity becomes complex due to the diverse arrangements of these defects. Current prediction methods rely heavily on experimental data and computational simulations, which are limited by the need for exhaustive testing across various pore configurations. To overcome this limitation, we introduce a novel ML framework to forecast critical velocities in PBX-9501 samples featuring multiple pores of varying sizes, quantities, and spatial distributions. In this framework, we employ the Computational Hydrocode (CTH) to simulate the shock response of each sample upon impact by a flyer plate, followed by the utilization of an automated bisection algorithm to compute critical velocities. We then develop two ML models, CNNs and GNNs, for predicting critical impact velocities. We perform rigorous evaluation of these models to assess their performance in predicting critical velocities across scenarios involving diverse spatial distributions, pore quantities, and pore sizes. The ultimate objective of this work is to develop ML-guided models capable of directly predicting critical velocities for unseen pore structures without the need for CTH simulations. By doing so, this framework lays the groundwork for accelerated comprehension of how different pore configurations influence shock sensitivity in HEMs.

The question of how to feed humans in space has persisted since the beginning of space exploration. Tubes of food paste, dehydrated meals, freeze-dried packets, powdered drink pouches: space food has always needed to be compact, lightweight, and pre-cooked. But humans cannot thrive on rehydrated meals alone, and the current space food system is insufficient for the longer duration missions to the moon and Mars that will launch in the coming decades. The challenges to developing food system solutions that meet the demands of future missions are immense. This dissertation navigates the multifaceted realm of space food science, from establishing the importance of pleasure in space dining to creating practical solutions for space cuisine. I adopt a system engineering approach to illuminate food needs by mission type, identify challenges, and propose potential solutions, thereby building a technology development roadmap to meet the space food demands of the future. I then delve into the design of a space galley as part of the larger SIRONA project, a greenhouse design for a two-year mission on a Mars outpost. Finally, I discuss the development of a prototype pot, H0TP0T, designed to address the challenges of cooking in a liquid medium in microgravity. Through two parabolic microgravity flights, I prove the concept's feasibility.

Intense noise levels produced by high-speed military aircraft have adverse impact on the personnel and surrounding structures. Noise levels are often above 120dB (the human hearing pain threshold), which leads to physical and mental health problems, including hearing loss. These acoustic waves can also cause structural damage to surrounding buildings and aircraft control surfaces. Thus, a study of jet noise and control strategies for noise reduction is vital. There has been a renewed interest in the study of non-axisymmetric jets, in particular, those generated from rectangular nozzles, due to their superior air-frame integration properties and lower drag penalty in comparison to an axisymmetric nozzle. Many active and passive noise control techniques have been explored in the context of circular nozzles but very few on rectangular nozzles. One such active noise control technique involves leveraging the instabilities in the shear layer by imposing perturbations via the use of Localized Arc Filament Plasma Actuator (LAFPA). These plasma actuators have been shown to be effective in noise reduction for circular jets. However, its impact on rectangular jets has not been explored, posing numerous questions about the optimal forcing parameters (forcing frequency, duty cycle and phase difference between actuations), shear layer and acoustic response of the jet to forcing, flow field modifications and noise reduction efficacy unanswered. Also undetermined is its applicability to imperfectly expanded conditions. A computational study to determine the effects of LAFPA based control on the flow-field and acoustics of supersonic a Mach 1.5, 2:1 aspect ratio perfectly expanded rectangular jet is performed to address these queries. A preliminary linear analysis identifies that the frequency, St ∼ 1, has a relatively high overall amplification within the baseline shear layer while St ∼ 2 has the highest amplification rate, and is hence tested for control in the subsequent nonlinear simulations. Post validation of the baseline jet, effects of control in the context of noise reduction are studied at experimentally-guided forcing parameters, including frequencies, St = 0.3, 1.0 and St = 2.0, with duty cycles (DC), 20% and 50%. In general, high-frequency forcing reduces noise in the downstream direction, with the actuator signature appearing mostly in the sideline direction. St = 1 DC=50% yields an optimum balance between peak-noise reduction (of ∼ 1.5dB) and actuator tones, with control being most effective on the major axis plane that bisects the shorter edges of the nozzle. Shear layer response to the most effective forcing includes generation of successive arrays of mutually interacting staggered lambda vortices, which eventually energize streamwise vortical elements. Causal mechanisms of noise mitigation are further elucidated as follows; first, the control reduces the energy within the supersonic phase-speed regime of peak radiating frequencies, by redistributing a part of it into a high-frequency band. Second, it enhances azimuthal percolation of energy into the first and second helical modes at frequencies where noise reduction is seen, thus weakening the radiatively efficient axisymmetric mode. Finally, sound-producing intermittent events in the jet are significantly reduced, thereby minimizing the high-intensity acoustic emissions. This small perturbation-based control strategy results in only minor variations in the mean flow properties. However, reduced production and enhanced convection attenuate turbulent kinetic energy within the spreading shear layer in the controlled jet. These control parameters also produced less than 1% change in performance characteristics such as thrust. Post identification of optimal forcing frequency and duty cycle, a computational analysis is also performed to study the three-dimensional response of rectangular shear layers to plasma actuator-based control, in the context of sound mitigation of supersonic non-axisymmetric jets. The rectangular jet is now controlled using experimentally informed actuation patterns, referred to as M0, M1, M2, M3, Mπ and M+/-1. While the first five progressively increase the phase difference between successive actuators thus enhancing three-dimensionality of the shear layer structures, the latter corresponds to the flapping mode of the jet. Each actuation reveals unique near-field vortical and acoustic responses that have a profound impact on far-field noise levels. M0 actuation induces circumferentially interconnected strong streamwise vortices, while M1 actuation enhances the circumferential variability in the coherent structures. M2 actuation encompasses both these effects, and along with the least tonal impact of forcing, produces the most desirable far-field noise mitigation (∼ 2.6dB), contributed by a broadband reduction around the column mode peak of the baseline jet. Through a near-field analysis of the acoustic component, the efficacy of M2 actuation is attributed to the attenuation of the radiative efficiency of the jet, including reduced energy in the supersonic phase speeds, and redistribution of energy into the higher helical modes. Further, it curtails the nonlinear difference interactions in the plume that energize column mode frequencies, which often appear as strong intermittent sound-producing events. While the shear layer turbulent kinetic energy decreases with actuation, the controlled jets show minimal variations in mean flow properties, particularly under M2 actuation, suggesting this to be a promising small perturbation-based noise control strategy. Control authority was observed to saturate with higher phase differences (M3 and Mπ). Based on the knowledge of flow field impact of control on perfectly expanded jets, control is then applied to an over-expanded jet containing additional noise components such as BBSAN and screech. Forcing patterns M0, M1, M2, M3 and M+/-1 are studied in this context at a forcing frequency of St = 1 and duty cycle of 50%. Significant changes to mean flow properties such as core collapse location and spreading rate were observed with M0 and M+/-1 forcing while they remained relatively similar across other forcing cases. In general TKE levels were seen to decrease with increased phase difference between actuations. Far-field acoustic spectra of the baseline jet identified three distinct noise components corresponding to turbulent mixing, BBSAN and screech. Control is able to significantly affect all three components with the largest reduction observed with M3 forcing. However, the penalty arising from the actuation tone at the forcing frequency is significant. Directivity and amplitude of the forcing frequency tone is observed to vary across forcing sequences. An overall noise reduction of ∼ 2.5dB is observed with M3 forcing at downstream polar angles and upstream polar angles on both planes. Detoned noise levels which excludes the contribution from the actuation tone showed that all control cases were successful in reducing noise levels by ≥ 3dB. In particular, M3 forcing showed 6dB reduction in peak noise levels and 7dB reduction in the upstream directed noise levels. Further, M3 forcing was observed to weaken the coherent-structure/shock interactions resulting in a subdued tonal response. It was also observed to curtail upstream propagating guided jet modes which form an important part of the screech feedback loop and was also successful in reducing jet flapping. These modifications ensured reduction in BBSAN and screech in addition to reduction in mixing noise while having minimal impact on thrust.

The use of architecture built into materials has led to the development of mechanical and acoustic metamaterials, which have enabled extraordinary and unprecedented manipulation of material properties (both static and dynamic). A broad degree of tailorability has been shown in these materials, but challenges have remained, chiefly among them the application to full scale dynamics and high strain rates. Herein these challenges are grouped into three broad categories: the challenge of inverse design processes for the mesostructured, the challenge of incorporating wave effects into the inverse design, and the challenge posed by the incorporation of high strain rate effects into modeling and design. A deep dive into these challenges is undertaken, exploring each of them in more detail. Both modeling and experiments are used to make strides in addressing the challenges of inverse design and wave effects, in which an inverse design framework coupled with a reduced order discrete element model is proposed and implemented. Experimental work is then undertaken to more thoroughly explore the challenges posed by high strain rates. Through these efforts this work advances toward the goal of inversely designed high strain rate metamaterials.

This dissertation introduces a control mechanism for addressing neuronal growth problems, which can be applied to neurological disorders such as spinal cord injuries, Parkinson's disease, and Alzheimer's disease that limit neuronal functionality. We consider a recent medical therapy, Chondroitinase ABC (ChABC), as a control mechanism for these conditions. ChABC aims to treat these conditions by restoring neuron functionality through axon growth for damaged neurons. It manipulates the extracellular matrix (ECM), a network of macromolecules and minerals that surrounds neurons and regulates their activity. As a result, neurons produce tubulin proteins, which cause the axon to elongate. This process is modeled as a Partial Differential Equation (PDE), representing the behavior of tubulin concentration along the axon, with a moving boundary governed by Ordinary Differential Equations (ODE) consisting of the dynamics of the axon length and tubulin concentration in the growth cone. In this dissertation, we propose nonlinear design methods for a novel state feedback control law, an observer, and an output feedback control law for a one-dimensional model of axonal elongation. We demonstrate the robustness of the model to parameter changes of up to 40\% relative to the original design and analysis framework. We also address potential challenges, such as input delay, and propose a compensation mechanism to overcome these issues. In addition to theoretical challenges, we enhance the practical applicability of the proposed control law by introducing an event-triggered control mechanism that allows users to update the control law in a sample-based manner. We ensured local exponential stability and convergence of the closed-loop system, integrating the plant dynamics with the proposed control law across all these techniques. The performance of the designed control methods was validated through numerical simulations, demonstrating neuron elongation by up to three orders of magnitude. These advancements offer promising avenues for enhancing neural regeneration therapies and contribute significantly to the understanding of neural growth dynamics, while also advancing theoretical control of Stefan-type moving boundary PDE-ODE coupled systems.