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A new generation of high-performance, ultra-high strength (UHS) steelsSteel are required for lightweight applications at low prices. Traditionally, the outstanding properties of maraging (martensite-aging) steelsSteel emerge from semi-coherent nanoprecipitation in a martensitic matrix. However, coherency strains originating from the semi-coherent precipitates promote crackCrack initiation under load and thus inevitably reduce ductility. Multiple authors have suggested as a solution a highly-dense nanoprecipitation of Ni(AlAl,Fe) coherent precipitates with minimal latticeLattices misfit and validated the idea experimentally. In this work, we computationally designed, from processing to performance, a UHS steelSteel composed of Fe-Ni-Al-Mo with a higher specific yield strength and much lower price. Several foundational computational tools within the ICMEICME framework were adopted to design the steelSteel, including Thermo-Calc, TC-PRISMA, DICTRA, and TC-Python., Part of ISBN 9783031503481QC 20240307

A distorted air stream entering an aeroengine fan or compressor leads to harmonic forces on the rotating blades. These aerodynamically induced forces are well-known causes of blade vibration and associated fatigue problems. Significant levels of distortion arise from different sources like side wind and high angles of attack that occur at specific operating conditions. For aircraft with the engine closely integrated with the fuselage, the engine will be exposed to distortion during the entire flight cycle. With a focus on understanding the aeroacoustic interaction the computational fluid dynamics (CFD) analyses used here consider harmonics of the distortion. Harmonic responses are calculated from low to transonic speeds for a range of cases. Major phenomena and driving parameters affecting the forcing strength and pressure amplitudes in the blade passage are identified from the analyses. It is demonstrated that the forcing strength is strongly affected by the cut-on/cutoff conditions upstream and downstream of the blades. Also, depending on design parameters of the blade, the aeroacoustics of the blade passage is important for the resulting forcing. All analyses are made in two-dimensional over a wide range of flow conditions as well as geometric variations. The results of the study provide an increased understanding of the harmonic forcing of blades. A simple model is proposed that can identify conditions where increased pressure amplitudes in the blade passage may be expected. The sensitivities to parameters may also give some guidance in how design and operation can be adapted to reduce the aerodynamic forcing., QC 20240215

Thunderstorms can be a large source of disruption for European air-traffic management causing a chaotic state of operation within the airspace system. In current practice, air-traffic managers are provided with imprecise forecasts which limit their ability to plan strategically. As a result, weather mitigation is performed using tactical measures with a time horizon of three hours. Increasing the lead time of thunderstorm predictions to the day before operations could help air-traffic managers plan around weather and improve the efficiency of air-traffic-management operations. Emerging techniques based on machine learning have provided promising results, partly attributed to reduced human bias and improved capacity in predicting thunderstorms purely from numerical weather prediction data. In this paper, we expand on our previous work on thunderstorm forecasting, by applying convolutional neural networks (CNNs) to exploit the spatial characteristics embedded in the weather data. The learning task of predicting convection is formulated as a binary-classification problem based on satellite data. The performance of multiple CNN-based architectures, including a fully-convolutional neural network (FCN), a CNN-based encoder–decoder, a U-Net, and a pyramid-scene parsing network (PSPNet) are compared against a multi-layer-perceptron (MLP) network. Our work indicates that CNN-based architectures improve the performance of point-prediction models, with a fully-convolutional neural-network architecture having the best performance. Results show that CNN-based architectures can be used to increase the prediction lead time of thunderstorms. Lastly, a case study illustrating the applications of convection-prediction models in an air-traffic-management setting is presented., QC 20231127

An open-source simulation model for aircraft noise prediction is presented and validated using backpropagated noise measurements for a state-of-the-art engine and aircraft. The validation is focused on approach procedures and was performed using ground-based noise measurements that were taken at 17 recording stations for a total of 18 consecutive flights carried out during the morning of 8 April 2021. The flights were performed using two A321neo aircraft with LEAP-1A engines. It is demonstrated that the presented noise model provides a satisfactory estimation of the source noise for varying approach configurations and flight conditions. Configurations using a greater number of high-lift devices are particularly well predicted in the mid- and high-frequency regions, whereas the lower configuration settings show greater spectral deviations, which are partly attributed to measurement uncertainties caused by the increased aircraft–microphone distance. The model can predict the overall mean total sound intensity level within a 2 dB accuracy for all configurations, while the average predicted level at each microphone differs by less than 3 dB from the measurement average, for all cases except one. Variation in aircraft speed showed to have a strong impact on the predicted total noise, which matches the well-recognized sixth-power Mach number far-field sound intensity scaling law for airframe noise models, while the measurements indicated a less significant dependency. This is mainly due to installation effects and noise reduction measures that are not included in the models. Nevertheless, the variations in the spectra of the predicted and measured noise showed similar patterns., QC 20231128

Thunderstorms can be a large source of disruption for European air-traffic management causing a chaotic state of operation within the airspace system. In current practice, air-traffic managers are provided with imprecise forecasts which limit their ability to plan strategically. As a result, weather mitigation is performed using tactical measures with a time horizon of three hours. Increasing the lead time of thunderstorm predictions to the day before operations could help air-traffic managers plan around weather and improve the efficiency of air-traffic-management operations. Emerging techniques based on machine learning have provided promising results, partly attributed to reduced human bias and improved capacity in predicting thunderstorms purely from numerical weather prediction data. In this paper, we expand on our previous work on thunderstorm forecasting, by applying convolutional neural networks (CNNs) to exploit the spatial characteristics embedded in the weather data. The learning task of predicting convection is formulated as a binary-classification problem based on satellite data. The performance of multiple CNN-based architectures, including a fully-convolutional neural network (FCN), a CNN-based encoder–decoder, a U-Net, and a pyramid-scene parsing network (PSPNet) are compared against a multi-layer-perceptron (MLP) network. Our work indicates that CNN-based architectures improve the performance of point-prediction models, with a fully-convolutional neural-network architecture having the best performance. Results show that CNN-based architectures can be used to increase the prediction lead time of thunderstorms. Lastly, a case study illustrating the applications of convection-prediction models in an air-traffic-management setting is presented., QC 20231127

Thunderstorms can be a large source of disruption for European air-traffic management causing a chaotic state of operation within the airspace system. In current practice, air-traffic managers are provided with imprecise forecasts which limit their ability to plan strategically. As a result, weather mitigation is performed using tactical measures with a time horizon of three hours. Increasing the lead time of thunderstorm predictions to the day before operations could help air-traffic managers plan around weather and improve the efficiency of air-traffic-management operations. Emerging techniques based on machine learning have provided promising results, partly attributed to reduced human bias and improved capacity in predicting thunderstorms purely from numerical weather prediction data. In this paper, we expand on our previous work on thunderstorm forecasting, by applying convolutional neural networks (CNNs) to exploit the spatial characteristics embedded in the weather data. The learning task of predicting convection is formulated as a binary-classification problem based on satellite data. The performance of multiple CNN-based architectures, including a fully-convolutional neural network (FCN), a CNN-based encoder–decoder, a U-Net, and a pyramid-scene parsing network (PSPNet) are compared against a multi-layer-perceptron (MLP) network. Our work indicates that CNN-based architectures improve the performance of point-prediction models, with a fully-convolutional neural-network architecture having the best performance. Results show that CNN-based architectures can be used to increase the prediction lead time of thunderstorms. Lastly, a case study illustrating the applications of convection-prediction models in an air-traffic-management setting is presented., QC 20231127

”The Eagle has landed”. With this words, astronaut Neil Armstrong, together with astronaut Edwin ”Buzz” Aldrin, confirmed the safe landing on the Moon of the Apollo11 on July 20th, 1969. This achievement would have never been possible without the engineering behind the construction of the Moon lander. One of the most innovative features installed aboard was the pintle injector, a specific type of injector capable of precise metering of the propellants into the combustion chamber, and capable of throttling. Furthermore, the pintle injector has demonstrated its inherent combustion stability andgood mixing properties over time. The current work serves as a feasibility study for the use of an electric motor as the actuator for the pintle. This paper is the result of a 9-month internship at ArianeGroup GmbH, which is investigating the use of a pintle injector as a back-up option for a future ESA lunar lander mission. A preliminary design of the pintle was already produced, and the scope of this work is the design of the mechanical linkages and the actuation of the injector, with the choice of the method of actuation, the electric motor and the necessary components.

The pursuit of precision and flexibility in satellite missions has led to an increased number of formation flying missions being developed. These systems consist of multiple satellites flying at close distances (from a few kilometres to a few meters) to achieve common objectives. This master thesis delves into the domain of the Guidance, Navigation and Control (GNC) for formation flying satellite systems, aiming to propose a novel architecture of different sets of sensors capable of determining absolute and relative positioning of the formation, ensuring mission success. This research begins by providing an overall status of existing and tested in-space systems. It will be complemented with novel and other systems already tested and promising new technologies in development. The thesis then delves into the design of an absolute and a relative Extended Kalman Filter (EKF) for distributed Synthetic Aperture Radar (SAR) systems implemented as part of an in-house simulator. Concluding with the results when using simulated Global Navigation Satellite Systems (GNSS) data as the filter input. Finally, the thesis will be completed with a trade-off analysis of the sensor systems, which could be used in formation-flying satellite systems in the near future. The outcome of this thesis is a novel proposal of a set of sensors to be brought to space navigation, with a corresponding detailed trade-off analysis. Additionally, to validate some of the sensor systems, an EKF is proposed, implemented and tested with the results from an in-house formation flying simulator. This master thesis report is the outcome of the work done during an internship at the Microwave and Radar Institute of the Deutsche Zentrum für Luft- und Raumfahrt e.V. (DLR) – German Aerospace Center – in Oberpfaffenhofen, Bavaria, Germany.

Docking maneuvers are a relevant part of the modern space mission, requiring precision and safety to ensure the success of the overall mission. This thesis proposes using a non-linear Model Predictive Control (MPC) as a controller with various constraints to ensure safe docking maneuvers for a satellite. This was done in MATLAB using as a model for the satellite the Sliders used by the Robotics Lab at Luleå University of Technology (LTU). The controller was tested first on the MATLAB model and then briefly on hardware.The main objective of this thesis is to develop and implement an MPC-based control strategy to achieve safe docking maneuvers between two satellites. Great attention has been paid to implementing constraints, such as collision avoidance, and hardware constraints, such as thrust limits, to ensure the safety and reliability of the process.Through the MATLAB simulations, it was possible to indicate that the introduced constraints contribute significantly to the safe execution of docking maneuvers, preventing collisions, andoptimizing fuel usage. The controller successfully adapts to unforeseen disturbances and uncertainties in real-time, showcasing its robustness and reliability in dynamic space environments.The hardware simulations have shown that the controller operates as expected but needs further tuning to adapt to the hardware uncertainties.In conclusion, this thesis comprehensively explores MPC-based control strategies with constraints for space docking maneuvers. The positive results underscore this approach’s potential to ensure the safety and reliability of future space missions, opening avenues for further research and application in autonomous space systems.

This master's thesis was conducted in collaboration with ECAPS, where a conjugate heat transfer analysis on their High Performance Green Propulsion (HPGP) 22N thruster was done. ECAPS is a Swedish propulsion company specializing in green propulsion. They develop thrusters for spacecraft orbit and attitude control, utilizing the propellant LMP-103S. LMP-103S is a non-toxic propellant, in contrast to the hazardous monopropellant hydrazine commonly used in thrusters. A previous master's thesis modified the original design of the 22N thruster to make it compatible with additive manufacturing. Some concerns about heat transfer in the feed tube surfaced with the new design as it showed elevated temperatures. The feed tube is a component that works as a pathway where liquid propellant is transported from the flow control assembly to the reactor chamber assembly, where combustion begins. The goal of this master's thesis was to determine the temperatures the liquid propellant reached, and to assess if the liquid propellant was at risk of vaporization in the feed tube before reaching the reactor chamber assembly. Since the feed tube is a limited volume, vaporization of the liquid propellant in the feed tube could have devastating consequences of the structure. Ansys Fluent was used as the Computational Fluid Dynamics (CFD) software, along with the Computer Aided Design (CAD) software NX and Matlab for data handling. Four extreme case scenarios were determined to be simulated, varying the liquid propellant inlet temperatures from highest to lowest operable temperatures, as well as the thruster's highest and lowest operable inlet pressures. A literature study on conjugate heat transfer in CFD was done, along with determination and calculations of necessary parameters for a correct simulation setup, and a grid independence study. Both steady-state and transient simulations were conducted. The results indicate that when the thruster operates with the highest inlet pressure, ther

The constant growth of space debris and the associated risks force the space community to find solutions to mitigate them. Today the most advanced solutions to dispose of satellites and rocket stages after the end of mission consists of moving them either into a graveyard orbit or towards an atmospheric re-entry ending in the demise of both spacecraft and its materials. Alternative solutions should be considered, such as providing a sustainable solution by reusing materials in space. However, it is crucial to understand better the ageing process of the materials present in currently active spacecraft and space debris. The space environment causes degradation and damage over time, making the state of those materials uncertain for potential re-use. Degradation effects have been studied as a source mechanism to result in paint flakes, ejecta particles, or delaminated insulation foils released into the space environment and sustaining a positive feedback loop through potential impacts into spacecraft. A better understanding of degradation effects would also help to better characterize the small debris environment and its evolution. The current materials databases used by the space industry could be useful tools to select materials for satellite missions with respect to their reusability, but they often do not include the evolution of material properties in space after the end of mission.This study will investigate the impact of the damage effects of radiation and meteoroid impact on solar panels. During this research, the methodology used to analyse these effects was explained. The results showed that radiation caused the most damage and could cause solar panels to lose more than a third of their performance over a period of 50 years. It was therefore possible to estimate the quantity of solar panels available for re-use. It was concluded that the results were valid, but that to obtain more accurate data, all the different types of deterioration would also have to be co, Creaternity

”The Eagle has landed”. With this words, astronaut Neil Armstrong, together with astronaut Edwin ”Buzz” Aldrin, confirmed the safe landing on the Moon of the Apollo11 on July 20th, 1969. This achievement would have never been possible without the engineering behind the construction of the Moon lander. One of the most innovative features installed aboard was the pintle injector, a specific type of injector capable of precise metering of the propellants into the combustion chamber, and capable of throttling. Furthermore, the pintle injector has demonstrated its inherent combustion stability andgood mixing properties over time. The current work serves as a feasibility study for the use of an electric motor as the actuator for the pintle. This paper is the result of a 9-month internship at ArianeGroup GmbH, which is investigating the use of a pintle injector as a back-up option for a future ESA lunar lander mission. A preliminary design of the pintle was already produced, and the scope of this work is the design of the mechanical linkages and the actuation of the injector, with the choice of the method of actuation, the electric motor and the necessary components.

The constant growth of space debris and the associated risks force the space community to find solutions to mitigate them. Today the most advanced solutions to dispose of satellites and rocket stages after the end of mission consists of moving them either into a graveyard orbit or towards an atmospheric re-entry ending in the demise of both spacecraft and its materials. Alternative solutions should be considered, such as providing a sustainable solution by reusing materials in space. However, it is crucial to understand better the ageing process of the materials present in currently active spacecraft and space debris. The space environment causes degradation and damage over time, making the state of those materials uncertain for potential re-use. Degradation effects have been studied as a source mechanism to result in paint flakes, ejecta particles, or delaminated insulation foils released into the space environment and sustaining a positive feedback loop through potential impacts into spacecraft. A better understanding of degradation effects would also help to better characterize the small debris environment and its evolution. The current materials databases used by the space industry could be useful tools to select materials for satellite missions with respect to their reusability, but they often do not include the evolution of material properties in space after the end of mission.This study will investigate the impact of the damage effects of radiation and meteoroid impact on solar panels. During this research, the methodology used to analyse these effects was explained. The results showed that radiation caused the most damage and could cause solar panels to lose more than a third of their performance over a period of 50 years. It was therefore possible to estimate the quantity of solar panels available for re-use. It was concluded that the results were valid, but that to obtain more accurate data, all the different types of deterioration would also have to be co, Creaternity

Docking maneuvers are a relevant part of the modern space mission, requiring precision and safety to ensure the success of the overall mission. This thesis proposes using a non-linear Model Predictive Control (MPC) as a controller with various constraints to ensure safe docking maneuvers for a satellite. This was done in MATLAB using as a model for the satellite the Sliders used by the Robotics Lab at Luleå University of Technology (LTU). The controller was tested first on the MATLAB model and then briefly on hardware.The main objective of this thesis is to develop and implement an MPC-based control strategy to achieve safe docking maneuvers between two satellites. Great attention has been paid to implementing constraints, such as collision avoidance, and hardware constraints, such as thrust limits, to ensure the safety and reliability of the process.Through the MATLAB simulations, it was possible to indicate that the introduced constraints contribute significantly to the safe execution of docking maneuvers, preventing collisions, andoptimizing fuel usage. The controller successfully adapts to unforeseen disturbances and uncertainties in real-time, showcasing its robustness and reliability in dynamic space environments.The hardware simulations have shown that the controller operates as expected but needs further tuning to adapt to the hardware uncertainties.In conclusion, this thesis comprehensively explores MPC-based control strategies with constraints for space docking maneuvers. The positive results underscore this approach’s potential to ensure the safety and reliability of future space missions, opening avenues for further research and application in autonomous space systems.

The pursuit of precision and flexibility in satellite missions has led to an increased number of formation flying missions being developed. These systems consist of multiple satellites flying at close distances (from a few kilometres to a few meters) to achieve common objectives. This master thesis delves into the domain of the Guidance, Navigation and Control (GNC) for formation flying satellite systems, aiming to propose a novel architecture of different sets of sensors capable of determining absolute and relative positioning of the formation, ensuring mission success. This research begins by providing an overall status of existing and tested in-space systems. It will be complemented with novel and other systems already tested and promising new technologies in development. The thesis then delves into the design of an absolute and a relative Extended Kalman Filter (EKF) for distributed Synthetic Aperture Radar (SAR) systems implemented as part of an in-house simulator. Concluding with the results when using simulated Global Navigation Satellite Systems (GNSS) data as the filter input. Finally, the thesis will be completed with a trade-off analysis of the sensor systems, which could be used in formation-flying satellite systems in the near future. The outcome of this thesis is a novel proposal of a set of sensors to be brought to space navigation, with a corresponding detailed trade-off analysis. Additionally, to validate some of the sensor systems, an EKF is proposed, implemented and tested with the results from an in-house formation flying simulator. This master thesis report is the outcome of the work done during an internship at the Microwave and Radar Institute of the Deutsche Zentrum für Luft- und Raumfahrt e.V. (DLR) – German Aerospace Center – in Oberpfaffenhofen, Bavaria, Germany.

This master's thesis was conducted in collaboration with ECAPS, where a conjugate heat transfer analysis on their High Performance Green Propulsion (HPGP) 22N thruster was done. ECAPS is a Swedish propulsion company specializing in green propulsion. They develop thrusters for spacecraft orbit and attitude control, utilizing the propellant LMP-103S. LMP-103S is a non-toxic propellant, in contrast to the hazardous monopropellant hydrazine commonly used in thrusters. A previous master's thesis modified the original design of the 22N thruster to make it compatible with additive manufacturing. Some concerns about heat transfer in the feed tube surfaced with the new design as it showed elevated temperatures. The feed tube is a component that works as a pathway where liquid propellant is transported from the flow control assembly to the reactor chamber assembly, where combustion begins. The goal of this master's thesis was to determine the temperatures the liquid propellant reached, and to assess if the liquid propellant was at risk of vaporization in the feed tube before reaching the reactor chamber assembly. Since the feed tube is a limited volume, vaporization of the liquid propellant in the feed tube could have devastating consequences of the structure. Ansys Fluent was used as the Computational Fluid Dynamics (CFD) software, along with the Computer Aided Design (CAD) software NX and Matlab for data handling. Four extreme case scenarios were determined to be simulated, varying the liquid propellant inlet temperatures from highest to lowest operable temperatures, as well as the thruster's highest and lowest operable inlet pressures. A literature study on conjugate heat transfer in CFD was done, along with determination and calculations of necessary parameters for a correct simulation setup, and a grid independence study. Both steady-state and transient simulations were conducted. The results indicate that when the thruster operates with the highest inlet pressure, ther

This report investigates the kinetics of lubricant molecules in the HAMR air bearing to understand the initiation and growth of PFPE contamination on the head surface. The collisions with the air bearing induce three forces—drag, thermophoresis, and lift. Of these, we find that lift forces are negligible. Then, a sensitivity analysis of the remaining two forces reveals the conditions where they dominate. Further, a hybrid simulation strategy is utilized to track their movements. The results show that the contaminations (smear) highly depend on the interplay between the thermophoresis and drag forces. We then explain the mechanism of the formation of the various observed patterns. Finally, we offer some recommendations to exploit the air bearing to contain smear on the head.

Electric multirotor aerial vehicles are an emerging technology with extensive potential applications across a wide range of fields, but flight time and range limitations currently impose significant constraints on the use of such vehicles. Improving the vehicle energy performance is therefore a critical research topic, and one promising strategy is to optimize operational energy efficiency through model-based motion planning and control. While there has been extensive research on the topic and important progress has been made, existing works generally oversimplify or disregard key vehicle subsystem behaviors, and therefore fail to capture the complete energy dynamics and exploit the full energy saving potential. To address this gap in the state of the art, a complete system-level vehicle model is developed and applied to planning and control, aiming at achieving significant energy performance improvements in this dissertation.The model captures all relevant subsystem dynamics related to the vehicle energy performance, including propeller aerodynamics, motor assembly electro-mechanical dynamics, battery electrical dynamics, and airframe rigid-body dynamics. Through experimental validation, the model demonstrates a high degree of fidelity over a wide range of operating conditions. The model is then used to demonstrate the importance and necessity of incorporating individual dynamics into model-based planning and control, highlighting the impact of battery dynamics on the propulsion limits, the influence of propeller (inflow) aerodynamics on the energy performance, and the breakdown of vehicle energy efficiency to each subsystem dynamics. An energy-optimal trajectory generation and feedback control framework is then developed based on this model, and is shown to reduce energy usage significantly relative to a baseline controller in both simulations and experimental validation over a range of waypoint-to-waypoint flight operations. Polynomial approximations of the optim

Hybrid rockets have recently become a more and more desirable method for small satellitepropulsion, due to their lack of safety issues compared to their liquid and solid rocket counterparts. A major reason for this is because the fuel and oxidizer are both separated by distance and state when stored in a hybrid rocket. This also makes it relatively more difficult to ignite and start up the rocket. While many igniter systems have been invented, currently no reliable, self-igniting system has been flown. Recently, a Hydrogen-Oxygen torch was designed, built, and tested in UC Davis’ Energy Research Lab. Methane is typically used in torch igniters for lab-scale testing of hybrid rocket motors. A side-by-side comparison on the same igniter system between Hydrogen and Methane as the igniter fuel was done to investigate which, if any, fuel can exhibit better transient and/or steady state performance. Due to the higher heat of combustion, adiabatic flame temperatures and theoretical characteristic exhaust velocities when reacting with Oxygen, Hydrogen was found to have more reliable and repeatable ignition transients. The solid fuel regression rates were also found to be higher when using Hydrogen despite competition to burn with Oxygen between Hydrogen and the solid Nylon-6 fuel. These performance benefits come at the cost of being less volumetrically efficient than Methane as Hydrogen has a significantly smaller density at a given temperature and pressure.

A vital element of any human-rated mission is the Environmental Control and Life Support System (ECLSS), composed of multiple subsystems, including an Air Revitalization subsystem that maintains a breathable atmosphere. Tracking performance, identifying performance degradation, predicting remaining useful life of components, and performing maintenance on such a critical system are paramount to creating a safe, habitable environment and are thus key research areas at the UC Davis Center for Spaceflight Research. This thesis outlines the design, build, and test of the ZeoDe (Zeolite Capacity Degradation) testbed at the UC Davis Center for Spaceflight research, as well as the background research that went into its conception. This testbed is a chemically functional CO2 removal system that generates degradation data for prognostics through the introduction of humidity into the system. The introduction of humidity can occur in a space habitat due to leaks or other faults. Humidity build-up within the system leads to CO2 removal capacity degradation of the sorbent. Thus, the study of sorbent degradation is of paramount importance to any zeolite-based CO2 removal system deployed on future spacecraft. The maintenance of such a system is equally important. The base requirements of the ZeoDe system take both human and robotic maintainability into account, along with the development of a twin robotically manipulable mockup that was also built up at the UCD Center for Spaceflight Research. The ZeoDe testbed will allow UC Davis, NASA, and any visiting researcher to investigate sensor criticality, degradation physics, detection sequences, and maintenance plans for a degraded ECLSS CO2 removal unit in both autonomous robotic tasks and integrated robot/human teaming scenarios. The modular build will also allow for future research and visiting research to take place at the center to further ECLSS research for future space habitation.

Without a precedent to laundering clothes off-Earth, a preliminary solution is required to develop a spaceflight laundry machine capable of operating in various gravity fields. With this thesis’ proposed solution, human exercise to power an agitating bladder, a closed-loop hydraulic system, and a wastewater sensor suite provide a desirable environment for quantifying waste-mass transfer away from textiles while minimizing textile damage. Bond Graph Theory is used to model the proposed solution and to evaluate how human-power and valve configurations affect the system’s cleaning performance. Bond Graph simulation results reveal preliminary performance metrics and hardware significantly impacting the machine’s performance. A human-powered laundry machine prototype and model are essential for maturing the technology to spaceflight readiness.

The enhancement of skin friction drag and surface heat flux by the transition to turbulence is a crucial physical phenomenon in wall-bounded flows. An interpretable mapping of how various flow phenomena such as turbulence and pressure gradient influence these key surface quantities is desirable for advancing our understanding of fundamental flow physics, as well as informing engineering design analysis and developing efficient flow control techniques. To accomplish such a mapping, in this study, integral forms based on the first-moment of conservation equations are developed. The angular momentum integral (AMI) equation, obtained from the first moment of the momentum equation, yields an identity for the skin friction coefficient (friction drag). Furthermore, the moment of (total) enthalpy integral (MTEI) equation, derived from the first moment of the en- ergy equation, provides a mapping for the Stanton number (surface heat flux). This first-moment approach uniquely isolates the skin friction (or surface heat flux) of a laminar BL in a single term that depends only on the Reynolds number (or Peclet number) most relevant to the flow’s engineer- ing context, hence other terms are interpreted as augmentations or reductions relative to the laminar case having the same Reynolds number (or Peclet number).In the case of zero-pressure-gradient incompressible transitional BLs, the AMI and MTEI equations examine the peak friction drag and surface heat flux during the transition. These tools demonstrate and quantify how the streamwise growth of the BL and the mean wall-normal flux resist the extreme growth of turbulent enhancement via Reynolds shear stress. This rapid growth of turbulence during transition imposes near-wall streamwise acceleration that results in a negative wall-normal velocity very close to the wall. For a fully turbulent regime, the explicit turbulent enhancement is the primary process of near-wall momentum (or heat) flux, not molecular transport. Consequent

Pressurized water reactors are designed to operate in a single-phase flow. However, during a flow loss or other off-design conditions liquid temperature may exceed saturation temperature and, if a continuous film of gas forms, a boiling casualty may result. If superhydrophobic surfaces are introduced among the fuel cell assembly, vapor bubbles show an affinity to these surfaces and gas may coalesce to escape faster, resulting in a larger margin to reach critical heat flux. In the present study, we consider air and liquid water mixture examining the overall flow dynamics in a case with no bulk liquid flow, reminiscent of a case with coolant pump failure. The parameter ranges examined span Reynolds number based on gas superficial velocity up to 5300 and produced bubble with bond numbers from 1 to 270, and Weber numbers based on estimated terminal velocity from 0.6 to 150. The Morton number was fixed at 2.63×10-11. As the flow with high gas volume fraction becomes optically opaque and is sensitive to intrusive instrumentation, a custom-built photon-counting dual energy threshold X-ray computed tomography system is employed for measurement of the time average void fraction within the bundle non-intrusively. Two dual plane wire mesh sensors upstream and downstream of the rod bundle are employed to obtain comparison void fraction, velocity profiles and bubble size distributions. Additionally, traditional pressure-based gas holdup measurements are employed to calculate time- and volume-averaged void fraction. The data show that the presence of superhydrophobic surface being present in the rod bundle results in a significantly lower gas volume fraction and higher localized void fraction at the superhydrophobic coating, as compared to those in a similar rod bundle without superhydrophobic internals. Graphical abstract: (Figure presented.)

Eulerian-Lagrangian (EL) models are developed that account for stochasticity and randomness in tracers of inertial particles forced by a carrier flow phase. Central to the novelty of the models is a forcing formulation that uses a series expansion with random coefficients to account for epistemic and aleatoric uncertainties, in lieu of commonly used stochastic, random-walk processes.Starting from randomly forced ordinary differential equations that govern the Lagrangian inertial point-particle tracer dynamics, Lagrangian cloud and Liouville models are derived. Both cloud and Liouville models are closed and are shown to more accurately and computationally efficiently predict the propagation of the forcing randomness into confidence intervals of the particle phase solution as compared to Monte Carlo sampling methods.The closed and predictive particle cloud tracer models the mean motion and deformation of a cloud of inertial particles at a singular point in space and along its Lagrangian trajectory in time. The tracer builds upon the Subgrid Particle-Averaged Reynolds Stress Equivalent (SPARSE) formulation first introduced in Davis et al. (2017) for the tracing of particle clouds. Using a combination of the forcing models, averaging and a truncated Taylor series expansion to estimate the statistical correlations in the cloud region, the SPARSE model is closed and achieves a third convergence for the confidence interval with respect the number of samples.The Liouville models are rigorously derived with the method of distributions and do not require truncation or ad-hoc assumptions. The deterministic PDF models are described by hyperbolic partial differential equations (PDEs). In Eulerian form, the PDEs are solved with grid-based spectral methods. To recover the Lagrangian character of the disperse phase, the method of characteristics is employed to derive a PDF formulation based on the computation of flow maps, circumventing difficulties of solving high-dimensional PDE

The autonomous decision-making capability of spacecraft is crucial for future missions, allowing for more versatile, independent, and affordable operations in space. The Earth-Moon system (i.e., cislunar space) is expected to become strategically important as national space agencies and private companies leverage the Moon as a platform to reach farther destinations. With increased traffic in the Earth-Moon region, a spacecraft's ability to autonomously navigate will be essential for the safer and more sustainable exploration of space. The objective of this investigation is to assess the feasibility of efficient autonomous optical navigation in the vicinity of the Moon. This Thesis implements recent breakthroughs in deep learning, leveraging convolutional neural networks (CNN), for computer vision. In the case of a spacecraft traveling to the Moon, the CNN is trained to identify key surface features, such as craters, to assist with the autonomous-relative-navigation process. Though CNNs have been proven reliable in terrain-relative navigation (TRN) close to the lunar surface, their applicability at extended distances remains unexplored. This study present a novel approach that harnesses CNNs for crater detection up to 70000 km using synthetic images with annotated craters from a comprehensive database. We employ the computer-vision model YOLOv5 for object detection and utilize POV-Ray for realistic lunar-surface rendering, along with JPL SPICE for precise Sun and spacecraft positioning. Of the three models trained, the model trained with the 10000 largest craters on the surface of the Moon displayed the highest potential for generalized crater detection. Key factors influencing the area and angular predictions were analyzed to inform on the feasibility and expected performance of autonomous navigation. Our findings display an average crater area percent error of 6.834% and an average normalized angular error of 0.088%. Post-analysis of our results indicate that the p

In this dissertation, we are going to develop safe, efficient motion planning algorithms for the operations of autonomous systems in uncertain environments. First, we assume that the uncertainties obey Gaussian distribution. We introduce a risk-bounded and fairness-aware path planning algorithm for multiple aircraft operating in such environments. This algorithm advances the sampling-based path planning with the risk domain formulation to generate stochastically safety assured collision-free paths that are robust to both vehicle and environmental obstacle uncertainties for multiple aircraft. Simulation studies demonstrate the promising performance of the proposed algorithm. Next, a safety assured decentralized online guidance algorithm with airborne self-separation capability is proposed and analyzed for multi-aircraft autonomous flight operations under uncertainties. The problem is formulated as a multi-agent Markov Decision Process with continuous action space and is solved by a customized decentralized online algorithm based on Monte Carlo Tree Search. A comprehensive numerical study shows that the proposed algorithm can provide safe onboard guidance with guaranteed low near mid-air collision probability in uncertain and high-density airspace environments. Given non-Gaussian uncertainties, we formulate a path planning problem for UAVs with those uncertainties and solve it through a chance-constrained optimization framework considering the convex approximation of the data-driven probabilistic reachable set. In this problem, the uncertainties of the model are converted to a convex approximation of a probabilistic reachable set and are then incorporated into the optimization framework. An efficient convex optimization algorithm is applied to solve the formulated optimization framework, and we achieve an optimal path for the UAV while ensuring the probability of collision is bounded by a threshold. Finally, numerical simulation validates the efficacy of our proposed

Aerospace vehicle design is a complex process involving multiple engineering disciplines such as aerodynamics, structures, propulsion, and controls. This complexity led to the emergence of multidisciplinary design optimization (MDO), a field that employs numerical optimization methods to improve the designs of engineering systems while simultaneously considering multiple disciplines. Integrating all disciplines significantly increases the problem's complexity, which motivates the use of gradient-based optimization methods with analytical computation of the derivatives. This approach has demonstrated considerable success in tackling practical large-scale MDO problems with hundreds of design variables. Recent applications can be found in the conceptual design of electrified aircraft, unmanned aerial vehicles, and launch vehicles. Presently, most MDO applications formulate and solve deterministic optimization problems in which the objective and constraint functions do not consider randomness. However, real-world scenarios introduce uncertainties arising from factors like variations in operating conditions, parameter fluctuations, and manufacturing discrepancies. Incorporating these uncertainties into MDO problems transforms them into MDO under uncertainty (MDOUU) problems. Addressing well-defined MDOUU problems can enhance the robustness and reliability of MDO-optimized designs in real-world scenarios. This dissertation presents a suite of graph-accelerated uncertainty propagation methods, designed to tackle various forward uncertainty quantification (UQ) and MDOUU problems. At the core of these methods lies a new computational graph transformation method called Accelerated Model Evaluations on Tensor Grids using Computational Graph Transformations (AMTC). AMTC leverages the sparsity in the computational graphs of multidisciplinary systems to accelerate tensor-grid evaluations. This approach has been effectively combined with the non-intrusive polynomial chaos method t

Aerial robots, including rotary-wing and fixed-wing unmanned aerial vehicles or UAVs, have shown great capabilities in surveying as well as search and rescue from above. However, either rotary-wing or fixed-wing UAVs have nearly insoluble flaws. In order to overcome the under-actuating nature of multi-rotor UAVs, Chapter 2 proposes modeling methods and control schemes for fully-actuated hexacopters. Additionally, rotary-wing robots suffer from limited battery life as well as lack of fail-safe mechanism upon losing motors, while fixed-wing robots lacks the ability to take off and land vertically. Therefore, Chapter 4 proposes a bio-inpired hybrid aerial robot to extend mutli-rotor flight time and fail-safe capability and provide fixed-wing glider with vertical take-off and landing or VTOL capability. Moreover, to extend the flight time and optimize the energy consumption of multi-rotor UAVs, Chapter 3 proposes a multi-disciplinary design optimization based flight trajectory optimizer involving linear rotor inflow models to reduce flight time or energy consumption of specific missions.In terms of unmanned ground vehicles or UGVs used for perception and mapping, there has been a research gap to provide a low-cost, highly agile over-actuated chassis design. Chapter 5 proposes a 3D-printable double Ackermann steering chassis design with 2-wheel standing and balancing capability to fill in this gap. Chapter 6, on the other hand, proposes the system design of a UGV capable of performing perception and mapping in a limited lighting, unstructured, and GPS-denied environment based on a nevertheless nonholonomic chassis, where primary concern becomes the reliability in performing real-time mapping and preservation of solely static environment.The last but not least topic discussed in this dissertation is to promote the role of UAV imagery in earthquake response. In Chapter 7 we combine the traditional UAV plan view perspective with north and east elevation view video data to p

Hydrogen (H2) combustion and solid oxide fuel cells (SOFCs) can potentially reduce aviation-produced greenhouse gas emissions compared to kerosene propulsion. This paper outlines a methodology for evaluating performance and emission tradeoffs when retrofitting conventional kerosene-powered aircraft with lower-emissionH2 combustion and SOFC hybrid alternatives. The proposed framework presents a constant-range approach for designing liquid hydrogen fuel tanks, considering insulation, sizing, center of gravity, and power constraints. A lifecycle assessment evaluates greenhouse gas emissions and contrail formation effects for carbon footprint mitigation, while a cost analysis examines retrofit implementation consequences. A Cessna Citation 560XLS+ case study shows a 5% mass decrease for H2 combustion and a 0.4% mass decrease for the SOFC hybrid, at the tradeoff of removing three passengers. The lifecycle analysis of green hydrogen in aviation reveals a significant reduction in CO2 emissions for H2 combustion and SOFC systems, except for natural-gas-produced H2 combustion, when compared to Jet-A fuel. However, this environmental benefit is contrasted by an increase in fuel cost per passenger-km for green H2 combustion and a rise for natural-gas-produced H2 SOFC compared to kerosene. The results suggest that retrofitting aircraft with alternative fuels could lower carbon emissions, noting the economic and passenger capacity tradeoffs.

This Dissertation investigates the three-dimensional nature of dynamic stall and introduces a new variational formulation for vortex dynamics, both contributing to a deeper understanding of aerodynamic phenomena. The first part of the research involves numerical simulation of the flow around a harmonically pitching NACA 0012 airfoil using Unsteady-Reynolds-Averaged Navier–Stokes (URANS) and Detached Eddy Simulation (DES) solvers, including Delayed-DES (DDES) and Improved-DDES (IDDES). Both two- and three-dimensional simulations are conducted, with results compared against experimental measurements. It is found that three-dimensional simulations, particularly those using DES solvers, outperform two-dimensional ones in capturing the different stages of dynamic stall and predicting the lift dynamics. The IDDES simulations, which are inherently three-dimensional, accurately model the cascaded amalgamation of vortices forming the dynamic stall vortex, supporting the hypothesis that dynamic stall is intrinsically a three-dimensional phenomenon. Since the complex flow in dynamic stall is mainly related to vortex-vortex interactions, richer models of vortex dynamics are needed to develop a reduced-order model for dynamic stall in the future. For this goal, the second part of the study introduces a new variational formulation for vortex dynamics based on the principle of least action. Unlike the traditional Kirchhoff-Routh (KR) function, which describes vortex dynamics through first-order differential equations of motion derived from the Biot-Savart law, this new formulation results in second-order differential equations that define vortex accelerations. This leads to more complex dynamics, such as unique patterns formed by equal-strength, counter-rotating vortices with different initial velocities. Moreover, the new model can incorporate arbitrary external body forces; when an electrodynamic force is considered, it reveals rich, counter-intuitive behaviors that cannot be ca

Electrospray thrusters are unique among electric propulsion due to their inherent scalability and their potential to cover a broad range of specific impulses and thrust. Capillary emitters, in particular, offer advantages such as enhanced controllability and reliability over externally wetted and porous emitters. However, prototypes of capillary emitter electrospray thrusters have so far achieved modest specific impulses compared to other types of emitters. The maximum specific impulse of electrosprays is closely tied to the minimum flow rate at which cone-jets can emit stably. This study investigates how altering the geometry of capillary emitters can increase the specific impulse while maintaining the advantages that capillary emitters offer over externally wetted and porous emitters. Time-of-flight and direct mass flow rate measurements were conducted to characterize electrosprays of various ionic liquids in a vacuum. It was found that electrosprays with emitters with smaller diameters resulted in a lower stable minimum flow rate by more than an order of magnitude compared to those with larger diameters, leading to a two- to threefold increase in the maximum specific impulse.

This MS thesis studies how to resolve the feed-through parasitic capacitance always present in MEMS vibratory capacitive sensors. MEMS capacitive sensors have been integrated into various applications due to their compact size, low power consumption, and compatibility with IC components. However, feed-through parasitic capacitance is a major issue that directly impacts the actual sensor reading, especially for miniaturized sensors. The unintended capacitance readings can result in measurement inaccuracies and degrade the signal-to-noise ratio (SNR). Electromechanical Amplitude Modulation (EAM) technique is used in this thesis to address the issue caused by feed-through parasitic capacitance within the sensors. EAM technique involves modulating a carrier signal and an AC driving signal to the sensor. A high-frequency carrier signal is applied to the sensor, modulating the sensor outputs to a higher-frequency region as sidebands of the carrier signal. This approach isolates the motional signal of the sensor from parasitic capacitance and background noise. The motional sensor output can be then reconstructed through demodulation and filtering. The modeling results were confirmed experimentally to mitigate the parasitic capacitance from the true sensor output using the EAM technique. Two MEMS vibratory capacitance sensors were the focus of this thesis for experimentally validation of the EAM technique: an Epi-Seal Toroidal Ring Gyroscope (TRG) and a Frequency-Modulated (FM) Accelerometer. The experimental setup consists of trans-impedance amplifiers, a control feedback loop with a Phase-Locked Loop (PLL), and Automatic Gain Control (AGC) to maintain the sensor in self-resonance with consistent amplitude and phase. Key performance metrics of the MEMS sensors were extracted, including the resonance frequency, quality factor, sensitivity, and noise parameters from Allan deviation analysis. The results of both sensors confirmed that the EAM technique can mitigate and increa

The proper construction of aerodynamic databases to support an ascent vehicle during the development phases, and flight, is a difficult task. It encompasses many different flight regimes and several types of aerodynamic coefficient data. The focus of this work addresses integrated force and moment, line load, and surface pressure aerodynamic databases covering the ascent phase of the vehicles flight. In particular, the work deals with a missing component in the uncertainty quantification of these databases, in which existing processes are able to estimate integrated aerodynamic coefficient uncertainty, however estimating an equivalent uncertainty for corresponding distributed loads is not done. The phrase "distributed loads" is used to refer to both line load and surface pressure data, as opposed to the scalar-valued integrated aerodynamic coefficients.The primary motivation of this work was to create a method that could generate uncertain distributed loads that are consistent with the quantified uncertainty in the integrated aerodynamic coefficients, while also being consistent with the statistical distributions of known data. A brief motivation and outline is included, before Chapter 2 introduces required background concepts. The methods developed for this work are described in Chapter 3 along with a brief survey of similar published works. The methods are validated and tested in a simulated uncertainty scenario, using both line load and surface pressure data, which are presented in Chapter 4. These results showed that the method using a multivariate normal copula was the most successful of the presented methods. Discussions of the performance of the methods in the various results is also included in Chapter 4, with summarizing conclusions and future work included in Chapter 5.

This thesis investigates the enhancement of crashworthiness and structural integrity in Glass Laminate Aluminum Reinforced Epoxy (GLARE) channel section beams through the introduction of cross stiffeners. The ultimate goal is to improve crashworthiness, with a specific focus on the comparatively longer and gradual process of buckling and post-buckling analysis under compressive loads, rather than conducting a classical impact analysis. The study's methodology integrates a literature review with advanced numerical modeling using ABAQUS, validated by experimental benchmarking. The ABAQUS eigenbuckling and Riks analyses are meticulously validated against experimental data, achieving minimal error margins for buckling loads (3.5% - 5.2%), which are well below the allowable 10% error margin, and accurately matching failure modes. The introduction of cross stiffeners in the GLARE channel beam effectively recreates the mode shape concentrated at the mid-span of the beam, decreasing the buckling load by 39% compared to the no-stiffener configuration, potentially creating a crumple zone and maximizing energy absorption during high impact tests. Additionally, a more distributed failure pattern, controlled deformation, and a higher and longer post-buckling path are achieved, indicating improved stability and load-bearing capacity, with a 36% increase in failure load compared to the no-stiffener configuration. These findings demonstrate significant improvements in damage tolerance and provide a solid motivation for future work to test the crashworthiness of GLARE structures with cross stiffeners in aerospace applications, such as airframes and subcomponents, to better protect occupants.

Gradient Adaptive Transfinite Elements (GATE) offer a generic method to implement arbitrary high-order numerical solutions to existing finite element formulations. GATE are a family of elements that are formulated using transfinite interpolation, a generic blending-based interpolation technique that can construct optimal interpolation functions about areas and volumes. The arbitrary nature of transfinite elements allows for the creation of elements that can serve a variety of useful purposes. Elements can be constructed to transition from a region using high-order representation to low-order representation. High-order representation is important in capturing large gradients, especially in regions near geometric boundaries. Without such capability, one is either left with the choice of paying a high cost to implement high-order representation across the entire domain, or excessively refining the low-order representation near the high gradient region. The high order nature of GATE is well suited for a Direct Numerical Simulation (DNS) of the Navier Stokes equations. In this present work, we apply GATE to find DNS solutions of the Navier Stokes equations and coupled Fluid-Structure Interaction (FSI) problems.The high-order representation provided by GATE is not limited to the representation of the solution but can be used in the same manner for the geometry. This is typically done using isoparametric mapping, a technique that maps the geometry to an element reference domain using the same basis functions used for the representation of the field. GATE can also be used as a parametric mapping with a high-order representation or exact representation used to represent the boundary geometry. The ability of GATE to transition between high-order and low-order regions is well suited for parametric mapping where a high degree of mapping accuracy is needed at the boundary and low-order mapping accuracy is acceptable in the field.GATE family elements can also be used for general

Induced magnetospheres form around planetary bodies with atmospheres through the interaction of the solar wind with their ionosphere. Induced magnetospheres are highly dependent on the solar wind conditions and have only been studied with single spacecraft missions in the past. Without simultaneous measurements of solar wind variations and phenomena in the magnetosphere, establishing a link between both can only be done indirectly, using statistics over a large set of measurements. This gap in knowledge could be addressed by a multi-spacecraft plasma mission, optimized for studying global spatial and temporal variations in the magnetospheric system around Venus, which hosts the most prominent example of an induced magnetosphere in our solar system. The MVSE mission comprises four satellites, of which three are identical scientific spacecraft, carrying the same suite of instruments probing different regions of the induced magnetosphere and the solar wind simultaneously. The fourth spacecraft is the transfer vehicle which acts as a relay satellite for communications at Venus. In this way, changes in the solar wind conditions and extreme solar events can be observed, and their effects can be quantified as they propagate through the Venusian induced magnetosphere. Additionally, energy transfer in the Venusian induced magnetosphere can be investigated. The scientific payload includes instrumentation to measure the magnetic field, electric field, and ion–electron velocity distributions. This study presents the scientific motivation for the mission as well as requirements and the resulting mission design. Concretely, a mission timeline along with a complete spacecraft design, including mass, power, communication, propulsion and thermal budgets are given. This mission was initially conceived at the Alpbach Summer School 2022 and refined during a week-long study at ESA's Concurrent Design Facility in Redu, Belgium.

Accurate and timely flight delay prediction cannot be overemphasized because of the ever-increasing demand for air travel and its importance in deploying intelligent transportation systems. Nonetheless, there has not been a universal solution to the problem, as more intelligent flight decision systems are required for the aviation industry's future growth. Existing flight delay classification and prediction approaches are mainly shallow traffic models and do not satisfy many applications in the real world. Our motivation to rethink the deep architecture model for predicting flight delays emanates from the problem. In this research, we proposed a technique that modified stacked autoencoder architecture parameters for training the network and understanding the link between space, time and information gained from the flight on-time data. We developed three different types of autoencoders based on the architecture of the modified stacked autoencoder. The models learn the generic flight delay features, and it's trained greedily in a layer-wise fashion. To the best of our knowledge, this is the first time these performances of vanilla autoencoder, logistic regression autoencoder and Multilayer perceptron for classification were evaluated based on the developed modified stacked autoencoder architecture. Moreover, our experiment demonstrates that the models achieved varying levels of accuracy in the flight delay classifications task. The deep vanilla autoencoder shows superior accuracy, recall and precision performance compared to logistic regression autoencoder and Multilayer perceptron autoencoders at different parameter settings.

Regeringen har gett Trafikverket i uppdrag att utreda om det finns förutsättningar att ställa krav på elflyg i Trafikverkets upphandlingar av flygtrafik. Trafikverket ska också lämna förslag på åtgärder som kan bidra till en tidig introduktion av elflyg på dessa linjer eller vissa av dem. Utredningen fokuserar på de praktiska förutsättningarna för elflyg och innehåller en genomgång av elflygens utveckling, de krav som kommer ställas på flygplatser och de utmaningar som aktörerna inom systemet står inför.

Due to the increasing emphasis on environmental protection and the higher demands for air traffic management, the aviation industry is seeking a method to better predict the environmental variables regarding aircraft emissions. The study introduces STSCBRE (Spatio-Temporary Self-attention CNN-BiLSTM Network with Relative Embedding), a novel model for multi-step, multi-variate time series forecasting, aimed at improving environmental variable prediction in aviation emissions analysis. It enhances Transformer architecture by incorporating relative position encoding and variable embedding to capture spatio-temporal dependencies more effectively. Unlike traditional Transformers, which rely on absolute positioning and often overlook spatial factors, STSCBRE restructures multi-head attention to better utilize spatiotemporal dependencies. The presented model outperforms others in NRMSE and maintains systematic prediction errors below 2%. An ablation test is performed to enhance the model's transparency and assess the contribution of each module within the overall framework., På grund av det ökande fokuset på miljöskydd och de högre kraven på flygtrafikledning, söker flygindustrin en metod för att bättre förutsäga miljövariabler relaterade till flygutsläpp. Studien introducerar STSCBRE (Spatio-Temporal Self-attention CNN-BiLSTM Network with Relative Embedding), en ny modell för flerstegs och multivariat tidsserieprognos som syftar till att förbättra förutsägelser av miljövariabler inom flygutsläpp. Modellen förbättrar Transformer-arkitekturen genom att införliva relativ positionskodning och variabelinbäddning för att mer effektivt fånga rumsliga och tidsmässiga beroenden. Till skillnad från traditionella Transformer-modeller, som förlitar sig på absolut positionering och ofta förbiser rumsliga faktorer, omstrukturerar STSCBRE multihead-attention för att bättre utnyttja rumsliga och tidsmässiga beroenden. Modellen överträffar andra i NRMSE och upprätthåller systematiska förutsägelser med fel under 2%. Ett ablationstest har utförts för att öka modellens transparens och bedöma varje moduls bidrag inom den övergripande strukturen.

This thesis presents the development and comprehensive analysis of an open-source aeroelastic model for the Douglas DC-3 with some modifications. The model serves as a platform for software testing, capturing essential aeroelastic phenomena. It features a conventional configuration with two engines, control surfaces, and a wing with a leading-edge sweep angle of 15.5°, dihedral angle of 5°, aspect ratio of 9.2, and cambered airfoil, operating in a subsonic regime.The development process included finite element modeling using beam elements, aerodynamic modeling with the Doublet Lattice Method (DLM), and mass modeling, including a complex fuel mass model. Four distinct mass configurations were analyzed. Trim case analyses were performed using both Loads Kernel and SOL144 in MSC Nastran, revealing significant differences between rigid and flexible configurations. Maneuver load analyses were conducted exclusively using Loads Kernel.Additionally, gust loads were studied using the (1-cos) Discrete Gust Model, demonstrating coupling with the short-period mode due to high static margin. Flutter checks showed matching results between Loads Kernel and MSC Nastran, with flutter speeds of 195 m/s and 203 m/s, respectively, confirming the model’s plausibility for aeroelastic analysis., Denna avhandling presenterar utvecklingen och en omfattande analys av en öppen källkods aeroelastisk modell för Douglas DC-3 med vissa modifieringar. Modellen fungerar som en plattform för programvarutestning och fångar viktiga aeroelastiska fenomen. Den har en konventionell konfiguration med två motorer, styrytor och en vinge med en framkantssvepvinkel på 15,5°, en dihedralvinkel på 5°, ett aspektförhållande på 9,2 och en välvd vingprofil, som opererar i ett subsoniskt regime.Utvecklingsprocessen inkluderade finita element-modellering med balkelement, aerodynamisk modellering med Doublet Lattice Method (DLM) och massmodellering, inklusive en komplex bränslemassmodell. Fyra distinkta masskonfigurationer analyserades. Trimsituationer analyserades med både Loads Kernel och SOL144 i MSC Nastran, vilket avslöjade betydande skillnader mellan stela och flexibla konfigurationer. Manöverlastanalyser genomfördes exklusivt med Loads Kernel.Dessutom studerades vindbybelastningar med (1-cos) Diskret Gustmodell, vilket visade koppling med kortperiodläget på grund av hög statisk marginal. Fladdertester visade matchande resultat mellan Loads Kernel och MSC Nastran, med fladderhastigheter på 195 m/s respektive 203 m/s, vilket bekräftade modellens tillförlitlighet för aeroelastisk analys.

As the performance of a rocket launcher is closely linked to its flight control system, a significantchallenge in rocket science is the design of attitude control algorithms, to ensure the stabilityof the vehicle, while following a designated trajectory and rejecting external disturbances. Thisreport aims at describing a general method for designing such a controller and finally assessfor its performance. First, a state-of-the-art review of existing attitude control methods isprovided, along with an introduction to linear control theory. Important phenomena influencingthe vehicle, including the rigid-body dynamics, aerodynamics, inertia of the engines, sloshingmodes and bending modes are then introduced. Thereafter, through the example of a given studycase, the parameters describing all of these phenomena are estimated. The linear equationsof motion are then derived and a method for constructing the state-space representation ofthe vehicle and its actuators is presented. Based on this linear model, a step-by-step methodis described to compute a stable PID controller, designed to handle all of the consideredphenomena. Finally, a performance analysis including stability, time response, sensitivity androbustness is conducted to evaluate the behavior of the controller., Eftersom prestanda för en bärraket är nära kopplad till dess flyg regler system, är en betydandeutmaning inom rymdfarten utformningen av en attityd reglerings algoritm för att säkerställabärraketens stabilitet, samtidigt som den följer en bestämd bana och avvisar externa störningar.Denna rapport syftar till att beskriva en allmän metod för att utforma en sådan reg leralgoritmoch slutligen bedöma dess prestanda. Först ges en genomgång av befintliga metoder för attitydreglering och en introduktion till linjär reglerteori. Viktiga fenomen som påverkar bärraketen,inklusive den stela kroppens dynamik, aerodynamik, tröghet i motorerna, slasknings lägenoch böjmoder introduceras sedan. Därefter uppskattas de parametrar som beskriver alla dessafenomen med hjälp av ett givet studiefall som exempel. De linjära rörelseekvationerna härledssedan och en metod för att konstruera en tillståndsmässig representation av farkosten och dessställdon presenteras. Baserat på denna linjära modell beskrivs en steg-för-steg-metod för attberäkna en stabil PID-styrenhet som är utformad för att hantera alla de aktuella fenomenen.Slutligen genomförs en prestandaanalys som inkluderar stabilitet, tidsrespons, känslighet ochrobusthet för att utvärdera regulatorns beteende.

The study of the flow around a car is of crucial importance in seeking energy efficiency and performance. With Volvo cars rapidly transitioning towards BEV-basedarchitecture (fully electrified fleet by 2030), newer avenues to further improve existing external vehicular aerodynamic knowledge are being explored. This requiresan update of the generic rules of thumb and an overall understanding of the fundamental principles. The goal of this work is to therefore develop an optimization andanalysis workflow that identifies the key contributors to vehicular aerodynamic drag.This will contribute to the creation of a generalized set of geometrical trends, whichis further backed up by physics and CFD results. The study’s findings align closelywith established literature, underlining the importance of adopting tophat-specificoptimization approaches. The guidelines and rules-of-thumb derived from this studymainly pertains to SUVs and select squareback configurations., Studiet av flödet runt en bil är av avgörande betydelse för att uppnå energieffektivitetoch prestanda. Med Volvo Cars snabba övergång mot BEV-baserad arkitektur (heltelektrifierad flotta till 2030), utforskas nya vägar för att ytterligare förbättra befintligextern fordonsaerodynamisk kunskap. Detta kräver en uppdatering av de generellatumreglerna och en övergripande förståelse av de grundläggande principerna. Måletmed detta arbete är därför att utveckla ett optimerings- och analysflöde som identifierar de viktigaste bidragsgivarna till fordonsaerodynamiskt luftmotstånd. Dettakommer att bidra till skapandet av en generell uppsättning geometriska trender, somytterligare stöds av fysik och CFD-resultat. Studien visar att resultaten överensstämmer nära med etablerad litteratur, vilket understryker vikten av att anta specifikaoptimeringsmetoder för tophat. De riktlinjer och tumregler som härleds från dennastudie bör huvudsakligen gälla för SUVar och utvalda squareback-konfigurationer.

Certification noise limits represent an important aspect of the design and certification of aircraft engines. The ability to rapidly compute aircraft certification point noise results during the conceptual aircraft engine design process is, therefore, a valuable capability. This work presents the integration of a geared turbofan Numerical Propulsion System Simulation (NPSS) engine model with the Chalmers Noise Code (CHOICE), enabling the computation of aircraft certification point noise in the Numerical Propulsion System Simulation. A geared turbofan engine model was implemented in the Numerical Propulsion System Simulation, and the flight trajectory of a wide body civil aircraft was modelled in Pacelab APD. A comparison of the geared turbofan engine model was performed against a GasTurb model of the same engine, showing good agreement for engine performance, but differences in engine component geometries. Lateral sideline reference noise results are presented, as is the effect of varied engine bypass ratios on lateral certification noise. The booster and low pressure turbine are observed to be the dominant aircraft noise sources for lateral noise, due to the high rotational speeds and rotor tip Mach numbers of the booster and low pressure turbine. Flyover certification noise contour plots, and lateral end of runway fan tonal noise results are presented. The presented fan tonal noise shows significant differences between theoretical, computational fluid dynamics, and empirical results, and is an area in which further work is required. The integration of engine modelling and noise modelling codes was successful, and the capability to rapidly compute lateral and flyover noise results for Numerical Propulsion System Simulation engine models has been demonstrated, providing noise modelling functionality during the initial engine design process., Certifieringskrav med avseende på buller är en viktig del av designen och certifieringen av flygplansmotorer. Att snabbt kunna prediktera buller för certifieringspunkter under konceptarbetet för flygmotorer är därför en värdefull förmåga. I detta arbete presenteras en integration av en motorprestandamodell av en växlad turbofläktmotor i programvaran Numerical Propulsion System Simulation (NPSS) med Chalmers Noise Code (CHOICE), vilket möjliggör beräkning av buller för flygplanscertifieringspunkter i Numerical Propulsion System Simulation. En växlad turbofläktmotormodell implementerades i NPSS, och flygbanan för ett civilt ”wide body” flygplan modellerades i Pacelab APD. En jämförelse av den NPSS-modellen gjordes mot en GasTurb-modell av samma motor, vilket visade god överensstämmelse för motorprestanda, men skillnader i motorkomponenternas geometrier. Resultat av bullerprediktering vid ”lateral sideline” presenteras, liksom effekten av olika motor-massflödes-förhållanden på lateralt certifieringsljud. Booster- och lågtrycksturbin observerades vara de dominerande flygbullerkällorna. Detta på grund av de höga rotationshastigheterna och rotor-Machtalen för booster- och lågtrycksturbinen. Bullerkonturbilder från överflygning och tonalt fläktbuller presenteras. De presenterade tonala fläktbullerresultaten visar signifikanta skillnader mellan teoretiska, CFD-baserade och empiriska resultat, och är ett område där ytterligare arbete krävs. Integreringen av motormodellen NPSS och bullermodelleringskoden CHOICE var framgångsrik, och förmågan att snabbt beräkna ”lateral” och ”flyover” bullerresultat för NPSS-motormodeller har demonstrerats, vilket ger bullermodelleringsfunktionalitet under tidig motordesign-fas.

This study presents a preliminary launch abort concept for the Nyx Earth Crew spacecraft developed at The Exploration Company. A requirements study of general human mission certification focusing on abort requirements is followed by a more detailed assessment of abort needs, interfaces and performance. Assuming launch with the Ariane 6 from French Guiana, a total of nine abort modes, three major abort criteria, seven success parameters, a layout of an abort control system and a mission sequence are defined, including an assessment of the most substantial risks during an abort manoeuvre. Five driving abort requirements were identified in the areas of safety, performance, reusability, in-house development and system complexity. Based on this extensive analysis, three different abort architectures with two design variations each are proposed: A "puller tower" similar to the one used on the Orion spacecraft, a "pusher engine" similar to the one used on the Crew Dragon spacecraft and an architecture using solid rocket boosters which does not yet exist for abort purposes. An architecture trade-off is performed by means of studying the components, accommodation, propulsion system and driving requirements of each architecture. The new hybrid booster concept is deemed the most feasible as it combines several advantages of both the pusher and puller system, namely a lightweight, jettisoned and simple solid propulsion system. Nonetheless, given that this concept has no abort heritage, several analyses have to be conducted to determine whether this concept is technically feasible, in particular in terms of continuous abort capability, booster jettison and potential reusability. The most feasible alternative to be further investigated was identified as the pusher engine, given potential synergies with the main propulsion system and advantages in terms of reusability. The puller tower is proposed to be discarded as a potential launch abort system for Nyx Earth Crew given its exce, I denna studie presenteras ett preliminärt avbrytningskoncept för uppskjutningen av rymdfarkosten Nyx Earth Crew som utvecklats av The Exploration Company. En kravstudie för certifiering av allmänna bemannade uppdrag med fokus på avbrytningskrav följs av en mer detaljerad bedömning av avbrytningsbehov, gränssnitt och prestanda. Förutsatt uppskjutning med Ariane 6 från Franska Guyana definieras totalt nio avbrytningslägen, tre huvudkriterier för avbrytning och sju framgångsparametrar, en layout för ett avbrytningskontrollsystem och en uppdragssekvens, inklusive en bedömning av de mest väsentliga riskerna under en avbrytningsmanöver. Fem drivande krav identifierades inom områdena säkerhet, prestanda, återanvändbarhet, egen utveckling och systemkomplexitet. Baserat på denna omfattande analys föreslås tre olika avbrottsarkitekturer med två designvarianter vardera: Ett "puller"-torn liknande det som används på Orion, en "pusher"-motor liknande den som används på Crew Dragon och en arkitektur som använder fasta raketmotorer som ännu inte finns för avbrottsändamål. En avvägning mellan olika arkitekturer görs genom att studera komponenter, boende, framdrivningssystem och drivkrav för varje arkitektur. Det nya hybridboosterkonceptet anses vara det mest genomförbara eftersom det kombinerar flera fördelar med både pusher- och puller-systemet, nämligen ett lättviktigt, kasserbart och enkelt solitt framdrivningssystem. Med tanke på att detta koncept inte har något avbrottssystem måste dock flera analyser genomföras för att avgöra om konceptet är tekniskt genomförbart, i synnerhet när det gäller kontinuerlig avbrottsförmåga, boosterutskjutning och potentiell återanvändbarhet. Det mest genomförbara alternativet som ska undersökas vidare identifierades som pusher-motorn, med tanke på potentiella synergier med huvudsakliga framdrivningssystem och fördelar när det gäller återanvändbarhet. Puller-torn föreslås att uteslutas som ett potentiellt avbrytningssystem för Nyx Earth Crew med