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Critical Thinking (CT) skills are highly valued by employers, leading to their integration into engineering education through various design- and problem-based approaches. Despite their recognized importance, the varying perceptions of CT present challenges in achieving a unified approach to its development and assessment. This paper reviews CT assessment in engineering education, particularly mapping Facione's CT skills with assessment approaches to discern how CT is evaluated. We conducted a systematic keyword search in the SCOPUS database and identified 462 articles from 2010 to March 2023. These were reviewed and distilled down to 80 articles included in this study. We find that CT has been recognized as an essential skill set, but there are no consistent definitions or means to assess it. Further, while CT is a multifaced skill, we find that very few assessment methods assess CT holistically. We identify three goals for CT assessment: (1) understand and recognize CT, (2) demonstrate CT, and (3) identify if CT has changed due to intervention. We discuss how different assessment approaches, including rubrics, surveys, standardized tests, and customized assessments, have been used and propose recommendations to support reaching a better understanding of CT assessment in engineering education. Further research is needed to understand better how these skills can be taught and assessed as part of engineering education to meet the needs of employers. [ABSTRACT FROM AUTHOR]

In this paper, a multi-fidelity Bayesian optimization approach is presented to tackle computationally expensive constrained multiobjective optimization problems (MOPs). The proposed approach consists of a three-stage optimization framework designed to search for promising candidate points. In the first stage, an acquisition function is proposed to identify a feasible solution if none is available in the current set of sampling points. Subsequently, a new multi-fidelity weighted expected hypervolume improvement function is developed to find better solutions. In the third stage, a constrained weighted lower confidence bound acquisition function is presented to enhance the constraint predictions and refine the solutions near the constraint boundary. Additionally, a filter strategy is suggested to determine whether constraint updating is necessary, aiming to save computational resources and improve optimization efficiency. Moreover, to expedite the optimization process, a parallel optimization approach is further developed based on the suggested three-stage optimization framework. To achieve this, a multi-fidelity influence function is introduced, allowing the proposed approach to determine a desired number of candidate points within a single iteration. Lastly, the proposed approach is demonstrated through six numerical benchmark examples, which verifies its significant advantages in addressing expensive constrained MOPs. Besides, the proposed approach is applied to the multiobjective optimization of a metamaterial vibration isolator, resulting in the attainment of satisfactory solutions. [ABSTRACT FROM AUTHOR]

Variational integrators play a pivotal role in the simulation and control of constrained mechanical systems. Current Lagrange multiplier-free variational integrators for such systems are concise but inevitably face issues with parameterization singularities, hindering global integration. To tackle this problem, this paper proposes a novel method for constructing variational integrators on manifolds without introducing Lagrange multipliers, offering the benefit of avoiding singularities. Our approach unfolds in three key steps: (1) the local parameterization of configuration space; (2) the formulation of forced discrete Euler-Lagrange equations on manifolds; and (3) the construction and implementation of high-order variational integrators. Numerical tests are conducted for both conservative and forced mechanical systems, demonstrating the excellent global energy behavior of the proposed variational integrators. [ABSTRACT FROM AUTHOR]

In this paper, we develop a nonlinear mixed finite element method for flexoelectric semiconductors and analyze the mechanically tuned redistributions of free carriers and electric currents through flexoelectric polarization in typical structures. We first present a macroscopic theory for flexoelectric semiconductors by combining flexoelectricity and nonlinear drift-diffusion theory. To use C0 continuous elements, we derive an incremental constrained weak form by introducing Langrage multipliers, in which the kinematic constraints between the displacement and its gradient are guaranteed. Based on the weak form, we established a mixed C0 continuous nine-node quadrilateral finite element as well as an iterative process for solving nonlinear boundary-value problems. The accuracy and convergence of the proposed element are validated by comparing linear finite element method results against analytical solutions for the bending of a beam. Finally, the nonlinear element method is applied to more complex problems, such as a circular ring, a plate with a hole, and an isosceles trapezoid. Results indicate that mechanical loads and doping levels have distinct influences on electric properties. [ABSTRACT FROM AUTHOR]

This paper deals with the problem of integral sliding mode disturbance observer (ISDOB)-based preview repetitive control (PRC) for a class of nonlinear systems subject to external disturbances and nonlinearity. First, an ISDOB-based PRC law is presented to estimate and compensate the exogenous disturbances and nonlinearity. Next, by using a new equality constraint, a continuous-discrete two-dimensional (2D) system is established. Then, the stability of the combined controller-observer system is derived on the basis of a Lyapunov analysis, 2D system theory, and the singular-value-decomposition technique. By solving an linear matrix inequality (LMI), the gains of the controller and state observer can be obtained. Finally, two numerical examples are provided to illustrate the effectiveness and superiority of the proposed method. [ABSTRACT FROM AUTHOR]

Recently, a class of adaptive schemes has been developed for rejecting sinusoidal output disturbances with unknown frequencies, phases, and amplitudes. These adaptive schemes require an accurate model of the affected system's dynamics to function, and the controller performance degrades as the modeling error increases. While linear time-invariant (LTI) dynamics can adequately model the dynamics of some systems, a time-varying model of the system dynamics is more appropriate in certain scenarios. This paper proposes a robust adaptive scheme for rejecting disturbances that affect the output of a system described by a known linear time-varying model. The disturbances are described by an unknown number of sinusoidal terms with unknown time-varying frequencies. Analysis is done in ideal case where the disturbance frequencies are perfectly known to provide conditions guaranteeing the existence of a controller and a corresponding set of parameters which reject the disturbance. Analysis is then done in the more realistic adaptive scenario where the disturbance frequencies are unknown, and a robust adaptive scheme for selecting controller parameters which reject the disturbance is proposed. Performance of the controller with respect to the speed of variation in the plant model parameters is assessed via simulation. [ABSTRACT FROM AUTHOR]

Virtual coupling of railway trains is an emerging technology that has the potential to significantly increase railway operational efficiency by reducing the train following distance from absolute braking distances to relative braking distances. Current research in this topic is mainly focused on passenger trains and uses distance-based headways. This paper studied virtual coupling for heavy haul freight trains and demonstrated that the distance headway scheme was challenging and sometimes impractical for heavy haul trains to achieve virtual coupling. A time-based headway scheme was then proposed to set the follower train to be a certain time behind the schedule of the leader train rather than a distance headway. The time-based headway required the follower train to reproduce the leader train's operational status at the same track location. This also allowed the follower train to copy any optimized train driving strategies from the leader train. Demonstrative simulations were carried out without the consideration of communication errors and train localization errors. The results show that a conventional distance headway simulation had maximum distance and speed errors of 716 m (36%, reference 2 km) and 24 km/h (66%, reference 36 km/h), respectively. A time-based headway simulation reduced the maximum distance and speed errors to 0.07 m (0%, reference 2 km) and 0.1 km/h (9%, reference 1.18 km/h), respectively. [ABSTRACT FROM AUTHOR]

In many nonlinear systems, the observability of the system is dependent on its state and control input. Thus, incorporating observability into a control scheme can enhance an observer's ability to recover accurate estimates of unmeasured states, minimize estimation error, and ultimately, allow the original control objective to be achieved. The accommodation of observability, however, may conflict with the original control goal at times. In this paper, we propose the use of control barrier functions (CBFs) to enforce observability and thereby facilitate the convergence of the state estimate to the true state while accommodating the original control objectives. Motivated by practical applications for autonomous robots operating in global positioning system-denied environments, we focus on the problem of target tracking for a unicycle model when only the distance to the target is measured. The proposed approach is compared in simulation with a model predictive control (MPC) approach that treats an observability-related metric as part of the cost function, where several different options for the observability metric are explored. It is found that the CBF-based approach achieves control and estimation performance that is comparable to that of the MPC approach, but with significantly less computational complexity. These findings are further experimentally verified in range-based target tracking with a swimming robotic fish. [ABSTRACT FROM AUTHOR]

Advanced control strategies for delivering heat to users in a district heating network have the potential to improve performance and reduce wasted energy. To enable the design of such controllers, this paper proposes an automated plant modeling framework that captures the relevant system dynamics, while being adaptable to any network configuration. Starting from the network topology and system parameters, the developed algorithm generates a state-space model of the system, relying on a graph-based technique to facilitate the combination of component models into a full network model. The accuracy of the approach is validated against experimental data collected from a laboratory-scale district heating network. The verification shows an acceptable average normalized root-mean-square error of 0.39 in the mass flow rates delivered to the buildings, and 0.15 in the network return temperature. Furthermore, the ability of the proposed modeling technique to rapidly generate models characterizing different network configurations is demonstrated through its application to topology optimization. The optimal design, obtained via a branch and bound algorithm, reduces network heat losses by 15% as compared to the conventional length-minimized topology. [ABSTRACT FROM AUTHOR]

This paper describes an efficient method of manufacturing thin-walled metal tubes. The proposed method is an expansion drawing and it consists of two stages, flaring and drawing, during which high thickness reduction is achieved because the tube being processed is subjected to tensile stress in both the circumferential and axial directions. The optimal plug half-angle for various materials is investigated using a finite element analysis and experiments, revealing the plug shape with the highest expansion limit and the highest thickness reduction ratio. To investigate the deformation characteristics of different materials during the expansion drawing process, the strain in tubes formed using different materials was measured experimentally using a square grid on the outer surface of the tubes. In addition, a finite element analysis using hypothetical material properties revealed that the work-hardening exponent and friction coefficient affect tube deformation. The results of this work explain the influences of material properties on experimentally observed phenomena. Materials with a large work-hardening exponent are less prone to thinning during forming and have a greater forming limit. On the other hand, the larger the friction coefficient between the plug and the mother tube, the larger the deformation in the axial direction was, and then the thickness reduction increased due to biaxial tension. [ABSTRACT FROM AUTHOR]

In practical semiconductor processes, the defect analysis for wafer map is a critical step for improving product quality and yield. These defect patterns can provide important process information so that the process engineers can identify the key cause of process anomalies. However, in supervised learning, the manual annotation for wafer maps is an extremely exhausting task, and it can also induce misjudgment when a long-term operation is implemented. Toward this end, this paper proposes a new auto-labeling system based on ensemble classification. The noted VGG16 model is used in ensemble learning as the building block to train the classifier via a limited number of labeled data. Through the model being trained, the auto-labeling procedure is executed to annotate abundant unlabeled data. Therefore, the classification performances between the models trained by supervised and semi-supervised learning can be compared. In addition, the gradient-weighted class activation mapping (Grad-CAM) is also adopted to analyze and verify the quality of auto-labeling by visual inspection. Based on the experimental results, the proposed auto-label system can return a satisfactory classification performance, and then, the manual labeling operation can be drastically reduced. The classification performance for wafer defect patterns can be further assured as the auto-labeled data are given with corresponding confidence scores of specific defect patterns being identified in this study. [ABSTRACT FROM AUTHOR]

This paper introduces a novel wafer-edge quality inspection method based on analysis of curved-edge diffractive fringe patterns, which occur when light is incident and diffracts around the wafer edge. The proposed method aims to identify various defect modes at the wafer edges, including particles, chipping, scratches, thin-film deposition, and hybrid defect cases. The diffraction patterns formed behind the wafer edge are influenced by various factors, including the edge geometry, topography, and the presence of defects. In this study, edge diffractive fringe patterns were obtained from two approaches: (1) a single photodiode collected curved-edge interferometric fringe patterns by scanning the wafer edge and (2) an imaging device coupled with an objective lens captured the fringe image. The first approach allowed the wafer apex characterization, while the second approach enabled simultaneous localization and characterization of wafer quality along two bevels and apex directions. The collected fringe patterns were analyzed by both statistical feature extraction and wavelet transform; corresponding features were also evaluated through logarithm approximation. In sum, both proposed wafer-edge inspection methods can effectively characterize various wafer-edge defect modes. Their potential lies in their applicability to online wafer metrology and inspection applications, thereby contributing to the advancement of wafer manufacturing processes. [ABSTRACT FROM AUTHOR]

This paper develops a theoretical basis and a systematic process for resolving all inertia forces along generalized coordinates from the overall energy equation of a dynamical system. The theory is developed for natural systems with scleronomic constraints, where the potential energy is independent of generalized velocities. The process involves expansion of the energy equation, and specifically a special expansion of the kinetic energy term, from which the inertia forces emerge. The expansion uses fundamental kinematic identities of the phase space. It is also guided by insights drawn from the structure of the Hamiltonian function. The resulting equation has the structure of the D'Alembert's equation but involving generalized coordinates, from which the Lagrange's equations of motion are obtained. The expansion process elucidates how certain inertia forces manifest in the energy equation as composite terms that must be accurately resolved along different generalized coordinates. The process uses only the system energy equation, and neither the Hamiltonian nor the Lagrangian function are required. Extension of this theory to non-autonomous and non-holonomic systems is an area of future research. [ABSTRACT FROM AUTHOR]

The stability of a current-carrying beam in an external magnetic field is studied in this paper. The beam rests on periodic supports and is modeled as an Euler-Bernoulli elastic beam. Based on the linearized stability equation and propagator transfer matrix approach for a multi-span finite-length beam, the stability equation and solutions of the several boundary value problems are obtained. While the Floquet-Bloch theory is widely used in the dynamic problem of phononic and photonic structure conditions, its application to the solution of infinite length beam static stability problem is novel. The stability values of the periodic infinite beam model are in very good agreement with one of the finite-length multi-span beams. [ABSTRACT FROM AUTHOR]

The post-buckling behavior of a beam that is subjected to lateral constraints is of relevance to a range of medical and engineering applications, such as endoscopic examination of internal organs, the insertion of a guidewire into an artery in-stent procedures, root growth, deep-drilling, and more. In this paper, we address a disconnect between the existing literature and the reality of these systems, in which the lateral constraints are flexible and experience nonlinear deformations. As a step towards bridging this gap, we consider a beam undergoing planar deformations that is laterally constrained by a nonlinear springy wall, i.e., a wall that is laterally pushed by the beam against a nonlinear spring. Based on a simplified mathematical model, we obtain closed-form analytical solutions, which provide valuable insights and intuition. For example, we show that important features of the behavior, such as the transition from point contact to line contact and switching to the next mode, are dictated solely by a non-dimensional force, regardless of all other parameters of the system, and that the full description of the behavior is possible by means of two non-dimensional quantities that describe the relative stiffness of the nonlinear spring compared to that of the beam. The results also highlight the fundamental differences between the behavior with a stiffening spring or with a softening spring, such as the number of attainable modes and the monotonicity of the overall force-displacement relation. These results are then validated by experiments. [ABSTRACT FROM AUTHOR]

This paper presents a solution verification and validation study for an overset mesh based numerical wave tank in OPENFOAM, which considers the coupling between a free-surface hydrodynamic flow model, a rigid body motion model, and an overset mesh. The coupling between the rigid body motion solver and the free-surface flow solver was achieved in a segregated manner. Free decay of roll motion of a barge was modeled using the numerical wave tank, and the damping coefficient was selected as the target quantity for solution verification. The least-square based solution verification procedure was adopted, where one of the four types of error estimators was fit to the data in the least-square sense. Both structured and unstructured mesh were tested, and their effects on the convergence order, numerical uncertainty, and error were carefully investigated. From the numerical tests, it is found that the numerical wave tank exhibits a very good convergence property for the floating body problems with structured mesh, i.e., nearly second order in space and first order in time. However, when switching the body-fitted mesh to unstructured mesh, the grid convergence is reduced to first order. Unstructured mesh does not significantly affect the convergence order in time domain, but results in a larger uncertainty due to data scattering. [ABSTRACT FROM AUTHOR]

Execution of a marine operation (MO) requires coordinated actions of several vessels conducting simultaneous and sequential offshore activities. These activities have their operational limits given in terms of environmental parameters. Wave parameters are important because of their high energetic level. During the execution of a MO, forecast wave spectral parameters, i.e., significant wave height (Hs), peak period (Tp), and peak direction, are used to make an on-board decision. For critical operations, the use of forecasts can be complemented with buoy measurements. This paper proposes to use synthetic statistics of vessel dynamic responses to predict "real-time" wave spectral parameters using multi-output machine learning (ML) regression algorithms. For a case study of a vessel with no forward speed, it is observed that the random forest model predicts accurate Hs and Tp parameters. The prediction of wave direction is not very accurate but it can be corrected with on-board observations. The random forest model has good performance; it is efficient, useful for practical purposes, and comparable with other deep learning models reported in the scientific literature. Findings from this research can be valuable for real-time assessment of wave spectral parameters, which are necessary to support decision-making during the execution of MOs. [ABSTRACT FROM AUTHOR]

In general, submarines are designed to optimize operation below the water surface because they spend most of their time underwater. On the other hand, the performance in the free surface condition is also important because submarines face a variety of scenarios to complete operational missions, and the free surface condition is unavoidable for port departure and arrival. In the case of a submarine, the numerical accuracy of the potential theory for seakeeping analysis is excellent in submerged conditions, but it is poor in free surface conditions because of nonlinear effects near the free surface area. In this study, STAR-CCM+ was used as a Reynolds-averaged Navier-Stokes (RANS) solver to estimate the seakeeping performance of a Canadian Victoria Class submarine in irregular waves. The results were compared with those of model tests from a published paper. In addition, the potential theory code was also used to assess the seakeeping performance and compare it with computational fluid dynamics (CFD) results. From the calculation results, the motion responses in irregular waves using CFD showed similar trends to the experimental results. In contrast, motion responses from potential code showed significantly larger values than the experimental results. In conclusion, CFD simulations with irregular waves can be a good solution to predict the seakeeping performance of submarines in free surface conditions. [ABSTRACT FROM AUTHOR]

This paper proposes an investigation of a novel design of receiver absorber tube (circular-trapezoidal shaped) for parabolic trough concentrator (PTC) system aiming at catching a part of the lost (reflected) solar rays due to effects related to the incidence angle deviation and thus improving the PTC's thermal performance. Although they are always present in PTC, the effects of the deviation angle are often not considered in the literature. These effects are considered here in view of presenting a better and more useful focal area, the optimal circular-trapezoidal absorber tube shape is determined according to the maximal limit of the deviation angle that allows catching the maximum amount of solar rays. The corresponding model is established considering it as a two-dimensional problem and the derived deviation angle coefficient is compared to that obtained for a traditional circular-shaped tube. Moreover, the energy balance model is adapted to simulate the thermal efficiency of the considered tubes as a function of the deviation angle with some assumptions. The obtained results prove that from a deviation angle value of 0.1 deg, the gain in efficiency becomes more significant; it can reach 5% and even be higher for a deviation angle value of 0.5 deg. Finally, comsol multiphysics software package was used to determine the pressure drops, temperature, and velocity field distributions, considering a deviation angle value of 0.2 deg. The results confirm that the proposed tube absorbs more heat than the traditional one. [ABSTRACT FROM AUTHOR]

For large-scale constructed wind farms, reducing wake loss and improving the overall output power are the main objectives for their optimal operation. Therefore, a wind farm power maximization method based on a multi-strategy improved sparrow search algorithm (MS-ISSA) is proposed in this paper. Integrating the wake propagation mechanism of wind turbines and the characteristics of the classic Jensen wake model, the Jensen-Gaussian wake model and wake superposition model were constructed to accurately calculate the wind farm wake distribution. The constructed Jensen-Gaussian wake model and wake superposition model can accurately describe the non-uniform distribution characteristics of wake velocity. The Sin chaotic model, Cauchy distribution, and hyperparameter adaptive adjustment strategy were used to improve the sparrow search algorithm (SSA), and the optimization ability, convergence speed, and stability of the SSA were improved. Accordingly, considering the maximum output power of the wind farm as the optimization target and axial induction factor as the optimization variable, a coordinated optimization model for wind turbines based on MS-ISSA was proposed to realize the coordinated optimal operation of wind turbines with reduced wake loss. Considering the Danish Horns Rev wind farm as the research object, the results of optimization using particle swarm optimization algorithm, whale optimization algorithm, basic sparrow search algorithm, and MS-ISSA were calculated and analyzed. The calculation results revealed that under different incoming wind conditions, the MS-ISSA exhibited better optimization results than the other optimization algorithms. [ABSTRACT FROM AUTHOR]

In this paper, experimental work has been presented to study the novel design of a solar crop dryer that includes an inverted absorber perforate type collector with forced airflow. A novel design configuration was constructed and tested in the eastern Algeria climate (El Oued city) for drying potatoes. We aimed to present a test of the thermal performance of the novel dryer and use only clean energy sources for evaluating the drying efficiency. Under real climatic conditions, the experimental test indicated that the average air temperature of the drying chamber is 50 °C, and the time required for drying potatoes starting at the initial moisture content (MC) of 84.17% until the final MC of 12.5% is 6h. The highest specific moisture extraction rate value was obtained as 1.074 g water/kWh. The drying efficiencies ranged from 20.37% to 34.01%, whereas the exergy efficiency ranged from 58.48% to 93.22%. The payback period was estimated as 1.39 years. The proposed novel dryer will dry potatoes free of cost for almost its entire life period, and about $13.92 can be saved. Compared with electric oven drying, the novel one has the following advantages: the cost of electricity saving and avoiding penalty tax for CO2 emission were $11.69 and $2.235, respectively. [ABSTRACT FROM AUTHOR]

A horizontal smooth copper tube and two enhanced tubes (a dimpled tube and a diamond-shaped tube) with a length of 2 m and an outer diameter of 9.52 mm were studied in a two-phase condensation experiment using R410A and R32 as heat transfer working fluids. The condensation heat transfer performance of different heat transfer tubes at various mass fluxes ranging from 150 to 400 kg/(m²s) and different vapor qualities ranging from 0.8 to 0.2 was studied experimentally. For R410A, the heat transfer coefficients (HTCs) of the dimpled tube and the diamond-shaped tube were found to be 1.39-1.52 times and 1.30-1.35 times higher than those of the smooth tube, respectively. For R32, the HTCs were found to be 1.46-1.59 times higher for the dimpled tube and 1.26-1.35 times higher for the diamond-shaped tube than for the smooth tube. The diamond-shaped tube was found to be effective in directing the flow of the liquid phase and in thinning the liquid film thickness. The dimpled tube was found to promote droplet entrainment and disturbance. Both of those effects contributed to improving the HTCs in the two enhanced tubes investigated. The HTCs of R410A were found to be lower than those of R32 because of the smaller specific heat capacity, smaller latent heat of condensation, and relatively poorer thermal conductivity of R410A. Taking the combined effect of heat transfer and pressure drop into account, a performance enhancement factor (PEF) was computed and was found to range from 0.9 to 1.51. Based on the experimental data collected, a new empirical correlation equation has been proposed with a maximum error band of 10%. Flow pattern maps for the tested tubes have also been generated and are presented in the paper. Both of the two enhanced tubes were found to promote the development of annular flow. The HTCs were found to be highest when the flow pattern was of the annular flow type. [ABSTRACT FROM AUTHOR]

In this paper, a segmented specular reflection solar concentrator is proposed. Many mirrors are arranged in the same plane, and all the reflected rays fall on the cylindrical focal surface. The glass mirrors are placed in different positions, tilt angles, and widths, and reflect light without blocking each other. Through the theoretical analysis of this type of concentrating system, in the same space span, with the increase of the installation height of the cylindrical focal surface, the concentrating ratio and area utilization rate gradually increase. The area utilization ratio is related to the ratio of mirror installation span and receiver height, and the concentrating ratio is linear to the number of mirrors. Through multiple groups of photothermal experimental analysis, it can be concluded that under the same heat collection temperature, the greater the radiation intensity received of the heat collecting tube, the higher the heat collection efficiency of the solar collecting system. [ABSTRACT FROM AUTHOR]

Multi-injector burner systems offer a high spatial-temporal mixture homogeneity due to their small size and thus have a high NOx emission reduction potential at increasing flame temperatures. This potential is reduced due to the sensitivity of the mixing quality to inflow distortions caused by the flow path in the burner head. A deep understanding of the link between the inflow conditions and the mixture quality helps to optimize the flow field upstream of the injectors within the spatial and pressure loss constraints of gas turbine combustors to obtain minimal NOx emissions. This paper presents a new model approach for determining the mixture quality in multi-injector burners with output-based proper orthogonal decomposition (O-POD). The sensitivity to the inflow distortion is considered with the so-called observable vector, which describes the injector inflow conditions and is given as model input. The target quantity is the probability mass function (PMF) of the equivalence ratio at the injector outlet. This model allows a fast estimation of the mixing PMF for arbitrary inflow conditions, which is otherwise only accessible with complex time-resolved experimental or numerical approaches. The performance of the model was demonstrated with 21 reference datasets, for which a good agreement between the experimental results and the model output was obtained. [ABSTRACT FROM AUTHOR]

Tip clearance monitoring is essential for the active health monitoring of turbomachinery and their development toward more efficient systems. Proper sensor calibration is paramount to this purpose, frequently being a time-consuming process. This paper introduces a novel in situ dynamic calibration routine for high-frequency capacitance sensor measurements for tip clearance. The method predicts the calibration curve based on a single clearance measurement, the evolution of the acquired signal through various operational conditions, and the dimensional features of the multirim squealer-tip passing blades. The experimental data were obtained at 2 MHz in a state-of-the-art two-stage high-speed turbine operated by the purdue experimental turbine aerothermal lab (PETAL). A description of the empirical setup is provided, emphasizing the capacitance probes, the conditioning and acquisition systems, the metrology instruments used, and other ancillary instrumentation relevant to the calibration procedure. The prior filtering and data identification from the raw signal are detailed. The step-by-step development of the algorithm is presented, including justification of the curves imposed by the method. The resulting calibrations are provided, achieving accuracies of a few microns. The results are compared against previously used calibration techniques, emphasizing the potential advantages of the presented routine. Finally, the time-resolved tip clearance is analyzed against high-frequency aerothermal data within the gap region, identifying relationships between the tip gap, unsteady pressure, and heat flux on the shroud. [ABSTRACT FROM AUTHOR]

This paper evaluates the effect of a microsecond pulsed plasma (MPP) on the stabilization and emission characteristics of non-premixed biogas/air flames with various CO2 contents. The MPP is generated by a unique DC-pulsed power generator providing high voltage (HV) pulses over a wide range of pulse repetition frequencies (PRFs). The burner configuration is made up of two concentric tubes in which a swirler is placed inside the annular part, ensuring the oxidizer's rotation. The central tube delivers the fuel through an injector placed close to the burner exit. Electrical diagnostics, including voltage, were performed. OH* chemiluminescence measurements were done to describe the structure and stability of the flame. Results showed that plasma generated by microsecond HV pulses can improve flame stability. In this regard, the distribution of key active species in the burner was studied via optical emission spectroscopy (OES). The results revealed that the pulsed plasma generates chemically active species such as excited N2*, CH*, OH* molecules, and H* and O* atoms, thereby improving flame stability. The dependence of the emitted species intensities on plasma parameters was investigated in detail. It is demonstrated that MPP can drastically enhance the dynamic flame stability of swirling non-premixed biogas flames, especially at lean operating conditions. In addition, NOx and CO emissions were studied over a wide range of pulse repetition frequencies. It is seen that the pulsed plasma increases NOx emission slightly and significantly reduces CO concentration in the flue gases. [ABSTRACT FROM AUTHOR]

The in situ imaging of the cutting process exhibits outstanding advantages in reconstructing the precise and visual thermoplastic deformation fields. The physical and geometric characteristics of deformation fields provide a deeper understanding of the cutting processes. In this paper, a mechanism-image hybrid analysis method is proposed to acquire the characteristics of the serrated chip deformation in the orthogonal cutting of TA15 titanium alloy based on in situ imaging. The established hybrid analysis method combines the shear-plane theory with the streamline method and image segmentation method, which realizes the identification of pixel coordinates of the main shear plane (MSP) and the primary shear zone (PSZ) and then the extraction of the physical and geometric variables from the digital image correlation (DIC) full-field measurements. Consequently, the variations of equivalent strain rate, strain, temperature, and the geometric characterizations of MSP and PSZ during an individual serration formation of TA15 titanium alloy were quantitatively investigated. It was found that the physical and geometric variables reached stability in the final stage of serration evolution and were averaged as the DIC-based equivalent characterizations to analyze the impact of cutting depth and tool rake angle. Meanwhile, the DIC-based equivalent characterizations were compared with the results obtained by the classical analytical models to illustrate the advantages of the DIC-based analysis. The findings also support that the established hybrid analysis method holds the potential to characterize the serrated chip formation of other materials and improve the models of PSZ. [ABSTRACT FROM AUTHOR]

This paper presents a novel nondestructive testing system, magneto-eddy-current sensor (MECS), to enable surface profiling of dissimilar materials by combining magnetic sensing for ferromagnetic materials and eddy-current sensing for nonferromagnetic materials. The interactions between an electromagnetic field and nonferromagnetic surface and between a magnetic field and ferromagnetic surface were measured by the MECS. The MECS consists of a conic neodymium magnet and a copper coil wound around the magnet. Aluminum and steel surfaces bonded together were prepared to test nondestructive surface profiling of dissimilar materials by the MECS. The interactions between an electromagnetic field and aluminum surface were characterized by monitoring the impedance of the coil, and the interactions between a magnetic field and steel surface were characterized by using a force sensor attached to the neodymium magnet. The magnetic and electromagnetic effects were numerically analyzed by the finite element model. The developed MECS showed the following performance: measurement spot size 5 mm and 10 mm, dynamic measurement bandwidth (eddy-current sensing 1 kHz and magnetic sensing 200 Hz), measuring range 25 mm and 17 mm, polynomial fitting error 0.51% and 0.50%, and resolution 0.655 µm and 0.782 µm for nonferromagnetic and ferromagnetic surface profiling, respectively. This technique was also applied to surface profiling and inspection of the rivet joining sheet materials. The results showed that the MECS is capable of nondestructively monitoring and determining the riveting quality in a fast, large-area, low-cost, convenient manner. [ABSTRACT FROM AUTHOR]

This paper presents a new method to efficiently update workpiece and determine cutter-workpiece engagement (CWE) in multi-axis milling simulation based on a uniform voxel modeling space. At each cutter location, a novel algorithm named direct voxel tracing is developed and used to generate a functional cutter surface voxel model to reliably establish the internal space of the milling cutter. The cutter internal space is represented by its voxel boundary with small memory usage. Through the Boolean subtraction between two successive voxel boundaries of the cutter internal space, a minimal voxel deactivation region is attained within which all active workpiece voxels are deactivated (removed) to update the workpiece model. To determine the associated CWE map, a 3D circle voxelization algorithm is employed. By slicing the cutter surface by a sequence of planes perpendicular to and along the cutter axis, CWE can be determined as the sliced 3D circles are voxelized. Quantitative comparisons of the proposed method against existing voxel modeling and vector modeling-based methods have been made. The results have demonstrated much improved computational efficiency of the proposed method in simulating the complex multi-axis milling operations. [ABSTRACT FROM AUTHOR]

Owing to the advantages of monolithic structure and little need for assembling, compliant guiding mechanisms appear to be an effective solution for decoupling multi-freedom precision motions but are still prone to geometric nonlinearities of parasitic error and stiffening effect for large strokes. This paper proposes a coiled L-shape compliant guiding mechanism featuring millimeter-scale strokes with a compact structure, constant stiffness, and minimized parasitic error. The coiled compliant guiding mechanism is formed by convolving L-shape flexure beams in a zigzag configuration with decoupled XY motions achieved. Its geometrically nonlinear parasitic error, variation in stiffness, and primary vibration are captured by using a dynamic beam constraint model (DBCM). It is theoretically, numerically, and experimentally found, by comparing with double parallel guiding mechanisms, that the kinetostatic and dynamic behaviors of the coiled L-shape compliant mechanism are nearly independent on the applied force within intermediate-deformation ranges. Such a weak geometric nonlinearity with the minimized influence of axially loaded stiffening and kinematics-arching effects is much different from the double parallel guiding mechanisms. The obtained results indicate that large strokes with constant stiffness and invariable resonance frequency can be realized, which also allows small parasitic errors. [ABSTRACT FROM AUTHOR]

In the development of innovative and high-performance products, design expertise is a critical factor. Nevertheless, novel manufacturing processes often frequently lack an accessible comprehensive knowledge base for product developers. To tackle this deficiency in the context of emerging additive manufacturing processes, substantial design knowledge has already been established. However, novel additive manufacturing processes like continuous fiber-reinforced material extrusion have often been disregarded, complicating the process's wider dissemination. The importance of design knowledge availability is paramount, as well as the need for user-friendly design knowledge preparation, standardized structure, and methodological support for accessing the accumulated knowledge with precision. In this paper, we present an approach that provides formalized opportunistic and restrictive design knowledge, ensuring both the comprehensive exploitation of process-specific potentials and the consideration of restrictive limitations in the construction of components. Opportunistic knowledge, presented as principle cards, is systematically derived, prepared, and made accessible. Moreover, an access system is developed to ensure the comprehensive utilization of process-specific potentials throughout the development process. Furthermore, we propose linking these principles through a synergy and conflict matrix, aiming to consider synergistic principles and identify potential conflicts at an early stage. Additionally, an approach to provide restrictive design knowledge in the form of a design rule catalog is proposed. The application of the knowledge system is demonstrated exemplarily using a weight-optimized component. [ABSTRACT FROM AUTHOR]

In the early stages of the design process, designers explore opportunities by discovering unmet needs and developing innovative concepts as potential solutions. From a human-centered design perspective, designers must develop empathy with people to truly understand their experiences and needs. However, developing empathy is a complex and subjective process that relies heavily on the designer's empathic capability, and is often subject to the experiences of a small group of people. Therefore, the development of empathic understanding is intuitive, and the discovery of underlying needs can be serendipitous and unrepresentative. This paper aims to provide insights from artificial intelligence research to indicate the future direction of AI-driven human-centered design, considering the essential role of empathy. Specifically, we conduct an interdisciplinary investigation of research areas such as data-driven user research, empathic design, and artificial empathy. Based on this foundation, we discuss the role that artificial empathy can play in human-centered design and propose an artificial empathy framework for human-centered design. Building on the mechanisms behind empathy and insights from empathic design research, the framework aims to break down the rather complex and subjective process of developing empathic understanding into modules and components that can potentially be modeled computationally. Furthermore, we discuss the expected benefits of developing such systems and identify research opportunities to suggest future research efforts. [ABSTRACT FROM AUTHOR]

Motivated by heat dissipation, the rigid-compliant hybrid cellular expansion mechanisms with motion amplification and superposition are proposed in this paper. Compared with existing studies, the expansion mechanism is not only easy to realize the plane tessellation via cellular design due to its regular polygon structure but also has the ability of motion amplification and superposition due to its compliant displacement amplifier and rigid scissors. First, the scheme of expansion mechanisms, especially the working principle of motion amplification and superposition, is introduced. The configuration design of a family of expansion mechanisms is presented, including varying number of edges, concave/convex property, and inner/outer layout. Second, the constraint condition and analytical modeling of relations between output performances of expansion mechanisms and dimensional parameters are carried out. Third, the displacement amplification ratio of expansion mechanisms and output performances of several typical expansion mechanisms when they act as cells to tessellate a plane with a constrained area are analyzed. Finally, the output performances of expansion mechanisms are verified via the finite element analysis. The results show that proposed cellular expansion mechanisms are beneficial for realizing plane tessellation and offer motion amplification and superposition, which provide prospects in the field of mechanism design such as metamaterials. [ABSTRACT FROM AUTHOR]

Sequential sampling methods have gained significant attention due to their ability to iteratively construct surrogate models by sequentially inserting new samples based on existing ones. However, efficiently and accurately creating surrogate models for high-dimensional, nonlinear, and multimodal problems is still a challenging task. This paper proposes a new sequential sampling method for surrogate modeling based on a hybrid metric, specifically making the following three contributions: (1) a hybrid metric is developed by integrating the leave-one-out cross-validation error, the local nonlinearity, and the relative size of Voronoi regions using the entropy weights, which well considers both the global exploration and local exploitation of existing samples; (2) a Pareto-TOPSIS strategy is proposed to first filter out unnecessary regions and then efficiently identify the sensitive region within the remaining regions, thereby improving the efficiency of sensitive region identification; and (3) a prediction-error-and-variance (PE&V) learning function is proposed based on the prediction error and variance of the intermediate surrogate models to identify the new sample to be inserted in the sensitive region, ultimately improving the efficiency of the sequential sampling process and the accuracy of the final surrogate model. The proposed sequential sampling method is compared with four state-of-the-art sequential sampling methods for creating Kriging surrogate models in seven numerical cases and one real-world engineering case of a cutterhead of a tunnel boring machine. The results show that compared with the other four methods, the proposed sequential sampling method can more quickly and robustly create an accurate surrogate model using a smaller number of samples. [ABSTRACT FROM AUTHOR]

The moment method is commonly used in reliability analysis, in which the maximum entropy method (MEM) and polynomial fitting (PF) have been widely used due to their advantages in accuracy and efficiency, respectively. In this paper, we propose a novel reliability analysis method by combining MEM and PF. The probability density function is preliminarily estimated using the fractional moment maximum entropy method (FM-MEM), based on which PF is then used to further improve the accuracy. The proposed method can avoid the phenomenon of the negative probability density and function oscillations in PF effectively. Moreover, the order of the exponential polynomial in the FM-MEM is adaptively selected in the preliminary solution calculation process. An iterative process for the number of exponential polynomial terms is also proposed, using the integral of the moment error function and the integrals of the local and global negative probability density as the convergence criteria. Four numerical examples and one engineering example are tested, and the results are compared with those of the Monte Carlo simulation and the classical FM-MEM results, respectively, demonstrating the good performance of the proposed method. [ABSTRACT FROM AUTHOR]

Bayesian optimization (BO) is a sequential optimization strategy that is increasingly employed in a wide range of areas such as materials design. In real-world applications, acquiring high-fidelity (HF) data through physical experiments or HF simulations is the major cost component of BO. To alleviate this bottleneck, multi-fidelity (MF) methods are used to forgo the sole reliance on the expensive HF data and reduce the sampling costs by querying inexpensive low-fidelity (LF) sources whose data are correlated with HF samples. However, existing multi-fidelity BO (MFBO) methods operate under the following two assumptions that rarely hold in practical applications: (1) LF sources provide data that are well correlated with the HF data on a global scale, and (2) a single random process can model the noise in the MF data. These assumptions dramatically reduce the performance of MFBO when LF sources are only locally correlated with the HF source or when the noise variance varies across the data sources. In this paper, we view these two limitations and uncertainty sources and address them by building an emulator that more accurately quantifies uncertainties. Specifically, our emulator (1) learns a separate noise model for each data source, and (2) leverages strictly proper scoring rules in regularizing itself. We illustrate the performance of our method through analytical examples and engineering problems in materials design. The comparative studies indicate that our MFBO method outperforms existing technologies, provides interpretable results, and can leverage LF sources which are only locally correlated with the HF source. [ABSTRACT FROM AUTHOR]

The Rivlin-Thomas classical energy balance model for tearing tests suggests that the fracture energy G is proportional to the work of the external load in the legs (potential energy), for not too large stretches in the legs, so the increase of G with loading rate is observed or measured, but not really explained by the model. Shrimali and Lopez-Pamies (SLP) have recently built a theory on viscoelastic fracture from recent experimental evidence of a critical (stretch rate-independent) stretch on nucleation of cracks in the pure shear tests. The theory in other words incorporates this evidence in an otherwise energy-based criterion. In the paper "The trousers fracture test for viscoelastic elastomers" (ASME J. Appl. Mech., 2023, 90(7), p. 071010), they seem to obtain the critical (stretch rate-independent) stretch condition for the case of trouser tests (applying their theory from a long enough crack) both in nucleation and steady-state propagation. This outcome seems reasonable since for a linear material, looking at the elastic limit cases of very slow and very fast rates, it would produce an increase of the load, and hence of the fracture energy, proportional to the increase of the modulus, which is in line with what has been found experimentally, although possibly in contrast with classical rate-independent cohesive models, at least for crack nucleation. [ABSTRACT FROM AUTHOR]

Rotating waves can be observed in structures with periodic conditions, such as cylinders and spheres. Compared with traveling waves and standing waves, rotating waves have received less attention. In this paper, an odd elastic dynamic model of the cylindrical shells is established, and the dispersion relation, traveling waves, and standing waves are investigated. The non-Hermitian rotating waves and single-handedness chiral standing spin waves are reported, which are novel dynamic phenomenon caused by odd elastic effects. Waves generally cannot propagate in passive materials with vanishingly small elastic modulus. However, a unidirectional wave with the highest cut off frequency can occur in an odd elastic cylindrical shell with vanishingly small elastic modulus. For incompletely restrained end displacements, the odd elastic cylindrical shell can also generate a hybrid mode combining standing spin waves with unidirectional waves. [ABSTRACT FROM AUTHOR]

Snap-through instabilities in single and interconnected dielectric elastomer actuators have demonstrated their potential in enabling many functionalities such as large deformation, high-speed actuation, and enhanced flowrates in fluid pumps. However, the nonlinear nature of dielectric elastomers and the complex interplay of mechanics in interconnected inflated actuators, make the modeling of such systems challenging. In this paper, we present a methodology to analytically model the instabilities in a system of three interconnected homogeneous spherical dielectric elastomer actuators through graphical and numerical approaches. The simulation results reveal the presence of a locus of initial stable states that the interconnected actuators can achieve at zero voltage. In specific loading conditions, the system exhibits multiple stable states which can be cyclically transitioned between by selectively applying voltage to specific actuators. In other conditions, the system may undergo two successive instabilities when the voltage applied to a single actuator in the system is increased monotonically. These results retrieve existing experimental results theoretically for the first time and identify a new behavior of cascading instabilities in inflated dielectric elastomer actuators. We hope this work will pave the way for programmable design of multistable systems to unravel new capabilities in dielectric elastomer actuators and soft robotics. [ABSTRACT FROM AUTHOR]

Existing studies on wrinkling, an instability phenomenon commonly observed on electro-active polymers (EAP), have largely ignored the unequal-biaxial taut states, focusing instead on the equal-biaxial deformations of such a material class. EAP-based soft actuators, primarily used in soft robotics, frequently exhibit a variety of instabilities, which may adversely affect their functioning and trigger device failure. Conversely, wrinkles can be utilized proactively in specific applications that necessitate an intentional transformation in surface morphology along with functional particle reinforcement on EAP composites. The dielectric elastomer is a promising EAP material class for the same, often filled with functional particles to improve its electromechanical performance. This paper theoretically develops a continuum physics-based unequal-biaxial deformation model incorporating the classical tension field theory to predict the thresholds on the taut domains in the plane of principal stretches. The model solution ties an unanswered ideal remark on the deviations of taut states with the biaxiality ratio of unequal-biaxially deformed wrinkle appearance in EAP composites. The proposed model solution may aid in designing next-generation soft robotic systems by offering guidelines for the wrinkling control of EAP composites. [ABSTRACT FROM AUTHOR]

With aviation's dependence on the high volumetric energy density offered by liquid fuels, Sustainable Aviation Fuels (SAFs) could offer the fastest path toward the decarbonization of aircrafts. However, the chemical properties of SAFs present new challenges, and research is needed to better understand their injection, combustion, and emission processes. While efforts such as the United States National Jet Fuel Combustion Program (NJFCP) that investigated several aspects in detail, certain processes were unfortunately beyond the reach of this program. One of them in particular is about droplet evaporation at relevant pressures and temperatures, and this represents the focus of the present paper. To address this gap, we characterized the evaporation and mixing of spray droplets injected into well-controlled thermodynamic environments at conditions relevant to modern and next-generation aero-engine combustors. We tested three fuels from the NJFCP, namely, an average Jet A fuel (A-2), an alcohol-to-jet fuel containing highly branched dodecane and hexadecane type components (C-1), and a blend made of 40% C-1 and 60% isoparaffins ranging from 9 to 12 carbon atoms (C-4). We also tested a single component normal alkane: n-dodecane, as well as an advanced bioderived cyclo-alkane fuel: bicyclohexyl. The time evolution of fuel droplets was monitored using high-speed long-distance microscopy in a specific configuration that enabled sharp images to be acquired at these extreme conditions. The collected images were processed using a purposely developed and trained machine learning (ML) algorithm to detect and characterize the droplets' evaporation regime. The results revealed different evaporation regimes, such as classical and diffusive. In agreement with previous studies, evaporation regimes appear to be controlled by ambient pressure, temperature, and fuel type. The measurements demonstrate that diffusive evaporation is relevant at high-pressure conditions, such as takeoff combustor pressures for modern commercial aircraft engines. However, classical evaporation mostly controls mixing at lower pressure, such as cruise altitude conditions. The ML analysis emphasized that multiple evaporation regimes co-existed at the same operating condition and no significant relationship was found between droplet size and evaporation regime. The findings of this work constitute a database for validating spray and droplet models that are necessary for implementing lower emissions fuels in aero-engines. [ABSTRACT FROM AUTHOR]

Current research on engine transient performance primarily focuses on the variation of key aerothermodynamic parameters in specific sections, neglecting the comprehensive understanding of the engine's inner flow field during transient operations. To address this gap, this paper proposes a two-dimensional transient simulation method that effectively captures the evolution of the flow field in the meridional plane. The approach involves deriving circumferential averaging equations in a rotating coordinate system with variable angular velocity, considering angular acceleration source terms. The engine components, including the compressor, combustion chamber, turbine, and rotating shaft, are individually modeled. The newly derived governing equations are solved using a dual-time-step approach, where an inner-iteration ensures mass flow conservation, and an outer-iteration updates the rotational speed. Using a real turbojet engine as a case study, transient examinations comprising acceleration and deceleration are performed. A comparative analysis of experimental and simulation results is conducted, revealing an average error of 0.9% in shaft speed, 7.8% in engine thrust, 1.7% in engine exhaust temperature, and 5.1% in compressor outlet pressure. Additionally, the study analyzes and compares the internal flow fields during the transient process, contributing to a deeper understanding of the engine's dynamic behavior. The research effort establishes a practical methodology and technology for conducting comprehensive two-dimensional engine transient cycle analyses within reasonable computational resources and timeframes. [ABSTRACT FROM AUTHOR]

At an ever-faster pace, market's requirements for operational flexibility and turn-down capabilities are fundamental for heavy-duty gas turbines. Gas turbine energy plants require the lowest minimum environmental load (MEL) for times when the power request is mainly covered by renewable sources and, however, need to promptly respond to green energy shortages. Ansaldo Energia has addressed such requirements overall its gas turbine portfolio, recently including GT26, as discussed in GT2021-59457. This paper addresses the MEL reduction for AE94.3A via a modular upgrade package intended for the 110+ units Service fleet. To accomplish that, several features were designed and tested including variable inlet guide vanes (VIGV) extra-closure, air bypass through compressor blow-off lines, and extended use of anti-ice air recirculation. None of these require major hardware changes but only upgrades within a normal service outage, together with minor control system adaptations. The wide-ranging technical challenges attached to the MEL reduction features are discussed. Validation on field via special instrumentation focused on compressor, secondary air system (SAS), and turbine for several engines is also presented. The achieved minimum environmental load reduction is shown and its potential discussed together with some features already in place, such as the use of CO catalyzer or the regulation of control valves put on external cooling lines. The readiness and performance level of this MEL upgrade package, already in operation on several power plants, is here demonstrated. This makes the AE94.3A gas turbine more flexible toward current and future market requirements. [ABSTRACT FROM AUTHOR]

This paper presents an analysis of the unsteady heat release rate response of industrially relevant axisymmetric premixed flames to harmonic velocity perturbations. The heat release rate response, quantified using the flame transfer function (FTF) definition, is measured from an acoustically forced swirl burner under perfectly premixed conditions. To understand the features of the measured FTF, a physics-based analytical model is developed in this study. To describe the heat release rate dynamics, a model for the flame spatiotemporal response is derived in the linear limit using the G-equation formulation. Inputs to the flame response model are selected to be consistent with values observed in the corresponding industrial burner, based on experimental and numerical studies. The relative contributions of acoustic and convecting vortical disturbances on specific features of the FTF are explored in this study. The results highlight the importance of capturing the appropriate disturbance velocity field as an input to the flame response model for accurate FTF predictions. [ABSTRACT FROM AUTHOR]

In this paper, an experimental test rig for friction saturated limit cycle oscillations is proposed to provide a validation basis for corresponding numerical methods. Having in mind the application of turbine blades, an instrumented beam-like structure equipped with an adjustable velocity feedback loop and dry frictional contacts is designed and investigated. After dimensioning the test rig by means of a simplified one-dimensional beam model and time domain simulations, the specific requirements of limit cycle oscillations for the design of the frictional contact, the velocity feedback loop and the excitation system are discussed and possible solutions are presented. Also appropriate measuring principles and evaluation techniques are assessed. After commissioning of the test rig, the influence of the negative damping and the normal contact force on the limit cycle oscillations is measured and the practical stability is investigated. The test rig shows linear dynamics for sticking contact and highly repeatable limit cycles. The measured results are discussed regarding the consistency with theory and compared to the predictions of a three dimensional reduced order model solved in frequency domain by the harmonic balance solver OrAgL. It is demonstrated that the numerical modeling strategy is able to accurately reproduce the measured limit cycle oscillations, which stabilized for different contact normal forces and self-excitation levels. [ABSTRACT FROM AUTHOR]

Reduction of gas turbine (GT) carbon emissions relies on a strategy for fueling the engines with pure or blended hydrogen. The major technical challenges to solve are (i) the adjustments to the engine and in particular the combustion chamber and (ii) a series of issues to solve to guarantee safe operations. In fact, compared to natural gas, hydrogen fueling implies higher risks of explosion in case of leak in the turbine enclosure and a more careful design of the ventilation system. Thus, a deeper comprehension of hydrogen leak scenarios is needed to adjust the safe design strategy of the enclosure. To this aim, a series of numerical investigations was carried out to understand how different methane-hydrogen blends (from pure methane to pure hydrogen) behave when leaking from a pipeline with fuel pressure that span from 1.5 to 4.5 MPa. The different fuel blends' leaks in form of underexpanded jets were studied under different cross-flow ventilation conditions, with ventilation velocity spanning from 0 m/s to 5 m/s. When compared to pure methane, the outcome is a three times longer penetration distance for pure hydrogen axisymmetric flammable clouds, whereas in cross-flow conditions a more complex three-dimensional behavior was found, potentially opening a safety-related concerns discussed in the paper. [ABSTRACT FROM AUTHOR]

The design of supersonic military aircraft is a complex multidisciplinary optimization process in which the dependencies and strong interactions between engine and aircraft must be imperatively considered. Applying a fully coupled propulsion-airframe design system is a highly challenging task, since it requires a set of numerically stable analysis tools capable of optimizing multiple design variables simultaneously. To improve computational efficiency, the application of low-fidelity design of experiment (DOE) methods aids in narrowing down the selection of suitable combinations of design parameters. This approach allows the division of the multidisciplinary process into subsystems, each of which can be served by specialized engineers. Interactions between the disciplines are then considered by exchanging DOE-based sensitivities. This paper presents the multidisciplinary design process developed at the German Aerospace Center (DLR)--in which the airframe and propulsion system are designed simultaneously while effectively utilizing DOE-based sensitivities. Guiding the work is an application case on the preliminary design of military engine concepts considering its effects on overall integrated aircraft architecture. The design process is used to investigate the influence of important engine parameters such as overall pressure ratio (OPR), bypass ratio (BPR), and turbine entry temperature (T4) on the design of military aircraft. Furthermore, the impacts of thrust requirements and technological constraints of the engine are analyzed. [ABSTRACT FROM AUTHOR]

Robust methods to predict heat transfer are vital to accurately control the blade-tip clearance in compressors and the radial growth of the disks to which these blades are attached. Fundamentally, the flow in the cavity between the co-rotating disks is a conjugate problem: the temperature gradient across this cavity drives large-scale buoyant structures in the core that rotate asynchronously to the disks, which in turn governs the heat transfer and temperature distributions in the disks. The practical engine designer requires expedient computational methods and low-order modeling. A conjugate heat transfer (CHT) methodology that can be used as a predictive tool is introduced here. Most simulations for rotating cavities only consider the fluid domain in isolation and typically require known disk temperature distributions as the boundary condition for the solution. This paper presents a novel coupling strategy for the conjugate problem, where unsteady Reynolds averaged Navier-Stokes (URANS) simulations for the fluid are combined with a series of steady simulations for the solid domain in an iterative approach. This strategy overcomes the limitations due to the difference in thermal inertia between fluid and solid; the method retains the unsteady flow features but allows a prediction of the disk temperature distributions, rather than using them as a boundary condition. This approach has been validated on the fundamental flow configuration of a closed co-rotating cavity. Metal temperatures and heat transfer correlations predicted by the simulation are compared to those measured experimentally for a range of engine-relevant conditions. [ABSTRACT FROM AUTHOR]

Carbondioxide at supercritical state shows particularly favorable thermodynamic properties for closed-loop Brayton and Rankine cycles. High density, close to a liquid, and low viscosity, close to a gas, drive to achieve higher energy conversion efficiency with smaller size turbines and components. Since minimizing the sCO2 leakage flows drives to a further increasing of overall efficiency, dry gas seals (DGS) are considered as a key enabling technology for achieving this purpose and for achieving a carbon footprint in line with the increasingly stringent targets. DGSs are gas-lubricated, mechanical, noncontacting, end-face seals, consisting of a mating (rotating) ring and a primary (stationary) ring. The operating equilibrium clearance of the seal is determined by the balance of opening dynamic forces, mainly depending on angular velocity and grooves shape, and closing forces caused by pressure gradients and spring force. Due to high rotational speeds, typical small size sealing gaps (order of magnitude of Micron), high fluid pressure and density, the heat generated by friction through the seal has a large impact on the temperature distribution, therefore a thermal design is needed to stay below the seal allowable temperature; this requirement has been even amplified in the last years with the DGS application to hot turbomachinery. Nowadays, numerical conjugate heat transfer (CHT) analysis is a good industrial practice to quantify the thermal distribution in turbomachinery components. On the other hand, due to different order of magnitude of secondary flows cavity sizes and DGS seal gaps, simulating the whole fluid domain with three-dimensional (3D) computational fluid dynamic (CFD) calculation could drive to prohibitive computational costs. In this regard, this paper presents a fast numerical iterative procedure based on a commercial one-dimensional flow network modeler (altair flow simulator), with real gas effects included, coupled with a commercial finite element solver (ansys mechanical). Additional 3D CFD simulations are carried out to enhance the predictability of the fluid solver in specific critical areas. The proposed procedure is applied and validated in a DGS specific test bench designed, owned and operated by Flowserve. The validation dataset has been generated operating the DGS in the test bench at 15 different conditions in terms of angular velocity and housing temperature with sCO2 as working fluid aligned with those expected on the unit. Test rig consists of a rotor and housing where the turbomachine operating condition (pressure, speed, temperature and sealing fluid) are mirrored to verify the seal performance. The rig is equipped with test seal and a plug seal mounted in a back-to-back configuration. Data set used for this comparison is composed by thermocouples on the statoric rings, retainers and housing of each seal, operating at five different angular speeds and three minimum levels of housing temperature (100 °C, 210 °C, and 250 °C). These temperatures are designed to mirror turbomachinery conditions around the seal, and, if friction heat is not enough to guarantee them, a series of 18x1 kW heating elements circumferentially distributed in the test bench housing, are activated. The nominal operating condition has been considered as the starting point of the model predictions and, there, several sensitivity analyses have been carried out to align the model to test bench measurements; then, the selected configuration has been frozen and used to assess the model performance on other operating conditions. The numerical results have shown a good agreement with experimental data at each operating condition in terms of punctual temperatures previously described and with extremely low computational times. [ABSTRACT FROM AUTHOR]

The current energy scenario requires that gas turbines (GTs) operate at their maximum efficiency and highest reliability. Trip is one of the most disrupting events that reduces GT availability and increases maintenance costs. To tackle the challenge of GT trip prediction, this paper presents a methodology that has the goal of monitoring the early warnings raised during GT operation and trigger an alert to avoid trip occurrence. The methodology makes use of an auto-encoder (prediction model) and a three-stage criterion (detection procedure). The auto-encoder is first trained to reconstruct safe operation data and subsequently tested on new data collected before trip occurrence. The trip detection criterion checks whether the individually tested data points should be classified as normal or anomalous (first stage), provides a warning if the anomaly score over a given time frame exceeds a threshold (second stage), and, finally, combines consecutive warnings to trigger a trip alert in advance (third stage). The methodology is applied to a real-world case study composed of a collection of trips, of which the causes may be different, gathered from various GTs in operation during several years. Historical observations of gas path measurements taken during three days of GT operation before trip occurrence are employed for the analysis. Once optimally tuned, the methodology provides a trip alert with a reliability equal to 75% at least 10 h in advance before trip occurrence. [ABSTRACT FROM AUTHOR]