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At least 1,189 records · Page 66

Demonstration of Probabilistic Sensitivity Analyses Tools on the Structural Response of a Representative Inflatable Space Structure

This work provides an initial step toward demonstrating a probabilistic numerical simulation capability to support trade studies and the development of a certification plan for inflatable space habitats. This study concentrates on interpreting the results from probabilistic analysis and numerical simulation tools to identify parameter sensitivities for a novel inflatable airlock concept, specifically the Non‐Axisymmetric Inflatable Pressure Structure (NAIPS) that was designed and tested under NASA's Minimalistic Advanced Softgoods Hatch (MASH) Program. A brief overview of the finite element model is provided along with the probabilistic sensitivity analysis approach. The sensitivity studies required a model that was numerically stable and efficient enough that hundreds of simulations could be completed in the allotted time. Therefore, the existing full model was simplified by: extracting a quarter symmetry section of the dome; focusing on a single inflation pressure; and replacing the non‐linear material stress‐strain curves with linear, isotropic materials defined by elastic moduli. Responses of interest include the sensitivity of various structural component loads to material properties, cord lengths, inflation pressure and friction. Multiple sensitivity studies were completed and three are reported here. The first study focused on utilizing wide input parameter ranges to provide an opportunity to assess numerical robustness. The next two studies narrowed the parameter ranges to enable focus on understanding uncertainty at a fixed operating condition. The completion of the sensitivity studies improved understanding of the interdependence of multiple inputs on the responses. In addition, numerical stability of the simulations over wide parameter ranges, shows the feasibility of incorporating uncertainty‐based methods in the design and certification of inflatable space habitats. With the experience and trust gained, it is anticipated that these same methods will be applied to nonlinear, orthotropic models in the future.

Lyle, Karen H.↗

Organized kinetic energy backscatter in the hurricane boundary layer from radar measurements

The fluid mechanics of hurricanes strongly depends on boundary layer energetics due to the warm-core nature of the system with peak velocities located at lower levels. One barrier that has inhibited a more complete characterization of energy transfer in the boundary layer is a lack of observations that resolve large, turbulent eddies. In particular, the occurrence and structure of upscale energy transfer (backscatter) in the hurricane boundary layer as well as the effects of backscatter on the vortex intensity are unknown. The analysis presented here of very high-resolution, three-dimensional wind observations from Hurricane Rita (2005) at peak intensity reveals large regions of organized backscatter in the boundary layer associated with coherent, turbulent eddies. Strong forwardscatter is also found next to the backscatter regions due to the interaction between adjacent eddies. Two components of the stress tensor are primarily responsible for this alternating scatter structure, as shown by large correlation coefficients between the fields: the radial–vertical component (τ13) and the azimuthal–vertical component (τ23) with average correlations of 79% and 49 %, respectively. The Leonard, Reynolds and cross-term stress components are also provided. The impact of the sub-filter-scale energy transfer is estimated by computing the kinetic energy budget for the resolved-scale and eddy-scale motions. The results show that the sub-filter-scale energy transfer term is of the same order as the other terms in the eddy-scale budgets, contributing between 16% and 40% to the local time tendency with an average contribution of approximately 30 %. These results indicate that the coherent turbulent eddies can affect the vortex dynamics through wave–wave nonlinear interactions, which can subsequently influence the wave–mean flow interactions. This is the first study to examine the full sub-filter-scale

Sydney Sroka↗

Chemical Thermodynamics and the Mathematical Integration of Reaction Kinetics

Key advances in the development of numerical methods for non-reacting compressible flows have been enabled by translating physical requirements into concrete numerical guidelines, such as the satisfaction of entropy inequalities for shock-capturing techniques [Lax, Contributions to Nonlinear Functional Analysis (1971) 603-634]. In the present work, we present nonlinear numerical analysis tools that draw from Chemical Thermodynamics , the branch of Nonequilibrium Thermodynamics that deals with chemical reactions. Through Gibbs formalism, chemical thermodynamics provides a well-known theoretical expression for the chemical equilibrium constant of a reaction in terms of reduced chemical potentials. A less-known, yet extremely valuable result, due to [Krambeck, Arch. Ration. Mech. Anal. , 38 (1970) 317], states that when this expression is implemented, mass-action kinetic models are consistent with the dynamical prescriptions of the 2nd law of thermodynamics. For fixed-temperature ordinary differential equations modeling constant-volume reacting gas mixtures, this leads to a decreasing Helmholtz free energy. If the temperature is allowed to vary in accordance with conservation of energy (1st law), this leads to the statement of increasing entropy. These nonlinear prescriptions can, and should be, used to further develop temporal integration techniques for reaction kinetics. We demonstrate that Krambeck's result holds even when the equilibrium constants are approximated from data. We prove this result by constructing the implicit free energy and the implicit entropy inherent to a given approximation. This is first done for a 5-species, 17-reaction model problem for air. With this structure established, elements of discrete entropy-stability theory [Tadmor, Acta Numer. , 12 (2003) 451] are leveraged to examine the consistency of time-integration schemes with these prescriptions. Using chemical potentials, one can compute the respective contributions of the kinetics model and of the temporal scheme to free energy/entropy variations. We introduce a nonlinear-stable version of the Discontinuous-Galerkin (DG) scheme in time which shows robustness improvements over the standard linearly-stable version. Most notably, the maximum timestep that can be resolved with the nonlinearly-stable variant tends to grow with polynomial order, in contrast to the linearly-stable variant. We generalize our constructions to arbitrary systems of reversible chemical reactions, ultimately showing that the compressible reacting Euler system admits the opposite of the implicitly constructed thermodynamic entropy as a mathematical entropy . This lays important theoretical foundations towards robust scheme development [Harten, J. Comput. Phys. 49 (1983) 151-164].

STMD↗

Invariant Theory for Dispersed Transverse Isotropy: An Efficient Means for Modeling Fiber Splay

Most soft tissues possess an oriented architecture of collagen fiber bundles, conferring both anisotropy and nonlinearity to their elastic behavior. Transverse isotropy has often been assumed for a subset of these tissues that have a single macroscopically-identifiable preferred fiber direction. Micro-structural studies, however, suggest that, in some tissues, collagen fibers are approximately normally distributed about a mean preferred fiber direction. Structural constitutive equations that account for this dispersion of fibers have been shown to capture the mechanical complexity of these tissues quite well. Such descriptions, however, are computationally cumbersome for two-dimensional (2D) fiber distributions, let alone for fully three-dimensional (3D) fiber populations. In this paper, we develop a new constitutive law for such tissues, based on a novel invariant theory for dispersed transverse isotropy. The invariant theory is based on a novel closed-form splay invariant that can easily handle 3D fiber populations, and that only requires a single parameter in the 2D case. The model is polyconvex and fits biaxial data for aortic valve tissue as accurately as the standard structural model. Modification of the fiber stress-strain law requires no re-formulation of the constitutive tangent matrix, making the model flexible for different types of soft tissues. Most importantly, the model is computationally expedient in a finite-element analysis.

Freed, alan D.↗

A General Interface Method for Aeroelastic Analysis of Aircraft

The aeroelastic analysis of an aircraft requires an accurate and efficient procedure to couple aerodynamics and structures. The procedure needs an interface method to bridge the gap between the aerodynamic and structural models in order to transform loads and displacements. Such an interface method is described in this report. This interface method transforms loads computed by any aerodynamic code to a structural finite element (FE) model and converts the displacements from the FE model to the aerodynamic model. The approach is based on FE technology in which virtual work is employed to transform the aerodynamic pressures into FE nodal forces. The displacements at the FE nodes are then converted back to aerodynamic grid points on the aircraft surface through the reciprocal theorem in structural engineering. The method allows both high and crude fidelities of both models and does not require an intermediate modeling. In addition, the method performs the conversion of loads and displacements directly between individual aerodynamic grid point and its corresponding structural finite element and, hence, is very efficient for large aircraft models. This report also describes the application of this aero-structure interface method to a simple wing and an MD-90 wing. The results show that the aeroelastic effect is very important. For the simple wing, both linear and nonlinear approaches are used. In the linear approach, the deformation of the structural model is considered small, and the loads from the deformed aerodynamic model are applied to the original geometry of the structure. In the nonlinear approach, the geometry of the structure and its stiffness matrix are updated in every iteration and the increments of loads from the previous iteration are applied to the new structural geometry in order to compute the displacement increments. Additional studies to apply the aero-structure interaction procedure to more complicated geometry will be conducted in the second phase of the present contract.

Tzong, T.↗

Model of a rotating magnetic cloud

The possibility that magnetic clouds rotate while they propagate antisunward was investigated. Magnetic clouds are modeled as magnetic flux ropes which rotate rigidly about the axis of symmetry. An ideal magnetohydrodynamic model, in which the evolution of the magnetic structure is related to the time evolution of the angular frequency, is developed. A class of 'separable' magnetic fields is employed to reduce the problem to a nonlinear ordinary differential equation for the evolution function, and it is solved numerically. The corresponding effective potential gives rise to two modes of evolution--expansion and oscillation--depending on the energy and on the value of a dimensionless parameter, k. Parameter k depends on the gas pressure, the ratio of the magnetic field components, and the frequency of rotation. There is a critical value of k, k(sub c), above which the oscillatory regime disappears and the flux rope invariably expands, regardless of the energy. Below k(sub c) the energy determines whether the configuration is confined or unbounded. Rotation always helps expansion by lowering the potential barrier. A data example was studied and features which are interpreted as signatures of rotation are presented. The angular speed is comparable to the Alfven speed, and the core of the rotating cloud completes on average one full revolution every three days at 1 AU. The parameter k is calculated from observations, and it is found to be close to, but below, critical. Only three out of the nine clouds examined showed signatures of rotation. Theoretical analysis suggests that close to the Sun rotation effects may play a more important role in the evolution of magnetic clouds than 1 AU.

Farrugia, C. J.↗

Feasibility Study of SDAS Instrumentation's Ability to Identify Mobile Launcher (ML)/Crawler-Transporter (CT) Modes During Rollout Operations

The Space Launch System (SLS) and its Mobile Launcher (ML) will be transported to the launch pad via the Crawler-Transporter (CT) system. Rollout (i.e., transportation) loads produce structural loads on the integrated SLS/Orion Multi-Purpose Crew Vehicle (MPCV) launch vehicle which are of a concern with respect to fatigue. As part of the risk reduction process and in addition to the modal building block test approach that has been adopted by the SLS Program, acceleration data will be obtained during rollout for use in modal parameter estimation. There are several occurrences where the ML/CT will be transported either into the Vertical Assembly Building (VAB) or to the launch pad and back without the SLS stack as part of the Kennedy Space Center (KSC) Exploration Ground Systems (EGS) Integrated Test and Checkout (ITCO). NASA KSC EGS has instrumentation installed on both the ML and CT to record data during rollout, at the launch pad, and during liftoff. The EGS instrumentation on the ML, which includes accelerometers, is referred to as the Sensor Data Acquisition System (SDAS). The EGS instrumentation on the CT, which also includes accelerometers, is referred to as the CT Data Acquisition System (CTDAS). The forces and accelerations applied to the ML and CT during a rollout event will be higher than any of the planned building block modal tests. This can be very beneficial in helping identify nonlinear behavior in the structure. Developing modal parameters from the same test hardware in multiple boundary conditions and under multiple levels of excitation is a key step in developing a well correlated FEM. The purpose of this study was three fold. First, determine the target modes of the ML/CT in its rollout configuration. Second, determine if the test degrees of freedom (DOF) corresponding to the layout of the SDAS/CTDAS accelerometers (i.e. position and orientation) is sufficient to identify the target modes. Third, determine if the Generic Rollout Forcing Functions (GRFF's) is sufficient for identifying the ML/CT target modes accounting for variations in CT speed, modal damping, and sensor/ambient background noise levels. The finding from the first part of this study identified 28 target modes of the ML/CT rollout configuration based upon Modal Effective Mass Fractions (MEFF) and engineering judgement. The finding from the second part of this study showed that the SDAS/CTDAS accelerometers (i.e. position and orientation) are able to identify a sufficient number of the target modes to support model correlation of the ML/CT FEM. The finding from the third part of this study confirms the GRFFs sufficiently excite the ML/CT such that varying quantities of the defined target modes should be able to be extracted when utilizing an Experimental Modal Analysis (EMA) Multi-Input Multi-Output (MIMO) analysis approach. An EMA analysis approach was used because Operational Modal Analysis (OMA) tools were not available and the GRFFs were sufficiently uncorrelated. Two key findings from this third part of the study are that the CT speed does not show a significant impact on the ability to extract the modal parameters and that keeping the ambient background noise observed at each accelerometer location at or below 30 µgrms is essential to the success of this approach.

Winkel, James P.↗

Analysis and Tests of Reinforced Carbon-Epoxy/Foam-Core Sandwich Panels with Cutouts

The results of a study of a low-cost structurally efficient minimum-gage shear-panel design that can be used in light helicopters are presented. The shear-panel design is based on an integrally stiffened syntactic-foam stabilized-skin with an all-bias-ply tape construction for stabilized-skin concept with an all-bias-ply tape construction for the skins. This sandwich concept is an economical way to increase the panel bending stiffness weight penalty. The panels considered in the study were designed to be buckling resistant up to 100 lbs/in. of shear load and to have an ultimate strength of 300 lbs/in. The panel concept uses unidirectional carbon-epoxy tape on a syntactic adhesive as a stiffener that is co-cured with the skin and is an effective concept for improving panel buckling strength. The panel concept also uses pultruded carbon-epoxy rods embedded in a syntactic adhesive and over-wrapped with a bias-ply carbon-epoxy tape to form a reinforcing beam which is an effective method for redistributing load around rectangular cutout. The buckling strength of the reinforced panels is 83 to 90 percent of the predicted buckling strength based on a linear buckling analysis. The maximum experimental deflection exceeds the maximum deflection predicted by a nonlinear analysis by approximately one panel thickness. The failure strength of the reinforced panels was two and a half to seven times of the buckling strength. This efficient shear-panel design concept exceeds the required ultimate strength requirement of 300 lbs/in by more than 100 percent.

Baker, Donald J.↗

Strain Measurement Using FBG on COPV in Stress Rupture Test

White Sands Test Facility (WSTF) was requested to perform ambient temperature hydrostatic pressurization testing of a Space Transportation System (STS) 40-in. Kevlar Composite Overwrapped Pressure Vessel (COPV). The 40-in. vessel was of the same design and approximate age as the STS Main Propulsion System (MPS) and Orbiter Maneuvering System (OMS) vessels. The NASA Engineering Safety Center (NESC) assembled a team of experts and conducted an assessment that involved a review of national Kevlar COPY data. During the review, the STS COPVs were found to be beyond their original certification of ten years. The team observed that the likelihood of STS COPV Stress rupture, a catastrophic burst before leak failure mode, was greater than previously believed. Consequently, a detailed assessment of remaining stress rupture life became necessary. Prior to STS-114, a certification deviation was written for two flights of OV-103 (Discovery) and OV-104 (Atlantis) per rationale that was based on an extensive review of the Lawrence Livermore National Laboratories, COPV data, and revisions to the STS COPV stress levels. In order to obtain flight rationale to extend the certification deviation through the end of the Program, the Orbiter Project Office has directed an interagency COPV team to conduct further testing and analysis to investigate conservatism in the stress rupture model and evaluate material age degradation. Additional analysis of stress rupture life requires understanding the fiber stresses including stress that occurs due to thru-wall composite compression in COPV components. Data must be obtained at both zero gauge pressure (pre-stress) and at the component operating pressure so that this phenomenon can be properly evaluated. The zero gauge pressure stresses are predominantly a result of the autofrettage process used during vessel manufacture. Determining these pre-stresses and the constitutive behavior of the overwrap at pressure will provide necessary information to better predict the remaining life of the STS COPVs. The primary test objective is obtaining data to verify the hypothesis of a radially oriented thru-thickness stress-riser in the COPV composite whose magnitude is a function of the applied pressure and the load history. The anticipated load dependent response follows from the constitutive behavior of the composite overwrap so data to quantify its nonlinear and time dependent response will be sought. The objective of the Fiber Braggs Gratings (FBGs) were to advance the state-of-the-art by developing techniques using FBG sensors that are capable of assessing stress-rupture degradation in Kevlar COPVs in a health monitoring mode (1). Moreover, they sought to answer questions of how embedded sensors affect overall integrity of the structure. And lastly, they sought to provide an important link in the overall stress rupture study that will help close the loop on the COPV fabrication process. NDE inspection methods will be used from start to finish and FBG will be an integral link within the overall chain.

Banks, Curtis↗

On the dynamics of approximating schemes for dissipative nonlinear equations

Since one can rarely write down the analytical solutions to nonlinear dissipative partial differential equations (PDE's), it is important to understand whether, and in what sense, the behavior of approximating schemes to these equations reflects the true dynamics of the original equations. Further, because standard error estimates between approximations of the true solutions coming from spectral methods - finite difference or finite element schemes, for example - and the exact solutions grow exponentially in time, this analysis provides little value in understanding the infinite time behavior of a given approximating scheme. The notion of the global attractor has been useful in quantifying the infinite time behavior of dissipative PDEs, such as the Navier-Stokes equations. Loosely speaking, the global attractor is all that remains of a sufficiently large bounded set in phase space mapped infinitely forward in time under the evolution of the PDE. Though the attractor has been shown to have some nice properties - it is compact, connected, and finite dimensional, for example - it is in general quite complicated. Nevertheless, the global attractor gives a way to understand how the infinite time behavior of approximating schemes such as the ones coming from a finite difference, finite element, or spectral method relates to that of the original PDE. Indeed, one can often show that such approximations also have a global attractor. We therefore only need to understand how the structure of the attractor for the PDE behaves under approximation. This is by no means a trivial task. Several interesting results have been obtained in this direction. However, we will not go into the details. We mention here that approximations generally lose information about the system no matter how accurate they are. There are examples that show certain parts of the attractor may be lost by arbitrary small perturbations of the original equations.

Jones, Donald A.↗

Use of Generalized Fluid System Simulation Program (GFSSP) for Teaching and Performing Senior Design Projects at the Educational Institutions

This paper describes the experience of the authors in using the Generalized Fluid System Simulation Program (GFSSP) in teaching Design of Thermal Systems class at University of Alabama in Huntsville. GFSSP is a finite volume based thermo-fluid system network analysis code, developed at NASA/Marshall Space Flight Center, and is extensively used in NASA, Department of Defense, and aerospace industries for propulsion system design, analysis, and performance evaluation. The educational version of GFSSP is freely available to all US higher education institutions. The main purpose of the paper is to illustrate the utilization of this user-friendly code for the thermal systems design and fluid engineering courses and to encourage the instructors to utilize the code for the class assignments as well as senior design projects. The need for a generalized computer program for thermofluid analysis in a flow network has been felt for a long time in aerospace industries. Designers of thermofluid systems often need to know pressures, temperatures, flow rates, concentrations, and heat transfer rates at different parts of a flow circuit for steady state or transient conditions. Such applications occur in propulsion systems for tank pressurization, internal flow analysis of rocket engine turbopumps, chilldown of cryogenic tanks and transfer lines, and many other applications of gas-liquid systems involving fluid transients and conjugate heat and mass transfer. Computer resource requirements to perform time-dependent, three-dimensional Navier-Stokes computational fluid dynamic (CFD) analysis of such systems are prohibitive and therefore are not practical. Available commercial codes are generally suitable for steady state, single-phase incompressible flow. Because of the proprietary nature of such codes, it is not possible to extend their capability to satisfy the above-mentioned needs. Therefore, the Generalized Fluid System Simulation Program (GFSSP1) has been developed at NASA Marshall Space Flight Center (MSFC) as a general fluid flow system solver capable of handling phase changes, compressibility, mixture thermodynamics and transient operations. It also includes the capability to model external body forces such as gravity and centrifugal effects in a complex flow network. The objectives of GFSSP development are: a) to develop a robust and efficient numerical algorithm to solve a system of equations describing a flow network containing phase changes, mixing, and rotation; and b) to implement the algorithm in a structured, easy-to-use computer program. The analysis of thermofluid dynamics in a complex network requires resolution of the system into fluid nodes and branches, and solid nodes and conductors as shown in Figure 1. Figure 1 shows a schematic and GFSSP flow circuit of a counter-flow heat exchanger. Hot nitrogen gas is flowing through a pipe, colder nitrogen is flowing counter to the hot stream in the annulus pipe and heat transfer occurs through metal tubes. The problem considered is to calculate flowrates and temperature distributions in both streams. GFSSP has a unique data structure, as shown in Figure 2, that allows constructing all possible arrangements of a flow network with no limit on the number of elements. The elements of a flow network are boundary nodes where pressure and temperature are specified, internal nodes where pressure and temperature are calculated, and branches where flowrates are calculated. For conjugate heat transfer problems, there are three additional elements: solid node, ambient node, and conductor. The solid and fluid nodes are connected with solid-fluid conductors. GFSSP solves the conservation equations of mass and energy, and equation of state in internal nodes to calculate pressure, temperature and resident mass. The momentum conservation equation is solved in branches to calculate flowrate. It also solves for energy conservation equations to calculate temperatures of solid nodes. The equations are coupled and nonlinear; therefore, they are solved by an iterative numerical scheme. GFSSP employs a unique numerical scheme known as simultaneous adjustment with successive substitution (SASS), which is a combination of Newton-Raphson and successive substitution methods. The mass and momentum conservation equations and the equation of state are solved by the Newton-Raphson method while the conservation of energy and species are solved by the successive substitution method. GFSSP is linked with two thermodynamic property programs, GASP2 and WASP3 and GASPAK4, that provide thermodynamic and thermophysical properties of selected fluids. Both programs cover a range of pressure and temperature that allows fluid properties to be evaluated for liquid, liquid-vapor (saturation), and vapor region. GASP and WASP provide properties of 12 fluids. GASPAK includes a library of 36 fluids. GFSSP has three major parts. The first part is the graphical user interface (GUI), visual thermofluid analyzer of systems and components (VTASC). VTASC allows users to create a flow circuit by a 'point and click' paradigm. It creates the GFSSP input file after the completion of the model building process. GFSSP's GUI provides the users a platform to build and run their models. It also allows post-processing of results. The network flow circuit is first built using three basic elements: boundary node, internal node, and branch.

Majumdar, A. K.↗

Using Machine Learning to Infer Material Properties of Debris Fragments from X-ray Images in the DebriSat Project

The DebriSat project is a collaboration effort with the NASA Orbital Debris Program Office, the U.S. Space Force Space Systems Command Center, The Aerospace Corporation, and the University of Florida. To date, over 200,000 fragments from this ground-based, hypervelocity impact experiment have been collected, and processing is underway to determine their physical characteristics, such as material, shape, color, characteristic length, and average cross-sectional area. The x-ray process is primarily used to identify the location of the fragments and estimated size for extraction, so that these physical characteristics can be assessed. This paper proposes a machine learning-based approach to characterize materials from x-ray images of debris fragments embedded in soft-catch foam used in the DebriSat project. The novel methodology discussed in this paper will highlight the use of x-ray imagery data to characterize these fragments without extraction or a human-in-the-loop. Both supervised and unsupervised machine learning techniques are utilized with this approach to infer the physical parameters of the fragments embedded in the soft-catch foam panels used in the impact experiment based on x-ray images of the foam panels. Additionally, 3D reconstructions of the extracted fragments are created with images taken from two different angles using the structure from motion (SfM) method. The characteristic lengths and shape from the 3D reconstruction, alongside the physical characteristics of the debris, are used in the inference of the material type. To develop and test the approach, a dataset of x-ray images of debris fragments of varying sizes and materials is collected. Supervised learning methods such as convolutional neural networks (CNNs), support vector machines (SVM), decision trees, and random forest classifiers are used due to the high-dimensional feature spaces of the debris and nonlinear decision boundaries for material categorization. Given the limited pre-labeled data of embedded debris materials smaller than 10 mm, unsupervised machine learning techniques such as clustering algorithms and autoencoders are used, in addition to supervised learning methods. The clustering algorithms group similar fragments together based on their physical properties, and autoencoders reduce the dimensionality of the x ray images and extract relevant features. The performance of the proposed approach's is analyzed using a range of statistical methods, including confusion matrices, receiver operating characteristic curves, and precision-recall curves. The results are compared with those obtained using a baseline approach that relies on manual identification and classification of debris fragments. To evaluate the effectiveness of different machine learning methods, statistical tests such as t-tests, ANOVA, and cross-validation are performed, comparing the performance of CNNs, SVMs, clustering algorithms, and autoencoders. Additional analysis needs to be conducted to identify any sources of bias or variability that may affect the results, such as variations in imaging conditions or fragmentation patterns. Other topics explored are limitations, refinements, and the potential use of semi-supervised learning techniques, such as self-training to label unlabeled datasets and co-training using x-ray images taken from two different angles as two different models.

Saik Anam Siam↗

Using Machine Learning to Infer Material Properties of Debris Fragments from X-ray Images in the DebriSat Project

The DebriSat project is a collaboration effort with the NASA Orbital Debris Program Office, the U.S. Space Force Space Systems Command Center, The Aerospace Corporation, and the University of Florida. To date, over 200,000 fragments from this ground-based, hypervelocity impact experiment have been collected, and processing is underway to determine their physical characteristics, such as material, shape, color, characteristic length, and average cross-sectional area. The x-ray process is primarily used to identify the location of the fragments and estimated size for extraction, so that these physical characteristics can be assessed. This paper proposes a machine learning-based approach to characterize materials from x-ray images of debris fragments embedded in soft-catch foam used in the DebriSat project. The novel methodology discussed in this paper will highlight the use of x-ray imagery data to characterize these fragments without extraction or a human-in-the-loop. Both supervised and unsupervised machine learning techniques are utilized with this approach to infer the physical parameters of the fragments embedded in the soft-catch foam panels used in the impact experiment based on x-ray images of the foam panels. Additionally, 3D reconstructions of the extracted fragments are created with images taken from two different angles using the structure from motion (SfM) method. The characteristic lengths and shape from the 3D reconstruction, alongside the physical characteristics of the debris, are used in the inference of the material type. To develop and test the approach, a dataset of x-ray images of debris fragments of varying sizes and materials is collected. Supervised learning methods such as convolutional neural networks (CNNs), support vector machines (SVM), decision trees, and random forest classifiers are used due to the high-dimensional feature spaces of the debris and nonlinear decision boundaries for material categorization. Given the limited pre-labeled data of embedded debris materials smaller than 10 mm, unsupervised machine learning techniques such as clustering algorithms and autoencoders are used, in addition to supervised learning methods. The clustering algorithms group similar fragments together based on their physical properties, and autoencoders reduce the dimensionality of the x ray images and extract relevant features. The performance of the proposed approach's is analyzed using a range of statistical methods, including confusion matrices, receiver operating characteristic curves, and precision-recall curves. The results are compared with those obtained using a baseline approach that relies on manual identification and classification of debris fragments. To evaluate the effectiveness of different machine learning methods, statistical tests such as t-tests, ANOVA, and cross-validation are performed, comparing the performance of CNNs, SVMs, clustering algorithms, and autoencoders. Additional analysis needs to be conducted to identify any sources of bias or variability that may affect the results, such as variations in imaging conditions or fragmentation patterns. Other topics explored are limitations, refinements, and the potential use of semi-supervised learning techniques, such as self-training to label unlabeled datasets and co-training using x-ray images taken from two different angles as two different models.

Saik Anam Siam↗

Mathematical Model of a Regenerative Fuel Cell for System Optimization

This thesis developed a system-level optimization model of a regenerative fuel cell (RFC) system for long-duration, off-world energy storage applications. Prior RFC design studies have typically been limited to reduced parameter sets and simplified constraints due to computational limitations relative to the number of relevant degrees of freedom. As a result, important nonlinear interactions between subsystems have not been fully captured. This work began to address that gap by developing a higher-fidelity, nonlinear optimization framework that incorporates a broader set of design variables and coupled constraints, enabling a multidimensional model that captures the coupled behavior of RFC subsystems and demonstrates the feasibility of applying optimization to such systems. An expanded system-level optimization approach was established that captures interactions between electrochemical performance, structural requirements, and storage design. This enabled a more comprehensive evaluation of trade-offs than conventional formulations. The model integrates four coupled subsystems: a fuel cell, an electrolyzer, reactant gas, and high-pressure storage tanks, and was formulated to accommodate a wide range of mission parameters, including operational time and required output power. It incorporates constraints on available solar array power, reactant mass balance between production and consumption, and pressure-dependent storage requirements. To enable reliable convergence, the optimization problem was reformulated to reduce dimensionality and improve numerical stability, with subsystem models organized for efficient evaluation. Problem dimensionality was reduced by consolidating lower-level design variables into higher-level representative quantities, and subsystem behavior was evaluated within the optimization loop. A multi-start initialization strategy was employed to mitigate sensitivity to local minima and improve solution quality, while nonlinear relationships were solved using robust numerical methods. The results showed that convergence was achieved across a range of required output power values. Specific energy reached a maximum at a critical mission power level, where the electrolyzer power matched the available solar input and operated near its voltage and current density limits. Beyond this point, further increases in required power resulted in less mass-efficient operation, increasing total system mass and reducing overall performance. The developed model represents an advancement in RFC system-level optimization by enabling analysis of a broader and more tightly coupled design space than previous considerations. While convergence behavior and computational cost remain challenges, the methods introduced improve solvability and allow inclusion of additional design variables with minimal loss of physical fidelity. However, the numerical results should not be interpreted as definitive design recommendations, as the model includes simplifying assumptions and omits several higher-order effects. Future work should extend this framework by incorporating additional subsystems and loss mechanisms, such as thermal management, parasitic power consumption, and reactant losses, to improve fidelity and ensure more representative design conclusions.

Electrochemistry↗

Influence of Stationary Crossflow Modulation on Secondary Instability

A likely scenario for swept wing transition on subsonic aircraft with natural laminar flow involves the breakdown of stationary crossflow vortices via high frequency secondary instability. A majority of the prior research on this secondary instability has focused on crossflow vortices with a single dominant spanwise wavelength. This paper investigates the effects of the spanwise modulation of stationary crossflow vortices at a specified wavelength by a subharmonic stationary mode. Secondary instability of the modulated crossflow pattern is studied using planar, partial-differential-equation based eigenvalue analysis. Computations reveal that weak modulation by the first subharmonic of the input stationary mode leads to mode splitting that is particularly obvious for Y-type secondary modes that are driven by the wall-normal shear of the basic state. Thus, for each Y mode corresponding to the fundamental wavelength of results in unmodulated train of crossflow vortices, the modulated flow supports a pair of secondary modes with somewhat different amplification rates. The mode splitting phenomenon suggests that a more complex stationary modulation such as that induced by natural surface roughness would yield a considerably richer spectrum of secondary instability modes. Even modest levels of subharmonic modulation are shown to have a strong effect on the overall amplification of secondary disturbances, particularly the Z-modes driven by the spanwise shear of the basic state. Preliminary computations related to the nonlinear breakdown of these secondary disturbances provide interesting insights into the process of crossflow transition in the presence of the first subharmonic of the dominant stationary vortex.

Vortex structure↗

Laminar-Turbulent Transition Upstream of the Entropy-Layer Swallowing Location in Hypersonic Boundary Layers

Numerical and experimental studies have demonstrated that modal growth of planar Mack modes is responsible for laminar-turbulent transition on sharp cones at hypersonic speeds. However, the physical mechanisms that lead to transition onset upstream of the entropy-layer swallowing location over sufficiently blunt geometries are not well understood as yet. Modal amplification is too weak or nonexistent to initiate transition at moderate-to-large bluntness values. Nonmodal analysis shows that, with increasing nose bluntness, both planar and oblique traveling disturbances that peak within the entropy layer experience appreciable energy amplification. However, because of the relatively weak signature of the nonmodal traveling disturbances within the boundary-layer region, the route to transition onset subsequent to the nonmodal growth remains unclear. Thus, nonlinear parabolized stability equations (NPSE) and direct numerical simulations (DNS) have been used to investigate the potential transition mechanisms over a 7-degree blunt cone that was tested in the AFRL Mach-6 high-Reynoldsnumber facility. Computations are performed to separately follow the nonlinear development of two classes of inflow disturbances, namely, a pair of oblique traveling waves with equal but opposite angles with respect to the mean flow direction and a planar traveling wave. Results in both cases show an excellent agreement between the NPSE and DNS predictions, establishing that the NPSE is an accurate and efficient technique for predicting the nonlinear development for these particular nonmodal traveling disturbances. Computations reveal that the oblique mode interactions lead to the generation of stationary streaks inside the boundary layer that, in turn, facilitate the growth of a subharmonic sinuous disturbance. For relatively modest amplitudes of the inflow disturbance, the oblique-mode breakdown can lead to transition at the measured location of transition onset during the experiment. On the other hand, the nonlinear development of a planar traveling wave leads to the formation of inclined structures just above the boundary-layer edge and these structures are strongly reminiscent of the transitional events observed during blunt cone experiments by using schlieren flow visualizations.

Entropy↗

Incorporating Endmember Variability into Spectral Mixture Analysis Through Endmember Bundles

Variation in canopy structure and biochemistry induces a concomitant variation in the top-of-canopy spectral reflectance of a vegetation type. Hence, the use of a single endmember spectrum to track the fractional abundance of a given vegetation cover in a hyperspectral image may result in fractions with considerable error. One solution to the problem of endmember variability is to increase the number of endmembers used in a spectral mixture analysis of the image. For example, there could be several tree endmembers in the analysis because of differences in leaf area index (LAI) and multiple scatterings between leaves and stems. However, it is often difficult in terms of computer or human interaction time to select more than six or seven endmembers and any non-removable noise, as well as the number of uncorrelated bands in the image, limits the number of endmembers that can be discriminated. Moreover, as endmembers proliferate, their interpretation becomes increasingly difficult and often applications simply need the aerial fractions of a few land cover components which comprise most of the scene. In order to incorporate endmember variability into spectral mixture analysis, we propose representing a landscape component type not with one endmember spectrum but with a set or bundle of spectra, each of which is feasible as the spectrum of an instance of the component (e.g., in the case of a tree component, each spectrum could reasonably be the spectral reflectance of a tree canopy). These endmember bundles can be used with nonlinear optimization algorithms to find upper and lower bounds on endmember fractions. This approach to endmember variability naturally evolved from previous work in deriving endmembers from the data itself by fitting a triangle, tetrahedron or, more generally, a simplex to the data cloud reduced in dimension by a principal component analysis. Conceptually, endmember variability could make it difficult to find a simplex that both surrounds the data cloud and has vertices that are realistic endmember spectra with reflectances between 0 and 1. In this paper, we create endmember bundles and bounding fraction images for an AVIRIS subscene simulated with a plant canopy radiative transfer model. The simulated subscene is spatially patterned after a subscene from the AVIRIS image acquired August, 1993 over La Copita, Texas. In addition, for comparison, we performed a traditional unmixing with image endmembers.

Bateson, C. Ann↗

Airloads and Wake Geometry Calculations for an Isolated Tiltrotor Model in a Wind Tunnel

Th tiltrotor aircraft configuration has the potential to revolutionize air transportation by providing an economical combination of vertical take-off and landing capability with efficient, high-speed cruise flight. To achieve this potential it is necessary to have validated analytical tools that will support future tiltrotor aircraft development. These analytical tools must calculate tiltrotor aeromechanical behavior, including performance, structural loads, vibration, and aeroelastic stability, with an accuracy established by correlation with measured tiltrotor data. For many years such correlation has been performed for helicopter rotors (rotors designed for edgewise flight), but correlation activities for tiltrotors have been limited, in part by the absence of appropriate measured data. The recent test of the Tilt Rotor Aeroacoustic Model (TRAM) with a single, U4-scale V-22 rotor in the German-Dutch Wind Tunnel (DNW) now provides an extensive set of aeroacoustic, performance, and structural loads data. This paper will present calculations of airloads, wake geometry, and performance, including correlation with TRAM DNW measurements. The calculations were obtained using CAMRAD II, which is a modern rotorcraft comprehensive analysis, with advanced models intended for application to tiltrotor aircraft as well as helicopters. Comprehensive analyses have received extensive correlation with performance and loads measurements on helicopter rotors. The proposed paper is part of an initial effort to perform an equally extensive correlation with tiltrotor data. The correlation will establish the level of predictive capability achievable with current technology; identify the limitations of the current aerodynamic, wake, and structural models of tiltrotors; and lead to recommendations for research to extend tiltrotor aeromechanics analysis capability. The purpose of the Tilt Rotor Aeroacoustic Model (TRAM) experimental project is to provide data necessary to validate tiltrotor performance and aeroacoustic prediction methodologies and to investigate and demonstrate advanced civil tiltrotor technologies. The TRAM project is a key part of the NASA Short Haul Civil Tiltrotor (SHCT) project. The SHCT project is an element of the Aviation Systems Capacity Initiative within NASA. In April-May 1998 the TRAM was tested in the isolated rotor configuration at the Large Low-speed Facility of the German-Dutch Wind Tunnels (DNW). A preparatory test was conducted in December 1997. These tests were the first comprehensive aeroacoustic test for a tiltrotor, including not only noise and performance data, but airload and wake measurements as well. The TRAM can also be tested in a fill-span configuration, incorporating both rotors Lnd a fuselage model. The wind tunnel installation of the TRAM isolated rotor is shown. The rotor tested in the DNW was a 1/4-scale (9.5 ft diameter) model of the right-hand V-22 proprotor. The rotor and nacelle assembly was attached to an acoustically-treated, isolated rotor test stand through a mechanical pivot (the nacelle conversion axis). The TRAM was analyzed using the rotorcraft comprehensive analysis CAMRAD II. CAMRAD II is an aeromechanical analysis of helicopters and rotorcraft that incorporates a combination of advanced technologies, including multibody dynamics, nonlinear finite elements, and rotorcraft aerodynamics. The trim task finds the equilibrium solution (constant or periodic) for a steady state operating condition, in this case a rotor operating in a wind tunnel. For wind tunnel operation, the thrust and flapping are trimmed to target values. The aerodynamic model includes a wake analysis to calculate the rotor nonuniform induced-velocities, using a free wake geometry. The paper will present the results of CAMRAD II calculations compared to the TRAM DNW measurements for hover performance, helicopter mode performance, and helicopter mode airloads. An example of the hover performance results, comparing both mearements and calculations for the JVX (large scale) and TRAM (small scale) rotors, is shown. An example of the helicopter mode performance, showing the influence of the aerodynamic model (particularly the stall delay model) on the calculated power, induced power, and profile power is also shown. An example of the helicopter mode airloads, showing the influence of various wake and aerodynamic models on the calculations, is shown. Good correlation with measured airloads is obtained using the multiple-trailer wake model. The paper will present additional results, and describe and discuss the aerodynamic behavior in detail.

Johnson, Wayne↗