Results for “Optimized Structural Design” — Page 60

NASA NTRSDate not supplied

Use of Design of Experiments in Determining Neural Network Architectures for Loss of Control Detection

We describe empirical methods for selecting a neural network architecture to implement belief state inference on generic commercial transport aircraft. We highlight a case study on the planning, execution, and analysis of a set of experiments to determine the configurations of a conditional variational autoencoder (CVAE). Our main contribution is the application of a structured method that can be used for machine learning in many aerospace applications. This method optimizes the structure and training parameters of a neural network for belief state inference, using Design of Experiments (DOE) statistical methodologies. The motivation for this specific DOE analysis was to identify the appropriate hyperparameters for measuring the CVAE reconstruction probability and latent space, such that the measurements can be used to infer qualitative state changes for the aircraft. We demonstrate that this process yields information about a trained neural network’s utility for this specific application, along with a quantifiable range of certainty. We execute 84 experiments using loss-of-control flight maneuver data from the NASA T-2 aircraft, demonstrating that this empirical process allows us to construct cheap and simple models with specific attributes amenable to belief state inference in aerospace applications.

Loss of Control↗

NASA NTRSDate not supplied

Use of Design of Experiments in Determining Neural Network Architectures for Loss of Control Detection

We describe empirical methods for selecting a neural network architecture to implement belief state inference on generic commercial transport aircraft. We highlight a case study on the planning, execution, and analysis of a set of experiments to determine the configurations of a conditional variational autoencoder (CVAE). Our main contribution is the application of a structured method that can be used for machine learning in many aerospace applications. This method optimizes the structure and training parameters of a neural network for belief state inference, using Design of Experiments (DOE) statistical methodologies. The motivation for this specific DOE analysis was to identify the appropriate hyperparameters for measuring the CVAE reconstruction probability and latent space, such that the measurements can be used to infer qualitative state changes for the aircraft. We demonstrate that this process yields information about a trained neural network’s utility for this specific application, along with a quantifiable range of certainty. We execute 84 experiments using loss-of-control flight maneuver data from the NASA T 2 aircraft, demonstrating that this empirical process allows us to construct cheap and simple models with specific attributes amenable to belief state inference in aerospace applications.

Loss of Control↗

NASA NTRSDate not supplied

Use of Design of Experiments in Determining Neural Network Architectures for Loss of Control Detection

Abstract—We describe empirical methods for selecting a neural network architecture to implement belief state inference on generic commercial transport aircraft. We highlight a case study on the planning, execution, and analysis of a set of experiments to determine the configurations of a conditional variational autoencoder (CVAE). Our main contribution is the application of a structured method that can be used for machine learning in many aerospace applications. This method optimizes the structure and training parameters of a neural network for belief state inference, using Design of Experiments (DOE) statistical methodologies. The motivation for this specific DOE analysis was to identify the appropriate hyperparameters for measuring the CVAE reconstruction probability and latent space, such that the measurements can be used to infer qualitative state changes for the aircraft. We demonstrate that this process yields information about a trained neural network’s utility for this specific application, along with a quantifiable range of certainty. We execute 84 experiments using loss-of-control flight maneuver data from the NASA T-2 aircraft, demonstrating that this empirical process allows us to construct cheap and simple models with specific attributes amenable to belief state inference in aerospace applications.

neural networks↗

NASA NTRSDate not supplied

Computationally Guided Development of Components for High Energy Density Solid-State Lithium-Sulfur Batteries

All electric vertical take-off and landing vehicles (eVTOL) for urban air mobility (UAM) concepts face numerous challenging technical barriers before their introduction into the consumer marketplace. The most challenging of these technical barriers to overcome is developing an energy storage system capable of meeting the rigorous aerospace safety and performance criteria1. The performance metrics for eVTOL craft, such as specific energy, specific power, and safety, exceed those of electric automobiles by a factor of two to four. Current state-of-the-art (SOA) lithium-ion batteries are incapable of meeting the key performance criteria of energy and safety for eVTOL. Therefore, next generation advanced chemistries and designs must be developed to meet required performance metrics for electric aviation2. Beyond lithium-ion chemistries, such as lithium-sulfur, show promise in their high energy, while limitations exist in their power and cyclability due to low electrical conductivity and high intermediate solubility in organic liquid electrolytes. Several strategies to overcome the low electrical conductivity involve the use of selenium as a dopant in the active sulfur material, along with the incorporation of 2-dimensional electron-conducting holey-graphene to improve the composite cathodes electronic conductivity. Furthermore, combining this chemistry with a solid-electrolyte avoids the components’ dissolution issues3. However, the development of composite solid-state cathodes is non-trivial as several components must be intimately mixed so that the active component has sufficient access to both electrons and lithium ions to undergo full electrochemical conversion. Mathematical modeling of battery components can assist experimental design through a robust and rigorous combination of computational modeling techniques covering multiple length scales. The objective is to leverage modern computational materials methods combined with battery multiphysics tools to develop radically advanced compatible cathode and electrolyte materials, build and test solid state lithium-sulfur cells and packs. A NASA-based cross-organizational team of high-powered experts combined integrated computational predictive modeling, fundamental chemistry analysis, advanced material science, and battery cell development to tackle this very challenging, multidisciplinary problem. This presentation will show a multiscale computational modeling approach that has produced a novel particle dynamics method called Solid Electrolyte Sphere Approximation Model (SESAM). SESAM modeling targets the 1-10 µm scale structures and provides electromechanical and grain interactions for predictive design guidelines for the manufacturing of solid-state components. Parameters such as particle size and volume fraction of the constituent materials were modeled and experimentally fabricated to optimize electrochemical performance through improved microstructure design. Experimental feedback was provided through ionic and electronic conductivity assessment and structural analysis of developed materials and cell components.

battery↗

NASA NTRS1986

Automated Design Synthesis

Automated Design Synthesis (ADS) program is general-purpose numerical optimization program containing wide variety of algorithms. Assumed user prepares analysis problem capable of computing objective function and constraints. Program able to accept as part of input design variable quantities. Optimization process carried out by ADS coupled with user's program. ADS used for constrained and unconstrained function minimization. Solution of general problem separated into three basic levels: Strategy, Optimizer, and One-Dimensional Search. Already significant applications in area of structural synthesis (minimum-weight design).

Vanderplaats, G. N.↗

NASA NTRS1992

New approach to the design of Schottky barrier diodes for THz mixers

Near-ideal GaAs Schottky barrier diodes especially designed for mixing applications in the THz frequency range are presented. A diode fabrication process for submicron diodes with near-ideal electrical and noise characteristics is described. This process is based on the electrolytic pulse etching of GaAs in combination with an in-situ platinum plating for the formation of the Schottky contacts. Schottky barrier diodes with a diameter of 1 micron fabricated by the process have already shown excellent results in a 650 GHz waveguide mixer at room temperature. A conversion loss of 7.5 dB and a mixer noise temperature of less than 2000 K have been obtained at an intermediate frequency of 4 GHz. The optimization of the diode structure and the technology was possible due to the development of a generalized Schottky barrier diode model which is valid also at high current densities. The common diode design and optimization is discussed on the basis of the classical theory. However, the conventional fomulas are valid only in a limited forward bias range corresponding to currents much smaller than the operating currents under submillimeter mixing conditions. The generalized new model takes into account not only the phenomena occurring at the junction such as current dependent recombination and drift/diffusion velocities, but also mobility and electron temperature variations in the undepleted epi-layer. Calculated diode I/V and noise characteristics are in excellent agreement with the measured values. Thus, the model offers the possibility of optimizing the diode structure and predicting the diode performance under mixing conditions at THz frequencies.

Jelenski, A.↗

NASA NTRS1992

Project Wish: The Emerald City, phase 3

Phase 3 of Project Wish saw the evolution of the Emerald City (E-City) from a collection of specialized independent analyses and ideas to a working structural design integrated with major support systems and analyses. Emphasis was placed on comparing and contrasting the closed and open cycle gas core nuclear rocket engines to further determine the optimum propulsive system for the C-City. Power and thermal control requirements were then defined and the question of how to meet these requirements was addressed. Software was developed to automate the mission/system/configuration analysis so changes dictated by various subsystems constraints could be managed efficiently and analyzed interactively. In addition, the liquid hydrogen propellant tank was statically designed for minimum mass and shape optimization using a finite element modeling package called SDRC I-DEAS while spoke and shaft cross-sectional areas were optimized on ASTROS (Automated Structural Optimization System). A structural dynamic analysis also conducted using ASTROS enabled a study of the displacements, accelerations, modes and frequencies of the C-City. Finally, the attitude control system design began with an initial mass moment of inertia analysis and was then designed and optimized using linear quadratic regulator control theory.

Source record↗

DOE OSTI2022

Design of Graded Cathode Catalyst Layers with Various Ionomers for Fuel Cell Application

Proton exchange membrane fuel cells (PEMFCs) powered by green hydrogen (H2) have become a promising alternative to conventional hydrocarbon-fueled power generators. Despite technological advancements, further improvements in efficiency, durability, and low-cost production are required for the widespread adoption of PEMFCs. Though numerous approaches to improve PEMFC electrodes have been reported, most strategies utilize a single material set (e.g., one combination of catalyst and ionomer) to improve performance. Alternatively, anisotropic (graded) electrode structures with locally tunable properties may yield superior electrode performance due to improved ionic and gas phase transport. In this work, graded cathode catalyst layers (CCLs) incorporating different ionomers (Nafion D2020, Aquivion D79-25BS, and HOPI) were designed and prepared. Performance screening shows that some of these graded electrode structures have comparable performance to optimized single-ionomer electrode structures (D2020) suggesting some synergistic benefit. Additionally, we show that electrodes with lower equivalent weight (EW) D79 ionomer near the membrane and D2020 ionomer near the gas diffusion media outperformed electrodes with the inverted configuration. Finally, EIS analysis shows some graded ionomer structures (e.g. D79/D2020) have better than expected H+ conductivity, generally leading to better electrode performance. However, further optimization of ionomer content and catalyst ink formulations is needed to improve overall PEMFC performance.

DIRECT ENERGY CONVERSION↗

NASA NTRS1995

A novel unitized regenerative proton exchange membrane fuel cell

A difficulty encountered in designing a unitized regenerative proton exchange membrane (PEM) fuel cell lies in the incompatibility of electrode structures and electrocatalyst materials optimized for either of the two functions (fuel cell or electrolyzer) with the needs of the other function. This difficulty is compounded in previous regenerative fuel cell designs by the fact that water, which is needed for proton conduction in the PEM during both modes of operation, is the reactant supplied to the anode in the electrolyzer mode of operation and the product formed at the cathode in the fuel cell mode. Drawbacks associated with existing regenerative fuel cells have been addressed in work performed at Lynntech. In a first innovation, electrodes function either as oxidation electrodes (hydrogen ionization or oxygen evolution) or as reduction electrodes (oxygen reduction or hydrogen evolution) in the fuel cell and electrolyzer modes, respectively. Control of liquid water within the regenerative fuel cell has been brought about by a second innovation. A novel PEM has been developed with internal channels that permit the direct access of water along the length of the membrane. Lateral diffusion of water along the polymer chains of the PEM provides the water needed at electrode/PEM interfaces. Fabrication of the novel unitized regenerative fuel cell and results obtained on testing it will be presented.

Murphy, O. J.↗

NASA NTRS1996

A Novel Unitized Regenerative Proton Exchange Membrane Fuel Cell

A difficulty encountered in designing a unitized regenerative proton exchange membrane (PEM) fuel cell lies in the incompatibility of electrode structures and electrocatalyst materials optimized for either of the two functions (fuel cell or electrolyzer) with the needs of the other function. This difficulty is compounded in previous regenerative fuel cell designs by the fact that water, which is needed for proton conduction in the PEM during both modes of operation, is the reactant supplied to the anode in the electrolyzer mode of operation and the product formed at the cathode in the fuel cell mode. Drawbacks associated with existing regenerative fuel cells have been addressed. In a first innovation, electrodes function either as oxidation electrodes (hydrogen ionization or oxygen evolution) or as reduction electrodes (oxygen reduction or hydrogen evolution) in the fuel cell and electrolyzer modes, respectively. Control of liquid water within the regenerative fuel cell has been brought about by a second innovation. A novel PEM has been developed with internal channels that permit the direct access of water along the length of the membrane. Lateral diffusion of water along the polymer chains of the PEM provides the water needed at electrode/PEM interfaces. Fabrication of the novel single cell unitized regenerative fuel cell and results obtained on testing it are presented.

Murphy, O. J.↗

DOE OSTI2026

Structural effects of composition tuning in A-site disordered perovskite La0.5Li0.5−xMxTiO3 (M = Na, K) nanorods for fast interfacial transport for solid composite electrolyte design

Polymer-ceramic composite electrolytes (CPE) have emerged as promising replacements for currently used liquid organic electrolytes, which pose as safety hazards, in Li-ion batteries. Limits in conductivity enhancement in CPEs is often attributed to a high resistance for Li-ion transport along the interface due to the incompatibility of the polymer and ceramic phases. A clear understanding of the interfacial structure and how this impacts interfacial Li-ion transport is needed in order to efficiently design a CPE with optimal ionic conductivity. In this study, density functional theory (DFT) calculations, in conjunction with scanning transmission electron microscopy (STEM) and electron energy loss spectroscopy (EELS), are used to unveil the bulk and surface structure of La0.5Li0.5−xMxTiO3 (M = Na, K) (LMTO) nanorods, a newly-reported ceramic system with promising applications in CPEs, and the LMTO interactions with the poly(lithium sulfonyl (trifluoromethane sulfonyl)imide methacrylate) (p(MTFSILi)) polymerized ionic liquid. Substitution of lithium for sodium and potassium onto the A-site perovskite lattice is shown to increase the stability of the preferred pseudocubic perovskite phase because of their increased cation size which allows them to reduce the TiO6 octahedral rotations in the bulk and at the surface. STEM and EELS results show that LMTO nanorods with differing compositions have Ti-enriched (110)-oriented surfaces. Increased sodium and potassium compositions in LMTO is also shown using the DFT calculations to weaken the binding of the lithium atom to the MTFSI unit when LiMTFSI is adsorbed to the LMTO surface. This weakening of lithium binding to the polymer at the LMTO interface indicates that the lithium mobility is increased, correlating to an increase in interfacial Li-ion transport. Overall, this work provides insights into how to tune the interfacial interactions between the polymer (p(MTFSI)) and ceramic (LMTO) for optimal CPE design.

Shepard, Lauren B [Pennsylvania State University, ↗

NASA NTRS1989

Run-time scheduling and execution of loops on message passing machines

Sparse system solvers and general purpose codes for solving partial differential equations are examples of the many types of problems whose irregularity can result in poor performance on distributed memory machines. Often, the data structures used in these problems are very flexible. Crucial details concerning loop dependences are encoded in these structures rather than being explicitly represented in the program. Good methods for parallelizing and partitioning these types of problems require assignment of computations in rather arbitrary ways. Naive implementations of programs on distributed memory machines requiring general loop partitions can be extremely inefficient. Instead, the scheduling mechanism needs to capture the data reference patterns of the loops in order to partition the problem. First, the indices assigned to each processor must be locally numbered. Next, it is necessary to precompute what information is needed by each processor at various points in the computation. The precomputed information is then used to generate an execution template designed to carry out the computation, communication, and partitioning of data, in an optimized manner. The design is presented for a general preprocessor and schedule executer, the structures of which do not vary, even though the details of the computation and of the type of information are problem dependent.

Crowley, Kay↗

NASA NTRS1990

Run-time scheduling and execution of loops on message passing machines

Sparse system solvers and general purpose codes for solving partial differential equations are examples of the many types of problems whose irregularity can result in poor performance on distributed memory machines. Often, the data structures used in these problems are very flexible. Crucial details concerning loop dependences are encoded in these structures rather than being explicitly represented in the program. Good methods for parallelizing and partitioning these types of problems require assignment of computations in rather arbitrary ways. Naive implementations of programs on distributed memory machines requiring general loop partitions can be extremely inefficient. Instead, the scheduling mechanism needs to capture the data reference patterns of the loops in order to partition the problem. First, the indices assigned to each processor must be locally numbered. Next, it is necessary to precompute what information is needed by each processor at various points in the computation. The precomputed information is then used to generate an execution template designed to carry out the computation, communication, and partitioning of data, in an optimized manner. The design is presented for a general preprocessor and schedule executer, the structures of which do not vary, even though the details of the computation and of the type of information are problem dependent.

Saltz, Joel↗

DOE OSTI2022

Magneto-Structural Combined Dimensional and Topology Optimization of Interior Permanent Magnet Synchronous Machine Rotors

Not provided.

Engineering↗

NASA NTRS1979

Automated design using numerical optimization

Numerical optimization concepts are described with limited technical detail. The purpose is to provide the nonspecialist with sufficient information to judge the applicability of these methods to his particular design problem. The concepts are first described in physical terms to give a basic understanding of the iterative procedure employed by these methods. Next, the typical engineering task is presented and converted to a form ammenable to solution by numerical optimization. Basic algorithms for solving this problem are identified. Numerous applications are referenced, emphasizing the structural design discipline. The state of the art allows for the routine solution of nonlinear design problems of approximately 20 independent variables subject to 100 or more constraints. In many applications, much larger design problems may be solved. Selected references are provided which describe the methods and applications in more detail.

Vanderplaats, G. N.↗

DOE OSTI2021

Net Electronic Charge as an Effective Electronic Descriptor for Oxygen Release and Transport Properties of SrFeO 3 -based Oxygen Sorbents

Perovskite oxides, as oxygen sorbents, exhibit excellent potential in thermochemical redox applications such as chemical looping air separation (CLAS), resulting from their excellent redox properties and high tunability. The structural and compositional flexibility of perovskites, while making these mixed oxides highly versatile, also poses challenges for their design and optimization. Moreover, the elevated operating temperature and dynamic oxygen partial pressure swings during redox processes add additional complications for oxygen sorbent design. From a fundamental standpoint, finding simple yet effective descriptors for the effect of cation substitutions on oxygen sorbents’ redox and oxygen transport properties are of significant importance for rational optimization of perovskite-based oxygen sorbents. In the present study, a series of A/B-site-doped SrFeO 3-δ perovskites are investigated using density functional theory (DFT) + U simulations. From these simulations, an effective electronic structural descriptor, the net electronic charge (Δe) of oxygen anions, is extracted based on its excellent correlations with vacancy formation energy, experimentally derived oxygen capacity, and oxygen vacancy migration barrier. Overall, these findings provide an effective tool to correlate the oxygen sorbents’ redox performances with a simple yet physically meaningful descriptor for rational design and optimization of perovskites in the context of CLAS.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS2002

Performance Validation Approach for the GTX Air-Breathing Launch Vehicle

The primary objective of the GTX effort is to determine whether or not air-breathing propulsion can enable a launch vehicle to achieve orbit in a single stage. Structural weight, vehicle aerodynamics, and propulsion performance must be accurately known over the entire flight trajectory in order to make a credible assessment. Structural, aerodynamic, and propulsion parameters are strongly interdependent, which necessitates a system approach to design, evaluation, and optimization of a single-stage-to-orbit concept. The GTX reference vehicle serves this purpose, by allowing design, development, and validation of components and subsystems in a system context. The reference vehicle configuration (including propulsion) was carefully chosen so as to provide high potential for structural and volumetric efficiency, and to allow the high specific impulse of air-breathing propulsion cycles to be exploited. Minor evolution of the configuration has occurred as analytical and experimental results have become available. With this development process comes increasing validation of the weight and performance levels used in system performance determination. This paper presents an overview of the GTX reference vehicle and the approach to its performance validation. Subscale test rigs and numerical studies used to develop and validate component performance levels and unit structural weights are outlined. The sensitivity of the equivalent, effective specific impulse to key propulsion component efficiencies is presented. The role of flight demonstration in development and validation is discussed.

Trefny, Charles J.↗

NASA NTRS2002

Performance Validation Approach for the GTX Air-Breathing Launch Vehicle

The primary objective of the GTX effort is to determine whether or not air-breathing propulsion can enable a launch vehicle to achieve orbit in a single stage. Structural weight, vehicle aerodynamics, and propulsion performance must be accurately known over the entire flight trajectory in order to make a credible assessment. Structural, aerodynamic, and propulsion parameters are strongly interdependent, which necessitates a system approach to design, evaluation, and optimization of a single-stage-to-orbit concept. The GTX reference vehicle serves this purpose, by allowing design, development, and validation of components and subsystems in a system context. The reference vehicle configuration (including propulsion) was carefully chosen so as to provide high potential for structural and volumetric efficiency, and to allow the high specific impulse of air-breathing propulsion cycles to be exploited. Minor evolution of the configuration has occurred as analytical and experimental results have become available. With this development process comes increasing validation of the weight and performance levels used in system performance determination. This paper presents an overview of the GTX reference vehicle and the approach to its performance validation. Subscale test rigs and numerical studies used to develop and validate component performance levels and unit structural weights are outlined. The sensitivity of the equivalent, effective specific impulse to key propulsion component efficiencies is presented. The role of flight demonstration in development and validation is discussed.

Trefny, Charles J.↗