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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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DOE OSTI2020

Reification of latent microstructures: On supervised unsupervised and semi-supervised deep learning applications for microstructures in materials informatics

Machine learning (ML), including deep learning (DL), has become increasingly popular in the last few years due to its continually outstanding performance. In this context, we apply machine learning techniques to "learn" the microstructure using both supervised and unsupervised DL techniques. In particular, we focus (1) on the localization problem bridging (micro)structure (localized) property using supervised DL and (2) on the microstructure reconstruction problem in latent space using unsupervised DL. The goal of supervised and semi-supervised DL is to replace crystal plasticity finite element model (CPFEM) that maps from (micro)structure (localized) property, and implicitly the (micro)structure (homogenized) property relationships, while the goal of unsupervised DL is (1) to represent high-dimensional microstructure images in a non-linear low-dimensional manifold, and (2) to discover a way to interpolate microstructures via latent space associating with latent microstructure variables. At the heart of this report is the applications of several common DL architectures, including convolutional neural networks (CNN), autoencoder (AE), and generative adversarial network (GAN), to multiple microstructure datasets, and the quest of neural architecture search for optimal DL architectures.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Data Summarization and Inference at Scale

This is the final report for the DOE ASCR grant SC-0022260, Data Summarization and Inference at Scale, PI: Alex Pothen, Purdue University. The goal of the project was to solve data-intensive and compute-intensive problems in the physical sciences, engineering, information science, data science, etc. by designing and implementing new algorithms that could work with a subset of the data. The four subgoals were: (a) The solution of problems where the data is too large to be stored in the memory of a computer. In this streaming model of computation, the data arrives as a stream of elements to the computer, each element is processed as it arrives, and a decision is made to discard the data or to store it; only a small subset of the data proportional to the size of the output solution is stored, and when all the data has been streamed, a solution to the problem is computed from the stored subset. (b) The use of machine learning methods to compute solutions to data-intensive problems. The use of GPUs is critical to obtain high performance on machine learning tasks, but their memory sizes are smaller relative to that of CPUs. For large-scale problems, the data is sampled many times, and small samples are used with repetition, for robustness, to compute solutions to inference tasks. This sampling reduces the memory required to solve the problem, but attention is needed to avoid slow convergence to the solutions, and reduced accuracy of inference. We propose submodular optimization, Large Language Models, and physics-informed neural networks to enable GPU computations here. (c) Modeling and visualization of high-dimensional data using interpretable features. Clinical proteomic data sets from immunology for the detection of cancer and other diseases are temporal and high-dimensional, and algorithms for visualizing these data sets using clinically interpretable features are lacking. We propose methods that compute distances based on the optimal transportation problem and graph edit distances to address this problem. We also propose the use of optimal transport-based distances, spatial statistics, and network structure to classify image data sets, We apply these algorithms to electron micrographs of the peripheral nervous system in the digestive tract. (d) The design of data-intensive algorithms on emerging architectures, specifically, noisy, intermediate-scale quantum (NISQ) devices. Quantum computers offer the possibility of exploring large solution spaces due to the principle of superposition, but current quantum computers are limited by few qubits, short coherence times due to noise, poor interconections among the qubits, etc. We propose the use of the divide and conquer paradigm to solve large-scale problems, wherein collections of small subproblems are solved on the quantum devices, and the solutions to the subproblems are integrated into a solution for the original problem on a classical computer.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS2009

Traditional Cardiovascular Risk Factors as Predictors of Cardiovascular Events in the U.S. Astronaut Corps

Risk prediction equations from the Framingham Heart Study are commonly used to predict the absolute risk of myocardial infarction (MI) and coronary heart disease (CHD) related death. Predicting CHD-related events in the U.S. astronaut corps presents a monumental challenge, both because astronauts tend to live healthier lifestyles and because of the unique cardiovascular stressors associated with being trained for and participating in space flight. Traditional risk factors may not hold enough predictive power to provide a useful indicator of CHD risk in this unique population. It is important to be able to identify individuals who are at higher risk for CHD-related events so that appropriate preventive care can be provided. This is of special importance when planning long duration missions since the ability to provide advanced cardiac care and perform medical evacuation is limited. The medical regimen of the astronauts follows a strict set of clinical practice guidelines in an effort to ensure the best care. The purpose of this study was to evaluate the utility of the Framingham risk score (FRS), low-density lipoprotein (LDL) and high-density lipoprotein levels, blood pressure, and resting pulse as predictors of CHD-related death and MI in the astronaut corps, using Cox regression. Of these factors, only two, LDL and pulse at selection, were predictive of CHD events (HR(95% CI)=1.12 (1.00-1.25) and HR(95% CI)=1.70 (1.05-2.75) for every 5-unit increase in LDL and pulse, respectively). Since traditional CHD risk factors may lack the specificity to predict such outcomes in astronauts, the development of a new predictive model, using additional measures such as electron-beam computed tomography and carotid intima-media thickness ultrasound, is planned for the future.

Halm, M. K.↗

NASA NTRS2010

Solar Array Disturbances to Spacecraft Pointing During the Lunar Reconnaissance Orbiter (LRO) Mission

The Lunar Reconnaissance Orbiter (LRO), the first spacecraft to support NASA s return to the Moon, launched on June 18, 2009 from the Cape Canaveral Air Force Station aboard an Atlas V launch vehicle. It was initially inserted into a direct trans-lunar trajectory to the Moon. After a five day transit to the Moon, LRO was inserted into the Lunar orbit and successfully lowered to a low altitude elliptical polar orbit for spacecraft commissioning. Successful commissioning was completed in October 2009 when LRO was placed in its near circular mission orbit with an approximate altitude of 50km. LRO will spend at least one year orbiting the Moon, collecting lunar environment science and mapping data, utilizing a suite of seven instruments to enable future human exploration. The objective is to provide key science data necessary to facilitate human return to the Moon as well as identification of opportunities for future science missions. LRO's instrument suite will provide the high resolution imaging data with sub-meter accuracy, highly accurate lunar cartographic maps, mineralogy mapping, amongst other science data of interest. LRO employs a 3-axis stabilized attitude control system (ACS) whose primary control mode, the "Observing Mode", provides Lunar nadir, off-nadir, and inertial fine pointing for the science data collection and instrument calibration. This controller combines the capability of fine pointing with on-demand large angle full-sky attitude reorientation. It provides simplicity of spacecraft operation as well as additional flexibility for science data collection. A conventional suite of ACS components is employed in the Observing Mode to meet the pointing and control objectives. Actuation is provided by a set of four reaction wheels developed in-house at NASA Goddard Space Flight Center (GSFC). Attitude feedback is provided by a six state Kalman filter which utilizes two SELEX Galileo Star Trackers for attitude updates, and a single Honeywell Miniature Inertial Measurement Unit (MIMU) to provide body rates for attitude propagation. Rate is computed by differentiating accumulated angle provided by the MIMU. The Observing Mode controller is required to maintain fine pointing while a large fully-articulated solar array (SA) maintains its panel normal to the solar incidence. This paper describes the disturbances to the attitude control resulting from the SA articulation. Observing Mode performance in the presence of this disturbance was assessed while the spacecraft was in an initial elliptical low altitude orbit during the commissioning phase, which started about two weeks after launch and lasted for 90 days. LRO demonstrated excellent pointing performance during Observing Mode nadir and inertial attitude target operations during this phase. Transient LRO attitude errors observed during commissioning resulted primarily from three sources, Diviner instrument calibrations, RW zero crossings, and SA articulation. Even during times of considerable disturbance from SA articulation, the attitude errors were maintained below the statistical attitude error requirement level of 15 arc-sec (3 sigma).

Calhoun, Philip↗

NASA NTRS2010

Optical Imaging and Radiometric Modeling and Simulation

OPTOOL software is a general-purpose optical systems analysis tool that was developed to offer a solution to problems associated with computational programs written for the James Webb Space Telescope optical system. It integrates existing routines into coherent processes, and provides a structure with reusable capabilities that allow additional processes to be quickly developed and integrated. It has an extensive graphical user interface, which makes the tool more intuitive and friendly. OPTOOL is implemented using MATLAB with a Fourier optics-based approach for point spread function (PSF) calculations. It features parametric and Monte Carlo simulation capabilities, and uses a direct integration calculation to permit high spatial sampling of the PSF. Exit pupil optical path difference (OPD) maps can be generated using combinations of Zernike polynomials or shaped power spectral densities. The graphical user interface allows rapid creation of arbitrary pupil geometries, and entry of all other modeling parameters to support basic imaging and radiometric analyses. OPTOOL provides the capability to generate wavefront-error (WFE) maps for arbitrary grid sizes. These maps are 2D arrays containing digital sampled versions of functions ranging from Zernike polynomials to combination of sinusoidal wave functions in 2D, to functions generated from a spatial frequency power spectral distribution (PSD). It also can generate optical transfer functions (OTFs), which are incorporated into the PSF calculation. The user can specify radiometrics for the target and sky background, and key performance parameters for the instrument s focal plane array (FPA). This radiometric and detector model setup is fairly extensive, and includes parameters such as zodiacal background, thermal emission noise, read noise, and dark current. The setup also includes target spectral energy distribution as a function of wavelength for polychromatic sources, detector pixel size, and the FPA s charge diffusion modulation transfer function (MTF).

Ha, Kong Q.↗

NASA NTRS2012

Characterization of the Vectron PX-570 Crystal Oscillator for Use in Harsh Environments

Computing hardware, data-acquisition systems, communications systems, and many electronic control systems require well-controlled timing signals for proper and accurate operation. These signals are, in most cases, provided by circuits that employ crystal oscillators due to availability, cost, ease of operation, and accuracy. In some cases, the electronic systems are expected to survive and operate under harsh conditions that include exposure to extreme temperatures. These applications exist in terrestrial systems as well as in aerospace products. Well-logging, geothermal systems, and industrial process control are examples of ground-based applications, while distributed jet engine control in aircraft, space-based observatories (such as the James Webb Space Telescope), satellites, and lunar and planetary landers are typical environments where electronics are exposed to harsh operating conditions. To ensure these devices produce reliable results, the digital heartbeat from the oscillator must deliver a stable signal that is not affected by external temperature or other conditions. One such solution is a recently introduced commercial-off-the-shelf (COTS) oscillator, the PX-570 series from Vectron International. The oscillator was designed for high-temperature applications and as proof, the crystal oscillator was subjected to a wide suite of tests to determine its ruggedness for operation in harsh environments. The tests performed by Vectron included electrical characterization under wide range of temperature, accelerated life test/aging, shock and vibration, internal moisture analysis, ESD threshold, and latch-up testing. The parametric evaluation was performed on the oscillator's frequency, output signal rise and fall times, duty cycle, and supply current over the temperature range of -125 C to +230 C. The evaluations also determined the effects of thermal cycling and the oscillator's re-start capability at extreme hot and cold temperatures. These thermal cycling and restart tests were performed at the NASA Glenn Research Center. Overall, the crystal oscillator performed well and demonstrated very good frequency stability. This paper will discuss the test procedures and present details of the performance results.

Li, Jacob↗

NASA NTRS2008

Assessments of Hollow Cathode Wear in the Xenon Ion Propulsion System (XIPs(c)) by Numerical Analyses and Wear Tests

The standard approach presently followed by NASA to qualify electric propulsion for the required mission throughput has been based largely on life tests, which can be costly and time consuming. Revised electric propulsion lifequalification approaches are being formulated that combine analytical and/or computational methods with (shorter-duration) wear tests. As a model case, a wear test is being performed at JPL to assess the lifetime of the discharge hollow cathode in the Xenon Ion Propulsion System (XIPS(c)), a 25-cm ion engine developed by L-3 Communications Electron Technologies, Inc. for commercial applications. Wear and plasma data accumulated throughout this life-assessment program are being used to validate the existing 2-D hollow cathode code OrCa2D. We find that the OrCa2D steady-state solution predicts very well the time-averaged plasma data and the keeper voltage after 5500 hrs of operation in high-power mode. When the wave motion that occurs naturally in these devices is accounted for, based on an estimate of the maximum wave amplitude, the molybdenum-keeper erosion profile observed in the XIPS(c) discharge cathode is also reproduced within a factor of two of the observation. When the same model is applied to predict the erosion of a tantalum keeper we find that erosion is reduced by more than two orders of magnitude compared to the molybdenum keeper due the significantly lower sputtering yield of tantalum. A tantalum keeper would therefore allow keeper lifetimes that greatly exceed the present requirements for deep-space robotic missions considered by NASA. Moreover, such large reduction of the erosion renders the largest uncertainties in the models, which are associated with the wave amplitude estimates and the electron transport model, negligible.

plasma simulations↗

DOE OSTI2025

SANE: strategic autonomous non-smooth exploration for multiple optima discovery in multi-modal and non-differentiable black-box functions

Both computational and experimental material discovery bring forth the challenge of exploring multidimensional and multimodal parameter spaces, such as phase diagrams of Hamiltonians with multiple interactions, composition spaces of combinatorial libraries, material structure image spaces, and molecular embedding spaces. Often these systems are black-boxes and time-consuming to evaluate, which resulted in strong interest towards active learning methods such as Bayesian optimization (BO). However, these systems are often noisy which make the black box function severely multi-modal and non-differentiable, where a vanilla BO can get overly focused near a single or faux optimum, deviating from the broader goal of scientific discovery. To address these limitations, here we developed Strategic Autonomous Non-Smooth Exploration (SANE) to facilitate an intelligent Bayesian optimized navigation with a proposed cost-driven probabilistic acquisition function to find multiple global and local optimal regions, avoiding the tendency to becoming trapped in a single optimum. To distinguish between a true and false optimal region due to noisy experimental measurements, a human (domain) knowledge driven dynamic surrogate gate is integrated with SANE. We implemented the gate-SANE into pre-acquired piezoresponse spectroscopy data of a ferroelectric combinatorial library with high noise levels in specific regions, and piezoresponse force microscopy (PFM) hyperspectral data. SANE demonstrated better performance than classical BO to facilitate the exploration of multiple optimal regions and thereby prioritized learning with higher coverage of scientific values in autonomous experiments. Our work showcases the potential application of this method to real-world experiments, where such combined strategic and human intervening approaches can be critical to unlocking new discoveries in autonomous research.

Biswas, Arpan [University of Tennessee, Knoxville,↗

NASA NTRS2003

SpaceWire Driver Software for Special DSPs

A computer program provides a high-level C-language interface to electronics circuitry that controls a SpaceWire interface in a system based on a space qualified version of the ADSP-21020 digital signal processor (DSP). SpaceWire is a spacecraft-oriented standard for packet-switching data-communication networks that comprise nodes connected through bidirectional digital serial links that utilize low-voltage differential signaling (LVDS). The software is tailored to the SMCS-332 application-specific integrated circuit (ASIC) (also available as the TSS901E), which provides three highspeed (150 Mbps) serial point-to-point links compliant with the proposed Institute of Electrical and Electronics Engineers (IEEE) Standard 1355.2 and equivalent European Space Agency (ESA) Standard ECSS-E-50-12. In the specific application of this software, the SpaceWire ASIC was combined with the DSP processor, memory, and control logic in a Multi-Chip Module DSP (MCM-DSP). The software is a collection of low-level driver routines that provide a simple message-passing application programming interface (API) for software running on the DSP. Routines are provided for interrupt-driven access to the two styles of interface provided by the SMCS: (1) the "word at a time" conventional host interface (HOCI); and (2) a higher performance "dual port memory" style interface (COMI).

Clark, Douglas↗

DOE OSTI2026

Learning genetic perturbation effects with variational causal inference

Advances in sequencing technologies have enhanced the understanding of gene regulation in cells. In particular, Perturb-seq has enabled high-resolution profiling of the transcriptomic response to genetic perturbations at the single-cell level. This understanding has implications in functional genomics and potentially for identifying therapeutic targets. Various computational models have been developed to predict perturbational effects. While deep learning models excel at interpolating observed perturbational data, they tend to overfit in the lack of enough data and may not generalize well to unseen perturbations. In contrast, mechanistic models, such as linear causal models based on gene regulatory networks, hold greater potential for extrapolation, as they encapsulate regulatory information that can predict responses to unseen perturbations. However, their application has been limited to small studies due to overly simplistic assumptions, making them less effective in handling noisy, large-scale single-cell data. We propose a hybrid approach that combines a mechanistic causal model with variational deep learning, termed Single Cell Causal Variational Autoencoder (SCCVAE). The mechanistic model employs a learned regulatory network to represent perturbational changes as shift interventions that propagate through the learned network. SCCVAE integrates this mechanistic causal model into a variational autoencoder, generating rich, comprehensive transcriptomic responses. Our results indicate that SCCVAE exhibits superior performance over current state-of-the-art baselines for extrapolating to predict unseen perturbational responses. Additionally, for the observed perturbations, the latent space learned by SCCVAE allows for the identification of functional perturbation modules and simulation of single-gene knockdown experiments of varying penetrance, presenting a robust tool for interpreting and interpolating perturbational responses at the single-cell level.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS1993

CFD flowfield simulation of Delta Launch Vehicles in a power-on configuration

This paper summarizes recent work at McDonnell Douglas Aerospace (MDA) to develop and validate computational fluid dynamic (CFD) simulations of under expanded rocket plume external flowfields for multibody expendable launch vehicles (ELVs). Multi engine reacting gas flowfield predictions of ELV base pressures are needed to define vehicle base drag and base heating rates for sizing external nozzle and base region insulation thicknesses. Previous ELV design programs used expensive multibody power-on wind tunnel tests that employed chamber/nozzle injected high pressure cold or hot-air. Base heating and pressure measurements were belatedly made during the first flights of past ELV's to correct estimates from semi-empirical engineering models or scale model tests. Presently, CFD methods for use in ELV design are being jointly developed at the Space Transportation Division (MDA-STD) and New Aircraft Missiles Division (MDA-NAMD). An explicit three dimensional, zonal, finite-volume, full Navier-Stokes (FNS) solver with finite rate hydrocarbon/air and aluminum combustion kinetics was developed to accurately compute ELV power-on flowfields. Mississippi State University's GENIE++ general purpose interactive grid generation code was chosen to create zonal, finite volume viscous grids. Axisymmetric, time dependent, turbulent CFD simulations of a Delta DSV-2A vehicle with a MB-3 liquid main engine burning RJ-1/LOX were first completed. Hydrocarbon chemical kinetics and a k-epsilon turbulence model were employed and predictions were validated with flight measurements of base pressure and temperature. Zonal internal/external grids were created for a Delta DSV-2C vehicle with a MB-3 and three Castor-1 solid motors burning and a Delta-2 with an RS-27 main engine (LOX/RP-1) and 9 GEM's attached/6 burning. Cold air, time dependent FNS calculations were performed for DSV-2C during 1992. Single phase simulations that employ finite rate hydrocarbon and aluminum (solid fuel) combustion chemistry are currently in progress. Reliable and efficient Eulerian algorithms are needed to model two phase (solid-gas) momentum and energy transfer mechanisms for solid motor fuel combustion products.

Pavish, D. L.↗

NASA NTRS2012

Overview of Heat Addition and Efficiency Predictions for an Advanced Stirling Convertor

The U.S. Department of Energy (DOE) and Lockheed Martin Space Systems Company (LMSSC) have been developing the Advanced Stirling Radioisotope Generator (ASRG) for use as a power system for space science missions. This generator would use two high-efficiency Advanced Stirling Convertors (ASCs), developed by Sunpower Inc. and NASA Glenn Research Center (GRC). The ASCs convert thermal energy from a radioisotope heat source into electricity. As part of ground testing of these ASCs, different operating conditions are used to simulate expected mission conditions. These conditions require achieving a particular operating frequency, hot end and cold end temperatures, and specified electrical power output for a given net heat input. Microporous bulk insulation is used in the ground support test hardware to minimize the loss of thermal energy from the electric heat source to the environment. The insulation package is characterized before operation to predict how much heat will be absorbed by the convertor and how much will be lost to the environment during operation. In an effort to validate these predictions, numerous tasks have been performed, which provided a more accurate value for net heat input into the ASCs. This test and modeling effort included: (a) making thermophysical property measurements of test setup materials to provide inputs to the numerical models, (b) acquiring additional test data that was collected during convertor tests to provide numerical models with temperature profiles of the test setup via thermocouple and infrared measurements, (c) using multidimensional numerical models (computational fluid dynamics code) to predict net heat input of an operating convertor, and (d) using validation test hardware to provide direct comparison of numerical results and validate the multidimensional numerical models used to predict convertor net heat input. This effort produced high fidelity ASC net heat input predictions, which were successfully validated using specially designed test hardware enabling measurement of heat transferred through a simulated Stirling cycle. The overall effort and results are discussed.

Wilson, Scott D.↗

NASA NTRS1983

Autonomy and the human element in space

NASA is contemplating the next logical step in the U.S. space program - the permanent presence of humans in space. As currently envisioned, the initial system, planned for the early 1990's, will consist of manned and unmanned platforms situated primarily in low Earth orbit. The manned component will most likely be inhabited by 6-8 crew members performing a variety of tasks such as materials processing, satellite servicing, and life science experiments. The station thus has utility in scientific and commercial enterprises, in national security, and in the development of advanced space technology. The technical foundations for this next step have been firmly established as a result of unmanned spacecraft missions to other planets, the Apollo program, and Skylab. With the shuttle, NASA inaugurates a new era of frequent flights and more routine space operations supporting a larger variety of missions. A permanently manned space system will enable NASA to expand the scope of its activities still further. Since NASA' s inception there has been an intense debate over the relative merits of manned and unmanned space systems. Despite the generally higher costs associated with manned components, astronauts have accomplished numerous essential, complex tasks in space. The unique human talent to evaluate and respond inventively to unanticipated events has been crucial in many missions, and the presence of crews has helped arouse and sustain public interest in the space program. On the other hand, the hostile orbital environment affects astronaut physiology and productivity, is dangerous, and mandates extensive support systems. Safety and cost factors require the entire station complex, both space and ground components, to be highly automated to free people from mundane operational chores. Recent advances in computer technology, artificial intelligence (AI), and robotics have the potential to greatly extend space station operations, offering lower costs and superior productivity. Extended operations can in turn enhance critical technologies and contribute to the competitive economic abilities of the United States. A high degree of automation and autonomy may be required to reduce dependence on ground systems, reduce mission costs, diminish complexity as perceived by the crew, increase mission lifetime and expand mission versatility. However, technologies dealing with heavily automated, long duration habitable spacecraft have not yet been thoroughly investigated by NASA. A highly automated station must amalgamate the diverse capabilities of people, machines, and computers to yield an efficient system which capitalizes on unique human characteristics. The station also must have an initial design which allows evolution to a larger and more sophisticated space presence. In the early years it is likely that AI-based subsystems will be used primarily in an advisory or planning capacity. As human confidence in automated systems grows and as technology advances, machines will take on more critical and interdependent roles. The question is whether, and how much, system autonomy will lead to improved station effectiveness.

Source record↗

NASA NTRS1993

Parametric binary dissection

Binary dissection is widely used to partition non-uniform domains over parallel computers. This algorithm does not consider the perimeter, surface area, or aspect ratio of the regions being generated and can yield decompositions that have poor communication to computation ratio. Parametric Binary Dissection (PBD) is a new algorithm in which each cut is chosen to minimize load + lambda x(shape). In a 2 (or 3) dimensional problem, load is the amount of computation to be performed in a subregion and shape could refer to the perimeter (respectively surface) of that subregion. Shape is a measure of communication overhead and the parameter permits us to trade off load imbalance against communication overhead. When A is zero, the algorithm reduces to plain binary dissection. This algorithm can be used to partition graphs embedded in 2 or 3-d. Load is the number of nodes in a subregion, shape the number of edges that leave that subregion, and lambda the ratio of time to communicate over an edge to the time to compute at a node. An algorithm is presented that finds the depth d parametric dissection of an embedded graph with n vertices and e edges in O(max(n log n, de)) time, which is an improvement over the O(dn log n) time of plain binary dissection. Parallel versions of this algorithm are also presented; the best of these requires O((n/p) log(sup 3)p) time on a p processor hypercube, assuming graphs of bounded degree. How PBD is applied to 3-d unstructured meshes and yields partitions that are better than those obtained by plain dissection is described. Its application to the color image quantization problem is also discussed, in which samples in a high-resolution color space are mapped onto a lower resolution space in a way that minimizes the color error.

Bokhari, Shahid H.↗

NASA NTRS2005

Reconfigurable Processing Module

To accommodate a wide spectrum of applications and technologies, NASA s Exploration System's Missions Directorate has called for reconfigurable and modular technologies to support future missions to the moon and Mars. In response, Langley Research Center is leading a program entitled Reconfigurable Scaleable Computing (RSC) that is centered on the development of FPGA-based computing resources in a stackable form factor. This paper details the architecture and implementation of the Reconfigurable Processing Module (RPM), which is the key element of the RSC system. The RPM is an FPGA-based, space-qualified printed circuit assembly leveraging terrestrial/commercial design standards into the space applications domain. The form factor is similar to, and backwards compatible with, the PCI-104 standard utilizing only the PCI interface. The size is expanded to accommodate the required functionality while still better than 30% smaller than a 3U CompactPCI(TradeMark)card and without the overhead of the backplane. The architecture is built around two FPGA devices, one hosting PCI and memory interfaces, and another hosting mission application resources; both of which are connected with a high-speed data bus. The PCI interface FPGA provides access via the PCI bus to onboard SDRAM, flash PROM, and the application resources; both configuration management as well as runtime interaction. The reconfigurable FPGA, referred to as the Application FPGA - or simply "the application" - is a radiation-tolerant Xilinx Virtex-4 FX60 hosting custom application specific logic or soft microprocessor IP. The RPM implements various SEE mitigation techniques including TMR, EDAC, and configuration scrubbing of the reconfigurable FPGA. Prototype hardware and formal modeling techniques are used to explore the performability trade space. These models provide a novel way to calculate quality-of-service performance measures while simultaneously considering fault-related behavior due to SEE soft errors.

Somervill, Kevin↗

NASA NTRS2019

Ensuring Flexibility and Security in SDN-Based Spacecraft Communication Networks Through Risk Assessment

Software-defined networking (SDN) has enabled elastic networking and resource distribution in cloud computing. The centralization and separation of the Control Plane also offers a high degree of network configurability and management, which can be used to mitigate and manage threats to the network. Space communication networks have historically been restricted and circuit switching in these networks has been a manual process. This study evaluates the potential role of SDN in space communication networks from a networking security standpoint. The evaluation covers the networking security needs of spacecraft missions and their associated assets. The results from the evaluation lead to a risk assessment that identifies vulnerabilities in an SDN-based communications architecture. Security challenges introduced into the network from integrating SDN are also considered. A risk register summarizes the severity of the attack outcomes, as well as occurrence likelihood. The study identifies Denial-of-Service (DoS) attacks as a new threat (presently unmitigated by existing security controls) that would be prevalent in an SDN-based space communication environment. A Mininet-based emulation testbed is built to demonstrate the susceptibility of spacecraft flight software to a flooding DoS attack when on an interconnected SDN-managed network. This type of attack would be highly consequential to mission assets, and therefore SDN-based space communications would need to be resilient to such attacks. Future work will need to be performed to fully characterize DoS attack methods that can apply to the space communication scenario, as well as to devise a comprehensive DoS-resilient solution.

Baker, Dylan Z.↗

DOE OSTI2026

Modeling Material Interfaces with the Six-Equation Model in FLEXO

FLEXO is a multiphysics code developed at Sandia National Laboratories for predictive simulation of pulsed power target physics with extended magnetohydrodynamics modeling. Given this application space, FLEXO must be able to perform high-fidelity simulations of pulsed-power systems that include multiple materials. This work presents the augmentation of FLEXO with a six-equation model for multimaterial flow. We design and analyze discretizations of the six-equation model, emphasizing desirable properties for robust multimaterial simulation. We also present solution limiting, bounds preservation, and pressure equilibration/relaxation techniques that enhance the robustness of the overall multimaterial scheme. We present a suite of test problems to document these new capabilities of the FLEXO code.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

NASA NTRS1999

System Analyses of Pneumatic Technology for High Speed Civil Transport Aircraft

The primary aspiration of this study was to objectively assess the feasibility of the application of a low speed pneumatic technology, in particular Circulation Control (CC) to an HSCT concept. Circulation Control has been chosen as an enabling technology to be applied on a generic High Speed Civil Transport (HSCT). This technology has been proven for various subsonic vehicles including flight tests on a Navy A-6 and computational application on a Boeing 737. Yet, CC has not been widely accepted for general commercial fixed-wing use but its potential has been extensively investigated for decades in wind tunnels across the globe for application to rotorcraft. More recently, an experimental investigation was performed at Georgia Tech Research Institute (GTRI) with application to an HSCT-type configuration. The data from those experiments was to be applied to a full-scale vehicle to assess the impact from a system level point of view. Hence, this study attempted to quantitatively assess the impact of this technology to an HSCT. The study objective was achieved in three primary steps: 1) Defining the need for CC technology; 2) Wind tunnel data reduction; 3) Detailed takeoff/landing performance assessment. Defining the need for the CC technology application to an HSCT encompassed a preliminary system level analysis. This was accomplished through the utilization of recent developments in modern aircraft design theory at Aerospace Systems Design Laboratory (ASDL). These developments include the creation of techniques and methods needed for the identification of technical feasibility show stoppers. These techniques and methods allow the designer to rapidly assess a design space and disciplinary metric enhancements to enlarge or improve the design space. The takeoff and landing field lengths were identified as the concept "show-stoppers". Once the need for CC was established, the actual application of data and trends was assessed. This assessment entailed a reduction of the wind tunnel data from the experiments performed by Mr. Bob Englar at the GTRI. Relevant data was identified and manipulated based on the required format of the analysis tools utilized. Propulsive, aerodynamic, duct sizing, and vehicle sizing investigations were performed and information supplied to a detailed takeoff and landing tool, From the assessments, CC was shown to improve the low speed performance metrics, which were previously not satisfied. An HSCT with CC augmentation does show potential for full-scale application. Yet, an economic assessment of an HSCT with and without CC showed that a moderate penalty was incurred from the increased RDT&E costs associated with developing the CC technology and slight increases in empty weight.

Mavris, Dimitri N.↗