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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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At least 829 records · Page 46
All sourcesNASA NTRSDOE OSTI
NASA NTRS1996

TPS Sizing for Access-to-Space Vehicles

A study was carried out to identify, develop, and benchmark simulation techniques needed for optimum thermal protection system (TPS) material selection and sizing for reusable launch vehicles. Fully viscous, chemically reacting, Navier-Stokes flow solutions over the Langley wing-body single stage to orbit (SSTO) configuration were generated and coupled with an in-depth conduction code. Results from the study provide detailed TPS heat shield materials selection and thickness sizing for the wing-body SSTO. These results are the first ever achieved through the use of a complete, trajectory based hypersonic, Navier-Stokes solution database. TPS designs were obtained for both laminar and turbulent entry trajectories using the Access-to-Space baseline materials such as tailorable advanced blanket insulation. The TPS design effects (materials selection and thickness) of coupling material characteristics to the aerothermal environment are illustrated. Finally, a sample validation case using the shuttle flight database is included.

Henline, William↗
NASA NTRS1995

SSBRP User Operations Facility (UOF) Overview and Development Strategy

This paper will present the Space Station Biological Research Project (SSBRP) User Operations Facility (UOF) architecture and development strategy. A major element of the UOF at NASA Ames Research Center, the Communication and Data System (CDS) will be the primary focus of the discussions. CDS operational, telescience, security, and development objectives will be discussed along with CDS implementation strategy. The implementation strategy discussions will include: Object Oriented Analysis & Design, System & Software Prototyping, and Technology Utilization. A CDS design overview that includes: CDS Context Diagram, CDS Architecture, Object Models, Use Cases, and User Interfaces will also be presented. CDS development brings together "cutting edge" technologies and techniques such as: object oriented development, network security, multimedia networking, web-based data distribution, JAVA, and graphical user interfaces. Use of these "cutting edge" technologies and techniques translates directly to lower development and operations costs.

Picinich, Lou↗
NASA NTRSDate not supplied

The LuNaMaps Project: Advancing Capabilities for Developing and Validating Digital Elevation Models of Rocky Surfaces from Orbital Data

Both navigation and surface science can benefit from the ability to generate high resolution and accurate maps of the surface of the Moon and other solar system bodies. The primary way these maps are generated is through the use of orbital imagery and ranging data. Traditionally, the process of using orbital imagery and ranging data is tedious and labor-intensive. Additionally, once maps have been built, there has generally been limited effort in developing standards by which to verify the accuracy and quality of the generated maps. The Lunar Navigation Maps (LuNaMaps) project is a NASA Game Changing Development (GCD) project which over the last 4 years has aimed to address these issues both for the Moon and for other rocky solar system bodies. This has been accomplished through development of new and existing capabilities including: a suite of methods and tools to combine all sources of orbital imagery; a benchmark data set as well as basic requirements for high-fidelity simulations of precision landing functions; tools to synthetically enhance map products with lander-scale features for use in the development and testing of hazard detection systems; methods and tools to evaluate the accuracy of developed digital elevation maps (DEMs) and their quality for use in terrain relative navigation scenarios; and tools to realistically render image and lidar data. In this work, we provide an overview of the capabilities developed through LuNaMaps, demonstrating its use for processing existing lunar data, and describing how it can be applied to other use cases. We additionally provide preliminary results showing the application of the developed tools and processes to the generation of elevation maps of the Lunar Surface Proving Grounds (LSPG) lunar analog at Astrobotic’s Mojave testing facility using “orbital imagery” captured by a drone. In this terrestrial demonstration, we have the benefit of being able to compare the results to a ground truth model of the LSPG. We finally describe plans to use the newly created maps in a terrestrial terrain relative navigation demonstration over the LSPG in early 2025.

optical navigation↗
DOE OSTI2023

Adaptive Ensemble Refinement of Protein Structures in High Resolution Electron Microscopy Density Maps with Radical Augmented Molecular Dynamics Flexible Fitting

Recent advances in cryo-electron microscopy (cryo-EM) have enabled modeling macromolecular complexes that are essential components of the cellular machinery. The density maps derived from cryo-EM experiments are often integrated with manual, knowledge or artificial intelligence driven, and physics-guided computational methods to build, fit, and refine molecular structures. Going beyond a single stationary- structure determination scheme, it is becoming more common to interpret the experimental data with an ensemble of models, which contributes to an average observation. Hence, there is a need to decide on the quality of an ensemble of protein structures on-the-fly, while refining them against the density maps. Here, we introduce such an adaptive decision making scheme during the molecular dynamics flexible fitting (MDFF) of biomolecules. Using RADICAL-Cybertools, and the new RADICAL augmented MDFF implementation (R-MDFF) is examined in high-performance computing environments for refinement of two protein systems, Adenylate Kinase and Carbon Monoxide Dehydrogenase. For the test cases, use of multiple replicas in flexible fitting with adaptive decision making in R-MDFF improves the overall correlation to the density by 40% relative to the refinements of the brute-force MDFF. The improvements are particularly significant at high, 2 - 3 Å, map resolutions. More importantly, the ensemble model captures key features of biologically relevant molecular dynamics that is inaccessible to a single-model interpretation. Finally, the pipeline is applicable to systems of growing sizes, which is demonstrated using ensemble refinement of capsid proteins from Chimpanzee adenovirus. The overhead for decision making remaining low and robust to computing environments. The software is publicly available on GitHub and includes a short user guide to install the R-MDFF on different computing environments, from local Linux based workstations to High Performance Computing (HPC) environments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Recovery Simulator and Analysis Formulation: Mathematical Framework for Enhanced Resilience and Resource Allocation

This report introduces recovery simulator and analysis (RSA), a framework aimed at enhancing the resilience of electrical grids post-disruption. The RSA model leverages an optimization problem formulation that focuses on maximizing the load served (or optionally customers served) through a coordinated and cooptimized recovery of non-black start generation, transmission lines, feeders and substations subject to labor budget constraints. By integrating advanced linear programming techniques, the simulator selects efficient reocovery pathways, optimizing both short-term and long-term grid recovery strategies. The mathematical framework guides decision-making through a comprehensive evaluation of potential recovery actions, factoring in the trade-offs between labor constraints and load (or optionally customer) restoration efficacy. This enables grid operators to simulate diverse outage scenarios and delineate optimal recovery pathways, thereby prioritizing critical repair tasks and ensuring resource allocation is both economical and effective. The intended use case of RSA is to allow planners to explore many recovery scenarios quickly and determine assets most critical across a wide range of scenarios, and therefore strong candidates for hardening or additional investment. RSA might also be used in an operational setting, following a single event, for exploring efficient recovery pathways.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2012

Programmatic Impact of SDRAM SEFI

The Elpida EDS5104(08)ABTA 512Mb SDRAM is examined for programmatic impact of SEE. Use cases for the devices including EDAC and mode register reload are examined. Results indicate some SEE mitigation methods require careful application to achieve system-level benefits, while some event types are essentially mitigated by the application use. In the studied devices MBE and SEFI are identified and investigated as mechanisms requiring special consideration.

Single Event Functionality Interrupt (SEFI)↗
NASA NTRSDate not supplied

Optimization Algorithms as Quantum Performance Benchmarks

Combinatorial optimization is anticipated to be one of the primary use cases for quantum computation in the coming years. The Quantum Approximate Optimization Algorithm (QAOA) and Quantum Annealing (QA) have the potential to demonstrate significant run-time performance benefits over current state-of-the-art solutions. Using existing methods for characterizing classical optimization algorithms, we analyze solution quality obtained by solving Max-Cut problems using a quantum annealing device and gate-model quantum simulators and devices. This is used to guide the development of an advanced benchmarking framework for quantum computers designed to evaluate the trade-off between run-time execution performance and the solution quality for iterative hybrid quantum-classical applications. The framework generates performance profiles through effective visualizations that show performance progression as a function of time for various problem sizes and illustrates algorithm limitations uncovered by the benchmarking approach. The framework is an enhancement to the existing open-source QED-C Application-Oriented Benchmark suite and can connect to the open-source analysis libraries. The suite can be executed on various quantum simulators and quantum hardware systems.

benchmarking↗
DOE OSTI2021

Direct-DC Power in Buildings: Identifying the Best Applications Today for Tomorrow’s Building Sector

Driven by the increased use of direct current (DC) sources (photovoltaics, battery storage) and DC end-use devices (electronics, solid-state lighting, efficient motors), DC power distribution in buildings and DC microgrids have been proposed as a way to achieve greater efficiency, cost savings, and resiliency in a transitioning building sector.Despite these important benefits, several market and technological barriers inhibit the development of DC distribution, and the market for DC in buildings is still largely in the demonstration phase. Therefore, to jumpstart this technology, a clear path forward must emerge at this early stage of deployment. The goal of this paper is to define specific end-use cases for which DC distribution in buildings is a value proposition today by defining clear efficiency and resiliency benefits while addressing barriers to implementation.The paper begins with a technology and market assessment of DC distribution equipment, end uses, and technology standards. That is followed by results from an expert elicitation of DC power and building end-use professionals (e.g., electrical designers, building operators, engineers) and reports on-site visits and lessons learned from successful (and less successful) field deployments of DC distribution projects in North America. We present specific adoption pathways at the community and building level that can be implemented today, and evaluate them using qualitative and quantitative metrics, such as technology and market readiness, energy savings, and resiliency.

Vossos, Evangelos↗
DOE OSTI2024

FORCE Regression Testing

Via programs including the Light Water Reactor Sustainability and Integrated Energy Systems, the U.S. Department of Energy has invested in the Framework for Optimization of ResourCes and Economics (FORCE) software framework (Idaho National Laboratory 2024a) for the technical and economic analysis of nuclear-integrated energy systems (IES). Nuclear IES expand the use of nuclear from traditional baseload electricity generation to a flexible and adaptive source of combined heat and power. Nuclear heat can be used in the production of a variety of energy currencies such as hydrogen and ammonia as well as other heat applications including water desalination and district heating. FORCE is designed with the intent to provide interconnected analysis tools that enable the accurate technical and economic assessment of specific nuclear IES configurations for individual energy markets. FORCE consists of three main analysis pathways: HYBRID (Idaho National Laboratory 2024b), which contains high-resolution physical models for IES; Holistic Energy Resource Optimization Network (HERON) (Idaho National Laboratory 2024c), which analyzes IES long-term economic viability; and Optimization of Real-time Capacity Allocation (ORCA) (Idaho National Laboratory 2024d), designed for real-time control of IES via digital twins and optimal decision making, including autonomous and remote operation research. Development of the FORCE ecosystem is guided by three pillars: capability, which assures that the computational requirements of IES analysis are met by the software tools; reliability, which provides for consistent code performance and expected behaviors; and accessibility, which lowers the barrier to entry for using the software and accelerates analysis by users beyond the FORCE primary developers. Reliability of the FORCE ecosystem is established according to the American Nuclear Society?s Nuclear Quality Assurance (NQA-1) program [American Society of Mechanical Engineers 1982], with specific levels of software quality assurance (SQA) within NQA-1 applied to each software tool in FORCE. As the tools within FORCE have matured, some integration algorithms to accurately connect the software tools for holistic analysis have been developed and deployed within the FORCE software repository. In accordance with NQA-1 standards, regression tests are required to guarantee the software performs consistently even when new capabilities are added to the software. In this report, we document the deployment of both unit tests, which test the consistent behavior of small pieces of the FORCE code base, as well as integration tests, which test the consistent performance of full use cases for the FORCE integration algorithms. We further document the encapsulation of these tests within a test harness, which collectively checks for each successful test completion on demand. Finally, we document the automation of the test harness using GitHub Actions [GitHub 2024], which require all tests succeed before any new capability or other changes can be added to the FORCE integration software

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1983

Space Shuttle propulsion parameter estimation using optimal estimation techniques

This fourth monthly progress report again contains corrections and additions to the previously submitted reports. The additions include a simplified SRB model that is directly incorporated into the estimation algorithm and provides the required partial derivatives. The resulting partial derivatives are analytical rather than numerical as would be the case using the SOBER routines. The filter and smoother routine developments have continued. These routines are being checked out.

Source record↗
DOE OSTI2024

Hls4ml Synthesis Testing

HLS4ml (high level synthesis for machine learning) Is a Python package used to translate commonly used open-source machine learning models into HLS. This is useful in machine learning applications on FPGAs. Machine learning algorithms are only as fast as the hardware that they are used on, and some applications require high speed without sacrificing accuracy. In these situations, an FPGA is a good choice since it is faster than a CPU or a GPU, but programming an FPGA is difficult. This is where HLS4ml can be used to simplify the process, as a well-known learning model can be converted to HLS and more easily deployed onto an FPGA. There are many use cases for a machine learning algorithm running on an FPGA. For example, detectors in a particle accelerator cannot keep every event that they detect, and so a computer must decide which events to keep and which to discard. Using an FPGA with a machine learning algorithm would be a good way to keep as many events as possible.

Swanson, Caiden↗
NASA NTRS2005

High Resolution Aerospace Applications using the NASA Columbia Supercomputer

This paper focuses on the parallel performance of two high-performance aerodynamic simulation packages on the newly installed NASA Columbia supercomputer. These packages include both a high-fidelity, unstructured, Reynolds-averaged Navier-Stokes solver, and a fully-automated inviscid flow package for cut-cell Cartesian grids. The complementary combination of these two simulation codes enables high-fidelity characterization of aerospace vehicle design performance over the entire flight envelope through extensive parametric analysis and detailed simulation of critical regions of the flight envelope. Both packages. are industrial-level codes designed for complex geometry and incorpor.ats. CuStomized multigrid solution algorithms. The performance of these codes on Columbia is examined using both MPI and OpenMP and using both the NUMAlink and InfiniBand interconnect fabrics. Numerical results demonstrate good scalability on up to 2016 CPUs using the NUMAIink4 interconnect, with measured computational rates in the vicinity of 3 TFLOP/s, while InfiniBand showed some performance degradation at high CPU counts, particularly with multigrid. Nonetheless, the results are encouraging enough to indicate that larger test cases using combined MPI/OpenMP communication should scale well on even more processors.

Mavriplis, Dimitri J.↗
NASA NTRS2018

Adaptive Load Control of Flexible Aircraft Wings Using Fiber Optic Sensing

Over the past century aircraft wing design has transformed from the morphing wing used on the Wright Flyer to rigid wings with little to no shape-tailoring abilities. Modern day wings are designed to fly at a single trim condition and optimized to have a maximum aerodynamic efficiency at only this condition. Shape morphing wings on the other hand have the potential to undergo geometric changes allowing them to adapt to their mission profiles. Several flight demonstrations have been conducted over the decades using morphing-wing technologies. Active wing-twist control was demonstrated on the X-53 Active Aeroelastic Wing (AAW) research project by utilizing multiple leading- and trailing-edge control surfaces. Passive morphing technology has been demonstrated on the Rockwell RPRV-870 Highly Maneuverable Aircraft Technology (HiMAT) aircraft. In the current study, the wings of a small unmanned aerial system (sUAS) were modified to have segmented control surfaces (SCS). The modifications include segmenting the original wing control surfaces (one flap and one aileron per wing) into 44 individual sections, each section having its own independent servo control motor. The wings were also instrumented with a network of over 1800 fiber-optic strain sensors (on four sensing fibers distributed over the top and bottom surfaces of the wing) monitoring the strain response of the wing to aerodynamic loading. The SCS positions were manipulated in real time to modify the spanwise lift distribution of the wings on the sUAS. The change in the structural response of the wings caused by load redistribution was quantified by measuring the bending strains on the upper and lower wing surfaces using an on-board compact fiber-optic strain sensing (cFOSS) system. A feedback controller was developed to control the SCS positions using strain-based shape estimations from the Displacement Transfer Function (DTF). Post-processing of the strain data allowed for the transverse displacement distributions and load distributions to be compared for the conventional and segmented control surface cases using displacements and loads algorithms developed by Richards and Ko at AFRC (refs. 5-10). While the current study focused on the shifting of the spanwise aerodynamic loads as quantified by displacements, future applications for loads or displacement control might include active gust alleviation and flutter suppression.

Pena, Francisco↗
NASA NTRSDate not supplied

Openet: Applications of Satellite-Based Evapotranspiration Data for Water Resources Management in the Western United States

Advancing water security in overallocated river basins globally requires consistent and reproducible information on consumptive use of water that can anchor the development of data-driven solutions to the challenge of balancing water supply and demand. OpenET is a fully automated system for field-scale (30 m), satellite-based mapping of evapotranspiration (ET) at daily, monthly and annual timesteps. OpenET currently provides spatially contiguous data throughout the 23 westernmost states in the continental US, and includes both current information as well as multi-year timeseries of ET. The OpenET consortium has implemented an ensemble of satellite-based ET models (ALEXI/DisALEXI, eeMETRIC, PT-JPL, geeSEBAL, SIMS and SSEBop) on Google Earth Engine, which provides a shared computing platform for collaboration on processing of data from Landsat and other satellites, land cover and meteorological inputs, leading to increased consistency and accuracy across the ensemble of models. Earth Engine also facilitates hosting and distribution of data via open data collections and an application programming interface. We provide updates on the OpenET framework, open data services and data access tools, approach to geographic expansion, recent accuracy assessments, and describe how a user-driven design approach has facilitated successful applications of OpenET data for a wide range of water resource management activities. Applications to date include: use of ET data to improve quantification of ET and consumptive use in Oregon, Utah and the Upper Colorado River Basin; streamlining of water use reporting requirements in the California Delta; support for calculation of water budgets for the implementation of the Sustainable Groundwater Management Act in California; and integration into decision support tools for irrigation management. The use cases demonstrate how satellite-derived ET data that are easily accessed and seen as broadly accepted can accelerate adoption of innovative water management practices at scale, and support advances in the sustainability of water supplies. Uptake and use of data by the OpenET science community has also led to advances in our understanding of the impacts of landcover change, irrigation intensification and wildfire events on hydrology and the water security.

Applications↗
DOE OSTI2020

Direct-DC Power in Buildings: Identifying the Best Applications Today for Tomorrow’s Building Sector

Driven by the increased use of direct current (DC) sources (photovoltaics, battery storage) and DC end-use devices (electronics, solid-state lighting, efficient motors), DC power distribution in buildings and DC microgrids have been proposed as a way to achieve greater efficiency, cost savings, and resiliency in a transitioning building sector. Despite these important benefits, several market and technological barriers inhibit the development of DC distribution, and the market for DC in buildings is still largely in the demonstration phase. Therefore, to jumpstart this technology, a clear path forward must emerge at this early stage of deployment. The goal of this paper is to define specific end-use cases for which DC distribution in buildings is a value proposition today by defining clear efficiency and resiliency benefits while addressing barriers to implementation. The paper begins with a technology and market assessment of DC distribution equipment, end uses, and technology standards. That is followed by results from an expert elicitation of DC power and building end-use professionals (e.g., electrical designers, building operators, engineers) and reports on-site visits and lessons learned from successful (and less successful) field deployments of DC distribution projects in North America. We present specific adoption pathways at the community and building level that can be implemented today, and evaluate them using qualitative and quantitative metrics, such as technology and market readiness, energy savings, and resiliency.

building-level electrical distribution↗
DOE OSTI2024

hls4ml

hls4ml (high level synthesis for machine learning) Is a Python package used to translate commonly used open-source machine learning models into HLS. This is useful in machine learning applications on FPGAs. Machine learning algorithms are only as fast as the hardware that they are used on, and some applications require high speed without sacrificing accuracy. In these situations, an FPGA is a good choice since it is faster than a CPU or a GPU, but programming an FPGA is difficult. This is where hls4ml can be used to simplify the process, as a well-known learning model can be converted to HLS and more easily deployed onto an FPGA. There are many use cases for a machine learning algorithm running on an FPGA. For example, detectors in a particle accelerator cannot keep every event that they detect, and so a computer must decide which events to keep and which to discard. Using an FPGA with a machine learning algorithm would be a good way to keep as many events as possible.

Swanson, Caiden↗
NASA NTRS1999

Testing and Analysis of Composite Skin/Stringer Debonding Under Multi-Axial Loading

Damage mechanisms in composite bonded skin/stringer constructions under uniaxial and biaxial (in-plane/out- of-plane) loading conditions were examined. Specimens consisted of a tapered composite flange bonded onto a composite skin. Tests were performed under monotonic loading conditions in tension, three-point bending, and combined tension/bending . For combined tension/bending testing, a unique servohydraulic load frame was used that was capable of applying both in-plane tension and out-of-plane bending loads simultaneously. Specimen edges were examined on the microscope to document the damage occurrence and to identify typical damage patterns. The observations showed that, for all three load cases, failure initiated in the flange, near the flange tip, causing the flange to almost fully debond from the skin. A two-dimensional plane-strain finite element model was developed to analyze the different test cases using a geometrically nonlinear solution. For all three loading conditions, principal stresses exceeded the transverse strength of the material in the flange area. Additionally, delaminations of various lengths were simulated in two locations where delaminations were observed. The analyses showed that unstable delamination propagation is likely to occur in one location at the loads corresponding to matrix ply crack initiation for all three load cases.

Krueger, Ronald↗
DOE OSTI2022

BESTEST-GSR (Building Energy Simulation Test - Generation Simulation and Reporting) 2023 [SWR 18-23]

Building Energy Simulation Test (BESTEST) is an NREL-developed method to validate the qualitative performance of different whole building simulations engines relative to each other. https://www.nrel.gov/docs/legosti/old/6231.pdf The purpose of this repository is to generate BESTEST test case models, run simulations, and populate data for ASHRAE Standard 140 reporting spreadsheets for EnergyPlus® based whole building simulation tools. It was originally setup for 2014 version of Standard 140. In May of 2022 it was updated to the 2020 version of Standard 140. This update included updates and additions to existing test suites, the bulk of which was in Section 5.2 (Building Thermal Envelope and Fabric Load Tests). We did not add Section 5.5 Airside HVAC Equipment Performance, but we hope to add that later in 2022. At some point we also hope to add Section 5.2.4 ground modeling, which is currently excluded. Supported Tools The default IDF generation is based on the OpenStudio® CLI, but the workflow supports a 'Bring your own IDF' use case. Additionally, for non-EnergyPlus® based tools the post processing scripts can be used if simulation results are provided as a CSV file.The scripts on this repository should work on Mac, Windows, and Linux. Dependencies Install OpenStudio® 3.4.0 make sure command line can recognize the 'openstudio' command This includes EnergyPlus® 22.1 Install Ruby on your system if it isn't already setup. 2.7 is used for development but other versions may work Since OpenStudio has its own embedded Ruby, which is used for running measures, you don't necessarily have to use a version of Ruby supported by OpenStudio. Install RubyXL Ruby gem This is used to modify Microsoft Excel spreadsheets Install Parallel Ruby gem This allows the CLI to run simulations in parallel

Goldwasser, David↗