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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 883 records · Page 49
All sourcesNASA NTRSDOE OSTI
NASA NTRS2002

Occupant Responses in a Full-Scale Crash Test of the Sikorsky ACAP Helicopter

A full-scale crash test of the Sikorsky Advanced Composite Airframe Program (ACAP) helicopter was performed in 1999 to generate experimental data for correlation with a crash simulation developed using an explicit nonlinear, transient dynamic finite element code. The airframe was the residual flight test hardware from the ACAP program. For the test, the aircraft was outfitted with two crew and two troop seats, and four anthropomorphic test dummies. While the results of the impact test and crash simulation have been documented fairly extensively in the literature, the focus of this paper is to present the detailed occupant response data obtained from the crash test and to correlate the results with injury prediction models. These injury models include the Dynamic Response Index (DRI), the Head Injury Criteria (HIC), the spinal load requirement defined in FAR Part 27.562(c), and a comparison of the duration and magnitude of the occupant vertical acceleration responses with the Eiband whole-body acceleration tolerance curve.

Jackson, Karen E.↗
NASA NTRS2002

Occupant Responses in a Full-Scale Crash Test of the Sikorsky ACAP Helicopter

A full-scale crash test of the Sikorsky Advanced Composite Airframe Program (ACAP) helicopter was performed in 1999 to generate experimental data for correlation with a crash simulation developed using an explicit nonlinear, transient dynamic finite element code. The airframe was the residual flight test hardware from the ACAP program. For the test, the aircraft was outfitted with two crew and two troop seats, and four anthropomorphic test dummies. While the results of the impact test and crash simulation have been documented fairly extensively in the literature, the focus of this paper is to present the detailed occupant response data obtained from the crash test and to correlate the results with injury prediction models. These injury models include the Dynamic Response Index (DRI), the Head Injury Criteria (HIC), the spinal load requirement defined in FAR Part 27.562(c), and a comparison of the duration and magnitude of the occupant vertical acceleration responses with the Eiband whole-body acceleration tolerance curve.

Jackson, Karen E.↗
NASA NTRS2019

A Comparison of ARTEMIS Data with the Lunar Plasma Design Environment for NASA Crewed Missions

NASA’s Gateway will provide the capability for sustaining a human presence in cis-lunar space. Operations of the Gateway will include spacecraft dockings, extra vehicular activities (EVA), and high-power solar arrays. NASA’s experience with the International Space Station highlighted the importance of evaluating spacecraft charging effects for such operations. For crewed spacecraft, which tend to employ the use of dielectric surfaces in this dynamic plasma environment, reliance on spacecraft charging simulation packages, such as the NASA/Air Force Spacecraft Charging Analyzer Program (Nascap-2k) [Mandell et al., 2006] and Spacecraft Plasma Interaction System (SPIS) [Roussel et al., 2008], is required to understand the risks to hardware and humans. The variability in the lunar plasma environment as the Moon revolves around the Earth, lunar wake effects, and a strong dependency on photoemission and secondary electron emission creates challenges for spacecraft charging analysis. The Design Specification for Natural Environments (DSNE) [NASA, MSFC] is the primary resource for space environments affecting NASA’s crewed missions, and the DSNE provides plasma environments in a standard form for input into simulation packages. NASA developed the existing lunar plasma environment using data from Geotail [Nishida, 1994] along with published lunar plasma wake models [Halekas et al., 2005] based on Lunar Prospector. Since 2011, NASA’s twin Acceleration Reconnection Turbulence & Electrodynamics of Moon’s Interaction with the Sun (ARTEMIS) satellites [Angelopoulos, 2010] have been collecting high resolution plasma and fields observations within the lunar plasma environment providing a much larger dataset of the plasma properties in cislunar space. This research compares the existing lunar plasma environment definition with ARTEMIS data and makes recommendations on the refinement of the environment definition for future lunar missions.

ARTEMIS mission↗
DOE OSTI2023

BUILD: Binary Understanding and Integration Logic for Dependencies (Final Report)

Increasingly diverse mission needs, the emergence of AI and cloud, and increasing hardware diversity are driving HPC software to be more complex. Modern codes are built from hundreds of small, complex components, and much of the software development process involves integrating these components rather than developing new components from scratch. The goal of the BUILD project was to ease the task of software integration for developers across LLNL’s programs. The project focused on (1) modeling software compatibility, (2) modeling ABI compatibility with binary analysis, (3) developing solver techniques to reason about compatibility, and (4) developing AI/ML models to fill gaps in our understanding of software compatibility. The project has developed several key technologies that help developers—by accelerating development workflows, removing the need for rebuilds, and enabling faster, automatic, and less error-prone code sharing. These technologies are used in LLNL codes and will be ready for the new El Capitan Exascale system in Livermore Computing. Many of these technologies have been hardened and integrated with LLNL’s Spack package manager, and they are already in use by production code teams. Results of BUILD have laid the groundwork for future advances in software integration—the ML and binary modification techniques developed in this project still need to be operationalized but have great potential to further speed up software integration.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

The future of self-driving laboratories: from human in the loop interactive AI to gamification

Recent developments in artificial intelligence (AI) and machine learning (ML), implemented through self-driving laboratories (SDLs), are rapidly creating unprecedented opportunities for the accelerated discovery and optimization of materials. This paper provides a joint analysis of SDLs from both academic and industry perspectives, highlighting the importance of integrating human intelligence in these systems. It discusses the necessity of careful planning in SDL design across physical, data, and workflow dimensions, including instrumental setup, experimental workflow, data management, and human–SDL interaction. The significance of integrating human input within SDLs, especially as the focus shifts from individual tools and tasks to the creation and management of complex workflows, is emphasized. The paper stresses on the crucial role of reward function design in developing forward-looking workflows and examines the interplay between hardware evolution, ML application across chemical processes, and the influence of reward systems in research. Ultimately, the article advocates for a future where SDLs blend human intuition in hypothesis formulation with AI's precision, speed, and data-handling capabilities.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Ultrafast High-Voltage Kicker System for Ion-Clearing Gaps

Ionization scattering of electron beams with residual gas molecules causes ion trapping in electron rings, both in a collider and electron cooling system. These trapped ions may cause emittance growth, tune shift, halo formation, and coherent coupled bunch instabilities. In order to clear the ions and prevent them from accumulating turn after turn, the gaps in a temporal structure of the beam are typically used. Typically, the gap in the bunch train has a length of a few percent of the ring circumference. In those regions, the extraction electrodes with high pulsed voltages are introduced. In this paper, we present the design consideration and initial test results of the high-voltage pulsed kicker hardware that includes vacuum device and pulsed voltage driver, capable of achieving over 3 kV of deflecting voltage amplitude, rise and fall times of less than 10 ns, 100 ns flat-top duration at 1.4 MHz repetition rate.

43 PARTICLE ACCELERATORS↗
NASA NTRS1987

Neutralization of beam-emitting spacecraft by plasma injection

An impulsive plasma injection has been used to study charge neutralization of the Space Shuttle Orbiter while it was emitting an electron beam into space. This investigation was performed by Space Experiments with Particle Accelerators on Spacelab-1. A plasma consisting of 10 to the 19th argon ion-electron pairs was injected into space for 1 ms while an electron beam was also being emitted into space. The electron beam energy and current were as high as 5 keV and 300 mA. While the orbiter potential was positive before the plasma injection and began to decrease during the plasma injection, it was near zero for 6 to 20 ms after the plasma injection. The recovery time to the initial level of charging varied from 10 to 100 ms. In a laboratory test in a large space chamber using the same flight hardware, the neutralization time was 8-17 ms and the recovery time was 11-20 ms. The long duration of the neutralization effect in space can be explained by a model of diffusion of the cold plasma which is produced near the Orbiter by charge exchange between the neutral argon atoms and the energetic argon ions during plasma injection.

Sasaki, S.↗
DOE OSTI2019

FERMILAB PIP-II BOOSTER LLRF UPGRADE

A proposed upgrade to the Fermilab Booster synchrotron is presented. A new LLRF system is required for interfac-ing to the PIP-II Linac that is currently under construction. The present feedback system has legacy analog hardware interleaved with updated digital components for control. A prototype of a new digital system using an FPGA controller is presented along with the RF hardware to handle up and down conversion of RF signals. A prototype FPGA con-troller is implemented using an Altera Cyclone V System on Chip, with 14-bit ADC’s and DAC’s running at 66 MHz. The controller theory and implementation are described in this paper, along with a description of the RF signal processing scheme.

43 PARTICLE ACCELERATORS↗
DOE OSTI2019

BSTC: A Novel Binarized-Soft-Tensor-Core Design for Accelerating Bit-Based Approximated Neural Nets

Binarized neural network (or BNN) promises tremendous performance improvement over traditional DNNs through simplified bit-level computation and significantly reduced memory access/storage cost. In addition, it has other advantages of low-cost, low-energy and high-robustness, showing great utilization potential in resources-constrained, volatile and latency-critical applications, which are critical for future HPC execution. However, the promised significant performance gain of BNN inference has never been fully demonstrated on general-purpose processors, particularly on GPUs, due to: (i) the challenge to extract and leverage sufficient fine-grained bit-level-parallelism to saturate GPU cores when batch is small; (ii) the fundamental design conflict between bit-based BNN algorithm and underlying word-based architecture; (iii) architecture \& performance unfriendly BNN network design. To address (i) and (ii), we propose binarized-soft-tensor-core as a software-hardware codesign approach to construct bit-manipulation capability for modern GPUs to effectively harvest the emerging bit-level-parallelism. To tackle (iii), we propose intra- and inter-layer fusion techniques so that the entire BNN inference can be packed into a single GPU kernel, to avoid high-cost frequent launching. Experiments demonstrate that our design can achieve over 1000x speedup for raw inference latency and 10x for inference throughput over the state-of-the-art full-precision simulated BNN inference for AlexNet on ImageNet.

Li, Ang↗
DOE OSTI2020

The Accelerator Neutrino Neutron InteractionExperiment: Design, Construction and Preparationfor First Physics

This thesis covers work performed for the Accelerator Neutrino Neutron Interaction Experiment (ANNIE) between 2015 and 2020. ANNIE is a beamline neutrino experiment located at the Fermi National Accelerator Laboratory in Chicago. Its primary physics goals are the measurement of neutrino interaction cross-sections on oxygen, and a measurement of the multiplicity of final state neutrons from these interactions, both as functions of final state kinematics. In order to achieve these goals ANNIE will be pioneering the use of Large Area Picosecond Photodetectors and the use of gadolinium doping to enhance neutron visibility in a water Cherenkov detector. Over the time period of this thesis the ANNIE detector was constructed, an initial 'Phase I' background run was completed, the detector was decommissioned and then substantially upgraded in preparation for the main 'Phase II' physics run. At the time of writing ANNIE is being re-commissioned, with Phase II data taking anticipated to begin in 2021. During this time I spent 21/2 years on-site contributing to almost all aspects of hardware work, while performing software development for the simulation and analysis frameworks. As my first software task I developed Monte Carlo simulations of the detector response, based on the WCSim framework. While thismore » framework provided a starting point for the tank simulation significant modifications were required to implement the complete ANNIE detector system. This included a rewrite of the geometry, along with modifications to the photosensor definitions, hit collections, digitization, triggering, input and output interfaces, etc. To take advantage of improved modelling of neutrons in Geant4.10 the physics lists were also reimplemented in the new version format. As part of this work I determined performance metrics based on the output files, calculating kinematic acceptance, detector efficiency and expected event rates. My contributions on reconstruction focused primarily on the MRD, for which I implemented two track reconstruction algorithms, specialised for high and low energy muons. The high energy algorithm achieves >90% efficiency for tracks with at least 8 hits, and is robust against dead paddles and unrelated hits. The low energy algorithm performs a search in combination with tank information to provide sensitivity down to a single MRD hit. Early data handling work for the Phase I background run included writing the code for handling TDC hits and performing studies on neutron detection without the requirement of multi-hit coincidence. As the collaboration moved to a new framework for the Phase II analysis I performed a substantial amount of work to develop the codebase, implementing tools to perform tasks such as file IO, data parsing, waveform processing, event building, timestamp alignment, time clustering, hit residual calculation, event visualisation etc. I helped develop the python API for integrating multi-language tools, and ported the framework into a Singularity container to provide a self-contained environment that…« less

43 PARTICLE ACCELERATORS↗
NASA NTRS1996

Energy Beam Highways Through the Skies

The emergence of Energy Beam Flight Transportation Systems could dramatically change the way we travel in the 21st Century. A framework for formulating 'Highways of Light' and the top level architectures that invoke radically new Space Power Grid infrastructure, are introduced. Basically, such flight systems, hereafter called Lightcraft, would employ off-board energy beam sources (either laser or microwave) to energize on-board dependent 'motors' -- instead of the traditional autonomous 'engines' with their on-board energy sources (e.g., chemical fuels). Extreme reductions in vehicle dry mass appear feasible with the use of off-board power and a high degree of on-board artificial intelligence. Such vehicles may no longer need airports for refueling (since they require no propellant), and could possibly pick up travelers at their homes -- before motoring over to one of many local boost stations, for the flight out. With off-board power, hyper-energetic acceleration performance and boost-glide trajectories become feasible. Hypersonic MS airbreathing propulsion can enable boosts up to twice escape velocity, which will cut trip times to the moon down to 5.5 hours. The predominant technological, environmental and social factors that will result from such transportation systems will be stressed. This presentation first introduces the remote source siting options for the space power system infrastructure, and then provides three representative laser/microwave Lightcraft options (derived from historical Case Studies): i.e., 'Acorn', 'Toy Top', and 'Disc.' Next the gamut of combined-cycle engine options developed for these Lightcraft are examined -- to illuminate the 'emerging technologies' that must be harnessed to produce flight hardware. Needed proof-of concept experiments are identified, along with the Macro-Level Issues that can springboard these revolutionary concepts into hardware reality.

Myrabo, Leik N.↗
DOE OSTI2020

Machine learning for collective variable discovery and enhanced sampling in biomolecular simulation

Classical molecular dynamics simulates the time evolution of molecular systems through the phase space spanned by the positions and velocities of the constituent atoms. Molecular-level thermodynamic, kinetic, and structural data extracted from the resulting trajectories provide valuable information for the understanding, engineering, and design of biological and molecular materials. The cost of simulating many-body atomic systems makes simulations of large molecules prohibitively expensive, and the high-dimensionality of the resulting trajectories presents a challenge for analysis. Driven by advances in algorithms, hardware, and data availability, there has been a flare of interest in recent years in the applications of machine learning – especially deep learning – to molecular simulation. Furthermore, these techniques have demonstrated great power and flexibility in both extracting mechanistic understanding of the important nonlinear collective variables governing the dynamics of a molecular system, and in furnishing good low-dimensional system representations with which to perform enhanced sampling or develop long-timescale dynamical models. It is the purpose of this article to introduce the key machine learning approaches, describe how they are married with statistical mechanical theory into domain-specific tools, and detail applications of these approaches in understanding and accelerating biomolecular simulation.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2019

FASPAX ASIC revision 1.b first articles testing and support

Fermi National Accelerator Laboratory (Fermilab) and Field Viewers Ltd. Inc. (FV) will work together for a period of two weeks to bring up the FASPAX_V1.0b. During this period, Fermilab will help FV come up to speed with the ASIC functionality testing and train in the usage of the FASPAX test setup at Fermilab that uses the NIPXIe architecture with FleXRIO modules. This setup will be initially used for testing of chips to ensure the basic functionality and design parameters. The NIPXIe setup was developed by the Fermilab team, but it is has not yet been verified to be capable of fully testing the FASPAX_V1.0 chip. Fermilab will offer the developed software and hardware to FV for the on-site use at Fermilab. No guarantee is given by Fermilab for the setup to be able to fully cover the scope of the necessary tests. FV will be responsible for using and modifying of the setup to achieve the DOE-BES Phase-I targets.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS2005

Results of a 2000 hour wear test of the NEXIS ion engine

The Nuclear Electric Xenon Ion System (NEXIS) ion thruster was developed for potential outer planet robotic missions under NASA's Prometheus program. This engine was designed to operate at power levels ranging from 16 to over 20 kWe at specific impulses of 6000 to 7500 s for burn times of up to 10 years, satisfying the requirements of nuclear electric propulsion systems such as that on the proposed Prometheus 1 mission to explore the icy moons of Jupiter. State-of-the-art performance and life assessment tools were used to design the thruster. Following the successful performance validation of a Laboratory Model thruster, Development Model hardware was fabricated and subjected to vibration and wear testing. The results of a 2000-hour wear test are reported herein. Thruster performance achieved the target requirements and was steady for the duration of the test. Ion optics performance was similarly stable. Discharge loss increases of 6 eV/ion were observed in the first 500 hours of the test and were attributed to primary electron energy decreases due to cathode insert conditioning. Relatively high recycle rates were observed and were identified to be high-voltage-to-ground arcs in the back of the thruster caused by wire insulation outgassing and electron penetration through the plasma screen. Field emission of electrons between the accelerator and screen grids was observed and attributed to evolution of field emitter sites at accelerator grid aperture edges caused by ion bombardment. Preliminary modeling and analysis indicates that the NEXIS engine can meet mission performance requirements over the required lifetime. Finally, successful validation of the NEXIS design methodology, design tools, and technologies with the results of the wear test and companion performance and vibration tests presents significant applicability of the NEXIS development effort to missions of near-term as well as long-term interest for NASA.

Nuclear Electric Xenon Ion System (NEXIS)Thruster ↗
NASA NTRS2005

Results of a 2000 Hour Wear Tof the NEXIS Ion Engine

The Nuclear Electric Xenon Ion System (NEXIS) ion thruster was developed for potential outer planet robotic missions under NASA's Prometheus program. This engine was designed to operate at power levels ranging from 16 to over 20 kWe at specific impulses of 6000 to 7500 s for burn times of up to 10 years, satisfying the requirements of nuclear electric propulsion systems such as that on the proposed Prometheus 1 mission to explore the icy moons of Jupiter. State-of-the-art performance and life assessment tools were used to design the thruster. Following the successful performance validation of a Laboratory Model thruster, Development Model hardware was fabricated and subjected to vibration and wear testing. The results of a 2000-hour wear test are reported herein. Thruster performance achieved the target requirements and was steady for the duration of the test. Ion optics performance was similarly stable. Discharge loss increases of 6 eV/ion were observed in the first 500 hours of the test and were attributed to primary electron energy decreases due to cathode insert conditioning. Relatively high recycle rates were observed and were identified to be high-voltage-to-ground arcs in the back of the thruster caused by wire insulation outgassing and electron penetration through the plasma screen. Field emission of electrons between the accelerator and screen grids was observed and attributed to evolution of field emitter sites at accelerator grid aperture edges caused by ion bombardment. Preliminary modeling and analysis indicates that the NEXIS engine can meet mission performance requirements over the required lifetime. Finally, successful validation of the NEXIS design methodology, design tools, and technologies with the results of the wear test and companion performance and vibration tests presents significant applicability of the NEXIS development effort to missions of near-term as well as long-term interest for NASA.

Thruster performance↗
DOE OSTI2026

MIND-MAC: Multi-Level In-memory Quasi Non-Destructive MAC Operation in Compact 2T-nC FeRAM for Efficient DNN Accelerator

We present MIND-MAC, a compact 2T-nC FeRAM architecture that performs multi-level, quasi-non-destructive in-memory multiply–accumulate (MAC) for deep neural networks. By exploiting voltage-controlled partial domain switching in MFM capacitors and read-transistor amplification, the cell stores multi-bit weights and gates bit-serial inputs to produce an accumulated current on shared lines. We combine TCAD-extracted parasitics with experimentally calibrated ferroelectric models in SPICE to validate device-/circuit-level behavior, and validate multi-level sensing and QNRO with measurements on a fabricated 2T-3C test vehicle. An analytical system model maps MIND-MAC to a 6-GB main-memory in-memory compute (IMC) architecture and benchmarks VGG13 inference in 61.08 ms at 964.99 mJ. Results indicate high density, reduced rewrite overhead, and energy efficiency, positioning 2T-nC FeRAM as a promising IMC candidate for next-generation AI hardware.

36 MATERIALS SCIENCE↗
DOE OSTI2021

EXAGRAPH: Graph and combinatorial methods for enabling exascale applications

Combinatorial algorithms in general and graph algorithms in particular play a critical enabling role in numerous scientific applications. However, the irregular memory access nature of these algorithms makes them one of the hardest algorithmic kernels to implement on parallel systems. With tens of billions of hardware threads and deep memory hierarchies, the exascale computing systems in particular pose extreme challenges in scaling graph algorithms. The codesign center on combinatorial algorithms, ExaGraph, was established to design and develop methods and techniques for efficient implementation of key combinatorial (graph) algorithms chosen from a diverse set of exascale applications. Algebraic and combinatorial methods have a complementary role in the advancement of computational science and engineering, including playing an enabling role on each other. In this paper, we survey the algorithmic and software development activities performed under the auspices of ExaGraph from both a combinatorial and an algebraic perspective. In particular, we detail our recent efforts in porting the algorithms to manycore accelerator (GPU) architectures. We also provide a brief survey of the applications that have benefited from the scalable implementations of different combinatorial algorithms to enable scientific discovery at scale. We believe that several applications will benefit from the algorithmic and software tools developed by the ExaGraph team.

97 MATHEMATICS AND COMPUTING↗