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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
NASA NTRS1999

Seasonal Predictions with the GEOS GCM

A number of ensembles of seasonal forecasts have recently been completed as part of NASA's Seasonal to Interannual Prediction Project (NSIPP). The focus is on the extratropical response of the atmosphere to observed Surface Sea Temperature (SST) anomalies during boreal winter. The prediction experiments consist of nine forecasts starting from slightly different initial conditions for each year of the 15 year period 1981-95, employing version 2 of the Goddard Earth Observing System (GEOS) atmospheric Global Circulation Models (GCM). The initial conditions are obtained from the NASA GEOS-1 reanalysis data. Comparisons with a companion set of six long-term simulations with observed SST (starting in 1978, so they have no memory of the initial conditions for the periods of interest) are used to assess the relative contributions of the initial conditions and SST anomalies to forecast skill ranging from daily to seasonal time scales. The ensembles are used to isolate the signal, and to assess the nature of the inherent variability (noise) of the forecasts.

Schubert, Siegfried↗
NASA NTRS1996

Long-term modifications of synaptic efficacy in the human inferior and middle temporal cortex

The primate temporal cortex has been demonstrated to play an important role in visual memory and pattern recognition. It is of particular interest to investigate whether activity-dependent modification of synaptic efficacy, a presumptive mechanism for learning and memory, is present in this cortical region. Here we address this issue by examining the induction of synaptic plasticity in surgically resected human inferior and middle temporal cortex. The results show that synaptic strength in the human temporal cortex could undergo bidirectional modifications, depending on the pattern of conditioning stimulation. High frequency stimulation (100 or 40 Hz) in layer IV induced long-term potentiation (LTP) of both intracellular excitatory postsynaptic potentials and evoked field potentials in layers II/III. The LTP induced by 100 Hz tetanus was blocked by 50-100 microM DL-2-amino-5-phosphonovaleric acid, suggesting that N-methyl-D-aspartate receptors were responsible for its induction. Long-term depression (LTD) was elicited by prolonged low frequency stimulation (1 Hz, 15 min). It was reduced, but not completely blocked, by DL-2-amino-5-phosphonovaleric acid, implying that some other mechanisms in addition to N-methyl-DL-aspartate receptors were involved in LTD induction. LTD was input-specific, i.e., low frequency stimulation of one pathway produced LTD of synaptic transmission in that pathway only. Finally, the LTP and LTD could reverse each other, suggesting that they can act cooperatively to modify the functional state of cortical network. These results suggest that LTP and LTD are possible mechanisms for the visual memory and pattern recognition functions performed in the human temporal cortex.

NASA Discipline Neuroscience↗
NASA NTRS1990

Primary lithium cell life studies

One solution for providing a truly independent power source is to package, within the critical subsystem element, a primary battery that can remain dormant for time periods as long as the mission life, which can be 10-15 years, maximum. When primary power from the spacecraft solar array/battery system is interrupted, the backup battery system, which is connected through a diode to the power input line, would automatically support the load to avoid a power interruption to the critical load for a time period long enough to ensure that ground control could access the satellite and correct the anomaly by sending appropriate commands to the spacecraft. Critical subsystems identified for the application are telemetry and command circuits, volatile computer memory, attitude control circuits, and some critical payloads. Due to volume packaging and weight restrictions that exist on most spacecraft, coupled with the long storage periods required, lithium cell technology was selected for the backup power source. Because of the high energy density (200-400 Wh/kg), long shelf life, and load capability, soluble cathode primary lithium technology was chosen. The most important lithium cell properties that require detail characterization for this application are capacity loss, shelf life, and the voltage delay mechanism. These are functions of storage time and temperature. During storage, a passive film builds up on the lithium electrode. The film protects the lithium electrode from progressive capacity decay but requires time to break down when a load is applied. This phenomenon results in a depressed voltage during the period of film breakdown which can last from fractions of a second to minutes.

Capulli, John↗
DOE OSTI2025

RingX: Scalable Parallel Attention for Long-Context Learning on HPC

The attention mechanism has become foundational for remarkable AI breakthroughs since the introduction of the Transformer, driving the demand for increasingly longer context to power frontier models such as large-scale reasoning language models and high-resolution image/video generators. However, its quadratic computational and memory complexities present substantial challenges. Current state-of-the-art parallel attention methods, such as ring attention, are widely adopted for long-context training but utilize a point-to-point communication strategy that fails to fully exploit the capabilities of modern HPC network architectures. In this work, we propose ringX, a scalable family of parallel attention methods optimized explicitly for HPC systems. By enhancing workload partitioning, refining communication patterns, and improving load balancing, ringX achieves up to 3.4 × speedup compared to conventional ring attention on the Frontier supercomputer. Optimized for both bi-directional and causal attention mechanisms, ringX demonstrates its effectiveness through training benchmarks of a Vision Transformer (ViT) on a climate dataset and a Generative Pre-Trained Transformer (GPT) model, Llama3 8B. Our method attains an end-to-end training speedup of approximately 1.5 × in both scenarios. To our knowledge, the achieved 38% model FLOPs utilization (MFU) for training Llama3 8B with a 1M-token sequence length on 4,096 GPUs represents one of the highest training efficiencies reported for long-context learning on HPC systems. Our code implementation is available at https://github.com/jqyin/ringX-attention.

Yin, Junqi [ORNL] (ORCID:0000000338435520)↗
NASA NTRS1990

Galileo spacecraft power management and distribution system

The Galileo PMAD (power management and distribution system) is described, and the design drivers that established the final as-built hardware are discussed. The spacecraft is powered by two general-purpose heat-source-radioisotope thermoelectric generators. Power bus regulation is provided by a shunt regulator. Galileo PMAD distributes a 570-W beginning of mission (BOM) power source to a user complement of some 137 load elements. Extensive use of pyrotechnics requires two pyro switching subassemblies. They initiate 148 squibs which operate the 47 pyro devices on the spacecraft. Detection and correction of faults in the Galileo PMAD is an autonomous feature dictated by requirements for long life and reliability in the absence of ground-based support. Volatile computer memories in the spacecraft command and data system and attitude control system require a continuous source of backup power during all anticipated power bus fault scenarios. Power for the Jupiter Probe is conditioned, isolated, and controlled by a Probe interface subassembly. Flight performance of the spacecraft and the PMAD has been successful to date, with no major anomalies.

Detwiler, R. C.↗
NASA NTRS1994

Technical report series on global modeling and data assimilation. Volume 3: An efficient thermal infrared radiation parameterization for use in general circulation models

A detailed description of a parameterization for thermal infrared radiative transfer designed specifically for use in global climate models is presented. The parameterization includes the effects of the main absorbers of terrestrial radiation: water vapor, carbon dioxide, and ozone. While being computationally efficient, the schemes compute very accurately the clear-sky fluxes and cooling rates from the Earth's surface to 0.01 mb. This combination of accuracy and speed makes the parameterization suitable for both tropospheric and middle atmospheric modeling applications. Since no transmittances are precomputed the atmospheric layers and the vertical distribution of the absorbers may be freely specified. The scheme can also account for any vertical distribution of fractional cloudiness with arbitrary optical thickness. These features make the parameterization very flexible and extremely well suited for use in climate modeling studies. In addition, the numerics and the FORTRAN implementation have been carefully designed to conserve both memory and computer time. This code should be particularly attractive to those contemplating long-term climate simulations, wishing to model the middle atmosphere, or planning to use a large number of levels in the vertical.

Suarex, Max J.↗
NASA NTRS1999

The Variability and Predictability of Precipitation over Southeast Asian

The large scale atmospheric moisture budget, including precipitation, moisture flux convergence, and evaporation is described over southeast Asian. ne results are from the Goddard Earth Observing System (GEOS-1) data assimilation system for the period March 1981 - February 1995. On average, in the late spring and early summer season, precipitation is largely balanced by the atmospheric moisture flux convergence over southeast Asian; evaporation is also an important contributor. The seasonal variability of precipitation is best related to variations in the moisture flux convergence. On the monthly time scales, both the precipitable water and precipitation anomalies are most closely related to moisture flux convergence anomalies and less closely related to evaporation anomalies. The impact of the low-level jet (LLJ) on the strong low-level moisture flux convergence will be discussed. An ensemble of GEOS-2 atmospheric General Circulation Model (GCM) seasonal forecasts and long-term simulation are analyzed to assess the controlling influences of boundary forcing and memory of initial conditions. We also assess the variability and potential predictability from these experiments.

Chang, Yehui↗
NASA NTRS2004

A Novel Metal-Ferroelectric-Semiconductor Field-Effect Transistor Memory Cell Design

The use of a Metal-Ferroelectric-Semiconductor Field-Effect Transistor (MFSFET) in a resistive-load SRAM memory cell has been investigated A typical two-transistor resistive-load SRAM memory cell architecture is modified by replacing one of the NMOS transistors with an n-channel MFSFET. The gate of the MFSFET is connected to a polling voltage pulse instead of the other NMOS transistor drain. The polling voltage pulses are of sufficient magnitude to saturate the ferroelectric gate material and force the MFSFET into a particular logic state. The memory cell circuit is further modified by the addition of a PMOS transistor and a load resistor in order to improve the retention characteristics of the memory cell. The retention characteristics of both the "1" and "0" logic states are simulated. The simulations show that the MFSFET memory cell design can maintain both the "1" and "0" logic states for a long period of time.

Phillips, Thomas A.↗
NASA NTRS1994

VLSI-based Video Event Triggering for Image Data Compression

Long-duration, on-orbit microgravity experiments require a combination of high resolution and high frame rate video data acquisition. The digitized high-rate video stream presents a difficult data storage problem. Data produced at rates of several hundred million bytes per second may require a total mission video data storage requirement exceeding one terabyte. A NASA-designed, VLSI-based, highly parallel digital state machine generates a digital trigger signal at the onset of a video event. High capacity random access memory storage coupled with newly available fuzzy logic devices permits the monitoring of a video image stream for long term (DC-like) or short term (AC-like) changes caused by spatial translation, dilation, appearance, disappearance, or color change in a video object. Pre-trigger and post-trigger storage techniques are then adaptable to archiving only the significant video images.

Williams, Glenn L.↗
NASA NTRS1993

JSC Director's Discretionary Fund 1992 Annual Report

Annual report of the Johnson Space Center Director's Discretionary Fund documenting effective use of resources. The $1,694,000 funding for FY92 was distributed among 27 projects. The projects are an overall aid to the NASA mission, as well as providing development opportunities for the science and engineering staff with eventual spinoff to commercial uses. Projects described include space-based medical research such as the use of stable isotopes of deuterium and oxygen to measure crew energy use and techniques for noninvasive motion sickness medication. Recycling essentials for space crew support is conducted in the Regenerative Life Support and the Hybrid Regenerative Water Recovery test beds. Two-phase fluid flow simulated under low-gravity conditions, hypervelocity particle impact on open mesh bumpers, and microcalorimetry to measure the long-term hydrazine/material compatibility were investigated. A patent application was made on a shape-memory-alloy release nut. Computer estimate of crew accommodations for advanced concepts was demonstrated. Training techniques were evaluated using multimedia and virtual environment. Upgrades of an electronic still camera provide high resolution images from orbit are presented.

Jenkins, Lyle↗
NASA NTRS2012

The Prompt-afterglow Connection in Gamma-ray Bursts: a Comprehensive Statistical Analysis of Swift X-ray Light-curves

We present a comprehensive statistical analysis of Swift X-ray light-curves of Gamma- Ray Bursts (GRBs) collecting data from more than 650 GRBs discovered by Swift and other facilities. The unprecedented sample size allows us to constrain the rest-frame X-ray properties of GRBs from a statistical perspective, with particular reference to intrinsic time scales and the energetics of the different light-curve phases in a common rest-frame 0.3-30 keV energy band. Temporal variability episodes are also studied and their properties constrained. Two fundamental questions drive this effort: i) Does the X-ray emission retain any kind of "memory" of the prompt γ-ray phase? ii) Where is the dividing line between long and short GRB X-ray properties? We show that short GRBs decay faster, are less luminous and less energetic than long GRBs in the X-rays, but are interestingly characterized by similar intrinsic absorption. We furthermore reveal the existence of a number of statistically significant relations that link the X-ray to prompt γ-ray parameters in long GRBs; short GRBs are outliers of the majority of these 2-parameter relations. However and more importantly, we report on the existence of a universal 3-parameter scaling that links the X-ray and the γ-ray energy to the prompt spectral peak energy of both long and short GRBs: E(sub X,iso)∝ E(sup 1.00+/-0.06)(sub γ,iso) /E(sup 0.60+/-0.10)(sub pk).

Gamma-Ray Bursts↗
DOE OSTI2026

When does global attention help: a unified empirical study on atomistic graph learning

Graph neural networks (GNNs) are widely used as surrogates for costly experiments and first-principles simulations to study the behavior of compounds at atomistic scale, and their architectural complexity is constantly increasing to enable the modeling of complex physics. While most recent GNNs combine more traditional message passing neural networks (MPNNs) layers to model short-range interactions with more advanced graph transformers (GTs) with global attention mechanisms to model long-range interactions, it is still unclear when global attention mechanisms provide real benefits over well-tuned MPNN layers due to inconsistent implementations, features, or hyperparameter tuning. We introduce the first unified, reproducible benchmarking framework–built on HydraGNN–that enables seamless switching among four controlled model classes: MPNN, MPNN with chemistry/topology encoders, GPS-style hybrids of MPNN with global attention, and fully fused localglobal models with encoders. Using seven diverse open-source datasets for benchmarking across regression and classification tasks, we systematically isolate the contributions of message passing, global attention, and encoder-based feature augmentation. Our study shows that encoder-augmented MPNNs form a robust baseline, while fused localglobal models yield the clearest benefits for properties governed by long-range interaction effects. We further quantify the accuracycompute trade-offs of attention, reporting its overhead in memory. Together, these results establish the first controlled evaluation of global attention in atomistic graph learning and provide a reproducible testbed for future model development.

Equivariant graph neural networks↗
DOE OSTI2025

Parallel Programming in MCNP6

Monte Carlo N-Particle (MCNP)1 is a general-purpose Monte Carlo particle transport code developed by Los Alamos National Laboratory (LANL). To efficiently handle long simulations, MCNP version 6 (MCNP6) supports parallel execution using two primary programming models: • Shared-memory task-based threading using OpenMP (Open Multi-Processing), and • Distributed-memory calculations using MPI (Message Passing Interface). The OpenMP and MPI programming models enable MCNP6 to scale from desktop systems to high-performance computing (HPC) clusters, allowing users to run MCNP in one of three parallel modes: • OpenMP-only, • MPI-only, and • Hybrid (MPI + OpenMP). The choice of parallelization mode depends on the underlying computer architecture and the characteristics of the simulation problem.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1978

Automatic radio-transmission monitor

System continuously monitors radio transmissions stored in memory. If spectrum deviates beyond present limits, alarm is tripped and spectrum is transferred to long-term storage for later analysis. Monitor can be useful in ensuring proper power level and spectral quality and in finding cause of failure. It might also be used to monitor radio-frequency interference or power levels of citizen's-band transmitters.

Bernstein, A. J.↗
NASA NTRS1992

Holographic data storage crystals for the LDEF

Lithium niobate is a significant electro-optic material, with potential applications in ultra high capacity storage and processing systems. Lithium niobate is the material of choice for many integrated optical devices and holographic mass memory systems. For crystals of lithium niobate were passively exposed to the space environment of the Long Duration Exposure Facility (LDEF). Three of these crystals contained volume holograms. Although the crystals suffered the surface damage characteristics of most of the other optical components on the Georgia Tech tray, the crystals were recovered intact. The holograms were severely degraded because of the lengthy exposure, but the bulk properties are being investigated to determine the spaceworthiness for space data storage and retrieval systems.

Callen, W. Russell↗
NASA NTRS1995

Nanoelectronics: Opportunities for future space applications

Further improvements in the performance of integrated electronics will eventually halt due to practical fundamental limits on our ability to downsize transistors and interconnect wiring. Avoiding these limits requires a revolutionary approach to switching device technology and computing architecture. Nanoelectronics, the technology of exploiting physics on the nanometer scale for computation and communication, attempts to avoid conventional limits by developing new approaches to switching, circuitry, and system integration. This presentation overviews the basic principles that operate on the nanometer scale that can be assembled into practical devices and circuits. Quantum resonant tunneling (RT) is used as the center-piece of the overview since RT devices already operate at high temperature (120 degrees C) and can be scaled, in principle, to a few nanometers in semiconductors. Near- and long-term applications of GaAs and silicon quantum devices are suggested for signal and information processing, memory, optoelectronics, and radio frequency (RF) communication.

Frazier, Gary↗
DOE OSTI2024

Collective dynamics and long-range order in thermal neuristor networks

Abstract In the pursuit of scalable and energy-efficient neuromorphic devices, recent research has unveiled a novel category of spiking oscillators, termed “thermal neuristors.” These devices function via thermal interactions among neighboring vanadium dioxide resistive memories, emulating biological neuronal behavior. Here, we show that the collective dynamical behavior of networks of these neurons showcases a rich phase structure, tunable by adjusting the thermal coupling and input voltage. Notably, we identify phases exhibiting long-range order that, however, does not arise from criticality, but rather from the time non-local response of the system. In addition, we show that these thermal neuristor arrays achieve high accuracy in image recognition and time series prediction through reservoir computing, without leveraging long-range order. Our findings highlight a crucial aspect of neuromorphic computing with possible implications on the functioning of the brain: criticality may not be necessary for the efficient performance of neuromorphic systems in certain computational tasks.

Science & Technology - Other Topics↗
DOE OSTI2025

Hybrid classical-quantum communication networks

Over the past several decades, the proliferation of global classical communication networks has transformed various facets of human society. Concurrently, quantum networking has emerged as a dynamic field of research, driven by its potential applications in distributed quantum computing, quantum sensor networks, and secure communications. This prompts a fundamental question: rather than constructing quantum networks from scratch, can we harness the widely available classical fiber-optic infrastructure to establish hybrid quantum–classical networks? This paper aims to provide a comprehensive review of ongoing research endeavors aimed at integrating quantum communication protocols, such as quantum key distribution, into existing lightwave networks. This approach offers the substantial advantage of reducing implementation costs by allowing classical and quantum communication protocols to share optical fibers, communication hardware, and other network control resources—arguably the most pragmatic solution in the near term. In the long run, classical communication will also reap the rewards of innovative quantum communication technologies, such as quantum memories and repeaters. Accordingly, our vision for the future of the Internet is that of heterogeneous communication networks thoughtfully designed for the seamless support of both classical and quantum communications.

Fiber-optic communication↗