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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 541 records · Page 30
All sourcesNASA NTRSDOE OSTI
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 OSTI2020

From a conventional ferromagnetism to a frustrated magnetism: An unexpected role of Fe in Nd(Al 1-x Fe x ) 2 (x ≤ 0.2)

The structure and magnetic properties of Nd(Al 1-x Fe x ) 2 alloys with x = 0, 0.05, 0.1 and 0.2, which adopt cubic MgCu 2 -type structure with space group Fd3¯m, are studied using x-ray powder diffraction, static and dynamic magnetization, and calorimetric measurements. The lattice constant decreases linearly with increasing Fe content from 8.0106(4) Å to 7.9044(4) Å. Large thermal irreversibilities between zero-field-cooled and field-cooled conditions are observed for all substituted samples. Here, the magnetic transition temperatures exhibit a minimum for x = 0.1, and coercive fields at 2 K increase from 70 Oe for x = 0 to 6.3 kOe for x = 0.2. The absence of λ-type peak in the heat capacity data, frequency dependence of ac magnetic susceptibility, and memory effects indicate formation of a cluster-glass magnetic state when x ≥ 0.1.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Logic in Memory Emulator

Logic in Memory Emulator (LiME) is a hardware/software tool specially designed for memory system evaluation and experiment. Emerging memories display a wide range of bandwidths, latencies, and capacities, making it challenging for the computer architect to navigate the design space of potential memory configurations, and for the application developer to assess performance implications of using such memories. With the LiME framework, architectural ideas can be prototyped in great detail yet with sufficient performance to support realistic evaluation on long running applications. LiME consists of two fundamental components: 1) the hardware and OS infrastructure for the emulator, and 2) a suite of benchmark applications to assist in characterizing the performance of current and future computer architectures. Some of the applications have been collected from other open source projects. Uses: Logging, replay and analysis of an application's memory behavior Evaluate impact of emerging memory technology on application performance. Emulate complex memory interactions in whole applications orders of magnitude faster than software simulation. Emulate acceleration hardware co-located with the memory subsystem. Features: Capture and log external memory accesses to a separate off-chip memory device without affecting application execution. Memory traces include the address, length, timestamp, and optionally the data for each transaction. Captured trace data can be saved to an SD card for off-line analysis. Configure a wide range of memory latencies in sub-nanosecond increments that encompass highbandwidth and storage class memories. Specify regions of interest (ROI) in applications to reduce the amount of trace data captured for analysis. Currently supports execution on Xilinx Zynq SoC which integrates an ARM processor with FPGA logic on a single device. Applications can be run under Linux or in bare metal mode on the ARM cores.

Jain, AbhishekK↗
DOE OSTI2021

The human aortic endothelium undergoes dose-dependent DNA methylation in response to transient hyperglycemia

Glycemic control is a strong predictor of long-term cardiovascular risk in patients with diabetes mellitus, and poor glycemic control influences long-term risk of cardiovascular disease even decades after optimal medical management. This phenomenon, termed glycemic memory, has been proposed to occur due to stable programs of cardiac and endothelial cell gene expression. This transcriptional remodeling has been shown to occur in the vascular endothelium through a yet undefined mechanism of cellular reprogramming.

60 APPLIED LIFE SCIENCES↗
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

Optical and microstructural characterization of Er 3+ doped epitaxial cerium oxide on silicon

Rare-earth ion dopants in solid-state hosts are ideal candidates for quantum communication technologies, such as quantum memories, due to the intrinsic spin–photon interface of the rare-earth ion combined with the integration methods available in the solid state. Erbium-doped cerium oxide (Er:CeO 2 ) is a particularly promising host material platform for such a quantum memory, as it combines the telecom-wavelength (~ 1.5 μm) 4f–4f transition of erbium, a predicted long electron spin coherence time when embedded in CeO 2 , and a small lattice mismatch with silicon. In this work, we report on the epitaxial growth of Er:CeO 2 thin films on silicon using molecular beam epitaxy, with controlled erbium concentration between 2 and 130 parts per million (ppm). We carry out a detailed microstructural study to verify the CeO 2 host structure and characterize the spin and optical properties of the embedded Er 3+ ions as a function of doping density. In as-grown Er:CeO 2 in the 2–3 ppm regime, we identify an EPR linewidth of 245(1) MHz, an optical inhomogeneous linewidth of 9.5(2) GHz, an optical excited state lifetime of 3.5(1) ms, and a spectral diffusion-limited homogeneous linewidth as narrow as 4.8(3) MHz. We test the annealing of Er:CeO 2 films up to 900 °C, which yields narrowing of the inhomogeneous linewidth by 20% and extension of the excited state lifetime by 40%.

36 MATERIALS SCIENCE↗
DOE OSTI2023

CrossLink: General Overview [Slides]

Problem: Traditional mesh generation approaches are labor intensive and have limited robustness when applied to parametric design exploration and optimization of complex geometries. While automatic mesh generation approaches exist, they tend to generate tetrahedral or mixed-hybrid meshes which are generally unsuitable for physics applications with strong shock waves, thin boundary layers, and strong gradients. In addition, simulations sizes in the billions of cells are becoming more common with traditional mesh generation methods quickly reaching scalability limits. Solution: CrossLink offers a topology-based mesh generation approach with unstructured block-filling methods and a scalable mesh generation engine. In addition, CrossLink incorporates a python-based API for seamless workflow integration and robust repeatability of the geometry handling and mesh generation process. This makes it ideal for parametric design study and optimization of complex geometries. Finally, future versions of CrossLink will offer a parametric mesh capability that optimizes a high-order mesh and enables reconstruction of the final mesh in memory by the physics solver.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

CrossLink: Advancements in Scalable Unstructured Mesh Generation [Slides]

Traditional mesh generation approaches are labor intensive and have limited robustness when applied to parametric design exploration and optimization of complex geometries. While automatic mesh generation approaches exist, they tend to generate tetrahedral or mixed-hybrid meshes which are generally unsuitable for physics applications with strong shock waves, thin boundary layers, and strong gradients. In addition, simulations sizes in the billions of cells are becoming more common with traditional mesh generation methods quickly reaching scalability limits. CrossLink offers a topology-based mesh generation approach with unstructured block-filling methods and a scalable mesh generation engine. In addition, CrossLink incorporates a python based API for seamless workflow integration and robust repeatability of the geometry handling and mesh generation process. This makes it ideal for parametric design study and optimization of complex geometries. Finally, future versions of CrossLink will offer a parametric mesh capability that optimizes a high-order mesh and enables reconstruction of the final mesh in memory by the physics solver.

97 MATHEMATICS AND COMPUTING↗
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↗