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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

THE BRAKING INDEX OF A RADIO-QUIET GAMMA-RAY PULSAR

We report the discovery and timing measurements of PSR J1208−6238, a young and highly magnetized gamma-ray pulsar, with a spin period of 440 ms. The pulsar was discovered in gamma-ray photon data from the Fermi Large Area Telescope (LAT) during a blind-search survey of unidentified LAT sources, running on the distributed volunteer computing system Einstein@Home . No radio pulsations were detected in dedicated follow-up searches with the Parkes radio telescope, with a flux density upper limit at 1369 MHz of 30 μ Jy. By timing this pulsar’s gamma-ray pulsations, we measure its braking index over five years of LAT observations to be n = 2.598 ± 0.001 ± 0.1, where the first uncertainty is statistical and the second estimates the bias due to timing noise. Assuming its braking index has been similar since birth, the pulsar has an estimated age of around 2700 years, making it the youngest pulsar to be found in a blind search of gamma-ray data and the youngest known radio-quiet gamma-ray pulsar. Despite its young age, the pulsar is not associated with any known supernova remnant or pulsar wind nebula. The pulsar’s inferred dipolar surface magnetic field strength is 3.8 × 10{sup 13} G, almost 90% of the quantum-critical level. We investigate some potential physical causes of the braking index deviating from the simple dipole model but find that LAT data covering a longer time interval will be necessary to distinguish between these.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Distributed heterogeneous compute infrastructure for the study of additive manufacturing systems

We present the current status of a large-scale computing framework to address the need of the multidisciplinary effort to study chemical dynamics. Specifically, we are enabling scientists to process and store experimental data, run large-scale computationally expensive high-fidelity physical simulation, and analyze these results using the state-of-the-art data analytics tools, machine learning, and uncertainty quantification methods using heterogeneous computing resources, such as CPU and GPU cluster. The framework can integrate or abstract out multiple domains based on roles. In order to develop this framework, we have leveraged an existing framework coupled with in-house heterogeneous computing resources. We present the results of using this framework on a single metadata triggered workflow to accelerate an additive manufacturing use case.

heterogeneous computing, hpc, workflows, reproduci↗
DOE OSTI2024

RuralAI in Tomato Farming: Integrated Sensor System, Distributed Computing, and Hierarchical Federated Learning for Crop Health Monitoring

Precision horticulture is evolving due to scalable sensor deployment and machine learning (ML) integration. These advancements boost the operational efficiency of individual farms, balancing the benefits of analytics with autonomy requirements. However, given concerns that affect wide geographic regions (e.g., climate change), there is a need to apply models that span farms. Federated learning (FL) has emerged as a potential solution. FL enables decentralized ML across different farms without sharing private data. Traditional FL assumes simple two-tier network topologies and, thus, falls short of operating on more complex networks found in real-world agricultural scenarios. Networks vary across crops and farms and encompass various sensor data modes, extending across jurisdictions. New hierarchical FL (HFL) approaches are needed for more efficient and context-sensitive model sharing, accommodating regulations across multiple jurisdictions. Here, we present the RuralAI architecture deployment for tomato crop monitoring, featuring sensor field units for soil, crop, and weather data collection. HFL with personalization is used to offer localized and adaptive insights. Model management, aggregation, and transfers are facilitated via a flexible approach, enabling seamless communication between local devices, edge nodes, and the cloud.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

An Integrated Framework for Memory-Centric Analysis: From Trace Collection to Co-Design

The memory wall phenomenon—where advances in processor performance significantly outpace those in memory subsystems—poses a fundamental challenge for contemporary computing systems. In memory-bound applications, memory subsystem behavior dominates performance, yet existing analysis approaches present significant limitations: detailed microarchitectural simulators require days to weeks to simulate modest workloads; hardware performance counters provide only aggregate statistics that obscure temporal and spatial access patterns; and scaled simulation approaches face challenges in capturing certain behaviors that emerge at larger scales. These limitations reflect a processor-centric design philosophy increasingly misaligned with memory-bound workloads where detailed understanding of memory access patterns, cache hierarchy interactions, and contention is critical for effective optimization. This paper presents an integrated framework for memory-centric analysis that enables effective hardware-software co-design. We describe practical trace collection techniques, including hardware-assisted processor tracing with minimal overhead and portable software-based instrumentation with statistical sampling. We present multi-perspective analysis methods that examine memory behavior from temporal, sequential, spatial, and relational viewpoints, revealing distinct optimization opportunities invisible in aggregate metrics. We detail an architectural modeling framework that uses sampled traces with temporal interpolation and confidence-based filtering to evaluate cache and memory configurations. Evaluation on representative benchmarks demonstrates that this framework achieves practical accuracy (L2 cache errors of 2.64\%, confidence-filtered L3 errors of 9.92\%, bandwidth errors of 7.33\%) while providing substantial speedup (26.8×) over cycle-accurate simulation, enabling rapid design space exploration. We demonstrate how this integrated framework enables systematic identification of both hardware optimizations (memory controller tuning, bank partitioning, NUMA configuration) and software optimizations (data layout restructuring, prefetching strategies, memory-aware scheduling). Through this comprehensive treatment of the memory-centric analysis pipeline—from trace collection through architectural modeling to co-design application—we provide researchers and practitioners with practical techniques for addressing memory bottlenecks in contemporary computing systems.

Gajaria, Dhruv Mayur↗
DOE OSTI2023

MrHyDE v.1.0

SAND2024-01324O MrHyDE, which stands for Multi-resolution Hybridized Differential Equations, is a general-purpose C++ package for the solution of coupled multiphysics and multiscale systems on massively parallel computing systems. MrHyDE is designed to enable moving beyond forward simulation for multiscale applications which includes optimization, control, uncertainty quantification, and stochastic inversion. The framework provides interfaces to several packages within the Trilinos framework and leverages automatic differentiation to enable adjoint capabilities for large-scale, gradient-based optimization. MrHyDE provides automated multiscale capabilities through a subgrid model interface and multiscale Dirichlet-to-Neumann maps. For extreme-scale applications, MrHyDE provides in situ data-compression algorithms to reduce memory requirements while maintaining performance. MrHyDE is a general-purpose, computational framework for the solution of multiscale and multiphysics applications. It uses a combination of structure-preserving, physics-compatible discretizations, fully implicit methods, multi-resolution schemes, or fully explicit methods. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

SciDAC↗
DOE OSTI2026

Electron–electrophile coupled dinitrogen reduction in a cerium– meta -tetraphenolate system: a computational study

The use of lanthanide complexes for catalytic dinitrogen reduction is a new development in homogeneous catalysis. Density functional theory calculations on our recently reported cerium phenolate catalyst [K 2 Ce 2 (sol) 4 (mTP) 2 ] (mTP = {(OC 6 H 2 - 2- t Bu-4-Me) 2 CH} 2 - 1,3-C 6 H 4 ; sol = OMe 2 here; THF in the experiment) have been undertaken to elucidate the reduction, activation and silylation steps at the bound dinitrogen molecule, in the presence of the reductant, potassium metal (K 0 ) and the electrophile Me 3 SiCl (TMSCl). Out of the total of six electron reductions required to cleave the N 2 , the first two-electron reduction step was found to be highly disfavoured unless potassium cations (K + ) are included, upon which the step is rendered strongly exergonic; N–Si bond formation at the two-electron stage is predicted to be unfavourable. The three-electron-reduced N 2 -adduct is found to be at the reductive activation limit in the absence of added electrophiles, which can form N-element bonds and lower the overall charge. Added electron density beyond three-electron reduction no longer localises on N 2 , preventing formal N 2 4− formation. A pathway in which both K 0 and Me 3 SiCl work in concert was modelled, and six sequential reduction–silylation steps were calculated, showing how the N–N bond is cleaved after the third reduction, eventually releasing two equivalents of N(SiMe 3 ) 3 , and regenerating the starting complex with the highest barrier of any step being 22 kcal mol −1 . We establish alkali metal coordination and coupled electron–electrophile transfer as key factors in the design of rare-earth-mediated dinitrogen functionalisation.

Ahmad, Shahbaz [Univ. of Manchester (United Kingdo↗
DOE OSTI2023

zPerf: A Statistical Gray-Box Approach to Performance Modeling and Extrapolation for Scientific Lossy Compression

With the scaling up of simulation-based scientific discovery on high-performance computing systems, the disparity between compute and I/O has increased, forcing domain scientists to save only a small amount of simulation data to persistent storage. This can result in the loss of essential physics fields that are needed for data analysis. While error-bounded lossy compression has made tremendous progress in bridging the gap between compute and I/O, the lack of understanding of compression performance remains a key hurdle to its wide adoption. Here, in this work, we present zPerf, a statistical gray-box performance modeling approach for scientific lossy compression. Our contributions are threefold: 1) We develop zPerf to estimate the performance of lossy compression techniques, based on in-depth understanding and statistical modeling for data features and core compression metrics; 2) We demonstrate the in-detailed implementation of zPerf using two case studies, where we derive the performance modeling for SZ and ZFP, two leading lossy compressors; 3) We evaluate the effectiveness of zPerf on real-world datasets across various domains. Based on the evaluation, we demonstrate the efficacy of the zPerf performance model; 4) We further discuss three case studies where zPerf is applied to extrapolate the compression ratio of SZ and ZFP with alternative encoding schemes as well as ZFP with an alternative transform scheme. Through the case studies, we demonstrate the potential of zPerf for exploring the design space of lossy compression, which has hardly been studied in the literature.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Miniature, mobile X-ray computed radiography system

A miniature, portable x-ray system may be configured to scan images stored on a phosphor. A flash circuit may be configured to project red light onto a phosphor and receive blue light from the phosphor. A digital monochrome camera may be configured to receive the blue light to capture an article near the phosphor.

36 MATERIALS SCIENCE↗