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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 685 records · Page 38
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

A parallel and performance portable implementation of a full-field crystal plasticity model

We have developed a parallel implementation of an Elasto-Viscoplastic Fast Fourier Transform-based (EVPFFT) micromechanical solver to enable computationally efficient crystal plasticity modeling for polycrystalline materials. Our primary focus lies in achieving performance portability, allowing a single EVPFFT implementation to run optimally on various homogeneous architectures, including multi-core Central Processing Units (CPUs), as well as on heterogeneous computer architectures comprising multi-core CPUs and Graphics Processing Units (GPUs) from different vendors. To accomplish this goal, we have leveraged MATAR, a C++ software library that simplifies the creation and utilization of multidimensional dense or sparse matrix and array data structures. These data structures are designed to be portable across diverse architectures through the use of Kokkos, a performance-portable library. Additionally, we have employed the Message Passing Interface (MPI) to efficiently distribute the computational workload among processors. The heFFTe (Highly Efficient FFT for Exascale) library is used to facilitate the performance portability of the fast Fourier transforms (FFTs) computation. The computational performance of EVPFFT is evaluated and presented in terms of parallel scalability and simulation runtime on different high-performance computing (HPC) architectures. As a result, the utility of the developed framework to efficiently simulate the micro-mechanical fields in polycrystalline microstructures in engineering applications is discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Pavement condition and climatic data in southeast Texas: A dataset for evaluating flood impacts on pavement performance

Effective pavement maintenance is essential for economic stability, optimal network performance, and roadway safety. Achieving this requires thorough evaluation of pavement conditions, including structural integrity, surface roughness, and distress characteristics. Pavement performance indicators play a critical role in influencing vehicle safety and ride quality. Recent advances have emphasized the use of data-driven modeling to anticipate pavement behavior, with the goal of optimizing resource allocation and refining Maintenance and Rehabilitation (M&R) strategies through accurate condition assessment. A foundational requirement for these modeling efforts is the availability of standardized, high-quality datasets that can support robust and reproducible infrastructure analysis. This data article presents a comprehensive dataset assembled to facilitate pavement performance prediction, with a geographic focus on Southeast Texas, particularly the flood-vulnerable area of Beaumont. The dataset encompasses pavement and traffic attributes, meteorological records, flood simulation outputs, ground deformation measurements, and topographic indices, enabling detailed examination of both load-associated and non-load-associated degradation mechanisms. Data preprocessing was performed using ArcGIS Pro, Microsoft Excel, and Python to ensure consistency and usability in data-driven modeling applications, including machine learning workflows. Key contributions of this dataset include its utility in analyzing the climatic and environmental factors affecting pavement conditions, identifying critical predictive features, and enabling in-depth correlation analysis across diverse variables. By filling existing gaps in input variable selection resources, this dataset supports the development of predictive tools for estimating future maintenance demand and enhancing the resilience of pavement networks in flood-impacted areas. The resource highlights the importance of standardized datasets for advancing pavement management practices and provides a robust foundation for ongoing infrastructure performance modeling.

42 ENGINEERING↗
DOE OSTI2025

Nature-inspired lotus-shaped fins combined with hybrid nanoparticles and metal foam for high-performance latent heat thermal energy storage

Latent heat thermal energy storage (LHTES) systems play a critical role in renewable energy integration by providing high energy density and nearly isothermal operation during phase transitions. However, their performance is often limited by slow melting/charging rates, which motivates the search for enhanced heat transfer designs. This study investigates the melting behavior of RT-82 phase change material (PCM) using novel lotus-shaped fins combined with copper metal foam and conductive graphene nanoparticles and carbon nanotubes. A two-dimensional enthalpy-porosity model in ANSYS Fluent was developed to simulate the charging/melting process, capturing non-thermal equilibrium between the foam and PCM/nano-PCM. In this study, effects of fin geometry, nanoparticle concentration, and foam porosity on melting dynamics and cost-performance trade-offs were investigated. Results showed that natural convection accelerated melting by ~12% compared to conduction-only scenarios. Optimized lotus-shaped fins with higher fin density (T3F4 and T3F10) achieved up to 63% faster melting relative to sparse configurations. Graphene nanoparticles improved thermal conductivity, with a 6% volume fraction, by reducing melting time by ~6.9%, while their combination with 75% porosity foam achieved a maximum reduction in the melting time of ~51% compared to pure PCM. Cost-performance analysis identified T3F4 as the most balanced design, offering rapid thermal response without excessive material costs, while moderate-density designs like T3S6 provided economical alternatives with acceptable performance. These results highlight the performance enhancement that can be achieved by integrating bio-inspired fins, nanoparticles, and foams, into compact and efficient LHTES for solar heating, building thermal management, and industrial waste-heat recovery applications.

25 ENERGY STORAGE↗
DOE OSTI2024

Impact of anisotropy on TRISO fuel performance

Manufacturing of tristructural isotropic (TRISO) particles involves the deposition of pyrolytic carbon (PyC) and silicon carbide (SiC) layers using the fluidized bed chemical vapor deposition (CVD) process. The CVD process is known to generate polycrystalline layers with crystallographic textures, which imparts anisotropic thermophysical properties to the layers. Past studies have shown the risk for particle failure increases with an increase in anisotropy. The limit beyond which the anisotropy of PyC layers becomes unacceptable due to failure risk has been identified as a high-priority knowledge gap. This work presents a first systematic study on the effects of anisotropic thermal and mechanical properties on TRISO fuel performance. This computational study, performed using the fuel performance code BISON, investigates how the anisotropy in elasticity and thermal properties affect the stresses, temperature, and failure of a TRISO particle. The influence of other factors, such as operating temperature and particle geometry on the anisotropy effects, also has been analyzed. The studies utilize the recently published anisotropic elasticity and thermal behavior models for TRISO PyC and SiC layers implemented using tensors with full anisotropic capability. The spherical TRISO particles with anisotropic properties were found to have greater maximum tensile stress and significantly higher failure probability than the spherical particles with isotropic properties. In conclusion, the fuel performance predicted using these recently developed models was found to be comparable with the performance obtained using the historical models.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

BISON analyses of TRISO fuel performance, its dependence on time-at-temperature, and possible implications for fuel design and qualification

The Advanced Gas Reactor Fuel Development and Qualification (AGR) program has established a substantial technical foundation to support private entry into the U.S. high-temperature gas-cooled reactor market. However, emerging tristructural isotropic (TRISO)-fueled reactor applications include small modular reactors and microreactors with longer fuel residence times, which may expose fuels to higher time-at-temperature (TAT) values than were explored by the AGR program. Increased TAT could affect diffusive and thermomechanical behaviors such as Pd penetration, fission gas release, creep, and fission product transport. In this work, we applied multiscale best-estimate BISON fuel performance modeling to assess these effects within a representative design space based on the AGR-5/6/7 experiment and analyzed trends in predicted particle and compact fuel performance metrics with possible implications for near-term fuel design and qualification. BISON unambiguously predicted that TRISO fuel performance is sensitive to TAT. Increasing TAT was not predicted to increase the magnitude of failure-inducing tangential stresses in particle coating layers. Predictions obtained using a mechanistic model for Pd penetration indicated that penetration depth does not depend strongly on TAT. While these observations suggest that AGR testing provides a conservative upper bound for the steady-state operation of TRISO particles at lower powers and higher residence times, BISON also predicted that the release of poorly retained Ag would increase with TAT. Because these analyses applied models to extrapolate beyond the available experimental data, the authors recommend performing targeted experiments to confirm these predictions. Nevertheless, these predictions may provide reactor developers with enough confidence to make near-term design decisions associated with the potential fuel performance trade-offs of increasing TAT.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Identifying the Role of Magnesium Content in Assessing the Electrochemical Performance of (CoCuMgNiZn)O

High-entropy oxides (HEOs) featuring 5 or more metals in approximately equimolar ratios, such as the prototypical rock-salt-structured (CoCuMgNiZn)O, have attracted interest for their potential to display material properties superior to oxides with combinations of 4 or fewer of the component metals. In particular, (CoCuMgNiZn)O has shown promise as an anode for lithium-ion batteries with a high specific capacity retention over extended cycling. Previous studies have suggested that magnesium, despite being electrochemically inert, provides a crucial contribution to the favorable performance of this HEO by stabilizing the crystal structure through repeated charge–discharge cycles. This paper probes the extent and mechanism of the magnesium effect by using a facile microwave-assisted hydrothermal synthesis method to vary the level of Mg content. Moreover, we extensively characterized the product with techniques such as 4D-STEM and ICP-OES, which have not previously been applied in combination with this material, in order to elucidate the relationships among chemical composition, nanostructure, and performance. Here, we show that the level of Mg incorporation is positively correlated with long-term stability and negatively correlated with rate capacity, and that the latter effect yields a stronger influence upon the overall performance, with the best-performing sample possessing a Mg quantity equivalent to ∼1/5 that of an equimolar concentration. This finding demonstrates not only that the variation of individual elemental levels offers a promising and relatively unexplored avenue to optimize the electrochemical performance of HEO materials but also that it should not be assumed that equimolar compositions of constituent elements are necessarily the best.

36 MATERIALS SCIENCE↗
DOE OSTI2026

A Feasibility Study on the Integration of Human Performance Data From Diverse Sources Based on the Complexity of a Proceduralized Task

Securing the safety of socio-technical systems including nuclear facilities is the upmost goal to ensure their sustainability because historical records demonstrate that the performance degradation of human operators (e.g., human errors) is one of the crucial contributors to the occurrence of unexpected events resulting in extensive casualties and financial losses. This implies that the collection of human performance data in diverse conditions with which they could be faced during the operation of nuclear facilities. As this collection requires significant resources, it is necessary to resolve how to accomplish it with limited resources. To address this challenge, as suggested in the SHEEP framework, it is indispensable to extract valuable insights after integrating various kinds of human performance data obtained from different sources. However, a practical method to soundly integrate them seems to be still incomplete. Accordingly, the applicability of TACOM (Task Complexity) measure is investigated as a tool to identify useful information based on the integration of human performance data observed from different simulation conditions. As a result, it is expected that the TACOM measure would play an important role in addressing the technical challenge in securing human performance data.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2026

Performance-Aligned LLMs for Generating Fast HPC Code

Optimizing scientific software is a difficult task because codebases are often large and complex, and performance can depend upon several factors including the algorithm, its implementation, and hardware among others. Causes of poor performance can originate from disparate sources and be difficult to diagnose. Recent years have seen a multitude of work that use large language models (LLMs) to assist in software development tasks. However, these tools are trained to model the distribution of code as text, and are not specifically designed to understand performance aspects of code. In this work, we introduce a reinforcement learning based methodology to align the outputs of code LLMs with performance. This allows us to build upon the current code modeling capabilities of LLMs and extend them to generate better performing code. Here, we demonstrate that our fine-tuned model improves the expected speedup of generated code over base models for a set of benchmark tasks from 0.9 to 1.6 for serial code and 1.9 to 4.5 for OpenMP parallel code.

Computer science↗
DOE OSTI2024

Evaluating Operators in Deep Neural Networks for Improving Performance Portability of SYCL

SYCL is a portable programming model for heterogeneous computing, so it is important to obtain reasonable performance portability of SYCL. Towards the goal of better understanding and improving performance portability of SYCL for machine learning workloads, we have been developing benchmarks for basic operators in deep neural networks (DNNs). These operators could be offloaded to heterogeneous computing devices such as graphics processing units (GPUs) to speed up computation. In this work, we introduce the benchmarks, evaluate the performance of the operators on GPU-based systems, and describe the causes of the performance gap between the SYCL and Compute Unified Device Architecture (CUDA) kernels. We find that the causes are related to the utilization of the texture cache for read-only data, optimization of the memory accesses with strength reduction, shared local memory accesses, and register usage per thread. We hope that the efforts of developing benchmarks for studying performance portability will stimulate discussion and interactions within the community.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Enhanced Component Performance Study: Emergency Diesel Generators 1998-2024

This report presents an enhanced performance evaluation of the emergency power system (EPS) and high-pressure core spray (HPCS) emergency diesel generators (EDGs) at U.S. commercial nuclear power plants. This report evaluates component performance over time using (1) Institute of Nuclear Power Operations (INPO) Industry Reporting and Information System (IRIS) data from 1998 through 2024 and (2) maintenance unavailability performance data from Mitigating Systems Performance Index (MSPI) Basis Document data from 2002 through 2024. The objective is to show estimates of current failure probabilities and rates related to EDGs, trend these data on an annual basis, determine if the current data are consistent with the probability distributions currently recommended for use in Nuclear Regulatory Commission (NRC) probabilistic risk assessments, show how the reliability data differ for different EDG manufacturers and for EDGs with different ratings; and summarize the subcomponents, causes, detection methods, and recovery associated with each EDG failure mode. The EDG failure modes considered are fail to start (FTS), fail to load and run (FTLR), and fail to run after one hour of operation (FTR>1H). Engineering analyses were performed with respect to time-period and failure mode without regard to the actual number of EDGs at each plant. The factors analyzed include subcomponent, failure cause, detection method, recovery, manufacturer, and EDG rating. The following increasing trends were identified for EDGs for the most recent 10-year period: • EPS and HPCS EDG frequency of start demands (demands per reactor year) • EPS and HPCS EDG frequency of FTLR demands • EPS and HPCS EDG frequency of run>1H hours. The following decreasing trends were identified for EDGs for the most recent 10-year period: • EPS EDG FTR>1H failure rate • EPS EDG unreliability • EPS and HPCS EDG frequency of FTR>1H events (failures per reactor year).

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

On a Simplified Approach to Achieve Parallel Performance and Portability Across CPU and GPU Architectures

This paper presents software advances to easily exploit computer architectures consisting of a multi-core CPU and CPU+GPU to accelerate diverse types of high-performance computing (HPC) applications using a single code implementation. The paper describes and demonstrates the performance of the open-source C++ matrix and array (MATAR) library that uniquely offers: (1) a straightforward syntax for programming productivity, (2) usable data structures for data-oriented programming (DOP) for performance, and (3) a simple interface to the open-source C++ Kokkos library for portability and memory management across CPUs and GPUs. The portability across architectures with a single code implementation is achieved by automatically switching between diverse fine-grained parallelism backends (e.g., CUDA, HIP, OpenMP, pthreads, etc.) at compile time. The MATAR library solves many longstanding challenges associated with easily writing software that can run in parallel on any computer architecture. This work benefits projects seeking to write new C++ codes while also addressing the challenges of quickly making existing Fortran codes performant and portable over modern computer architectures with minimal syntactical changes from Fortran to C++. We demonstrate the feasibility of readily writing new C++ codes and modernizing existing codes with MATAR to be performant, parallel, and portable across diverse computer architectures.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1993

Performance and mood-state parameters during 30-day 6 degrees head-down bed rest with exercise training

The study was designed to determine if performance and mood impairments occur in bed-rested subjects, and if different exercise-training regimens modify or prevent them. Eighteen normal, healthy men were divided on the basis of age, peak oxygen uptake, and maximal isometric knee extension strength into three similar groups: no exercise (NOE), isotonic exercise (ITE), and isokinetic exercise (IKE). A 15-min battery of 10 performance tests and 8 mood and 2 sleep scales were administered daily during ambulatory control, 30 d of absolute bed rest (BR), and 4 d of ambulatory recovery. Performance test proficiency increased (p < 0.05) for all three groups during BR in 7 of 10 tests and there were no consistent significant differences between the three groups. However, during BR, the ITE group was distinguished from the other groups by a decline (p < 0.05) in the activation mood dimension and in two of its constituent scales (motivation and concentration), and by improvement (p < 0.05) in the trouble-falling-asleep and psychological-tension scales. Since few deleterious changes in performance and mood occurred in the three groups and did not exceed baseline ambulatory levels, we conclude that mood and performance did not deteriorate in response to prolonged BR and were not altered by exercise training. However, the decline in activation mood scales in the ITE group may reflect overtraining or excess total workload in this group.

NASA Center ARC↗
NASA NTRS2003

Effects of a psychophysiological system for adaptive automation on performance, workload, and the event-related potential P300 component

The present study examined the effects of an electroencephalographic- (EEG-) based system for adaptive automation on tracking performance and workload. In addition, event-related potentials (ERPs) to a secondary task were derived to determine whether they would provide an additional degree of workload specificity. Participants were run in an adaptive automation condition, in which the system switched between manual and automatic task modes based on the value of each individual's own EEG engagement index; a yoked control condition; or another control group, in which task mode switches followed a random pattern. Adaptive automation improved performance and resulted in lower levels of workload. Further, the P300 component of the ERP paralleled the sensitivity to task demands of the performance and subjective measures across conditions. These results indicate that it is possible to improve performance with a psychophysiological adaptive automation system and that ERPs may provide an alternative means for distinguishing among levels of cognitive task demand in such systems. Actual or potential applications of this research include improved methods for assessing operator workload and performance.

Task Performance and Analysis↗
NASA NTRS2005

Circadian rhythms, sleep, and performance in space

Maintaining optimal alertness and neurobehavioral functioning during space operations is critical to enable the National Aeronautics and Space Administration's (NASA's) vision "to extend humanity's reach to the Moon, Mars and beyond" to become a reality. Field data have demonstrated that sleep times and performance of crewmembers can be compromised by extended duty days, irregular work schedules, high workload, and varying environmental factors. This paper documents evidence of significant sleep loss and disruption of circadian rhythms in astronauts and associated performance decrements during several space missions, which demonstrates the need to develop effective countermeasures. Both sleep and circadian disruptions have been identified in the Behavioral Health and Performance (BH&P) area and the Advanced Human Support Technology (AHST) area of NASA's Bioastronautics Critical Path Roadmap. Such disruptions could have serious consequences on the effectiveness, health, and safety of astronaut crews, thus reducing the safety margin and increasing the chances of an accident or incident. These decrements oftentimes can be difficult to detect and counter effectively in restrictive operational environments. NASA is focusing research on the development of optimal sleep/wake schedules and countermeasure timing and application to help mitigate the cumulative effects of sleep and circadian disruption and enhance operational performance. Investing research in humans is one of NASA's building blocks that will allow for both short- and long-duration space missions and help NASA in developing approaches to manage and overcome the human limitations of space travel. In addition to reviewing the current state of knowledge concerning sleep and circadian disruptions during space operations, this paper provides an overview of NASA's broad research goals. Also, NASA-funded research, designed to evaluate the relationships between sleep quality, circadian rhythm stability, and performance proficiency in both ground-based simulations and space mission studies, as described in the 2003 NASA Task Book, will be reviewed.

Review↗
NASA NTRS2007

A Covariance Analysis Tool for Assessing Fundamental Limits of SIM Pointing Performance

This paper presents a performance analysis of the instrument pointing control system for NASA's Space Interferometer Mission (SIM). SIM has a complex pointing system that uses a fast steering mirror in combination with a multirate control architecture to blend feed forward information with feedback information. A pointing covariance analysis tool (PCAT) is developed specifically to analyze systems with such complexity. The development of PCAT as a mathematical tool for covariance analysis is outlined in the paper. PCAT is then applied to studying performance of SIM's science pointing system. The analysis reveals and clearly delineates a fundamental limit that exists for SIM pointing performance. The limit is especially stringent for dim star targets. Discussion of the nature of the performance limit is provided, and methods are suggested to potentially improve pointing performance.

pointing control↗
NASA NTRS2013

Performance Measurement of Advanced Stirling Convertors (ASC-E3)

NASA Glenn Research Center (GRC) has been supporting development of the Advanced Stirling Radioisotope Generator (ASRG) since 2006. A key element of the ASRG project is providing life, reliability, and performance testing data of the Advanced Stirling Convertor (ASC). The latest version of the ASC (ASC-E3, to represent the third cycle of engineering model test hardware) is of a design identical to the forthcoming flight convertors. For this generation of hardware, a joint Sunpower and GRC effort was initiated to improve and standardize the test support hardware. After this effort was completed, the first pair of ASC-E3 units was produced by Sunpower and then delivered to GRC in December 2012. GRC has begun operation of these units. This process included performance verification, which examined the data from various tests to validate the convertor performance to the product specification. Other tests included detailed performance mapping that encompassed the wide range of operating conditions that will exist during a mission. These convertors were then transferred to Lockheed Martin for controller checkout testing. The results of this latest convertor performance verification activity are summarized here.

Stirling Cycle↗
NASA NTRS2016

Wind Tunnel and Hover Performance Test Results for Multicopter UAS Vehicles

There is currently a lack of published data for the performance of multicopter unmanned aircraft system (UAS) vehicles, such as quadcopters and octocopters, often referred to collectively as drones. With the rapidly increasing popularity of multicopter UAS, there is interest in better characterizing the performance of this type of aircraft. By studying the performance of currently available vehicles, it will be possible to develop models for vehicles at this scale that can accurately predict performance and model trajectories. This paper describes a wind tunnel test that was recently performed in the U.S. Army's 7- by 10-ft Wind Tunnel at NASA Ames Research Center. During this wind tunnel entry, five multicopter UAS vehicles were tested to determine forces and moments as well as electrical power as a function of wind speed, rotor speed, and vehicle attitude. The test is described here in detail, and a selection of the key results from the test is presented.

Multicopter UAS↗
NASA NTRS2016

NAS-Wide Fast-Time Simulation Study for Evaluating Performance of UAS Detect-and-Avoid Alerting and Guidance Systems

This presentation contains the analysis results of NAS-wide fast-time simulations with UAS and VFR traffic for a single day for evaluating the performance of Detect-and-Avoid (DAA) alerting and guidance systems. This purpose of this study was to help refine and validate MOPS alerting and guidance requirements. In this study, we generated plots of all performance metrics that are specified by RTCA SC-228 Minimum Operational Performance Standards (MOPS): 1) to evaluate the sensitivity of alerting parameters on the performance metrics of each DAA alert type: Preventive, Corrective, and Warning alerts and 2) to evaluate the effect of sensor uncertainty on DAA alerting and guidance performance.

DAA Alerting Performance↗