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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Beyond Price-Taker: Multiscale Optimization of Wind and Battery Integrated Energy Systems

Integrating renewable energy into the electric grid is challenging due to the intermittency and variability of wind and other non-dispatchable resources. Integrated energy systems (IESs) combine multiple energy technologies (e.g., fossil, nuclear, renewables, storage) to reduce costs and improve flexibility and reliability. However, standard techno-economic analysis (TEA) methods often overestimate the benefits of IESs because they fail to account for energy market adjustments. This paper systematically studies the limitations of the prevailing price-taker assumption for TEA and optimization of hybrid energy systems. As an illustrative case study, we retrofit an existing wind farm in the RTS-GMLC test system (which loosely mimics the Southwest U.S.) with battery energy storage to form an IES. We show that the standard price-taker model overestimates the electricity revenue and the net present value (NPV) of the IES up to 178% and 30.4%, respectively, compared to our more rigorous multiscale optimization. These differences arise because introducing storage creates a more flexible resource that impacts the larger wholesale electricity market. Moreover, this work highlights the impact of the IES has on the market via various strategic bidding, and underscores the importance of moving beyond price-taker for optimal storage sizing and TEA of IESs. We conclude by discussing opportunities to generalize the proposed framework to other IESs, and highlight emerging research questions regarding the complex interactions between IESs and markets.

25 ENERGY STORAGE↗
DOE OSTI2026

Improvement of Drop‐Hammer Impact Testing for Safety Assessment of High Explosives Using 10‐mg Samples

Here, in this study, we established an improved method for drop-hammer impact testing of small quantities of high explosives (10 mg). We performed about seven hundred impact tests under various experimental conditions (e.g., sandpaper vs bare anvil, different sample masses, drop-weights, and striker diameters) to determine an optimal set of conditions and reaction detection methods (e.g., gas analysis, video, and sound recordings) that give the most statistically reliable results with 10 mg samples. We used both Frequentist and Bayesian statistical approaches to compare estimates of the drop height (DH50) that initiates a reaction 50% of the time, and to quantify the associated uncertainty. Gas analysis proved to be the most reliable reaction detection method, showing unambiguous rises in HE decomposition products (e.g., CO 2 ) even when the other indicators (e.g., sound, video) were inconclusive. The impact tests performed with a bare anvil showed much better reproducibility than those conducted with sandpaper, reducing the largest uncertainty observed in the data sets by a factor of 1.7. The DH 50 values obtained from three different sample masses (10, 20, and 35 mg) fell within the uncertainties of the measurements. We demonstrated the improved procedure (i.e., 10-mg samples, gas analysis, bare anvil, and Bayesian approach) on a variety of PETN samples having different surface areas and thermal histories.

PETN↗
DOE OSTI2024

An Evaluation of The Dynamic Physical Security Risk Assessment Methodology for Fleet-Wide Applications

The requirements for U.S. nuclear power plants to maintain a large onsite physical security force contribute to their high operational costs. The cost of maintaining the current physical security posture is approximately 10% of the overall operation and maintenance budget for commercial nuclear power plants. The goal of the Light Water Reactor Sustainability (LWRS) program’s physical security pathway is to develop tools, methods, and technologies and provide the technical basis for an optimized physical security posture. The conservatisms built into current security postures may be analyzed and minimized to reduce security costs while still ensuring adequate security and operational safety. The research performed at Idaho National Laboratory within LWRS program’s physical security pathway has successfully developed a dynamic force-on-force modeling framework using various computer simulation tools and integrating them with the dynamic assessment Event Modeling Risk Assessment using Linked Diagrams (EMRALD) tool. This integrated process for physical security analysis is named Modeling and Analysis for Safety Security using Dynamic EMRALD Framework (MASS-DEF). This document provides an update on the progress in applying the MASS-DEF process to an operating commercial nuclear power plant as well as additional industry feedback regarding use of the tool for other physical security risk-informed topics. This report is only a summary of the progress and does not contain specific modeling results as those contain sensitive security information. Previous reports described how a user could integrate their plant-specific force-on-force models with the dynamic simulation tool EMRALD, model operator actions, and integrate with probabilistic risk assessment tools, such as CAFTA (Computer Aided Fault Tree Analysis System) or SAPHIRE (Systems Analysis Programs for Hands-on Integrated Reliability Evaluations), and with thermal-hydraulic tools, such as RELAP-5 or MAAP. Previous reports applied various combinations of available simulations codes with EMRALD using generic plant models to demonstrate how to perform the analysis. This report is an update the progress of applying the dynamic computational framework to an actual nuclear facility using their security scenarios and timelines. This report also provides an update to the procedural guidance for the MASS-DEF process and an overview of the generic models available for use by utilities. This report does not contain any plant’s sensitive information and/or safeguards information. This study’s purpose was to verify that the results achieved using generic models are similar to actual plant results and refine our guidance on the use of the framework. This assessment enables further analysis, such as what-if scenarios and staff-reduction evaluation, thereby optimizing physical security at plants.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS1997

IV and V Issues in Achieving High Reliability and Safety in Critical Control System Software

Risk analysis and integrated verification and validation are two important elements in a plan for ensuring the safety of critical software systems. We describe an approach we are currently developing for integrating risk analysis, and metrics analysis, and propose a fault predictor that would integrate the results of these activities. Practical difficulties associated with our approach are also discussed, as are limitations of the proposed predictor. We conclude with a discussion of what as been learned to date, and with suggestions for future work.

validation software reliability software risk asse↗
NASA NTRS1984

Evaluation methodologies for an advanced information processing system

The system concept and requirements for an Advanced Information Processing System (AIPS) are briefly described, but the emphasis of this paper is on the evaluation methodologies being developed and utilized in the AIPS program. The evaluation tasks include hardware reliability, maintainability and availability, software reliability, performance, and performability. Hardware RMA and software reliability are addressed with Markov modeling techniques. The performance analysis for AIPS is based on queueing theory. Performability is a measure of merit which combines system reliability and performance measures. The probability laws of the performance measures are obtained from the Markov reliability models. Scalar functions of this law such as the mean and variance provide measures of merit in the AIPS performability evaluations.

Schabowsky, R. S., Jr.↗
NASA NTRS2009

Stirling Convertor Extended Operation Testing and Data Analysis at GRC

This paper focuses on extended operation testing and data analysis of free-piston Stirling convertors at the NASA Glenn Research Center (GRC). Extended operation testing is essential to the development of radioisotope power systems and their potential use for long duration missions. To document the reliability of the convertors, regular monitoring and analysis of the extended operation data is particularly valuable; allowing us to better understand and quantity the long life characteristics of the convertors. Further, investigation and comparison of the extended operation data to baseline performance data provides us an opportunity for understanding system behavior should any off-nominal performance occur. GRC currently has 14 Stirling convertors under 24-hour unattended extended operation testing, including two operating the Advanced Stirling Radioisotope Generator Engineering Unit (ASRG-EU). 10 of the 14 Stirling convertors at GRC are the Advanced Stirling Convertors (ASC) developed by Sunpower, Incorporated. These are highly efficient (up to > 33.5% conversion efficiency), low mass convertors that have evolved through technologically progressive convertor builds. The remaining four convertors at GRC are Technology Demonstration Convertors (TDC) from Infinia Corporation. They have achieved> 27% conversion efficiency and have accumulated over 178,000 of the total 250,622 hours of extended operation currently at GRC. A synopsis of the Stirling convertor extended operation testing and data analysis at NASA GRC is presented in this paper, as well as how this testing has contributed to the Stirling convertor's progression toward flight.

Cornell, Peggy A.↗
DOE OSTI2025

Transforming Energy Through Computational Excellence: A View From NREL

At the National Renewable Energy Laboratory (NREL)—a U.S. Department of Energy laboratory—computational science, high-performance computing, applied mathematics, advanced computer science, visualization, and data play a pivotal role in advancing energy abundance, affordability, security, and reliability. From fundamental scientifc discovery to systems engineering and analysis, NREL researchers tackle market-relevant challenges to develop solutions for an independent energy system that is reliable, resilient and secure. Collaborative partnerships with industry, government, and academia ensure that our research remains cutting edge, impactful, applicable, and aligned with real-world energy needs. This special issue of Computing in Science & Engineering highlights exemplary NREL projects where computational tools and methodologies drive discovery and accelerate innovation in scalable and integrated energy systems. The featured articles explore the role of computational modeling, high-performance computing, generative AI, and adaptive computing in advancing independent energy solutions, optimizing sustainability research, and enhancing decision-making for energy solutions using a broad mix of energy technologies. Here, these contributions demonstrate how NREL’s computational research bridges the gap between theoretical advancements and practical implementation, emphasizing interdisciplinary collaboration and a commitment to innovation, with a focus on translating computational excellence into real-world impact, thus accelerate progress toward national energy goals. By showcasing cutting-edge research at the intersection of computational science and energy systems, this issue aims to inspire and inform researchers, practitioners, and policymakers dedicated to shaping a more reliable energy future.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Size–strain separation in diffraction line profile analysis

Separation of size and strain effects on diffraction line profiles has been studied in a round robin involving laboratory instruments and synchrotron radiation beamlines operating with different radiation, optics, detectors and experimental configurations. The studied sample, an extensively ball milled iron alloy powder, provides an ideal test case, as domain size broadening and strain broadening are of comparable size. The high energy available at some synchrotron radiation beamlines provides the best conditions for an accurate analysis of the line profiles, as the size–strain separation clearly benefits from a large number of Bragg peaks in the pattern; high counts, reliable intensity values in low-absorption conditions, smooth background and data collection at different temperatures also support the possibility to include diffuse scattering in the analysis, for the most reliable assessment of the line broadening effect. However, results of the round robin show that good quality information on domain size distribution and microstrain can also be obtained using standard laboratory equipment, even when patterns include relatively few Bragg peaks, provided that the data are of good quality in terms of high counts and low and smooth background.

Scardi, P. (ORCID:0000000310973917)↗
NASA NTRS2015

Wear-Out Sensitivity Analysis Project Abstract

During the course of the Summer 2015 internship session, I worked in the Reliability and Maintainability group of the ISS Safety and Mission Assurance department. My project was a statistical analysis of how sensitive ORU's (Orbital Replacement Units) are to a reliability parameter called the wear-out characteristic. The intended goal of this was to determine a worst case scenario of how many spares would be needed if multiple systems started exhibiting wear-out characteristics simultaneously. The goal was also to determine which parts would be most likely to do so. In order to do this, my duties were to take historical data of operational times and failure times of these ORU's and use them to build predictive models of failure using probability distribution functions, mainly the Weibull distribution. Then, I ran Monte Carlo Simulations to see how an entire population of these components would perform. From here, my final duty was to vary the wear-out characteristic from the intrinsic value, to extremely high wear-out values and determine how much the probability of sufficiency of the population would shift. This was done for around 30 different ORU populations on board the ISS.

Harris, Adam↗
DOE OSTI2017

Recordings and Analysis of Atomic Ledge and Dislocation Movements in InGaAs to Nickelide Nanowire Phase Transformation

The formation of low resistance and self‐aligned contacts with thermally stable alloyed phases is a prerequisite for realizing reliable functionality in ultrascaled semiconductor transistors. Detailed structural analysis of the phase transformation accompanying contact alloying can facilitate contact engineering as transistor channels approach a few atoms across. Original in situ heating transmission electron microscopy studies are carried out to record and analyze the atomic scale dynamics of contact alloy formation between Ni and In 0.53 Ga 0.47 As nanowire channels. It is observed that the nickelide reacts on the In 0.53 Ga 0.47 As (111) || Ni 2 In 0.53 Ga 0.47 As (0001) interface with atomic ledge propagation along the Ni 2 In 0.53 Ga 0.47 As direction. Ledges nucleate as a train of strained single‐bilayers and propagate in‐plane as double‐bilayers that are associated with a misfit dislocation of . The atomic structure is reconstructed to explain this phase transformation that involves collective gliding of three Shockley partials in In 0.53 Ga 0.47 As lattice to cancel out shear stress and the formation of misfit dislocations to compensate the large lattice mismatch in the newly formed nickelide phase and the In 0.53 Ga 0.47 As layers. This work demonstrates the applicability of interfacial disconnection (ledge + dislocation) theory in a nanowire channel during thermally induced phase transformation that is typical in metal/III–V semiconductor reactions.

Chen, Renjie↗
DOE OSTI2024

Analysis and Mitigation of Cascading Outages Using an Interaction Graph Addressing Transient Stability

Cascading outages of power systems pose great threats to system security and reliability, potentially leading to large-scale blackouts. For analysis and mitigation of cascading outages, this paper proposes a transient stability-incorporated interaction graph. This graph statistically quantifies the interactions among line outages and instabilities of generators, which can model propagation paths and patterns of cascading outages. Compared with an interaction graph that only models line outages, this new interaction graph provides important insights on how transient instability occurs along with cascading outages. It also offers more effective strategies for mitigating outage propagation. The proposed interaction graph can be constructed from datasets of historical or simulated cascading events. It is demonstrated on an NPCC 140-bus system with mitigation strategies.

Guo, Zhenping↗
NASA NTRS1985

Probabilistic structural analysis for space propulsion system components

Probabilistic design and analysis methods for the achievement of greater reliability in structural systems are especially useful in those cases where the structure operates in such severe environments as that of the Space Shuttle. Attention is presently given to the development status of a NASA-sponsored program for probabilistic structural analysis methods applicable to current and future reusable space propulsion systems. Methodologies for the assessment of structural response by means of integrated finite element and probabilistic analysis techniques are discussed, with illustrative examples.

Burnside, O. H.↗
DOE OSTI2021

BETO 2021 Peer Review - Strategic Analysis Support WBS 4.1.1.30

Strategic Analysis Support. The objective of the NREL strategic support project is to provide sound, unbiased, and consistent analyses to inform the strategic direction of the DOE BETO office. This project addresses key technological questions, provides critical data needed to inform strategy, and highlights barriers, gaps and data needs in support of the DOE BETO's mission to improve the affordability of bio-based fuels and products. This task employs various quantitative (techno-economic analysis, TEA) and qualitative (gap analysis) approaches to allow for direct comparisons of biomass conversion technologies across a wide slate of processing platforms and products. Furthermore, this project develops and utilizes novel analyses beyond traditional biorefinery focused TEA/LCAs to identify both technical (e.g., in sustainable design) and non-technical (e.g., in value proposition) barriers, as well as to outline mitigation strategies and R&D needs for emerging technologies. Additionally, the project is tasked with evaluating drivers that support the growing bio-economy, which is achieved by the development and public release of tools to advance the understanding and facilitate comparisons of socio-economic impacts along the supply chain. Critical to the success of this project is the development of defensible methodologies, analyses, and tools that are publicly available to support stakeholders and bioeconomy growth. To develop such high-quality analyses, the biggest challenge to this project, as with most analysis focused projects, is the availability and reliability of the underlying data. Therefore, the project team works extensively with key stakeholders (e.g., policy makers, bioenergy technology developers, and investors) in developing and reviewing the results of these analyses to overcome this challenge. Any remaining uncertainties associated with the analysis efforts are clearly defined and quantified.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Severe weather, utility spending, and the long-term reliability of the U.S. power system

There has been a limited amount of peer-reviewed literature on long-term trends in electricity reliability including the underlying factors that impact reliability across the United States. In this analysis, we considered up to 16 years of data from 203 U S. utilities—representing about 70% of electricity sales. Annual frequency of interruptions for an average customer—at the regional and U.S. national-level—has generally decreased over this timeframe. But we do not find that there is a statistically significant trend in the annual duration of interruptions for an average customer. We find that more explicit measures of severe weather are correlated with reliability. We are able to explain 7% and 16% of past variation in the reliability metrics system average interruption duration and frequency indices, respectively, is due to severe weather—a significant improvement over earlier studies. We find that current year spending by utilities is correlated with worse reliability and that cumulative spending over the preceding three years is correlated with better reliability. Finally, we demonstrate that using a statistical instrument to represent the annual frequency of interruptions for an average customer can greatly improve analysis of trends in the annual duration of interruptions for an average customer.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2018

Application of IR Thermography with Thermal Diffusivity Analysis for Detection of Plies Displacement in CFRP Composites

This paper presents an efficient nondestructive testing (NDT) method for detection of plies displacement in carbon fiber reinforced plastic (CFRP) composites using the active thermography technique. To assess the capability of the proposed technique for detection of plies displacement, the CFRP composite specimens with simulated fault were designed and manufactured. The IR thermography measurements were conducted using two-sided experimental arrangement. From recorded sequences of thermal images, the temperature variations versus time plots were extracted to obtain the maximum thermal contrasts. For quantitative interpretation of the results, the thermal diffusivity values for each composite material were determined and related to the fiber volume fraction. The experimental results showed that the thermal diffusivity increases with an increase of fiber volume fraction; further, the values of thermal diffusivity are specimen thickness dependent. The obtained values of thermal diffusivity varied from 1.5 × 10{sup −7} m{sup 2}/s (for 3.2 mm composite with 8.5 vol.% carbon fiber) to 2.6 × 10{sup −7} m{sup 2}/s (for 7.7 mm composite with 34.1 vol.% carbon fiber). On the basis of these results, it was concluded that the active thermography combined with thermal diffusivity analysis can be considered as a reliable NDT technique for detection of plies displacement in CFRP composites.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Learning model combining convolutional deep neural network with a self-attention mechanism for AC optimal power flow

Alternating current optimal power flow (OPF) analysis is critical for efficient and reliable operation of power systems. For large systems or repetitive computations, the traditional methods such as the direct and gradient methods, or non-traditional methods, such as the genetic algorithm and simulating annealing, are time-consuming and unsuitable for real-time computing. The work in this paper proposes a novel framework to obtain the optimal solution of power flow in real-time using a combination of convolutional neural networks and a self-attention mechanism. All parameters of the power networks are rearranged in an image-like shape of a multi-channel image where each channel is a two-dimensional matrix. The proposed approach is adaptive with every input size of power systems as well as frequent variations of network topologies without intervention to the framework core. The encompassment of all power system contexts in which all parameters of internal elements, generation costs, and topology information are included, contributes to the higher accuracy of inference compared to other current machine-learning-based OPF-solving methods. Besides, the proposed framework established on ubiquitous platforms is effortlessly integrated into current infrastructures of power systems, and the great efficiency along with the computation speed may serve as a critical point for practical implications, such as enabling faster decision-making during real-time operations, predicting system contingencies, and remedial actions based on an offline pre-trained model. Furthermore, this supervised learning process is applied to the dataset of four case studies of meshed power systems: the IEEE 5-bus system (IEEE-5), the IEEE 30-bus system (IEEE-30), the IEEE 39-bus system (IEEE-39), and the IEEE 57-bus system (IEEE-57) to prove the efficacy of the proposed method.

42 ENGINEERING↗
DOE OSTI2022

Machine learning-based optimization of air-cooled heat sinks

Machine learning-based models using Artificial Neural Network (ANN) and greedy search algorithm are used to optimize air-cooled parallel plate-finned heat sinks (PPFHSs) subjected to laminar flow over an extensive range of design parameters. Here, the thermal and hydraulic performances of PPFHSs are represented by heat transfer coefficient (h) and pressure drop (ΔP), respectively. Optimization objectives for PPFHS designs can vary from industry to industry depending on their design priorities. The present study proposes a novel and generalized optimization method that defines practical optimization objectives and provides an accurate optimization process to design effective PPFHSs for a wide range of industrial applications with different design requirements. Three optimization objectives are presented in this study: (i) the largest h PΔ, (ii) the largest h within a specified maximum allowed flow rate, and (iii) the lowest weight that maximizes h for operation within the maximum allowed flow rate. While the shortcoming of the first objective is demonstrated, the other two objectives are found to be suitable for designing effective heat sinks (HSs) across different applications. Results suggest a promising trend from the third objective to develop HSs with ~ 37-68% lower weight, 80-85% reduced ΔP, and negligible penalty in h compared with optimized HSs obtained from the second objective. However, since the third objective leads to HSs with thinner fins, structural analysis should be performed to ensure reliable operation of the HSs.

42 ENGINEERING↗
DOE OSTI2026

Accurate determination of chemical abundances near a supermassive black hole

The metal abundances in galactic nuclei carry key information on the history of star formation and mass transfer in central regions of galaxies. X-ray fluorescence analysis is a unique tool to reliably measure the abundances of various elements via simple physics. Here we present a new observation of the active nucleus in the Circinus galaxy with the XRISM satellite at unprecedented X-ray energy resolution. The fluorescent iron Kα line profile modified by Compton scattering indicates that the material responsible for its emission is cold and metal rich and is located ≳0.024 pc from the supermassive black hole, consistent with the dusty torus region. The abundance pattern derived from comparing fluorescent line intensities of different metals shows subsolar ratios of argon- and calcium-to-iron and a supersolar ratio of nickel-to-iron. This abundance pattern is best produced by a combination in number fraction of 92$^{+2}_{–4}$% core-collapse supernovae from progenitor stars less massive than 20$^{+3}_{–2}$ M ⊙ and 8$^{+4}_{–2}$% type Ia supernovae. This suggests that gas feeding the supermassive black hole was enriched by recent core-collapse supernovae. Our findings imply that in metal-rich environments stars more massive than about 20 M ⊙ directly collapse into black holes or make faint supernovae without ejecting heavy metals into the space.

Astronomy and AstroPhysics↗