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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 55 records · Page 3

Seismoacoustic Explosion Yield and Depth Estimation: Insights from the Large Surface Explosion Coupling Experiment

The Large Surface Explosion Coupling Experiment (LSECE) is a chemical explosion experiment conducted in Yucca Flat at the Nevada National Security Site in 2020. The experiment included two surface detonations of ~1000 kg trinitrotoluene equivalent. The main goal of this experiment was to provide the ground-truth data for seismoacoustic wave excitation by large chemical explosions near the ground surface. The seismic and acoustic energy partitioning between the surface is strongly governed by the depth or height of explosions, and either seismic or acoustic-only analysis may have inherent ambiguity in determining explosion yield and depth simultaneously. Previous studies suggested that joint seismoacoustic analysis can resolve the trade-off and reduce the uncertainty of yield and depth estimation dramatically. Here we demonstrate the capability of seismoacoustic analysis to improve the accuracy of explosion yield and depth estimation with the LSECE data. Local acoustic wave propagation in the atmosphere can be substantially affected by constantly varying weather conditions. Consisting of two detonations before dawn and in the afternoon, LSECE provides unique data to evaluate the model accuracy of acoustic wave propagation and seismoacoustic energy partitioning depending on local atmospheric conditions. We quantitatively evaluate the accuracy of yield and depth estimation depending on atmospheric variability and the improvement achieved by the joint seismoacoustic approach.

58 GEOSCIENCES↗

Numerical Simulation of Commercial-Scale CO2 Storage in a Saline Formation Evaluating Basin-Scale Pressure Interference and CO2 Plume Commingling

Presentation at NETL Carbon Management Project Review Meeting held in Pittsburgh, Pennsylvania, August 15–19, 2022. The presentation provides quantitative evaluation of subsurface pressure interference and emphasizes the importance of interproject coordination among stakeholders associated with multi-project geologic CO2 storage in a shared sedimentary basin.

Wijaya, Nur↗

Observations Regarding Commonly Available Materials for Face Shield Emulated-Personal Protective Equipment

The Center for Disease Control has recommended that to reduce potential exposure to COVID-19 the public should wear cloth face coverings in public settings where other social distancing measures are difficult to maintain. These face coverings and other Emulated-Personal Protective Equipment (E-PPE) can be made by using Commonly Available Materials (CAMs). As E-PPE recommendations continue to flood the media, a Sandia COVID-19 LDRD effort, the Sandia E-PiPEline Team, systematically evaluated E-PPE design options considering their effectiveness, durability, build difficulty, build cost, and comfort. Using qualitative and semi-quantitative evaluation tools, results of the investigation are presented here to provide guidelines for home and office construction of E-PPE.

36 MATERIALS SCIENCE↗

Observations Regarding Commonly Available Materials for Face Covering Emulated-Personal Protective Equipment

The Center for Disease Control has recommended that to reduce potential exposure to COVID-19 the public should wear cloth face coverings in public settings where other social distancing measures are difficult to maintain. These face coverings and other Emulated-Personal Protective Equipment (E-PPE) can be made by using Commonly Available Materials (CAMs). As E-PPE recommendations continue to flood the media, a Sandia COVID-19 LDRD effort, the Sandia E-PiPEline Team, systematically evaluated E-PPE design options considering their effectiveness, durability, build difficulty, build cost, and comfort. Using qualitative and semi-quantitative evaluation tools, results of the investigation are presented here to provide guidelines for home and office construction of E-PPE.

36 MATERIALS SCIENCE↗

Bootstrap current modeling in M3D-C1

Bootstrap current plays a crucial role in the equilibrium of magnetically confined plasmas, particularly in quasi-symmetric stellarators and in tokamaks, where it can represent bulk of the electric current density. Accurate modeling of this current is essential for understanding the magnetohydrodynamic (MHD) equilibrium and stability of these configurations. This study expands the modeling capabilities of M3D-C1, an extended-MHD code, by implementing self-consistent physics models for bootstrap current. It employs two analytical frameworks: a generalized Sauter model (Sauter et al. 1999 Phys. Plasmas vol. 6, no. 7, pp. 2834–2839), and a revised Sauter-like model (Redl et al. 2021 Phys. Plasmas vol. 28, no. 2, pp. 022502). The isomorphism described by Landreman et al. (2022 Phys. Rev. Lett. vol. 128, pp. 035001) is employed to apply these models to quasi-symmetric stellarators. The implementation in M3D-C1 is benchmarked against neoclassical codes, including NEO, XGCa and SFINCS, showing excellent agreement. These improvements allow M3D-C1 to self-consistently calculate the neoclassical contributions to plasma current in axisymmetric and quasi-symmetric configurations, providing a more accurate representation of the plasma behavior in these configurations. A workflow for evaluating the neoclassical transport using SFINCS with arbitrary toroidal equilibria calculated using M3D-C1 is also presented. This workflow enables a quantitative evaluation of the error in the Sauter-like model in cases that deviate from axi- or quasi-symmetry (e.g. through the development of an MHD instability).

fusion plasma↗

Trustworthiness modeling and evaluation for a nearly autonomous management and control system

The Nearly Autonomous Management and Control (NAMAC) system supports the advanced reactor operation by recommending control actions to operators based on real-time measurements and digital twins (DTs) learning from the knowledge base. To enable the safe and reliable use of autonomous technologies, NAMAC and its recommendations should be trustworthy to operators and regulators at both the design and operation stages. This study proposes a NAMAC trustworthiness modeling and evaluation framework supported by trustworthiness ontologies and evidence-based approaches. The development-time and run-time ontologies are separately constructed and then converted to Bayesian networks to quantitatively evaluate the NAMAC trustworthiness. This evaluation is demonstrated by collecting and characterizing evidence from NAMAC practices, such as the development and assessment of the NAMAC system, data coverage assessment, and the training and optimizations of neural-network-based DTs. Our proposed approach can aggregate various trustworthiness attributes of complex artificial-intelligence-supported systems for safety-critical applications. It also considers the interaction between different DTs and extends beyond the trustworthiness evaluation of a single DT. In conclusion, the evidence-based method enhances the transparency of the trustworthiness modeling and evaluation processes and helps identify uncertainties and subjectivity involved in the processes.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Experimental evaluation of localized creep deformation in grade 91 steel weldments

Spatially resolved measurement of localized creep deformation in heterogeneous creep resistant steel weldments is crucial but challenging for lifetime assessments of critical steam components in power plants. Here, experimental approaches were established to quantitatively evaluate commonly observed localized creep deformation in multi-pass Grade 91 steel weldments. An in-situ digital image correlation (DIC) system was utilized with a creep testing frame to monitor and measure both full-field strain and localized strain accumulation across the weldments during long-term creep testing at elevated temperatures. The in situ DIC method measured not only the creep deformation behavior of the weld metal, heat affected zone (HAZ), and base metal, but also creep strain evolution for each sub-region within the HAZ itself, including coarse-grained HAZ, fine-grained HAZ (FGHAZ), and intercritical HAZ (ICHAZ). The DIC results revealed that local creep strain in the ICHAZ reached up to 90% strain before final rupture, whereas nominal creep strain measured by the standard extensometer of the tested cross-weld specimen was below 10%, indicative of Type IV cracking of the Grade 91 weld. Microstructural analyses revealed that the faster creep degradation/deformation in the HAZ was caused mainly by accelerated matrix grain recrystallization/growth and a reduced pinning effect from the segregated and coarsened precipitates in the FGHAZ and ICHAZ. The ultimate creep rupture occurred in the ICHAZ owing to its lowest creep resistance induced by the largest recrystallized grain size, the lowest fraction of coincidence site lattice, and the lowest local strain energies/dislocation densities.

36 MATERIALS SCIENCE↗

Milestone M7 Report: Reducing Excess Data Movement Part 2

This milestone evaluates techniques to measure and, if possible, reduce data movement across all levels of the memory hierarchy, focusing on CPU/GPU page level data movement and on intra-GPU memory hierarchy. We quantitatively evaluate the efficacy of the techniques in reducing data movement and measure how performance tracks data movement reduction. We study a small collection of benchmarks and proxy mini-apps that run on advanced pre-exascale GPUs and on the Accelsim GPU simulator. Our approach has two thrusts: to measure advanced data movement reduction directives and techniques on the newest available GPUs, and to evaluate our benchmark set on simulated GPUs configured with architectural refinements to reduce data movement. We primarily evaluated NVidia-based architectures due to the unavailability of AMD GPU hardware and tools until very recently.

97 MATHEMATICS AND COMPUTING↗

A VOI Web Application for Distinct Geothermal Domains: Statistical Evaluation of Different Data Types within the Great Basin

The Great Basin region contains different domains that have different structural and hydrothermal flow patterns. Depending on the characteristics of these patterns, certain data types may be more successful at detecting hidden geothermal resources. In this paper, we quantitatively evaluate if certain data types are more successful in certain domains. Given different aquifer, strain and structural conditions, we explore which data types statistically reveal positively labeled geothermal sites. We utilize value of information (VOI) metrics to help quantify the reliability of data types to discriminate against "positive" and "negative" labeled geothermal sites. We also evaluate how kernel density estimation can help generalize the statistics that inform VOI, which is necessary given the limited data in geothermal exploration. Except for the Carbonate Aquifer, the highest ranking of the Vimperfect is the Local Structural Setting. Next, the slip and dilation tendency is first for Carbonate Aquifer and second for Central Nevada Seismic Belt and Western Great Basin. For the Carbonate Aquifer, heat flow is has the lowest Vimperfect value compared to the other three domains, which is consistent with the understanding of how heat flow measurements are masked by regional groundwater flow.

Bayesian analysis↗

Crash Risks Evaluation of Urban Expressways: A Case Study in Shanghai

We report that proactive traffic safety management systems can reduce crashes by identifying crash precursors, evaluating real-time crash risks, and implementing suitable interventions. The basic prerequisite for developing such a system is to propose a reliable crash risk evaluation model that takes real-time traffic flow data as input. Previous studies have primarily focused on real-time crash prediction using some statistical or machine-learning methods. However, further quantitative evaluation and classification of crash risks have been ignored. In this study, we conduct a systematic crash risk evaluation workflow, including crash risk prediction, crash risk quantification, and crash risk classification. Specifically, the crash risk prediction using an extended logit model is proposed, from which CAS, CSD, UAS, DAS, DTV are identified to be contributing factors of crash risks. Then a crash risk quantification model based on the parameter evaluation of the extended logit model is developed. The crash risks of urban expressways and their spatial-temporal evolution trends are quantified. Finally, the crash risks are classified into high crash risk level, moderate crash risk level, and low crash risk level by the k-means cluster algorithm. Then the threshold boundaries of different crash risk levels are determined. The research results provide a proactive guidance for traffic safety management of urban expressways.

33 ADVANCED PROPULSION SYSTEMS↗

Atomistic, macromolecular model of the Populus secondary cell wall informed by solid-state NMR

Plant secondary cell walls (SCWs) are composed of a heterogeneous interplay of three major biopolymers: cellulose, hemicelluloses, and lignin. Details regarding specific intermolecular interactions and higher-order architecture of the SCW superstructure remain ambiguous. Here, we use solid-state nuclear magnetic resonance (ssNMR) measurements to infer refined details about the structural configuration, intermolecular interactions, and relative proximity of all three major biopolymers within air-dried Populus wood. To enhance the utility of these findings and enable evaluation of hypotheses in a physics-based environment in silico, the NMR observables are articulated into an atomistic, macromolecular model for biopolymer assemblies within the plant SCW. Through molecular dynamics simulation, we quantitatively evaluate several variations of atomistic models to determine structural details that are corroborated by ssNMR measurements.

09 BIOMASS FUELS↗

Performance Evaluation of Weather@home2 Simulations over West African Region

Weather and climate forecasting, using climate models, have become essential tools and life-savers in the West African region; in spite of the fact that climate models do not fully comply with attributes of forecast qualities—RASAP: reliability, association, skill, accuracy, and precision. The objective of this paper is to quantitatively evaluate, in comparison to CRU and ERA5 datasets, the RASAP compliance-level of the weather@home2 modeling system (w@h2). Findings from some statistical evaluations show that, to a moderately significant extent, w@h2 model provides useful information during the monsoon seasons; skills to capture the Little Dry Season over the Guinea zone; predictive skills for the onset season; ability to reproduce all the annual characteristics of the surface maximum air temperature over the region; as well as skill to detect heat waves that usually ravage West Africa during the boreal spring. The model displays traces of attributes that are needed for seasonal climate predictions and applications. Deficiencies in the quantitative reproducibility point to the facts that the model does provide a reliability akin to that of regional climate models. This paper further furnishes a prospective user with information on whether the model might be “useful or not” for a particular application.

West Africa↗

Intelligent Manufacturing Support: Specialized LLMs for Composite Material Processing and Equipment Operation

Engineering educational curriculum and standards cover many material and manufacturing options. However, engineers and designers are often unfamiliar with certain composite materials or manufacturing techniques. Large language models (LLMs) could potentially bridge the gap. Their capacity to store and retrieve data from large databases provides them with a breadth of knowledge across disciplines. However, their generalized knowledge base can lack targeted, industry-specific knowledge. To this end, we present two LLM-based applications based on the GPT-4 architecture: (1) The Composites Guide: a system that provides expert knowledge on composites material and connects users with research and industry professionals who can provide additional support and (2) The Equipment Assistant: a system that provides guidance for manufacturing tool operation and material characterization. By combining the knowledge of general AI models with industry-specific knowledge, both applications are intended to provide more meaningful information for engineers. In this paper, we discuss the development of the applications and evaluate it through a benchmark and two informal user studies. The benchmark analysis uses the Rouge and Bertscore metrics to evaluate our models’ performance against GPT-4o. The results show that GPT-4o and the proposed models perform similarly or better on the ROUGE and BERTScore metrics. The two user studies supplement this quantitative evaluation by asking experts to provide qualitative and open-ended feedback about our model’s performance on a set of domain-specific questions. The results of both studies highlight a potential for more detailed and specific responses with the Composites Guide and the Equipment Assistant.

Kapoor, Gunnika [Oak Ridge National Laboratory (OR↗

System code evaluation of near-term accident tolerant claddings during pressurized water reactor station blackout accidents

Following the Fukushima Daiichi nuclear accident in 2011, researches on Accident-tolerant fuels (ATFs) are currently of high interest in not only the nuclear industry but also governmental and international organizations. In this work, a quantitative evaluation of the performance of monolithic FeCrAl cladding and Cr-coated Zircaloy cladding has been performed for Pressurized Water Reactor (PWR) Station Blackout (SBO) accidents. A generic PWR model has been built in system thermal-hydraulics code TRACE based on the Surry Nuclear Power Station with counter-current natural circulation modelling capability for hotleg and steam generator U-tube components during the accidents. The base model results are then compared to MELCOR and RELAP simulations to verify the system component implementation in TRACE. Two PWR SBO scenarios were investigated, including: short-term SBO and long-term SBO with early reactor coolant pump (RCP) seal failure. These scenarios are defined to be very similar to the accidents studied in the State-of-the-Art Reactor Consequence Analysis (SOARCA) project. TRACE code is modified to reflect the oxidation kinetics of FeCrAl and Cr-coating. Larson-Miller creep rupture model is also implemented in TARCE using its built-in control systems to simulate the creep rupture of hotlegs. Additionally, the comparison between the TRACE models with and without the counter-current flow modeling resulted in significant difference when comparing ATF cladding to Zircaloy for short term SBO, while it marginal impacted the performance during long term SBO with RCP seal failure. For short term SBO, both ATF cladding underwent hot leg creep rupture ~20 min after Zircaloy cladding. While Zircaloy and Cr-coated cladding had generated significant amount of hydrogen gas (>10 kg) before the creep rupture event, FeCrAl cladding had only generated <0.5 kg of hydrogen gas. For long term SBO with RCP seal failure, significant hydrogen generation and fuel melting was predicted before hot leg creep rupture for the ATF cladding while providing only 10–20 min additional coping time compared to Zircaloy.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Evaluation of Cease Fire CFP 640 for Use in Gloveboxes (Final Report)

A Los Alamos National Laboratory (LANL) task group was established to discuss and evaluate a candidate fire suppression system (FSS) for gloveboxes (GB) and dropboxes (DB, for brevity, this report will simply refer to gloveboxes). Suitability criteria include compliance, compatibility, and capability. LANL contracted with New Mexico Tech (NMT) to quantitatively evaluate the perfor mance of one of those systems including its ability to extinguish GB fires, limit over-pressurization of the GB, etc. Additionally, the results of these experiments provide data points that could be used when fire hazard evaluations (FHEs) are conducted for determining when to require a fire suppres sion system installation within a GB (as required by NFPA 801, Standard for Facilities Handling Radioactive Materials, DOE Standard 1066-2012 Fire Protection, and AGS-G010-2011 Standard of Practice for Glovebox Fire Protection).

42 ENGINEERING↗

Nanoscale defect evaluation framework combining real-time transmission electron microscopy and integrated machine learning-particle filter estimation

Observation of dynamic processes by transmission electron microscopy (TEM) is an attractive technique to experimentally analyze materials’ nanoscale phenomena and understand the microstructure-properties relationships in nanoscale. Even if spatial and temporal resolutions of real-time TEM increase significantly, it is still difficult to say that the researchers quantitatively evaluate the dynamic behavior of defects. Images in TEM video are a two-dimensional projection of three-dimensional space phenomena, thus missing information must be existed that makes image’s uniquely accurate interpretation challenging. Therefore, even though they are still a clustering high-dimensional data and can be compressed to two-dimensional, conventional statistical methods for analyzing images may not be powerful enough to track nanoscale behavior by removing various artifacts associated with experiment; and automated and unbiased processing tools for such big-data are becoming mission-critical to discover knowledge about unforeseen behavior. We have developed a method to quantitative image analysis framework to resolve these problems, in which machine learning and particle filter estimation are uniquely combined. The quantitative and automated measurement of the dislocation velocity in an Fe-31Mn-3Al-3Si autunitic steel subjected to the tensile deformation was performed to validate the framework, and an intermittent motion of the dislocations was quantitatively analyzed. The framework is successfully classifying, identifying and tracking nanoscale objects; these are not able to be accurately implemented by the conventional mean-path based analysis.

36 MATERIALS SCIENCE↗

HFTS-2 Completions Design and State-of-the-Art Diagnostics Results

Various completion schemes were tested as part of the Hydraulic Fracture Test Site-2 (HFTS-2) project. The wells were instrumented with permanent fiber optic (FO) cable, and unique near-wellbore and far-field region surveys were acquired to evaluate spatial and temporal hydraulic fracture characteristics. The state-of-the-art diagnostics included substantial monitoring of both the well stimulation and longer-term production performance. The objective was to evaluate and improve stimulation distribution effectiveness (SDE) for different completion designs based on the diagnostics results. A hydraulic fracturing (HF) profile (i.e., proppant/fluid allocation among clusters) was obtained using near-wellbore Distributed Acoustic Sensing (DAS) data acquired during stimulation. Statistical analysis provided a quantitative assessment of SDE for the different completion designs. A novel workflow was developed to assess time-lapse fracture property changes at the cluster and stage levels based on Distributed Strain Sensing (DSS) data acquired during the production phase. These time-lapse fracture property changes were compared with the HF profile. Based on the statistical analysis, Rate Per Cluster (RPC) during proppant slurry placement appears to be a primary completion design variable, rather than the typical Rate Per Perf (RPP). If RPC was not maintained at a certain level, the likelihood of uneven distribution increased dramatically. The stage configurations that created low RPC while maintaining high RPP did not show improved SDE. The strain change results based on DSS data during the production phase indicated near-wellbore fracture property changes (e.g., aperture changes during well shut-in and flow periods) and aligned well with near-wellbore DAS signals acquired during stimulation. More importantly, fracture property changes based on DSS data acquired during two tests over a 7-month period show high consistency and good alignment with the near-wellbore HF profile. This workflow quantitatively evaluates SDE for different completion designs using diagnostic results and could help optimize completion strategy for future development projects. Here, the analysis and interpretation of results demonstrate the technical feasibility of using permanent fiber optic cable for stimulation and production monitoring and indic

58 GEOSCIENCES↗

EVALUATION OF HRA METHODOLOGIES FOR APPLICATION IN SDP WORK

This study critically evaluates human reliability analysis (HRA) methodologies applicable to regulatory probabilistic safety assessment (PSA) model, with a particular focus on their role in supporting the significance determination process (SDP) in nuclear safety assessment. Firstly, three widely utilized HRA methods – IDHEAS-ECA, SPAR-H, and ASEP/THERP – were qualitatively and quantitatively assessed. Qualitative assessments were conducted using attributes from the NEA/CSNI/R(2015)1 report, while quantitative evaluations employed regression and correlation analyses to compare predicted human error probabilities (HEPs) against empirical data. Results reveal distinct strengths, for example, IDHEAS-ECA’s robust predictive accuracy and K-HRA’s alignment with operational practices. In addition, dependency analysis and recovery analysis were critically evaluated. For dependency analysis, the methods’ handling of inter-task dependencies and their impact on HEPs were examined, while recovery analysis highlighted strategies for mitigating failure events. Furthermore, strategies were proposed to evaluate performance-shaping factors under conditions of reduced human performance, such as stress, fatigue, or cognitive overload, addressing specific challenges faced in SDP evaluations. Human errors from KINS’s operational performance information system event reports were evaluated as a case study. This study identifies gaps and provides actionable insights to ensure their validity and applicability in SDP HRA applications. This paper is a part of research conducted by KINS, and it should be noted that this result does not represent the regulatory position of KINS.

99 - GENERAL AND MISCELLANEOUS↗