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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

Risk Analysis of a Hydrogen Generation Facility near a Nuclear Power Plant

Nuclear power plants (NPPs) are considering flexible plant operations to take advantage of excess thermal and electrical energy. One option for NPPs is to pursue hydrogen production through high temperature electrolysis as an alternate revenue stream to remain economically viable. The intent of this study is to investigate the risk of a hydrogen production facility in close proximity to an NPP. A 100 MW, 500 MW, and 1,000 MW facility are evaluated herein. Previous analyses have evaluated preliminary designs of a hydrogen production facility in a conservative manner to determine if it is feasible to co-locate the facility within 1 km of an NPP. This analysis specifically evaluates the risk components of different hydrogen production facility designs, including the likelihood of a leak within the system and the associated consequence to critical NPP targets. This analysis shows that although the likelihood of a leak in an HTEF is not negligible, the consequence to critical NPP targets is not expected to lead to a failure given adequate distance from the plant.

08 HYDROGEN↗

Risk Analysis of a 100 MW Hydrogen Generation Facility near a Nuclear Power Plant

Nuclear power plants (NPPs) are considering flexible plant operations to take advantage of excess thermal and electrical energy. One option for NPPs is to pursue hydrogen production through high temperature electrolysis as an alternate revenue stream to remain economically viable. The intent of this study is to investigate the risk of a 100 MW hydrogen production facility in close proximity to an NPP. Previous analyses have evaluated preliminary designs of a hydrogen production facility in a conservative manner to determine if it is feasible to co-locate the facility within 1 km of an NPP. This analysis specifically evaluates the risk components of a 100 MW hydrogen production facility design, including the likelihood of a leak within the system and the associated consequence to critical NPP targets. This analysis shows that although the likelihood of a leak in an HTEF is not negligible, the consequence to critical NPP targets is not expected to lead to a failure given adequate distance from the plant.

08 HYDROGEN↗

Uncertainty Quantification and Sensitivity Analysis for Quantitative Risk Assessments of Hydrogen Infrastructure

Typical QRAs provide deterministic estimates and understanding of risks posed but are constructed using significant assumptions and uncertainties due to limited data availability and historical momentum of using nominal estimates. This report presents a hydrogen QRA analysis using HyRAM+ that incorporates uncertainty with Latin hypercube sampling and sensitivity analysis using linear regression.

08 HYDROGEN↗

Compressor Station Differential Risk Assessment for Hydrogen and Natural Gas Blends

Blending hydrogen into existing natural gas pipelines is a current initiative for large-scale hydrogen deployment in the United States. Understanding changes in hazards and risk for fuel blends can help inform regulations. A differential risk assessment was conducted to understand how the safety profile of fires and unignited flammable plumes of leaking fuel would change based on blend composition. The area affected by harmful heat fluxes from jet fires was found to be larger for blends with more natural gas in them, while the distance affected by unignited flammable fuel concentrations was found to be larger for blends with more hydrogen in them. Component leak frequencies and ignition probabilities greatly impact both heat flux risk and the flammable plume risk. The collection of additional blend-specific industry data could help understand which assumptions are most valid to make when calculating risk.

08 HYDROGEN↗

GDSA Framework Development and Process Model Integration FY2024

The Disposal Research & Development (Disposal R&D) Campaign of the U.S. Department of Energy (DOE) Office of Nuclear Energy (NE), Office of Spent Fuel & High-Level Waste Disposition is conducting research and development (R&D) on geologic disposal of spent nuclear fuel (SNF) and high-level nuclear waste (HLW). A high priority for Disposal R&D is disposal system modeling (Sassani et al. 2023). The Geologic Disposal Safety Assessment (GDSA) work package is charged with developing a disposal system modeling and analysis capability for evaluating generic disposal system performance for nuclear waste in geologic media.

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Sensitivity Analysis Comparisons on Geologic Case Studies: An International Collaboration, Volume 2

Over the past six years, an informal working group has developed to investigate existing sensitivity analysis methods, examine new methods, and identify best practices. The focus is on the use of sensitivity analysis in case studies involving geologic disposal of spent nuclear fuel or nuclear waste. Three additional case studies are presented in this Volume 2 report, including more nonlinear behavior, outputs which exhibit bifurcation, regime changes, and nested sampling.

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Assessing Uncertainty in Modeling Stress Corrosion Cracking

This report summarizes the collaboration between Sandia National Laboratories (SNL) and the Nuclear Regulatory Commission (NRC) to improve the state of knowledge on chloride induced stress corrosion cracking (CISCC). The foundation of this work relied on using SNL’s CISCC computer code to assess the current state of knowledge for probabilistically modeling CISCC on stainless steel canisters. This work is presented as three tasks. The first task is exploring and independently comparing crack growth rate (CGR) models typically used in CISCC modeling by the research community. The second task is implementing two of the more conservative CGR models from the first task into SNL’s full CISCC code to understand the impact of the different CGR models on a full probabilistic analysis while studying uncertainty from three key input parameters. The combined work of the first two tasks showed that properly measuring salt deposition rates is impactful to reducing uncertainty when modeling CISCC. The work in Task 2 also showed how probabilistic CGR models can be more appropriate at capturing aleatory uncertainty when modeling SCC. Lastly, appropriate and realistic input parameters relevant for CISCC modeling were documented in the last task as a product of the simulations considered in the first two tasks.

36 MATERIALS SCIENCE↗

Challenges in quantifying unparameterized spatial uncertainties in deep geologic repositories for nuclear waste

Spatially heterogeneous uncertainties are prevalent in geophysical modeling applications, such as probabilistic post-closure performance assessment (PA) of deep geologic repositories for nuclear waste. Such uncertainties are often highly influential to model outputs, so it is desirable to identify the most important mechanisms by which they influence model predictions. However, these uncertainties are often unparameterized in the sense that there is no set of parameters that can be specified to yield a particular realization of the uncertainty. Additionally, the uncertainty is not intrinsically endowed with a parameterization that captures a realization’s mechanistic influence on model outputs. Therefore, in this work we present a novel methodology to develop and assess a set of proxy variables that aim to represent this influence. We show how they can be computed, downselected, and incorporated into the construction of statistical surrogate models mapping model inputs to outputs. We present our methodology in the context of a motivating application problem in deep geologic repository PA and discuss the challenges in capturing the effects of these spatial heterogeneities in uncertainty analyses.

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Uncertainty and Sensitivity Analysis Methods and Applications in the GDSA Framework (FY2025)

The Spent Fuel and Waste Science and Technology Campaign (SFWST) of the U.S. Department of Energy (DOE) Office of Nuclear Energy (NE) is conducting research and development on geologic disposal of spent nuclear fuel (SNF) and high-level nuclear waste (HLW). Two priorities for SFWST are design concept development and disposal system modeling. These priorities are directly addressed in the Geologic Disposal Safety Assessment (GDSA) control account, which is charged with developing a geologic repository system modeling and analysis capability, and the associated software, GDSA Framework, for evaluating disposal system performance for nuclear waste in geologic media. This report describes specific activities in the Fiscal Year (FY) 2025 associated with the GDSA Uncertainty and Sensitivity Analysis Methods work package. This report fulfills the GDSA Uncertainty and Sensitivity Analysis Methods work package (SF-25SN01030407) level 3 milestone, Uncertainty and Sensitivity Analysis Methods and Applications in GDSA Framework (FY2025) (M3SF-25SN010304072). This work was closely coordinated with the other Sandia National Laboratory GDSA work packages: the GDSA Framework Development work package (SF-25SN01030408), the GDSA Repository Systems Analysis work package (SF-25SN01030409), and the GDSA PFLOTRAN Development work package (SF-25SN01030410). This report builds on developments reported in previous GDSA Framework milestones, particularly M3SF-24SN010304072.

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Uncertainty and Sensitivity Analysis Methods and Applications in the GDSA Framework (FY2024)

The Spent Fuel and Waste Science and Technology Campaign (SFWST) of the U.S. Department of Energy (DOE) Office of Nuclear Energy (NE) is conducting research and development on geologic disposal of spent nuclear fuel (SNF) and high-level nuclear waste (HLW). Two priorities for SFWST are design concept development and disposal system modeling. These priorities are directly addressed in the Geologic Disposal Safety Assessment (GDSA) control account, which is charged with developing a geologic repository system modeling and analysis capability, and the associated software, GDSA Framework, for evaluating disposal system performance for nuclear waste in geologic media.

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Technical Justifications for Outdoor Bulk Gaseous Hydrogen Storage Setback Distances

Setback distances define a prescribed distance between a potentially hazardous system and different types of other systems, people, buildings, or materials that may be exposed to that hazard. Riskinformed separation distances are not meant to completely eliminate risk, but rather to limit the risk to an acceptable level. A sensitivity study of risk suggested that a leak size of 3% of the pipe cross-sectional area would be a conservative but reasonable basis. Calculation of the setback distances for gaseous hydrogen was done in a deterministic manner, using a selected leak size and harm criteria for each group of exposures. Harm criteria have been updated to better reflect the exposure types under consideration, and to be consistent with setback distances for liquid hydrogen. The resulting setback distance values are primarily driven by radiative heat flux values for all exposure groups. For the typical pipe sizes, the setback distances slightly increase compared to the previous version of NFPA 2.

08 HYDROGEN↗

Prioritizing Uncertainties in Hydrogen Contribution to Risk in Post-Crash Outcomes for Rail

This report presents analysis from Sandia National Laboratories predicting contributions to risk associated with the use of hydrogen technology for rail. Event sequence diagrams are used to describe possible accident scenarios and progressions. Initiating event frequencies and branch event probabilities for each scenario are quantified with uncertainty using distributions fit to Federal Railroad Administration and U.S. Department of Transportation Pipeline and Hazardous Materials Safety Administration data on applicable accidents from 2000 to 2020. Uncertainty is propagated through the event sequence diagram to estimate the frequency and conditional probability of accident end states. The analysis identifies four scenarios with significant contributions to risk from hydrogen that are predicted to occur relatively frequently, which may inform priorities for reducing uncertainty. These scenarios are 1) overpressure events resulting from collisions with hydrogen release due to mechanical damage and delayed ignition, 2) jet fire events resulting from collisions with hydrogen release due to mechanical damage and immediate ignition, 3) jet fires resulting from fire or explosion initiating events involving the hydrogen tank and correct operation of the thermally-activated pressure relief device (TPRD) subsequent to the thermal insult, and 4) pressure burst resulting from fire or explosion initiating events involving the hydrogen tank and failure of the TPRD. Delayed and immediate hydrogen ignition probabilities are identified as being highly uncertain and potential candidates for reducing conservatism in the predicted frequencies for these two scenarios.

08 HYDROGEN↗

ezAlign: A Tool for Converting Coarse-Grained Molecular Dynamics Structures to Atomistic Resolution for Multiscale Modeling

Soft condensed matter is challenging to study due to the vast time and length scales that are necessary to accurately represent complex systems and capture their underlying physics. Multiscale simulations are necessary to study processes that have disparate time and/or length scales, which abound throughout biology and other complex systems. Herein we present ezAlign, an open-source software for converting coarse-grained molecular dynamics structures to atomistic representation, allowing multiscale modeling of biomolecular systems. The ezAlign v1.1 software package is publicly available for download at github.com/LLNL/ezAlign. Its underlying methodology is based on a simple alignment of an atomistic template molecule, followed by position-restraint energy minimization, which forces the atomistic molecule to adopt a conformation consistent with the coarse-grained molecule. The molecules are then combined, solvated, minimized, and equilibrated with position restraints. Validation of the process was conducted on a pure POPC membrane and compared with other popular methods to construct atomistic membranes. Additional examples, including surfactant self-assembly, membrane proteins, and more complex bacterial and human plasma membrane models, are also presented. By providing these examples, parameter files, code, and an easy-to-follow recipe to add new molecules, this work will aid future multiscale modeling efforts.

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