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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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DOE OSTI2024

NREL Hydrogen Sensor Testing Laboratory

Relevance: Detection is recognized as a critical element for hydrogen facility safety design and supports risk mitigation. Detection methodologies will support validation of H2 behavior research. Hydrogen point sensors play a critical role for safety and process monitoring, but other methodologies can be developed. Approach: NREL Sensor Laboratory tests and verifies sensor performance for manufacturers, developers, end-users, regulatory agencies and SDOs/CDOs NREL deployment activity supports regulatory requirement verification, hydrogen behavior models, and method development for use by stakeholders. Accomplishments and Progress: NREL's R&D accomplishments have supported developers, industry, and SDOs by providing sensor performance and deployment expertise not otherwise available. Development of alternative detection strategies for hydrogen applications have been initiated. HyWAM and advanced detection methodologies deployments at H2@Scale Facilities are being implemented. Collaborations: Collaboration with government laboratories, universities, private organizations and regulatory agencies has leveraged the NREL Sensor Laboratory's success in advancing hydrogen safety sensors and process control. Proposed Future Work: NREL will support hydrogen deployment by the proper implementation of hydrogen sensors and advanced detection strategies. NREL will continue to support science-based codes and standards. This effort will be guided by the needs of the hydrogen community.

codes and standards↗
DOE OSTI2024

Estimating the Contributions to Human Error Probability from the Convolution of the Distribution of Time Available and Time Required

As part of their duties, Human Reliability Analysis must often evaluate if crews in nuclear power plants (NPPs) can complete tasks associated with a human-failure event within time limits. For example, the time required in NPP scenarios is determined by systematic and structured walkthroughs, feasibility studies, recorded times from training exercises, and interviews with experienced operators and experts. Typically, a point estimate is derived for the estimate (mean, maximum, or 95th percentile of time required). Using point-estimate values can mask the risk associated with variability among crews, plant conditions and set-up, environmental conditions, and other impact factors under which these actions are executed. While point estimates for time required and time available have served the industry well, without considering the uncertainty they could lead to biased understanding about the risk. The Integrated Human Event Analysis System - General Methodology (IDHEAS-G) model (developed by the US Nuclear Regulatory Commission, NRC) for human error probability calculates human error probability by summing two probabilities: insufficient time and cognitive error. As such, the model takes a more holistic approach by considering the full distributions for time required and time available to calculate the human error probability because the time available to complete the task is insufficient. In this study, we expand on the work of the NRC and discuss methods for estimating these time considerations. For example, for the time required, the impact of Performance Influencing Factors (PIFs) on the distribution was divided into impacts that are aleatory in nature, such as crew-to-crew variability, and those that are epistemic (i.e., the PIFs). Starting with the factors that introduce aleatory uncertainty, a first-order distribution was developed from a large set of time required (i.e., NPP task completion times) data for the range of operator actions that occur in the NPP control room under simulated accident conditions. The first-order distribution can then be adjusted to account for epistemic uncertainty using research associated with the impact of applicable PIFs on the time required. We also develop guidance for analysts to address the probability distributions for the time available. The guidance we developed on how to estimate time required and time available distributions is based on the identification of pertinent research and data, data analyses, and expert knowledge elicitation.

human error probability, human performance, time e↗
DOE OSTI2021

New Approach Methodology for Assessing Inhalation Risks of a Contact Respiratory Cytotoxicant: Computational Fluid Dynamics-Based Aerosol Dosimetry Modeling for Cross-Species and In Vitro Comparisons

Regulatory agencies are considering alternative approaches to assessing inhalation toxicity that utilizes in vitro studies with human cells and in silico modeling in lieu of additional animal studies. In support of this goal, computational fluid-particle dynamics models were developed to estimate site-specific deposition of inhaled aerosols containing the fungicide, chlorothalonil, in the rat and human for comparisons to prior rat inhalation studies and new human in vitro studies. Under bioassay conditions, the deposition was predicted to be greatest at the front of the rat nose followed by the anterior transitional epithelium and larynx corresponding to regions most sensitive to local contact irritation and cytotoxicity. For humans, simulations of aerosol deposition covering potential occupational or residential exposures (1–50 µm diameter) were conducted using nasal and oral breathing. Aerosols in the 1–5 µm range readily penetrated the deep region of the human lung following both oral and nasal breathing. Under actual use conditions (aerosol formulations >10 µm), the majority of deposited doses were in the upper conducting airways. Beyond the nose or mouth, the greatest deposition in the pharynx, larynx, trachea, and bronchi was predicted for aerosols in the 10–20 µm size range. Only small amounts of aerosols >20 µm penetrated past the pharyngeal region. Using the ICRP clearance model, local retained tissue dose metrics including maximal concentrations and areas under the curve were calculated for each airway region following repeated occupational exposures. These results are directly comparable with benchmark doses from in vitro toxicity studies in human cells leading to estimated human equivalent concentrations that reduce the reliance on animals for risk assessments.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
DOE OSTI2025

Radiological Safety Analysis Computer (RSAC 7.2) Presentation

This presentation will be for the graduate seminar class for the University of New Mexico. We will discuss the Radiological Safety Analysis Computer (RSAC) version 7.2, a critical tool in radiological consequence analysis within the nuclear safety domain. We will begin with an introduction to radiological consequence analysis and the importance of dose modeling in nuclear safety, referencing key regulatory frameworks such as DOE-STD-3009 and 10 CFR 20. The presentation will provide an overview of RSAC, including its history, primary functions, and the inputs and outputs involved in its calculations. A detailed examination of RSAC's atmospheric dispersion model, based on the Gaussian plume methodology, will be presented, highlighting how meteorological factors influence the results. We will discuss the regulatory alignment of RSAC with DOE and NRC guidelines, emphasizing the assumptions required for compliance and the balance between conservative and realistic inputs. The presentation will also address the limitations and assumptions inherent in RSAC, comparing it with other consequence analysis codes like MACCS, HotSpot, and RASCAL. An example RSAC run will be demonstrated, showcasing a hypothetical accident scenario and interpreting the resulting dose calculations. Finally, we will introduce new ideas to enhance the current RSAC framework. This future work aims to provide multi-industry adaptability and integration with new dispersion models, addressing the evolving needs of DOE and NRC. The presentation will conclude with a discussion on RSAC's ongoing role in nuclear safety and the opportunities for future innovation.

computer program↗
DOE OSTI2025

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↗
DOE OSTI2023

SCALE Modeling of the Sodium Cooled Fast-Spectrum Advanced Burner Test Reactor

This report documents the modeling and simulation of a sodium-cooled fast reactor (SFR) as part of a U.S. Nuclear Regulatory Commission–sponsored project to assess the modeling and simulation capabilities for accident progression, source term, and consequence analysis for advanced reactor technologies with the Oak Ridge National Laboratory code SCALE and the Sandia National Laboratories (SNL) code MELCOR. Based on publicly available benchmark specifications, a fully heterogeneous 3D SCALE model of the 250 MWth Advanced Burner Test Reactor (ABTR) was developed to demonstrate SCALE’s capabilities for full-core reactivity analysis, fuel inventory prediction, and decay heat analysis of an SFR. The benchmark specifications contain modeling details for the ABTR core at the beginning of equilibrium cycle (BOEC) at operating conditions; they were derived from a 2006 preconceptual design report produced by Argonne National Laboratory. The ABTR was designed to demonstrate reactor-based transmutation of transuranics, that is, to “burn” transuranics recovered from light-water reactor (LWR) spent fuel. The ABTR’s fuel is designed to operate in 4 month cycles using uranium/transuranic (U/TRU) metallic fuel, with a TRU content of approximately 20%, at a conversion ratio of approximately 0.6. Various reactivity calculations were performed with SCALE for the ABTR and, where possible, compared with results available in the open literature. Additionally, SCALE was used to perform a full-core depletion calculation over the 4 month cycle to obtain the nuclide inventory at the end of equilibrium cycle (EOEC). These nuclide inventories, decay heat, power profiles, and reactivity feedback coefficients at EOEC represent the initial conditions for analyzing severe accident scenarios with MELCOR.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

U.S. Domestic Pebble Bed Reactor: Security-by-Design

U.S. nuclear power facilities face increasing challenges in meeting dynamic security requirements caused by evolving and expanding threats while keeping cost reasonable to make nuclear energy competitive. The past approach has often included implementing security features after a facility has been designed and without attention to optimization, which can lead to cost overruns. Incorporating security in the design process can provide robust, cost effective, and sufficient physical protection systems. The purpose of this work is both to develop a framework for the integration of security into the design phase of High Temperature Gas Reactors (HTGRs) that utilize pebble-based fuels and increase the use of modeling and simulation tools to optimize the design of physical protection systems. Specifically, this effort focuses on integrating security into the design phase of a model HTGR that meets current Nuclear Regulatory Commission (NRC) physical protection requirements and providing advanced solutions to improve physical protection and decrease costs. A suite of tools, including SCRIBE3D©, PATHTRACE© and Blender© were used to model a hypothetical, generic domestic HTGR facility. Physical protection elements such as sensors, cameras, barriers, and guard forces were added to the model based on best practices for physical protection systems. Multiple outsider sabotage scenarios were examined with four-to eight adversaries to determine security metrics. The results of this work will influence physical protection system designs and facility designs for U.S. domestic HTGRs. This work will also demonstrate how a series of experimental and modeling capabilities across the Department of Energy (DOE) Complex can impact the design of and complete Safeguards and Security by Design (SSBD) for SMRs. The conclusions and recommendations in this document may be applicable to all SMR designs.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

U.S. Domestic Microreactor Security-by-Design

U.S. nuclear power facilities face increasing challenges in meeting dynamic security requirements caused by evolving and expanding threats while keeping cost reasonable to make nuclear energy competitive. The past approach has often included implementing security features after a facility has been designed and without attention to optimization, which can lead to cost overruns. Incorporating security in the design process can provide robust, cost effective, and sufficient physical protection systems. The purpose of this work is both to develop a framework for the integration of security into the design phase of a microreactor and increase the use of modeling and simulation tools to optimize the design of physical protection systems. Specifically, this effort focuses on integrating security into the design phase of a model microreactor that meets current Nuclear Regulatory Commission (NRC) physical protection requirements and providing advanced solutions to improve physical protection and decrease costs. A suite of tools, including SCRIBE3D©, PATHTRACE© and Blender© were used to model a hypothetical, generic domestic microreactor facility. Physical protection elements such as sensors, cameras, barriers, and guard forces were added to the model based on best practices for physical protection systems. Multiple outsider sabotage scenarios were examined with four-to-eight adversaries to determine security metrics. The results of this work will influence physical protection system designs and facility designs for U.S. domestic microreactors. This work will also demonstrate how a series of experimental and modeling capabilities across the Department of Energy (DOE) Complex can impact the design of and complete Safeguards and Security by Design (SSBD) for microreactors. The conclusions and recommendations in this document may be applicable to all microreactor designs.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2020

Development of a clostridia-based cell-free system for prototyping genetic parts and metabolic pathways

Gas fermentation by autotrophic bacteria, such as clostridia, offers a sustainable path to numerous bioproducts from a range of local, highly abundant, waste and low-cost feedstocks, such as industrial flue gases or syngas generated from biomass or municipal waste. Unfortunately, designing and engineering clostridia remains laborious and slow. The ability to prototype individual genetic part function, gene expression patterns, and biosynthetic pathway performance in vitro before implementing designs in cells could help address these bottlenecks by speeding up design. Unfortunately, a high-yielding cell-free gene expression (CFE) system from clostridia has yet to be developed. Here in this paper, we report the development and optimization of a high-yielding (236 ± 24 μg/mL) batch CFE platform from the industrially relevant anaerobe, Clostridium autoethanogenum. A key feature of the platform is that both circular and linear DNA templates can be applied directly to the CFE reaction to program protein synthesis. We demonstrate the ability to prototype gene expression, and quantitatively map aerobic cell-free metabolism in lysates from this system. We anticipate that the C. autoethanogenum CFE platform will not only expand the protein synthesis toolkit for synthetic biology, but also serve as a platform in expediting the screening and prototyping of gene regulatory elements in non-model, industrially relevant microbes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Integrated Mid-Continent Stacked Carbon Storage Hub Project Phase II (Final Summary Report)

The Phase II Integrated Midcontinent Stacked Carbon Storage Hub (IMSCS-HUB) is part of the Carbon Storage Assurance Facility Enterprise (CarbonSAFE) established by the United States Department of Energy (DOE) National Energy Technology Laboratory (NETL). CarbonSAFE is phased to support the development of commercial-scale (50 million metric tonnes [Mt] over a 30-year period) carbon capture, utilization, and storage (CCUS) in the United States. The IMSCS-HUB study area comprises carbon dioxide (CO 2 ) sources in Iowa, Kansas, and Nebraska (the source corridor), and CO 2 sinks in Kansas and Nebraska (the storage corridor), representing the first large-scale project for the Midcontinent region. The stacked storage corridor is characterized by alternating sequences of deep saline formations, oil-bearing reservoirs, shale, and evaporite units that are conducive to vertically stacked CO 2 injection for geologic storage and enhanced oil recovery (EOR). Three sites within the IMSCS-HUB stacked storage corridor were evaluated in Phase II for commercial CCUS feasibility: one in southwest-central Nebraska, Sleepy Hollow Field (SHF), a second in southwestern Nebraska near Madrid (Madrid), and a third in southwestern Kansas, the Patterson Site (composed of the Patterson, Heinitz, Hartland, and Oslo fields). In Phase II, the team assessed the feasibility of storage complexes at the potential storage sites in Nebraska and Kansas to support a commercial-scale storage hub that integrates proven CO 2 capture technology and transport from nearby ethanol sources. Building on lessons learned from the DOE-NETL Regional Carbon Sequestration Partnerships (RCSPs), the Project Team has identified a clear strategy to meet DOE’s 2025 objective of commercial carbon capture and storage (CCS) implementation by developing a CO 2 market and infrastructure that relies on multiple ethanol-based CO 2 sources in the short term and the incorporation of multiple coal-fired power plant CO 2 sources when commercial capture is economically viable. The team also leveraged the updated 45Q tax credit to develop capture and transport infrastructure. Commercial-scale CCUS is feasible at two candidate storage sites studied, the Madrid, Nebraska Site and the Patterson Site in Kearny County, Kansas. The Sleepy Hollow Field in Nebraska was found to be an attractive candidate for stacked storage with CO 2 -EOR (Battelle 2020e). Outreach efforts facilitated engagement from industry, government, and research sectors (Battelle and GPI, 2020) and an outreach plan for future phases of the project was developed to address issues that are of concern in the IMSCS-HUB project area (Battelle, 2020f). All components of a CCUS project were determined to be feasible in the IMSCS-HUB region and Risk Mitigation Plan was developed and includes strategies to mitigate risks associated with each project component (Battelle, 2020j). A roadmap was developed to obtain the required UIC permits for an integrated CCUS project (Battelle, 2020k). The regional storage resource characterization demonstrated significant opportunity for commercial-scale projects in the IMSCS-HUB storage corridor with 577.4 Mt of stacked CO 2 storage capacity and the potential to produce 181.9 MMbbls of oil via EOR across 17 individual storage areas (Battelle and ARI, 2020). The pipeline assessment study found viable pipeline routes that connected 45Q-eligible ethanol plants, coal fired power plants, and other sources in the IMSCS-HUB corridor. The comprehensive results of subsurface characterization, modeling efforts, outreach assessment, and regulatory analysis from were integrated to develop a Detailed Commercial Development Plan for the IMSCS-HUB (Battelle, 2020n). Commercialization efforts will involve obtaining Class VI UIC permits, establishing and finalizing the pipeline route, and evaluating capture projects at participating CO 2 sources. Phases I and II of the IMSCS-HUB CarbonSAFE provide a strong foundation for safely, efficiently, and cost-effectively characterizing and permitting commercial-scale project sites in the region. The plan for implementation of commercial-scale CCUS projects in the IMSCS-HUB is aligned with the objectives of CarbonSAFE Phase III: Site Characterization and CO 2 Capture Assessment.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2023

Advances in S. cerevisiae Engineering for Xylose Fermentation and Biofuel Production: Balancing Growth, Metabolism, and Defense

Genetically engineering microorganisms to produce chemicals has changed the industrialized world. The budding yeast Saccharomyces cerevisiae is frequently used in industry due to its genetic tractability and unique metabolic capabilities. S. cerevisiae has been engineered to produce novel compounds from diverse sugars found in lignocellulosic biomass, including pentose sugars, like xylose, not recognized by the organism. Engineering high flux toward novel compounds has proved to be more challenging than anticipated since simply introducing pathway components is often not enough. Several studies show that the rewiring of upstream signaling is required to direct products toward pathways of interest, but doing so can diminish stress tolerance, which is important in industrial conditions. As an example of these challenges, we reviewed S. cerevisiae engineering efforts, enabling anaerobic xylose fermentation as a model system and showcasing the regulatory interplay’s controlling growth, metabolism, and stress defense. Enabling xylose fermentation in S. cerevisiae requires the introduction of several key metabolic enzymes but also regulatory rewiring of three signaling pathways at the intersection of the growth and stress defense responses: the RAS/PKA, Snf1, and high osmolarity glycerol (HOG) pathways. The current studies reviewed here suggest the modulation of global signaling pathways should be adopted into biorefinery microbial engineering pipelines to increase efficient product yields.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Using PyBioNetFit to leverage qualitative and quantitative data in biological model parameterization and uncertainty quantification

Data generated in studies of cellular regulatory systems are often qualitative. For example, measurements of signaling readouts in the presence and absence of mutations may reveal a rank ordering of responses across conditions but not the precise extents of mutation-induced differences. Qualitative data are often ignored by mathematical modelers or are considered in an ad hoc manner, as in the study of Kocieniewski and Lipniacki (2013) [Phys Biol 10: 035006], which was focused on the roles of MEK isoforms in ERK activation. In this earlier study, model parameter values were tuned manually to obtain consistency with a combination of qualitative and quantitative data. This approach is not reproducible, nor does it provide insights into parametric or prediction uncertainties. Here, starting from the same data and the same ordinary differential equation (ODE) model structure, we generate formalized statements of qualitative observations, making these observations more reusable, and we improve the model parameterization procedure by applying a systematic and automated approach enabled by the software package PyBioNetFit. We also demonstrate uncertainty quantification (UQ), which was absent in the original study. Our results show that PyBioNetFit enables qualitative data to be leveraged, together with quantitative data, in parameterization of systems biology models and facilitates UQ. These capabilities are important for reliable estimation of model parameters and model analyses in studies of cellular regulatory systems and reproducibility.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

PDPTW-DB: MILP-Based Offline Route Planning for PDPTW with Driver Breaks

The Pickup and Delivery Problem with Time Windows (PDPTW) involves optimizing routes for vehicles to meet pickup and delivery requests within specific time constraints, a challenge commonly faced in logistics and transportation. Microtransit, a flexible and demand-responsive service using smaller vehicles within defined zones, can be effectively modeled as a PDPTW. Yet, the need for driver breaks—a key human constraint—is frequently overlooked in PDPTW solutions, despite being necessary for regulatory compliance. This study presents a novel mixed-integer linear programming formulation for the Pickup and Delivery Problem with Time Windows and Driver Breaks (PDPTW-DB). To the best of our knowledge this formulation is the first to consider mandatory periodic driver breaks within optimized Microtransit routes. The proposed model incorporates regulatory compliant break scheduling directly within the vehicle routing optimization framework. By considering driver break requirements as an integral component of the optimization process, rather than as a post-processing step, the model enables the generation of routes that respect hours of service regulations while minimizing operational costs. This integrated approach facilitates the generation of schedules that are operationally efficient and prioritize driver welfare through driver breaks. We work with a public transit agency from the southern USA, and highlight the specific nuances of driver break optimization, and present a Pickup and Delivery Problem with Time Windows formulation for optimizing Microtransit operations and scheduling driver breaks. We validate our approach using real-world data from the transit agency. Our results validate our formulation in producing cost-effective, and regulation-compliant solutions.

Applied Computing, Transportation↗
DOE OSTI2022

1.2.2.405 HydroWIRES Topic D1: Capacity Expansion Model (CEM) Enhancements

Long-term grid planning tools have difficulty representing detailed hydropower operating characteristics, which depend not only on technological specifications but also on water management practices and regulations. As a result, the value of hydropower is incompletely characterized, and the potential role of hydropower in the performance and resiliency of the future electric grid is not fully understood. This work will fill that gap by developing new ways to represent hydropower resource, technology, and operational characteristics in electric sector capacity expansion models and implementing them in the open-source version of the National Renewable Energy Laboratory's Regional Energy Deployment System (ReEDS) model. ReEDS is a well-established national scale grid planning tool used since 2003 by the U.S. Department of Energy and others to explore the evolution of the U.S. electric sector. Improvements will include a comprehensive national resource assessment for pumped storage hydropower and methods for modeling multiple hydropower technology categories characterized by technical, regulatory, and economic characteristics. The project will provide guiding principles and strategies for improving hydropower modeling in capacity expansion models and deliver a first-of-its kind versatile PSH dataset. All data, code, and methods will be publicly available, allowing the industry to better identify the value of hydropower in the future electricity system and make more informed planning decisions.

capacity expansion↗
DOE OSTI2022

Uncertainties in Local Intense Precipitation Flood Modeling

In the Task 1 report for the U.S. Nuclear Regulatory Commission (NRC) funded Local Intense Precipitation (LIP) Probabilistic Flood Hazard Assessment (PFHA) Pilot Study, the Pacific Northwest National Laboratory (PNNL) reviewed hydrologic and hydraulic modeling approaches for estimation of LIP flooding and their implementation in readily available simulation software packages (Prasad and Yuan 2020). NRC’s interest is in developing guidance for performing LIP PFHA at nuclear power plant (NPP) sites. This report describes the work done under Task 2 of the study that focused on describing uncertainties associated with LIP flood modeling. Two main types of uncertainties exist in LIP flood modeling: (1) aleatory uncertainties that arise from the inherent natural variability of the hydrometeorological system and (2) epistemic uncertainties that arise from the analysts’ incomplete knowledge of the hydrometeorological and site configuration. Principal sources for aleatory variability in LIP flood simulations at NPP sites include precipitation (i.e., magnitude, duration, and temporal distribution of LIP events), initial conditions (e.g., soil moisture content, stormwater drainage discharge, surface storage), boundary conditions (e.g., upstream discharge, downstream water surface elevations), and long-term temporal trends (e.g., climate change). This report describes approaches used for estimating the aleatory variability in precipitation including precipitation-frequency analysis, numerical weather prediction, and stochastic weather generation. Data sources that can be used to estimate aleatory variability in initial and boundary conditions are also described. Approaches to include effects of long-term trends like those from climate change into estimation of aleatory variability are summarized. Sources of epistemic uncertainty in LIP flood simulations at NPP sites include process representation (e.g., multiple approaches to represent runoff generation, stormwater drainage, and hydraulic routing), site configurations (e.g., site layout, flow features, status of temporary flood protection, blockage of drains), model resolution, and long-term temporal trends (e.g., known/planned site alterations, land-use changes at and in the vicinity of the site). The report describes alternative process representations (methods and models), particularly those implemented in the LIP flood simulation software packages reviewed in Task 1 report, and lists the associated model parameters. Approaches for estimating model parameters when surface and subsurface water exchanges occur are also described.

42 ENGINEERING↗
DOE OSTI2020

Consequence Analysis of Residual Water in a Storage Canister - 20484

Recent observations from projects sponsored under the DOE-Nuclear Energy Spent Fuel and Waste Disposition campaign show that residual free water, well above the 0.4 gm-moles that correspond to a 3 torr rebound pressure after a 30-minute hold following prototypic drying, may remain within SNF canisters used for long-term dry storage. Specifically, experimental observations in an Integrated Research Project showed subzero temperatures and a local pocket of frozen water in a mockup fuel assembly subjected to an industry practiced drying process. In gas sampling and analysis from the High Burnup (HBU) Demonstration project, using a fully loaded and dried SNF canister, indicated presence of 100 g of residual water had remained in the canister. The effects of residual water in terms of potential adverse impacts on the condition of the SNF and the canister internals during long-term dry storage has been rigorously evaluated to address inadvertent residual water contents. The impact of residual water on the fuel and canister internals, with a focus on the oxidation of the cladding and of postulated exposed (breached-clad) fuel, were evaluated using an integrated set of time-dependent environmental conditions with semi-empirical materials oxidation models. An 'integration model,' with coupled sub-models, developed and previously used by the Center for Nuclear Waste Regulatory Analysis (CNWRA), was applied and expanded with improved sub-models for water radiolysis, and for cladding and fuel oxidations. Cladding oxidation models for various alloys were developed using the rate constants for various cladding alloys in the dry storage temperature range. A burnup-dependent fuel oxidation model was developed; it accounted for inhibition effect of fission products on fuel oxidation rates. The potential for extension of the initial breach flaw (1 mm hole) was evaluated by two separate mechanics criteria. In the first case, a critical cladding strain criterion was used. In the second case, a critical stress intensity was used to evaluate stability of a planar axial flaw postulate. A failure condition exists when a sufficient amount of fuel oxidation (at the postulated breached-clad location) causes fuel pellet swelling to load the cladding to meet a mechanics criterion for flaw extension. The integration model's results provide the following insights. The radiolysis-generated oxygen is consumed with a partitioning between the cladding and the fuel. The extent of cladding oxidation is no more than 2 μm additional consumption of the cladding metal even with 10 moles of residual water, indicating that changes in cladding conditions due to water are expected to be negligible. The conditions for cladding failure (breach opening size extension) directly correlates with the extent of fuel oxidation. Fuel oxidation significant to extend the breach could occur even with 5.5 moles of residual water. The results indicate that fuel oxidation vis-a-vis cladding oxidation is more likely under a higher radiation field, i.e., when radiolytic decomposition of the residual water occurs in few years compared to several decades, and that the conditions to cause failure are increased with fuel and cladding temperatures approaching the peak storage temperature limit of 400 deg. C. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Enhancing Drinking Water Quality Modeling: Leveraging Physics Informed Neural Networks for Learning with Imperfect Reaction Models and Partial Data

Chemical kinetics models, typically formulated as systems of ordinary or partial differential equations, are valuable tools for simulating drinking water quality. However, these models often face inaccuracies due to discrepancies between the laboratory and the real-world conditions, as well as limitations in experimental analytical methods, hindering the accurate representation of the true underlying chemical mechanisms. In this study, we propose a Physics Informed Neural Network (PINN), using the eXtreme Theory of Functional Connections, to improve the prediction of chemical concentrations over time. The PINN method accounts for imperfect chemical models and incorporates partial data to improve predictions. Focusing on reactions describing water disinfection residual and disinfectant byproduct formation, which are crucial for public health and regulatory compliance, we demonstrate that the PINN model is able to accurately predict the concentrations of chemical species across various pH values. Notably, the model extends its accuracy to predict concentrations of chemical species not originally included in its training data. The developed method can be extended to a variety of chemical systems, offering a wide array of potential applications.

13 HYDRO ENERGY↗
DOE OSTI2020

A Comparison of RESRAD and GoldSim Models for Assessing Radiological Dose for a RCRA Landfill - 20418

US Ecology Idaho (USEI) operates a Resource Conservation and Recovery Act (RCRA) Subtitle C, Hazardous Waste Treatment, Storage, and Disposal (TSD) Facility on a 640-acre property in Owyhee County, Idaho. USEI accepts a wide variety of RCRA-exempt low activity radioactive wastes, including naturally occurring radioactive material (NORM) and technologically enhanced NORM (TENORM) (USEI 2009). The performance of the landfill with regard to radiological operating permit requirements was previously assessed using a model constructed with the residual radioactivity (RESRAD) computer program, developed by Argonne National Laboratory for the U.S. Department of Energy (DOE). RESRAD supports the evaluation of several environmental transport pathways related to a radionuclide-contaminated soil source term, but it was not conceived as a model for the evaluation of landfill radiological performance. A more comprehensive and realistic model is desired in order to better support submissions to both the State of Idaho's Department of Environmental Quality as well as the U.S. Nuclear Regulatory Commission. A Performance Assessment (PA) computer model was developed using GoldSim software for the USEI RCRA Subtitle C landfill. The RESRAD computer model was specifically developed for calculating soil cleanup criteria and radiological dose and cancer risk from residual radioactive material in soil. To evaluate site-specific conditions, users may select from among a number of available environmental transport and exposure pathways and modify 'default' parameter values. In GoldSim, a user must construct the model 'from scratch.' However, this modeling is facilitated by a number of specialized elements available in GoldSim to support a radiological mass transport model. These include elements for defining radiological decay and ingrowth, container failure and radiological release, advective and diffusive transport, and other processes. Advantages afforded by the use of RESRAD for modeling radiological dose for a RCRA Subtitle C landfill include ease of use and reasonable flexibility in specifying site-specific conditions. GoldSim allows for considerably more flexibility and site-specificity than RESRAD, including evaluation of potentially relevant environmental transport processes not supported in RESRAD. The probabilistic modeling capabilities of GoldSim also far exceed those of RESRAD. The pros and cons of RESRAD and GoldSim for this modeling problem are explored with a focus on identifying approaches and critical factors in identifying the appropriate platform. The capabilities of RESRAD and GoldSim for mathematically modeling the disposal system will be contrasted and compared. For example, the existing RESRAD radiological safety assessment evaluated potentially complete exposure pathways related to infiltration to groundwater and upwards diffusion of radon. Additional transport pathways identified in the USEI Idaho facility Conceptual Site Model include deposition of radon decay products in cover material, root uptake of radionuclides in disposed wastes by native plants, and mixing of cover material by burrowing animals. Results of the two models and how the different transport and dose pathways affect results will be discussed. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗