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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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Machine Learning script to predict groundwater ages based on auxiliary features in a publicly available dataset, based on publicly available software libraries. Code applied to data from the Groundwater Ambient Monitoring and Assessment (GAMA) program in California, including well location and construction information, chemical constituents and isotopic tracers, and land use metrics.
RAVEN is a software framework able to perform parametric and stochastic analysis based on the response of complex system codes. The initial development was aimed at providing dynamic risk analysis capabilities to the thermohydraulic code RELAP-7, currently under development at Idaho National Laboratory (INL). Although the initial goal has been fully accomplished, RAVEN is now a multi-purpose stochastic and uncertainty quantification platform, capable of communicating with any system code. In fact, the provided Application Programming Interfaces (APIs) allow RAVEN to interact with any code as long as all the parameters that need to be perturbed are accessible by input files or via python interfaces. RAVEN is capable of investigating system response and explore input space using various sampling schemes such as Monte Carlo, grid, or Latin hypercube. However, RAVEN strength lies in its system feature discovery capabilities such as: constructing limit surfaces, separating regions of the input space leading to system failure, and using dynamic supervised learning techniques. The development of RAVEN started in 2012 when, within the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, the need to provide a modern risk evaluation framework arose. RAVEN’s principal assignment is to provide the necessary software and algorithms in order to employ the concepts developed by the Risk Informed Safety Margin Characterization (RISMC) program. RISMC is one of the pathways defined within the Light Water Reactor Sustainability (LWRS) program. In the RISMC approach, the goal is not just to identify the frequency of an event potentially leading to a system failure, but the proximity (or lack thereof) to key safety-related events. Hence, the approach is interested in identifying and increasing the safety margins related to those events. A safety margin is a numerical value quantifying the probability that a safety metric (e.g. peak pressure in a pipe) is exceeded under certain conditions. Most of the capabilities, implemented having RELAP-7 as a principal focus, are easily deployable to other system codes. For this reason, several side activates have been employed (e.g. RELAP5-3D, any MOOSE-based App, etc.) or are currently ongoing for coupling RAVEN with several different software. The aim of this document is to provide a set of commented examples that can help the user to become familiar with the RAVEN code usage.
We assess how geospatial-temporal semantic graphs and our GeoGraphy code implementation might contribute to induced seismicity analysis. We focus on evaluating strengths and weaknesses of both 1) the fundamental concept of semantic graphs and 2) our current code implementation. With extensions and research effort, code implementation limitations can be overcome. The paper also describes relevance including possible data input types, expected analytical outcomes and how it can pair with other approaches and fit into a workflow.
This year, the Nuclear Energy Advanced Modeling Simulation program (NEAMS) thermal-hydraulics verification and validation (V&V) work has focused in three areas of Nek5000 V&V-driven development. First, in a close collaborative effort with the U. S. Nuclear Regulatory Commission (NRC) staff, we have continued V&V efforts for the HYMERES-2 project using the OECD/NEA sponsored testing in the PSI PANDA facility. This year’s focus of ANL-NRC collaboration involves Nek5000 setups and validation for a range of problems relevant to and including the HYMERES-2 benchmark from PSI. The primary outcome of this year efforts is a more efficient geometry and inlet modeling simplification after a careful sensitivity study of the inlet profiles and pipe geometries. The resulting modeling choice of a short recycling/fully-developed turbulent inlet is within the experimental uncertainty estimate. This finding simplifies the next step of the cross-V&V HYMERES-2 project. In addition, the ANL team continue to provide assistance to the NRC staff in the form of Nek5000 application support in general and on the use of the HPC platforms of ALCF and INL in particular. This supports the NRC’s assessment of Nek5000 for use with the NRC Blue CRAB code suite. Second, we have implemented and tested more robust model of URANS, namely the k – τ model, a variant of the k-ω model, along with other improvements to RANS Nek5000 modeling in general. Because of its demonstrated robustness and stability, the k – τ model is the only RANS model that has been implemented in the new GPU version of the Nek5000 code, nekRS. Lastly, we report the initial implementation of Jacobian-free Newton Krylov approach to the direct Newton method for steady fluid solvers aimed at acceleration of RANS modeling and at IC improvement for LES campaigns. Also leveraging the Exascale Computing Project (ECP) ANL/CEED & SMR team’s software development effort to support NEAMS problems at large scale of the advanced computing architectures, NekRS, a GPU variant of Nek5000, built on top of kernels from libParanumal using OCCA for portability, has been successfully run on the full system of Summit (4608 nodes, 27648 GPUs).
This project focuses on assessment and qualification of the SAS4A/SASSYS-1 advanced reactor safety analysis code and its capacity to fulfill requirements associated with license/authorization of a sodium-cooled fast reactor (SFR). Specific objectives of this proposal include: development of a formal documentation requirements matrix that complies with a vendor’s NQA-1 program to identify needs for qualification documentation; completion of software methods qualification gap analysis to identify and close gaps in the verification and validation basis of the software; generation of an Acceptance Test Report to confirm compliance with the software requirements specification; and closure of gaps in Software Design Description (SDD) to assist with the eventual generation of a Modeling Licensing Topic Report (LTR).
The United States nuclear industry is facing a strong challenge to ensure maximum safety while enhancing economic benefit. Safety is a key parameter to all aspects related to light water reactor (LWR) nuclear power plants (NPPs), especially cost savings. Since the goal is to extend the lifetimes of these NPPs, the traditional deterministic safety concept may not guarantee a current economic asset. The Light Water Reactor Sustainability (LWRS) Program has been promoting a wide range of research and development (R&D) in this field to maximize the safety, economics, and performance of these NPPs through improved scientific understanding. One of the best practices to achieve this goal is to identify and optimize safety margins, which can lead to cost reduction. To do this, under the LWRS framework, the Risk-Informed Systems Analysis (RISA) Pathway will focus on the optimization of safety margin and minimization of uncertainties to ensure both safety and economics at the highest level. The RISA Pathway will provide enhanced capabilities for analyzing and characterizing LWR systems performance by developing and demonstrating methods, tools, and data to enable risk-informed margins management (RIMM). The goals of the RISA Pathway are twofold: (1) deploy the risk-informed tools and methods that enable better representation of safety margins and factors that contribute to cost and safety; and (2) conduct advanced risk assessment applications with industry to support margin management strategies that enable more cost-effective plant operation. The tools and methods provided by the RISA Pathway will support effective margin management for both active and passive safety systems, structures, and components (SSC) of an NPP. The tools and methods used in the RISA Pathway should have high confidence and highest technical maturity for and implementation to industry at its current setting. They should also have a capability to support risk-informed decision making for both probabilistic and deterministic elements of safety. The RISA Pathway will, therefore, perform a comprehensive assessment of verification and validation (V&V) status of RISA Toolkit to enhance credibility RISA Toolkit which be used by industry. This report summarizes assessment technical maturity of RISA thermal-hydraulics accident analysis code RELAP5-3D and multi-purpose probabilistic risk analysis tool RAVEN V&V status including specific information of the tool such as capability and features, quality assurance program, developer/independent V&V record, separation/integral tests history, user documents, and feedback.
Hydrocodes were quickly adopted for planetary impact simulations and are now being combined with other codes (e.g. tsunami, atmospheric transport, general circulation, etc.) for hazard assessment and quantification.
The desire of the nuclear industry to improve the economics of existing nuclear power plants has necessitated research into the potential of a phenomenon known as fuel fragmentation, relocation, and dispersal (FFRD). This phenomenon is possible during a loss-of-coolant accident (LOCA) at relatively high burnup. The Nuclear Energy Advanced Modeling and Simulation program has been developing simulation capabilities for FFRD and LOCA in the BISON fuel performance code for multiple years. This year, the effort has been focused on evaluating new lower length scale informed pulverization thresholds as well as updating and adding new empirical models for various phenomena. Models added or updated this year include a preliminary transient fission gas release model, new high-temperature Zircaloy creep models, a Zircaloy rupture opening area model, and a temperature-dependent emissivity during radiation from the fuel rod to the surrounding atmosphere. The models are verified through implementation tests to demonstrate code correctness after addition to BISON. The models are then assessed against a subset of the existing BISON validation suite for LOCA and FFRD cases. Two new cases, Studsvik Rods 192 and 193, have been added. The results indicate that the inclusion of a bubble pressure evolution model in the bubbles in the high-burnup structure has the largest impact compared to the 3D fracture criterion on reducing the calculated amount of pulverized fuel.
We are reporting on the modeling of fusion alpha particle transport in the planned ARC fusion device being designed by the CFS (Commonwealth Fusion Systems: https://cfs.energy). The ARC tokamak is designed to operate in a burning-plasma regime characterized by a substantial population of fusion-born alpha particles. Alfvén eigenmode (AE) stability is assessed both analytically and numerically, incorporating alpha-particle drive, ion Landau, and radiative damping from thermal species and collisional damping from trapped electrons. Regions of unstable and near-threshold AE activity are mapped across ARC’s operational parameter space. Linear stability analysis with NOVA indicates multiple, often marginally unstable AEs, extending to toroidal mode numbers up to n= 30. The present report focuses on the ARC flat-top operating point prior to the sawtooth event. Alpha-particle transport on timescales exceeding the neoclassical slowing-down time is assessed using the NUBEAM module [1][2] of the TRANSP code [3], employing transport coefficients derived from the RBQ quasilinear modeling (cf. Appendix B). These global simulations identify favorable and unfavorable operating regimes with respect to alpha confinement, pressure redistribution, and overall alpha-heating efficiency. We also evaluate additional transport mechanisms—including neoclassical tearing mode (TM)–induced stochasticity, sawtooth-driven redistribution, and toroidal-field ripple using the kick model (cf. Appendix C) which makes use of the guiding-center code ORBIT, see Section 5. The kick model is integrated into TRANSP to enable self-consistent predictions of alpha-driven current formation and sustainment within the ARC scenario. Sensitivity scans are performed over the mode frequency, rational-surface alignment, island width, mode amplitude, and proximity of the limiter to the plasma. Our study provides an initial, physics-based guidance for machine design, operational planning, and equilibrium control, ensuring adequate alpha confinement and robust self-heating performance in ARC. Our simulations mostly targeted worst case scenarios, e.g. for TMs and sawteeth. Overall, we expect benign effects for the ARC scenario investigated in this work on fusion alpha confinement and losses in the presence of AEs, tearing modes and sawteeth. This report addresses three thrusts identified at the outset. The first thrust focuses on analytic estimates of the parametric dependencies of EP relaxation based on local AE stability simulations (Section 3). The second thrust involves global evaluations of AE stability using the NOVA, RBQ, and NUBEAM codes (Section 4). Finally, we investigate alpha-particle transport driven by low-frequency instabilities associated with sawteeth and tearing modes (Section 5).
The morphology of electrode materials plays a crucial role in determining the performance of lithium-ion batteries. Traditional computational models often simplify graphite flakes as uniformly sized spheres, which limits their predictive accuracy. In this study, we present a computational workflow that overcomes these limitations by incorporating a more realistic representation of graphite morphologies. This workflow is designed to be flexible and reproducible, enabling efficient evaluation of electrochemical performance across diverse material structures. By exploring different graphite morphologies, our approach accelerates the optimization of material preparation techniques and processing conditions. Our findings reveal that incorporating greater morphological complexity leads to significant deviations from classical model predictions. Instead, our refined model offers a more accurate representation of battery discharge behavior, closely aligning with experimental data. This improvement underscores the importance of detailed morphological descriptions in advancing battery design and performance assessments. To promote accessibility and reproducibility, we provide the developed code for seamless integration with the COMSOL API, allowing researchers to implement and adapt it easily. This computational framework serves as a valuable tool for investigating the impact of graphite morphology on battery performance, bridging the gap between theoretical modeling and experimental validation to enhance lithium-ion battery technology.
In this paper we propose IRTR-DETR an Interactive and Real-Time Rotated DEtection TRansformer that extends IRTDETR to predict rotated bounding boxes. IRTR-DETR maintains the Human-In-The-Loop (HIL) workflow of IRTDETR but introduces rotation-aware heads for improved detection of objects with arbitrary orientations. Similarly to IRTDETR IRTR-DETR can be trained with a small labeled sample set in an interactive setting but we show that it can also be pretrained on related but not identical data--such as a building damage dataset--before being applied to tasks like identifying buildings under construction. We demonstrate the efficacy of our approach on the publicly available Tiny-DOTA and xBD dataset as well as two study-cases on proprietary datasets of greenhouses and houses under construction ("waffle homes"). Detecting greenhouses is highly relevant in the context of damage assessment while "waffle homes" aid understanding typical floorplans and building codes in different areas both thereby supporting population modeling emergency response and policy planning. Our method outperforms the state of the art in interactive rotated object detection on the Tiny-DOTA dataset by 5.7 percent and improves upon the non interactive RTDETR by 7.85 to 19.39 percent (depending on the number of provided samples) while maintaining its real-time efficiency.
Fuel performance modeling codes that accurately predict the transport of radionuclides in high-temperature gas-cooled reactors that utilize tristructural isotopic (TRISO) fuel particles are an important aspect of reactor safety analyses. One objective of the Advanced Gas Reactor (AGR)-3/4 experiment was to assess the transport of fission products through fuel particles and their subsequent release into the compact matrix and structural graphite materials. This was accomplished by irradiating uranium oxycarbide (UCO) driver fuel particles and designed-to-fail (DTF) particles to serve as known sources of fission products. The fission product of particular interest when it comes to such transport is silver (Ag-110 m), as it has a 250-day half-life and has relatively high mobility in the TRISO coating layers. Furthermore, to assess the current modeling capabilities and diffusion parameters employed in the fuel performance codes PARFUME and BISON, the fractional release of silver release predicted by the two codes were compared against post-irradiation examination measurements from the AGR-3/4 experiment.
Code verification plays an important role in establishing the credibility of computational simulations by assessing the correctness of the implementation of the underlying numerical methods. In computational electromagnetics, the numerical solution to integral equations incurs multiple interacting sources of numerical error, as well as other challenges, which render traditional code-verification approaches ineffective. In this paper, we provide approaches to separately measure the numerical errors arising from these different error sources for the method-of-moments implementation of the combined-field integral equation. Here, we demonstrate the effectiveness of these approaches for cases with and without coding errors.
This report describes an assessment of sodium fast reactor assemblies loaded inside a Transnuclear B1 package. The assessment was performed to determine the state of the validation basis for sodium fast reactor fuel within a transportation package originally intended for fresh, light-water reactor fuel assemblies. The study employed the TSUNAMI-3D and TSUNAMI-IP sequences from the SCALE code system to determine correlation coefficients between various configurations and databases of validation assessments.
The U.S. Nuclear Regulatory Commission has stated that mechanistic source term (MST) calculations are expected to be required as part of the advanced reactor licensing process. A recent study by Argonne National Laboratory has concluded that fission product scrubbing in sodium pools is an important aspect of an MST calculation for a sodium-cooled fast reactor (SFR). To model the phenomena associated with sodium pool scrubbing, a computational tool, developed as part of the Integral Fast Reactor (IFR) program, was utilized in an MST trial calculation. This tool was developed by applying classical theories of aerosol scrubbing to the decontamination of gases produced as a result of postulated fuel pin failures during an SFR accident scenario. The model currently considers aerosol capture by Brownian diffusion, inertial deposition, and gravitational sedimentation. The effects of sodium vapour condensation on aerosol scrubbing are also treated. This paper provides details of the individual scrubbing mechanisms utilized in the IFR code as well as results from a trial mechanistic source term assessment led by Argonne National Laboratory in 2016.
This report surveys current creep-fatigue design and fitness-for-service assessment procedures, with a particular focus on environmental effects and creep-fatigue cracking near weldments. Included in this assessment are the American Society of Mechanical Engineers Boiler and Pressure Vessel Code Section III, Division 5, the British R5 standard, the French RCC-MRx design code, the ITER Structural Design Criteria, and the API-579/ASME FFS-1 fitness-for-service rules for petrochemical components. The focus of this review is to identify gaps in the available methods that could prevent regulators from evaluating future high temperature reactor designs. The report makes recommendations, where appropriate, on actions that could be taken to fill these gaps by either providing adequate assessment procedures for creep-fatigue damage in harsh environments or by evaluating strategies vendors could use to mitigate regulatory concerns with creep-fatigue damage in high temperature reactor components.
In this report, the activities and achievements made by Argonne National Laboratory for the Nuclear Energy Advanced Modeling and Simulation (NEAMS) BISON code metallic fuel validation and verification (V&V) project in FY2023, with a focus on the capability development and assessment case development for the out-of-pile transient experiments, are summarized. The liquid cladding penetration model was improved based on a comprehensive set of fuel behavior test apparatus (FBTA) test results. The new model was implemented into BISON along with a simple model to account for fuel melting effects. The metallic fuel meshing capability was also upgraded to allow local refinement using unstructured triangular mesh. Based on the previous success in developing the BISON-FIPD integration powered BISON assessment case, this database enabled BISON evaluation and V&V capability was expanded to the out-of-pile transient experiments by introducing BISON-OPTD integration. A series of initial out-of-pile transient assessment cases were implemented into BISON to provide powerful platforms to evaluate current BISON’s capabilities in simulating metallic fuel performance during out-of-pile transients. The established capabilities will also benefit the calibration and V&V of future advanced mechanistic models.
The Level 1 Milestone, L1:CASL.P13.03, “Assess the analysis capability for core-wide PWR Pellet-Clad Interaction (PCI) screening and demonstrate detailed 3-D analysis on selected sub-region.”, has been completed by the Fuels, Materials and Chemistry and Physics Integration focus areas of CASL. This report illustrates the application of VERA simulation to PWR core-wide PCI screening, with emphasis on the multi-dimensional analysis capabilities of BISON fuel performance code. The VERA codes utilized in this effort are: the fuel performance code BISON and the VERA-CS sub-element, which combines the neutron transport code MPACT and the thermal-hydraulics code COBRA-TF (CTF). The target reactor for this work is Watts Bar Unit 1, Cycles 6 and 7, selected on the basis that PCI failures had occurred during power start-up in both cycles, despite the moderate power levels, which offered an interesting test of the code’s veracity and a particularly challenging condition for this Milestone’s assessment. The analysis began by performing BISON-IN-VERA, i.e. VERA-CS + BISON, quarter-core depletion calculations, from which limiting assemblies and limiting fuel rods were selected using a four-parameter selection criterion: high power, high temperature, small gap thickness and high cladding hoop stress. The cladding material being Westinghouse Zirlo, the analysis utilized a new material model developed for this cladding by CASL’s FMC team using open literature sources. The VERA-CS + BISON analysis resulted in identifying 51 limiting rods as candidates for more detailed PCI analysis using stand-alone BISON, employing local 2D and 3D geometric models. This local-effects BISON analysis provided detailed PCI failure assessment, considering the impact of power histories on the two potential sources of PCI failure: the classical SCC-PCI and the missing pellet surface geometry MPS-PCI. The 51-rod analyses of Watts Bar Unit 1 cycle 6 and 7 revealed that the classical SCC-PCI stress levels were well below the failure threshold determined in a previous CASL study, which implicated the other mode of failure, namely MPS-PCI. Considering MPS defects to be the root cause for the failure, the local-effects calculations was repeated using MPS defect sizes equal to and larger than Westinghouse quality assurance standards. Initial results of this new analysis showed a significant increase in the cladding stress, indicating that an MPS may have been present in cycle 6 and 7 for the failure to occur. In order to determine the size of MPS needed for cycle 6 and 7 rods to fail, a sensitivity study using 2-D and 3-D models was performed. The results showed cladding hoop stresses, while remaining below the failure level for an MPS of equal size to the acceptance standard, continued to increase as the size of the MPS increased. This report has demonstrated the use of BISON, in consort with VERA’s simulation methodology, for core-wide PCI failure screening capability. Utilizing this demonstration, and emulating the PCI margin analysis methodology developed in the EPRI PCI guidelines, BISON-IN-VERA simulation can be used very effectively to develop core power histories to minimize PCI failure potential.