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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

AIF for Vis (Active Inference for simulating human interpretation of data visualization) [SWR-26-084]

AIF for Vis contains the Active Inference models and analysis scripts used to study a simple visualization-interpretation task: estimating the average value of two bars in a bar chart. The work is a proof of concept for translating hypothesized cognitive strategies into executable, inspectable process models. We implement two idealized strategies inspired by dual-process accounts of visualization-aided decision making: *Fast model: a compressed, heuristic strategy that estimates the visual midpoint of the two bars and maintains a single belief over their average. *Slow model: a sequential, analytic strategy that estimates the two bar heights separately and maintains them in working memory before computing an average. Both models use a common Active-Inference-inspired framework for sequential perception, belief updating, action selection, and reporting. Their different internal representations produce distinct predicted vulnerabilities: *the Fast model is more susceptible to tick-salience bias; *the Slow model is more susceptible to working-memory decay. The repository includes the model implementations, scripts used for the experiments reported in the paper, precomputed trial-level results, and plotting scripts.

Goldwyn, Harrison [National Laboratory of the Rock↗
DOE OSTI2024

MOOSE-Workbench integration and MOOSE meshing capability enhancements to facilitate inputs and outputs for multiphysics modeling

The Multiphysics Object-Oriented Simulation Environment (MOOSE) is an open-source framework that supports many of the US Department of Energy’s (DOE’s) Nuclear Energy Advanced Modeling and Simulation (NEAMS) technical areas (TA). These TAs develop and use NEAMS physics and coupling modules in multiple ways to enable the research and development of complex physics models. In addition to the MOOSE framework, the NEAMS Workbench user interface provides a common analysis environment with user-interaction accelerators that streamline the tasks of model creation, review, execution, and out put inspection. In FY 2024, objectives were realized in the MOOSE framework application development support and user-oriented improvements. Application development improvements support both developers and users with an expanded Reactor Module and Mesh System, stateful material property support for mortar contact, and customizable convergence criteria. Additionally, new user-oriented features were implemented in the MOOSE framework language server, including autocompletion snippets, definition from source and find reference navigations, and syntax overrides. Lastly, improvements were made to the input interpreter necessary to support the MOOSE language server and the NEAMS Workbench so that they can interact with syntactically incomplete user inputs. These improvements and more were intended to address stakeholder feedback and improve developer and user ability to conduct advanced nuclear energy modeling and simulation in support of DOE and industry needs.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

MOOSE–Workbench Integration and MOOSE Meshing Capability Enhancements to Facilitate Inputs and Outputs for Multiphysics Modeling

The Multiphysics Object-Oriented Simulation Environment (MOOSE) is an open-source framework that supports many of the US Department of Energy’s (DOE’s) Nuclear Energy Advanced Modeling and Simulation (NEAMS) technical areas (TA). These TAs develop and use NEAMS physics and coupling modules in multiple ways to enable the research and development of complex physics models. In addition to the MOOSE framework, the NEAMS Workbench user interface provides a common analysis environment with user-interaction accelerators that streamline the tasks of model creation, review, execution, and output inspection. In FY 2024, objectives were realized in the MOOSE framework application development support and user-oriented improvements. Application development improvements support both developers and users with an expanded Reactor Module and Mesh System, stateful material property support for mortar contact, and customizable convergence criteria. Additionally, new user-oriented features were implemented in the MOOSE framework language server, including autocompletion snippets, definition from source and find reference navigations, and syntax overrides. Lastly, improvements were made to the input interpreter necessary to support the MOOSE language server and the NEAMS Workbench so that they can interact with syntactically incomplete user inputs. These improvements and more were intended to address stakeholder feedback and improve developer and user ability to conduct advanced nuclear energy modeling and simulation in support of DOE and industry needs.

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2024

WETO Stack [SWR-24-81]

The WETO Stack software is a collection of data, data analysis scripts, and website content produced through the Holistic Modeling Project’s Portfolio Coordination task. The purpose of the software is to characterize the collection of wind energy software projects supported by the U.S. Department of Energy’s Wind Energy Technologies Office. The included data contains characteristics of the actively funded software projects, and the data analysis scripts provide insights into the breadth, depth, and maturity of the collection of software projects. The website content presents the results of the analyses as well as reports from workshops and other events. It can be viewed at https://nrel.github.io/WETOStack/index.html.

Mudafort, Rafael↗
DOE OSTI2025

Geothermal Reservoir Simulation Analysis in Support of Electricity Co-Production Feasibility Study at the Blackburn Oil Field, Nevada

Geothermal electricity co-production is a viable option for oil reservoirs producing large water cuts with elevated wellhead temperatures. Repurposing existing oil wells significantly reduces initial investment costs historically associated with geothermal resource utilization. The National Renewable Energy Laboratory (NREL), partnering with Gradient Geothermal, Inc. (formerly known as Transitional Energy) and Grant Canyon Oil and Gas, has been tasked to evaluate the feasibility of geothermal electricity co-production at the Blackburn Oil Field with Organic Rankine Cycle (ORC) generators. The Devonian steady-state reservoir has historically been producing high water cuts of 240 degrees F (115.6 degrees C) observed at the wellhead without documented pressure drawdown or thermal breakthrough. An estimated initial reservoir temperature of approx. 260 degrees F (126.7 degrees C) has been observed in the field and history-matched in a wellbore production analysis and reservoir simulation. Our objective was to develop a conceptual geological model of the subsurface, simulate a natural-state reservoir, model production scenarios, and complete a technical feasibility analysis to accomplish this task. Through extensive modeling and the use of available proprietary and public data, it was possible simulate three scenarios that indicated minimal thermal decline over the duration of a simulated ten-year production and re-injection scheme.

Blackburn Nevada↗
DOE OSTI2024

Geothermal Reservoir Simulation Analysis in Support of Electricity Co-Production Feasibility Study at the Blackburn Oil Field, Nevada: Preprint

Geothermal electricity co-production is a viable option for oil reservoirs producing large water cuts with elevated wellhead-observed temperatures. Repurposing existing oil wells significantly reduces initial investment costs historically associated with geothermal resource utilization. The National Renewable Energy Laboratory (NREL), partnering with Gradient Geothermal, Inc. (formerly known as Transitional Energy) and Grant Canyon Oil and Gas, has been tasked to evaluate the feasibility of geothermal electricity co-production at the Blackburn Oil Field with Organic Rankine Cycle (ORC) generators. The Devonian steady-state reservoir has historically been producing high water cuts of 240 degrees F (115.6 degrees C) observed at the wellhead without documented pressure drawdown or thermal breakthrough. An estimated initial reservoir temperature of approx. 260degreesF (126.7 degrees C) has been observed in the field and history-matched in a wellbore production analysis and reservoir simulation. Our objective was to develop a conceptual geological model of the subsurface, simulate a natural-state reservoir, model production scenarios, and complete a technical feasibility analysis to accomplish this task. Through extensive modeling and the use of available proprietary and public data, it was possible simulate three scenarios that indicated minimal thermal decline over the duration of a simulated ten-year production and re-injection scheme.

Blackburn Nevada↗
DOE OSTI2026

- Analysis of a suspended cylinder in a wave basin

The Offshore Code Comparison, Collaboration, Continued, with Correlation (OC5) is an international research project run under the International Energy Agency (IEA) Wind Task 30. The project is focused on validating the tools used design offshore wind systems. OC5 consists of four phases. Phase 1a: Analysis of a suspended cylinder in a wave basin This website provides the data used for validation in these four phases, as well as simulation results from multiple participants.

17 WIND ENERGY↗
DOE OSTI2024

Quantum-centric supercomputing for materials science: A perspective on challenges and future directions

Computational models are an essential tool for the design, characterization, and discovery of novel materials. Computationally hard tasks in materials science stretch the limits of existing high-performance supercomputing centers, consuming much of their resources for simulation, analysis, and data processing. Quantum computing, on the other hand, is an emerging technology with the potential to accelerate many of the computational tasks needed for materials science. In order to do that, the quantum technology must interact with conventional high-performance computing in several ways: approximate results validation, identification of hard problems, and synergies in quantum-centric supercomputing. Here in this paper, we provide a perspective on how quantum-centric supercomputing can help address critical computational problems in materials science, the challenges to face in order to solve representative use cases, and new suggested directions.

36 MATERIALS SCIENCE↗
DOE OSTI2026

The Role of Nuclear Data Sensitivities in Prompt α-Eigenvalue Predictions of Delayed Critical Benchmarks

Alpha (α) eigenvalues, which describe the logarithmic time derivative of the neutron population in a multiplying system, are integral to time-dependent behavior and diagnostic applications. However, uncertainties in the evaluated nuclear data can significantly impact the accuracy of transport simulations for such quantities. This work explores the use of machine learning models to predict two key outputs, α-eigenvalues and keff bias, using input features derived from α-eigenvalue sensitivities to nuclear data. The criticality safety benchmark models used in this study come from the International Handbook of Evaluated Criticality Safety Benchmark Experiments. Three models, random forest, XGBoost, and NGBoost, are trained on both energy-resolved and energy-summed α sensitivities. For the α-eigenvalue bias prediction, NGBoost achieved the highest R 2 (0.9476) using energy-resolved features, while XGBoost performed best using summed sensitivities. In contrast, when predicting the keff bias, all the models showed moderate predictive capability (best R 2 ≈ 0.72), as the mapping from the static α-sensitivities to the static keff bias was less direct. SHAP (SHapley Additive exPlanations) analysis was used to interpret the model predictions. Across both prediction tasks, the features associated with neutron capture [H-1 (n, γ)], uranium scattering reactions (such as 235 U elastic/inelastic), and actinide capture/fission reactions (such as 239 Pu and 234 U) were consistently identified as the most impactful. This highlights the key role of specific nuclear reactions and energy ranges in shaping both time-dependent and steady-state criticality behavior. These results demonstrated that α-sensitivities, despite being computed for time-dependent metrics, can provide valuable insights for predicting both α-eigenvalues and the keff bias. Moreover, machine learning models offer a promising pathway for uncovering important nuclear data dependencies and guiding future data evaluation efforts.

Nuclear data↗
DOE OSTI2024

FLARE: field line analysis and reconstruction for 3D boundary plasma modeling

The FLARE code is a magnetic mesh generator that is integrated within a suite of tools for the analysis of the magnetic geometry in toroidal fusion devices. A magnetic mesh is constructed from field line segments and permits fast reconstruction of field lines in 3D boundary plasma codes such as EMC3-EIRENE. Both intrinsically non-axisymmetric configurations (stellarators) and those with symmetry breaking perturbations of an axisymmetric equilibrium (tokamaks) are supported. The code itself is written in Modern Fortran with MPI support for parallel computing, and it incorporates object-oriented programming for the definition of the magnetic field and the material surface geometry. Extended derived types for a number of different magnetohydrodynamic equilibrium and plasma response models are implemented. The core element of FLARE is a field line tracer with adaptive step-size control, and this is integrated into tools for the construction of Poincaré maps and invariant manifolds of X-points. A collection of high-level procedures that generate output files for visualization is build on top of that. The analysis modules are build with Python frontends that facilitate customization of tasks and/or scripting of parameter scans.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

What Is the Limit of Quantification for the Minor Phase in Time-of-Flight Neutron Diffraction? A Case Study on Fe and Ni Powder Mixtures at VULCAN

A phase present in small quantities within materials may not simply serve as a secondary component; it can play a crucial role in determining the integrity, properties, and performance of the material. These minor but important phases usually draw attention in material design and processing for fundamental understanding as well as material quality control. Accurately quantifying a minor phase amid a majority phase, especially at extremely low fractions, remains a challenging task. Time-of-flight neutron diffraction, coupled with advanced pattern analysis techniques like Rietveld refinement, is a powerful tool for crystal structure identification and phase quantification. The deep penetrating capability of neutrons enables the detection and quantification of trace phases within materials. In this study, the quantification limits of time-of-flight neutron diffraction were explored using the VULCAN diffractometer at the Spallation Neutron Source, using Fe–Ni powder mixtures as a sample system. By comparing the refinement results to the known weighed values, it was determined that the reliable quantification of a minor Ni phase is achievable down to about 0.1 wt% while a Ni fraction as low as 0.02 wt% is difficult to trace. Effective control of the refinement parameters, especially the profile function parameters, are found to significantly influence the convergence of fittings and the accuracy of phase quantification.

Rietveld refinement↗
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 OSTI2026

- Analysis of a fixed-bottom cylinder in a wave basin

The Offshore Code Comparison, Collaboration, Continued, with Correlation (OC5) is an international research project run under the International Energy Agency (IEA) Wind Task 30. The project is focused on validating the tools used design offshore wind systems. OC5 consists of four phases. • Phase 1b: Analysis of a fixed-bottom cylinder in a wave basin This website provides the data used for validation in these four phases, as well as simulation results from multiple participants.

17 WIND ENERGY↗
DOE OSTI2024

Risk-Aware Framework Development for Disruption Prediction: Alcator C-Mod and DIII-D Survival Analysis

Abstract Survival regression models can achieve longer warning times at similar receiver operating characteristic performance than previously investigated models. Survival regression models are also shown to predict the time until a disruption will occur with lower error than other predictors. Time-to-event predictions from time-series data can be obtained with a survival analysis statistical framework, and there have been many tools developed for this task which we aim to apply to disruption prediction. Using the open-source Auton-Survival package we have implemented disruption predictors with the survival regression models Cox Proportional Hazards, Deep Cox Proportional Hazards, and Deep Survival Machines. To compare with previous work, we also include predictors using a Random Forest binary classifier, and a conditional Kaplan-Meier formalism. We benchmarked the performance of these five predictors using experimental data from the Alcator C-Mod and DIII-D tokamaks by simulating alarms on each individual shot. We find that developing machine-relevant metrics to evaluate models is an important area for future work. While this study finds cases where disruptive conditions are not predicted, there are instances where the desired outcome is produced. Giving the plasma control system the expected time-to-disruption will allow it to determine the optimal actuator response in real time to minimize risk of damage to the device.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

- Analysis of a scaled wind turbine on a floating semisubmersible in an ocean basin

The Offshore Code Comparison, Collaboration, Continued, with Correlation (OC5) is an international research project run under the International Energy Agency (IEA) Wind Task 30. The project is focused on validating the tools used design offshore wind systems. OC5 consists of four phases. • Phase 2: Analysis of a scaled wind turbine on a floating semisubmersible in an ocean basin This website provides the data used for validation in these four phases, as well as simulation results from multiple participants.

17 WIND ENERGY↗
DOE OSTI2024

Numerical Simulation and Experimental Comparison of System Analysis Module 1D Mixing Model for Cold Shock Transients in the Gallium Thermal-Hydraulic Mixing Facility

Abstract Liquid metals are being investigated as coolants in many advanced reactor designs because of their high thermal conductivity and effectiveness at high temperatures. However, they often pose challenges to reactor operation and safety because of the complex thermal mixing and stratification in the plenum of pool-type reactor designs. The advanced system analysis code System Analysis Module (SAM) currently under development at Argonne National Laboratory aims to develop and implement thermal mixing models to accurately capture these complex thermal fluid behaviors. In this study, the SAM thermal mixing model was compared against experimental data from the Gallium Thermal-Hydraulic Experiment facility, a scaled liquid metal test facility that uses gallium as a surrogate fluid to investigate the stratification and thermal mixing of low-Prandtl-number fluids in the upper plenum of a liquid metal-cooled reactor. Two cold shock transient cases were used: one with stable stratified flow (Ri = 32) and one with stronger thermal mixing (Ri = 0.5). The resultant temperatures were then compared with the experimental temperatures over the entire plenum to assess the ability of the mixing models to capture the thermal behavior and to better correspond mixing parameters to various flow scenarios. Generally, the zero-dimensional mixing model was more capable of capturing the bulk temperature of the component modeled assuming that an accurate mass flow rate was provided, but it was inherently unable to capture thermal gradients in space. The one-dimensional mixing model was capable of capturing that the thermal gradients provided accurate selection of the mixing coefficients. Further, the temperature at the outlet junction was compared over time for each of the mixing models with the recorded experimental temperature. The implemented mixing models demonstrated the ability to effectively capture the overall thermal behavior for stronger mixing scenarios but struggled with more stably stratified flows. It was found that a system analysis code's covering of the entire range of different operating conditions still remains a challenging task, and it is suggested that further model and closure improvements are necessary to accurately capture complex thermal mixing and stratification phenomena.

stratification↗
DOE OSTI2025

TCCSP Site Characterization and Feasibility Report

The Tulare County Carbon Storage Project (TCCSP) focused on establishing the geological and commercial viability of a 50 million metric ton (MMT) carbon storage complex located in Tulare County, California. The geologic scope of work included collecting new and existing subsurface data, such as two-dimensional (2D) seismic data, advanced geophysical logs, core and fluid samples, and specialized core-analysis datasets, to support the integration and interpretation of findings from earlier tasks. These efforts contributed to the comprehensive feasibility study for commercial carbon capture and storage (CCS) development at the TCCSP site and in the surrounding region. The TCCSP project team evaluated the feasibility of the Lower Monterey Group (Santa Margarita Sand Member or its equivalent), Temblor Formation sand members (Olcese, Jewett, Vedder), and Lodo-Martinez Zone (Domengine Sandstone, Walker Formation, Lodo Formation, and the Martinez Sand) to serve as commercial CCS reservoirs along with potential for the Upper Monterey Group (Reef Ridge, Antelope Members) and the Kreyenhagen Formation to vertically seal underlying reservoirs from shallow above-zones.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗