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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 991 records · Page 55
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Threadsafe Dynamic Neighbor Lists for Monte Carlo Ray Tracing

Monte Carlo (MC) transport codes offer high-fidelity modeling of particle transport physics, but their high computational cost makes them impractical for many applications. For some applications such as multiphysics and depletion that use finely discretized geometries, a large portion of this computational cost is attributable to ray tracing. Neighbor lists are a well-known method for accelerating ray-tracing calculations in a MC code, but despite their prevalence, little work has been published on the details of their implementation. The fine details can have a significant impact on performance, particularly when using shared-memory parallelism. This paper addresses these details of implementation with a discussion of different neighbor list schemes and their impact on software runtime. Performance tests were run by using OpenMC on a pin-cell problem discretized with up to 200 axial regions. The results demonstrate that switching from surface-based to cell-based neighbor lists leads to a 10 faster calculation rate for the most fine discretization. Finally, using a threadsafe shared-memory data structure results in a 20% faster calculation rate versus simple threadprivate neighbor lists. Results here show that a data structure that is contiguous in memory improves performance by only 1% to 2% over noncontiguous linked lists.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Serpent and MCNP Calculations of the Energy Deposition in the Transformational Challenge Reactor

This paper focuses on the calculation of the energy deposition in the Transformational Challenge Reactor by two major Monte Carlo codes: Serpent and MCNP. The first software computation relies on Kinetic Energy Released per unit Mass (KERMA) factors while the second one relies on Q-values. The results from these two independent computation methodologies are in very good agreement; however, Serpent runs much faster than MCNP (for the same computational model) and allows for a detailed energy deposition distribution from a 1-mm-side square mesh with a relative statistical error between 0.5% and 1%. This detailed energy deposition is suitable for multiphysics analyses aimed at design optimizations. In order to calculate the energy deposition, Serpent needs enhanced ACE files (distributed by the software developers). Unlike other Monte Carlo software that uses inputs based on Python or Java languages, the Serpent input syntax is very similar to that of MCNP; a Python script can convert a MCNP input to a Serpent input in seconds. For simulations not requiring the calculation of the energy deposition, Serpent can also read nuclear data from MCNP ACE files, which eventually improves the comparison of the results of the two codes.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Deep Learning for Multigroup Cross-Section Representation in Two-Step Core Calculations

Here we investigate using deep learning, a type of machine-learning algorithm employing multiple layers of artificial neurons, for the mathematical representation of multigroup cross sections for use in the Griffin reactor multiphysics code for two-step deterministic neutronics calculations. A three-dimensional fuel element typical of a high-temperature gas reactor as well as a two-dimensional sodium-cooled fast reactor lattice are modeled using the Serpent Monte Carlo code, and multigroup macroscopic cross sections are generated for various state parameters to produce a training data set and a separate validation data set. A fully connected, feedforward neural network is trained using the open-source PyTorch machine-learning framework, and its accuracy is compared against the standard piecewise linear interpolation model. Additionally, we provide in this work a generic technique for propagating the cross-section model errors up to the k eff using sensitivity coefficients with the first-order uncertainty propagation rule. Quantifying the eigenvalue error due to the cross-section regression errors is especially practical for appropriately selecting the mathematical representation of the cross sections. We demonstrate that the artificial neural network model produces lower errors and therefore enables better accuracy relative to the piecewise linear model when the cross sections exhibit nonlinear dependencies; especially when a coarse grid is employed, where the errors can be halved by the artificial neural network. However, for linearly dependent multigroup cross sections as found for the sodium-cooled fast reactor case, a simpler linear regression outperforms deeper networks.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Selection of Sampling and Surrogate Modeling Methods for State-Point Evaluations of an AGN-201M Reactor

Nuclear reactor digital twins (DTs) have been proposed for use as a safeguards technology to efficiently monitor new and novel reactors as they come online. A safeguards DT needs to be capable of detecting misuse and diversion as they occur, requiring physics models to be accurate and efficient. Mathematical surrogate models are capable of achieving the necessary efficiency and can largely maintain the accuracy of higher-order models given a quality training sample. The Multiphysics Object-Oriented Simulation Environment (MOOSE) code framework is specifically equipped to generate training samples and create surrogate models using full-order reactor physics models. Utilizing an operational AGN-201M reactor’s specifications, two surrogate types were trained on samples of variable size, and using Cartesian products, Latin hypercube sampling, and quadrature sampling, each was compared and evaluated on accuracy when compared to a full-order Monte Carlo model. Both surrogate types were able to capture reactivity changes within 0.05 $ of the Monte Carlo model while reducing the computation costs by eight orders of magnitude.

MOOSE↗
DOE OSTI2016

Modeling of interdendritic porosity defects in an integrated computational materials engineering approach for metal casting

Modeling and simulation of multiphysical phenomena needs to be considered in the design and optimization of mechanical properties of cast components in order to accelerate the introduction of new cast alloys. The data on casting defects, including microstructure features, is crucial for evaluating the final performance-related properties of the component. Here in this paper, the required models for the prediction of interdendritic casting defects, such as microporosity and hot tears, are reviewed. The data on calculated solidification shrinkage is presented and its effects on microporosity levels discussed. Numerical simulation results for microporosity are presented for A356, 356 and 319 aluminum alloys using ProCAST TM software. The calculated pressure drop of the interdendritic liquid was observed to be quite significant and the regions of high-pressure drop can be used as an indicator of the severity of interdendritic microporosity defects.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Modeling of Transport Processes in Liquid-Metal Fusion Blankets: Past, Present, and Future

The successful development of robust breeding blanket systems will strongly rely on computational tools for predicting the complex behavior of the electrically conducting liquid-metal (LM) breeder flowing in the complex-shaped blanket ducts in the presence of a strong plasma-confining magnetic field, volumetric heating, and tritium generation. Associated transport processes involve magnetohydrodynamic (MHD) flows, heat transfer, corrosion, and tritium transport. This paper is an overview of past and present efforts in the development, application, and verification and validation (V&V) of such computational tools. As a result of the ongoing campaign on V&V of computer codes for LM blankets, the international fusion community has identified several candidates that promise to become real blanket design and analysis tools in the near future. Among them are HIMAG, MHD-UCAS, COMSOL Multiphysics, ANSYS FLUENT, ANSYS CFX, and OpenFOAM. The progress, over the last decade, in the application of such codes in blanket studies is tremendous. This is illustrated with two examples for a dual-coolant lead-lithium (DCLL) blanket: (1) integrated computer modeling for the recently designed DCLL blanket in the United States and (2) application of the code MHD-UCAS to the analysis of PbLi flows and heat transfer in a generic DCLL blanket prototype at high Hartmann (Ha ~ 10 4 ) and Grashof numbers (Gr ~ 10 12 ). Here, this paper also presents an approach to the development of a new integrated computational tool called the virtual dual-coolant lead-lithium (VDCLL) blanket, which elaborates the existing U.S. MHD code HIMAG.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Design and Analysis of the Open-Surface Slow Li Flow Divertor and Comparison to the Fast Li Flow Divertor

In the ongoing U.S. project, “Liquid Metal Plasma Facing Components,” sponsored by the U.S. Department of Energy, efforts have been taken to develop two open-surface divertor designs for the Fusion Nuclear Science Facility using liquid lithium (Li) as a heat and particle flux removal media. The main focus of this study is the design and analysis of a slow (~1 mm/s) and thin (<1 mm) open-surface Li flow divertor with a Li-cooled substrate, which is then compared with an earlier design of a fast (up to 10 m/s) and thick (~0.5 cm) Li flow divertor with the substrate cooled with helium. The slow Li flow divertor design is based on the original LiWall concept developed at the Princeton Plasma Physics Laboratory. Such a thin and slow Li layer can remove the particle flux by reducing the recycling flux, while the heat flux is removed mainly through the heat sink located beneath. In the present study, the heat sink is provided through a Li cooling flow inside the substrate of reduced activation ferritic/martensitic steel. By performing a multiphysics analysis with COMSOL that included liquid-metal magnetohydrodynamics (MHD), heat transfer, and structural mechanics, the impact of various factors on the divertor heat removal capability, such as Li flow velocity, MHD effects, and inlet velocity boundary condition, were examined. Based on comparisons of the two divertor designs, it was shown that the fast-flow divertor significantly outperformed the slow-flow design, whose heat removal capability was limited to ~1 to 2 MW/m2.

Jiang, Yuchen [ORNL] (ORCID:0000000283280284)↗
DOE OSTI2026

The Development of Kinetic and Radiation Hydrodynamics Modeling of Thermonuclear Burn Propagation in Isochoric p - 11 B Through the Support of the INFUSE Program

The report summarizes DOE INFUSE-supported work between HB11 Energy and the University of Rochester’s TriForce Institute to improve computational modeling of advanced fusion fuels, especially proton–boron-11 (p- 11 B). The project extended the TriForce particle-in-cell/Monte Carlo collision code to include physics needed for dense, high-temperature p- 11 B burn studies, including p- 11 B fusion reactions, three-alpha-particle reaction products, relativistic Coulomb collisions, large-angle nuclear scattering, bremsstrahlung radiation, inverse bremsstrahlung absorption, and photon transport. The upgraded models were verified against focused physics tests and against known deuterium–tritium burn behavior. The study then used one-dimensional spherical simulations to estimate the conditions required for thermonuclear burn propagation in isochoric p- 11 B fuel. The calculations found that burn propagation is possible in the model, but only under very extreme hot-spot conditions, such as about 7000 g/cm 3 at 500 keV or 9000 g/cm 3 at 300 keV for a 20-micron hot spot. These conditions are much more demanding than current demonstrated inertial confinement fusion hot spots. The report concludes that the INFUSE collaboration successfully advanced kinetic and radiation modeling capabilities for p- 11 B fusion and provided useful estimates of ignition requirements. However, the simulated fuel gains remain below what would be needed for practical inertial fusion energy, and further work is needed to reconcile differences among kinetic, radiation-hydrodynamic, and analytic models and to identify more achievable target designs.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Verification methods for drift–diffusion reaction models for plasma simulations

Abstract Compared to other computational physics areas such as codes for general computational fluid dynamics, the documentation of verification methods for plasma fluid codes remains under developed. Current analytical solutions for plasma are often highly limited in terms of testing highly coupled physics, due to the harsh assumptions needed to derive even simple plasma equations. This work highlights these limitations, suggesting the method of manufactured solutions (MMSs) as a potential option for future verification efforts. To demonstrate the flexibility of MMS in verifying these highly coupled systems, the Multiphysics Object-Oriented Simulation Environment (MOOSE) framework was utilized. Thanks to the MOOSE framework’s robustness and modularity, as well as to its physics module capabilities and ecosystem applications (i.e. Zapdos and the chemical reaction network) developed for plasma physics modeling and simulation, this report lays the groundwork for a structured method of conducting plasma fluid code verification.

DeChant, Corey (ORCID:0000000293779732)↗
DOE OSTI2025

Simulations of the fault current limiting operation of a long-length REBCO CORC ® superconducting cable cooled by helium gas

Conductor-on-round-core (CORC®) cables composed of rare-earth-barium-copper-oxide high-temperature superconducting (HTS) tapes are of great interest for power transmission applications due to their many advantages such as high power density, light weight, and low loss. Closed circulation loops of cryogenic helium gas can be used to cool HTS cables down to low temperatures to significantly improve their current-carrying capacity. Coupled circuit-electromagnetic-thermal finite element simulations implemented in the COMSOL Multiphysics package were developed, validated, and then used for simulating the fault current limiting (FCL) performance and the cooling processes of an 8-layer CORC® cable cooled with a flow of cryogenic helium gas. In the simulations, the temperature dependence of the electrical and thermal properties of all component materials is implemented for improved accuracy. To overcome computational challenges caused by the considerable difference in geometrical scales (i.e. few-µm-thick HTS layers versus 10 m-long HTS cable), the model is divided into two separate simulations. The first simulation is performed on the transverse cross-section of the cable to calculate the electric field, heating power and temperature rise in each component of a CORC® cable during FCL operation. The heating power calculated in the first simulation is transferred to the second model to simulate the cooling of a 10 m-long cable after the fault is cleared. The effect of the helium gas flow rate on the cooling process is also investigated to develop strategic approaches for optimizing cooling systems for HTS cables with FCL capability. The simulations indicated that a 40 ms fault with a voltage drop of 20 V m −1 along the cable can result in a temperature increase from 60 K to about 165 K inside the cable, and it takes about 500 s to cool the cable back to nearly 60 K with a flow of cold helium gas at a rate of 5 g s −1 .

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Modelling the brittle failure of graphite induced by the controlled impact of runaway electrons in DIII-D

The thermo-mechanical response of an ATJ graphite sample to controlled runaway electron (RE) dissipation, realized in DIII-D, is modelled with a novel work-flow that features the RE orbit code KORC, the Monte Carlo particle transport code Geant4 and the finite element multiphysics software COMSOL. KORC provides the RE striking positions and momenta, Geant4 calculates the volumetric energy deposition and COMSOL simulates the thermoelastic response. Brittle failure is predicted according to the maximum normal stress criterion, which is suitable for ATJ graphite owing to its linear elastic behavior up to fracture and its isotropic mechanical properties. Measurements of the conducted energy, damage topology, explosion timing and blown-off material volume, impose a number of empirical constraints that suffice to distinguish between different RE impact scenarios and to identify RE parameters which provide the best match to the observations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2018

Validation of FAST.Farm Against Large-Eddy Simulations

FAST.Farm is a new midfidelity, multiphysics engineering tool for modeling the power performance and structural loads of wind turbines within a wind farm, including wake and array effects. Previous calibration of the tuneable model parameters of FAST.Farm has shown that its prediction of wake dynamics for a single wind turbine across different atmospheric stability conditions and nacelle-yaw errors matches well with high-fidelity large-eddy simulation at a small fraction of the computational expense. This paper presents a validation of FAST.Farm against large-eddy simulation for a series of cases - independent from those used to support the calibration - considering single-turbine and small wind-farm scenarios, which are both subject to variations in inflow and control. The validation has demonstrated that FAST.Farm reasonably accurately predicts: (1) thrust and power for individual turbines both in isolation and down the row of the small wind farm, (2) wake meandering behavior across different atmospheric conditions, and (3) averaged wake-deficit advection, evolution, and merging effects. As a result, the validation also highlights potential physics that could be improved in FAST.Farm in the future.

17 WIND ENERGY↗
DOE OSTI2019

Effects of Inflow Spatiotemporal Discretization on Wake Meandering and Turbine Structural Response using FAST.Farm

FAST.Farm is a newly developed multiphysics, midfidelity engineering tool that can be used to predict turbine power and structural loads of wind turbines in a wind farm with minimal computational expense. Previous studies have shown similarities and differences in wind turbine performance between FAST.Farm and high-fidelity large-eddy simulations (LES) using both LES precursor-generated inflow and TurbSim-generated synthetic inflow. While conservative resolutions have been used to date, no formal spatial or temporal discretization study has been performed for the FAST.Farm model wind domains. This work aims to study the effects of varying the spatial and temporal discretization of the wind domains on wake meandering (low-resolution domain) and turbine structural response (high-resolution domains) and resulting wake and load calculations. The purpose of this study is to establish convergence criteria and recommendations for discretization values in terms of rotor diameter (D, expressed in meters) that will maximize computational efficiency. To ensure a percent error of ≤ 1% in standard deviation of wake center position relative to the finest included resolution, a low-resolution time step of 0.024D s, 0.016D s, and 0.0079D s and a low-resolution spatial discretization of 0.079D m, 0.16D m, and 0.24D m is recommended for 8 m/s, 12 m/s, and 18 m/s mean ambient wind speed at hub height, respectively. These guidelines are likely applicable to other implementations of the dynamic wake meandering model. To ensure a percent error of ≤ 1% in standard deviation of all considered structural response outputs, a high-resolution time step that captures the highest influential excitation and natural frequencies in the system and a high-resolution spatial discretization comparable to the maximum airfoil cord length is recommended. Lastly, these guidelines are likely applicable to any aeroelastic analysis.

17 WIND ENERGY↗
DOE OSTI2019

Verification of Floating Offshore Wind Linearization Functionality in OpenFAST

The wind engineering community relies on multiphysics engineering software to run nonlinear time-domain simulations, e.g., for design standards-based loads analysis. Although most physics involved in wind energy are nonlinear, linearization of the underlying nonlinear system equations is often advantageous to understand the system properties and exploit well-established methods and tools for analyzing linear systems. Previous work in this area has focused on the development of the new linearization functionality of the open-source engineering tool OpenFAST for floating offshore wind turbines, as well as the concepts and mathematical background needed to understand and apply it correctly. This paper focuses on the verification of this new linearization functionality, which is carried out by comparing results to previous stable versions of FAST. A nonlinear time-domain simulation for a floating offshore platform is also compared to the time-domain response of the linearized state-space model. The linearized results show good alignment between OpenFAST and previous versions of FAST, as well as with the time-domain simulations, thereby showing the accuracy of the new features in OpenFAST.

17 WIND ENERGY↗
DOE OSTI2024

Development and Verification of an Improved Wake-Added Turbulence Model in FAST.Farm

We introduce a generalized wake-added turbulence (WAT) model in the multiphysics, multiturbine simulation tool FAST.Farm. The WAT model introduces additional small-scale turbulence that represents the breakdown of vortical structures and shear layers in the wake. The article describes the development, implementation, calibration, and verification of the model. The novelties of the model include support for wake asymmetry, buildup of WAT across the wind farm, and secondary effects of wake-induced turbulence (e.g., wake meandering) driven by smaller-scale turbulence structures that arise from wake breakdown. Large-eddy simulations were run to support the calibration of the WAT parameters and verification of the model. Previous studies hypothesized that the lack of WAT modeling was the source of underprediction of fatigue loads, in particular for cases at low turbulence intensities and/or stable atmospheric boundary layers. This study confirms that the newly implemented WAT model enhances the loads predictions in these cases.

17 WIND ENERGY↗
DOE OSTI2017

3D modeling of electric fields in the LUX detector

This work details the development of a three-dimensional (3D) electric field model for the LUX detector. The detector took data to search for weakly interacting massive particles (WIMPs) during two periods. After the first period completed, a time-varying non-uniform negative charge developed in the polytetrafluoroethylene (PTFE) panels that define the radial boundary of the detector's active volume. This caused electric field variations in the detector in time, depth and azimuth, generating an electrostatic radially-inward force on electrons on their way upward to the liquid surface. To map this behavior, 3D electric field maps of the detector's active volume were generated on a monthly basis. This was done by fitting a model built in COMSOL Multiphysics to the uniformly distributed calibration data that were collected on a regular basis. The modeled average PTFE charge density increased over the course of the exposure from -3.6 to -5.5 μC/m 2 . Here, from our studies, we deduce that the electric field magnitude varied locally while the mean value of the field of ~200 V/cm remained constant throughout the exposure. As a result of this work the varying electric fields and their impact on event reconstruction and discrimination were successfully modeled.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Precise magnetic field mapping of the EMPHATIC Phase 1 magnet with COMSOL

A compact Halbach array magnet is used to measure the momentum of the secondary particles in EMPHATIC(Experiment to Measure the Production ofHadrons At a Test beam InChicagoland). Hall probe data was taken for the central cylindrical bore of the magnet and a field map was constructed. COMSOL Multiphysics® Software is used for modeling the magnet and constructing the corresponding magnetic field map. Here, we present a fitting approach where the hall probe data is used to determine a 1mm-spacing map of the entire volume of the magnet using COMSOL. The new map will allow for linear interpolation within the volume, and expand the map to outside the measurement volume, thus increasing the acceptance and precision of EMPHATIC's tracking system.

47 OTHER INSTRUMENTATION↗
DOE OSTI2026

On the uncertainties in helium generation predictions for fission and fusion alloys

With ongoing advances in fusion and advanced fission reactors, quantifying irradiation effects in materials is critical. Transmutation-induced helium in cladding and structural materials can drive swelling and embrittlement, thereby reducing these components’ lifespans. Yet most studies ignore the considerable uncertainties in predicting helium generation rates. In this work, we created a code wrapper, F-SCATTER, that automatically performs simulations in FISPACT-II. We used this tool to investigate potential variance in helium generation rate, or He/dpa, calculations based on deviations in alloy composition, irradiating neutron flux spectrum, computational methodology, and nuclear data sources. We used 12 wt% Cr HT9 steel as the reference case and observed a 6.5%–98.3% He/dpa spread based on compositional variation within a single chemical specification, a 1.8%–11.5% He/dpa variation upon the incorporation of a 15% artificial uncertainty in flux at each energy, and a He/dpa difference as high as 231% when using ENDF/B-VIII.0 versus TENDL-2021 data libraries. Similar results were found for other prominent iron-based alloys, including Grade 91, castable nano-structured alloy, and 316H—where additional variations exist based on reactor type (e.g. thermal, fast, or fusion) and alloying elements such as carbon, nitrogen, and nickel. Based on the simulated results, we conclude that a significant part of the heat-to-heat variability in swelling responses of Fe-based alloys can be driven by impurity content in alloy compositions, and, therefore, chemical control should be a key element in supply chain design for advanced nuclear energy systems. Furthermore, we provide critical recommendations on best practices for evaluating and reporting helium production and lattice damage rates when computing predictions with multiphysics programs such as FISPACT-II.

FISPACT-II↗