Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Nuclear Modeling”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 505 records · Page 28
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Enabling the Broader Use of MOOSE for Nuclear Energy and Other Simulation

This Final Scientific and Technical Report summarizes work performed under the Phase IIA SBIR project “Enabling the Broader Use of MOOSE for Nuclear Energy and Other Simulation” (DE-SC0020906) from August 2023 through August 2025. The objective of the Phase IIA effort was to mature and harden capabilities developed during Phase II, with the goal of enabling practical interoperability between Coreform’s isogeometric analysis (IGA) technologies and the Multiphysics Object-Oriented Simulation Environment (MOOSE), while improving robustness, performance, and scalability for complex, nuclear-relevant geometries. Over the course of Phase IIA, the project established and validated an extraction-based interoperability pathway between Coreform tools and MOOSE. A combined mesh and matrix format was defined collaboratively with MOOSE developers and integrated into the solver, enabling standard MOOSE workflows to operate on data exported from Coreform’s IGA and Flex Representation Method (FRM) pipelines. Early demonstrations validated architectural compatibility using linear solid mechanics problems, while later efforts focused on benchmark testing and external use. By the end of the project period, engineers at BWXT were able to independently set up and execute a simulation using the Coreform–MOOSE workflow and provide direct feedback that informed further refinement. In parallel, substantial effort was devoted to improving the robustness of trimmed U-spline construction for complex CAD geometries. A growing test suite of nuclear-relevant models was compiled through collaboration with multiple stakeholders and used to drive extensive bug fixing and reliability improvements. These efforts resulted in improved robustness and performance, including the addition of fallback capabilities that enhance reliability when the underlying commercial CAD kernel fails. Performance-oriented work progressed later in the project, with the development and demonstration of methods to decompose complex geometries into structured subregions and updated data representations to support more efficient solver processing. Additionally, extensive enhancements to threadsafe parallel data structures and trimming operations established a foundation for scalable processing of large assemblies. Collaboration with Sandia National Laboratories on the SGM geometric modeling kernel advanced to a functioning interface test case, positioning the workflow for future kernel integration. Overall, the Phase IIA effort successfully transitioned the project from architectural proof-of-concept to externally exercised, solver-integrated capability, while clarifying remaining technical challenges related to standardization, performance optimization, and kernel integration.

42 ENGINEERING↗
DOE OSTI2026

Transverse Kinematic Imbalance in MicroBooNE's New nue CC0pi Measurements

Neutrino-nucleus cross section measurements require accurate modelling of neutrino interactions. Neutrino beams are not monoenergetic, and the energy of each interaction must instead be modelled using nuclear interaction assumptions. This introduces significant systematic uncertainty into cross section measurements. Effects such as Fermi motion, nuclear correlations, and final-state interactions (FSI) smear the underlying quasi-elastic scattering signal, making it difficult to disentangle genuine quasi-elastic kinematics from nuclear effects across the full range of interaction channels (QE, MEC, RES, DIS) probed in these measurements. Transverse Kinematic Imbalance (TKI) variables, such as $\delta p_T$ and $\delta \alpha_T$, probe this same phase space by exploiting the fact that the incoming neutrino has zero transverse momentum ($\vec{p}_T^{\,\nu} = 0$). Any measured transverse imbalance in the final state therefore arises from nuclear effects rather than from uncertainty in the incident neutrino energy, allowing cross section measurements to select a phase space that is rich in quasi-elastic-like events with minimal contamination from FSI and other nuclear effects, independent of energy reconstruction. Recent unfolded MicroBooNE cross section measurements of electron-neutrino charged-current interactions with zero pions and at least one proton ($\nu_e$ CC0$\pi$, 1eNp0$\pi$) show that several leading nuclear interaction generators (including GENIE variants, NuWro, GiBUU, and NEUT) reproduce the differential cross section in electron energy reasonably well, but consistently struggle to describe the differential cross section in the cosine of the leading proton's angle, yielding lower $p$-values across all seven generators tested. This tension points to a more fundamental, kinematics-driven disagreement between data and generators that is not visible in energy-only cross section observables. This is precisely the regime TKI variables are designed to probe. Following previous TKI cross section measurements with muon-neutrino data in MicroBooNE, this poster presents the case for extending the TKI framework to electron-neutrino cross section measurements as a next step to isolate and characterize the source of the observed generator tension in proton kinematics.

Burridge, Jessica [U. Manchester (main)] (ORCID:00↗
DOE OSTI2022

Analyzing rotational bands in odd-mass nuclei using effective field theory and Bayesian methods

We recently developed an Effective Field Theory (EFT) for rotational bands in odd-mass nuclei. Here we use EFT expressions to perform a Bayesian analysis of data on the rotational energy levels of 99 Tc, 155,157 Gd, 159 Dy, 167,169 Er, 167,169 Tm, 183 W, 235 U and 239 Pu. The error model in our Bayesian analysis includes both experimental and EFT truncation uncertainties. It also accounts for the fact that low-energy constants (LECs) at even and odd orders are expected to have different sizes. We use Markov Chain Monte Carlo (MCMC) sampling to explore the joint posterior of the EFT and error-model parameters and show both the LECs and the breakdown scale can be reliably determined. We extract the LECs up to fourth order in the EFT and find that, provided we correctly account for EFT truncation errors in our likelihood, results for lower-order LECs are stable as we go to higher orders. LEC results are also stable with respect to the addition of higher-energy data. We extract the expansion parameter for all the nuclei listed above and find a clear correlation between the extracted and the expected value of the inverse breakdown scale, W, based on the single-particle and vibrational energy scales. However, the W that actually determines the convergence of the EFT expansion is markedly smaller than would be naively expected based on those scales.

EFT↗
DOE OSTI2023

Abundances and Transients from Neutron Star–White Dwarf Mergers

Abstract We systematically investigate the mergers of neutron star–white dwarf binaries from beginning to end, with a focus on the properties of the inflows and outflows in accretion disks and their electromagnetic emissions. Using population synthesis models, we determine a subset of these binaries in which the white dwarf companion undergoes unstable mass transfer and complete tidal disruption, forming a large accretion disk around the neutron star. The material evolves according to a one-dimensional advection-dominated accretion-disk model with nuclear burning, neutrino emissions, and disk-surface wind ejection. The extreme dynamics of the entire process have proven difficult to analyze, and thus currently, the properties are poorly understood. The outflows from the mergers are iron- and nickel-rich, giving rise to optical and infrared emissions powered by the decay of the radioactive iron-type isotopes, calculated via the SuperNu light-curve code. We find these systems capable of powering bright, yet short-lived, optical transients with the potential to power gamma-ray bursts.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Recent results from MicroBooNE

Modelling and reconstructing neutrino-nucleus scattering is difficult, but it is crucial to do it precisely to enable next-generation oscillation measurements. Liquid argon time projection chambers (LArTPCs), such as MicroBooNE, can be the tool for this job as they are excellent precision neutrino detectors with their ability to produce detailed three-dimensional interaction images and precise energy and spatial resolution. MicroBooNE currently possesses the world's largest neutrino-argon scattering data set collected over five years using the BNB and NuMI neutrino beams at Fermilab. The experiment has performed measurements over a broad range of physics topics including neutrino argon cross sections, searches for BSM physics, and investigations of the MiniBooNE LEE excess. Many of these measurements are essential for improving the modelling of nuclear effects for both MicroBooNE and future LArTPC neutrino experiments, such as DUNE. This talk will give an overview of recent MicroBooNE results, the analysis techniques that enable them, and prospects for future measurements.

Parkinson, Holly B. [U. Edinburgh (main)] (ORCID:0↗
DOE OSTI2022

Multiphysics Modeling in Support of NASA Nuclear Thermal Propulsion Designs

This presentation provides and overview of INL and some of the work we do, but focuses on analysis and methods at INL being performed in support of NASA nuclear thermal propulsion. This presentation will be given at department seminars at Texas A&M University and at Georgia Tech.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Results of South-East Flux Trap Dosimetry Measurements for the Advanced Test Reactor Critical Facility in support of Advanced Sensors and Instrumentation Development

Reactor dosimetry measurements are commonly used to validate simulation and modeling in nuclear reactor tests. Numerous standard dosimeter materials exist which are commonly utilized with sensitivities to different energy ranges of neutrons. At the Advanced Test Reactor (ATR), cobalt alloy and pure nickel wires are installed every cycle to monitor thermal- and fast-neutron fluence rates. However, there is growing interest in exploring less commonly used materials which are either more sensitive to different parts of the neutron energy spectrum or which can incorporate multiple activation paths in a single material. Epithermal and fast-neutron energies beyond the typical 1-MeV threshold are of particular interest. Two ATR-C Flux Runs took place during 2024; each flux run included supplemental dosimetry packages in the South-East Flux Trap (SEFT) Filler. The focus of the dosimetry package for flux run 23-4 was to test two novel dosimetry methods that can provide simultaneous thermal and threshold (fast) sensitivity in a single dosimeter wire. A selection of 3% Au in Cu alloyed wires were available that provided sensitivity to fast and thermal neutrons through 5 different reactions. Likewise, Fe offers multiple interaction pathways with sensitivity to both thermal and fast neutrons. The main question to be answered by these irradiations was if sufficient radioactivation would take place in the ATR-C SEFT during a nominal 20-minute irradiation at typical power levels (near 600Wth) to observe the threshold reactions that have smaller activation cross-sections than the thermal reactions without being saturated by interfering interactions and Compton continuum during the High-Purity Germanium (HPGe) measurements. The results from comparing the measurement results to anticipated activity levels provide confidence in our ability to activate both traditional and novel dosimetry materials in ATR-C, however not all the measured values matched with the predicted activities. This leaves further room for investigation both on the experimental and computational approaches for future irradiation experiments.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗
DOE OSTI2021

Modeling Environmental Effects on Ventilated Spent Fuel Storage Systems

This report describes newly developed external environment wind effects models of spent nuclear fuel (SNF) dry storage systems. The primary purpose of these wind effects models is to better understand particle deposition on SNF canisters in the context of chloride-induced stress corrosion cracking. The goal of this effort is to further the understanding and improve the wind effects model of the Nuclear Horizontal Modular Storage (NUHOMS ® ) Advanced Horizontal Storage Module–High Seismic (AHSM-HS) storage system in support of the planned Canister Deposition Field Demonstration (CDFD) project (Durbin et al. 2021, Suffield et al. 2021). The steps in this wind effects investigation begin with a validation case of comparing experimental data with a STAR-CCM+ computational fluid dynamics (CFD) model of the Belowground Vertical Dry Cask Simulator (BVDCS) with the external environment explicitly modeled. Next, a test case is performed with the AHSM-HS models comparing solar-loading strategies for a standalone and wind effects model in STAR-CCM+ and a standalone model in ANSYS Mechanical Parametric Design Language (APDL). The final portion of this study compares results of the validation exercise with applications of wind effects models for two horizontal storage systems, a site specific NUHOMS ® horizontal storage module and a NUHOMS ® AHSM-HS.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Enhancement of PyARC for Westinghouse Electric Company’s Lead Fast Reactor Design and Modeling (Final TCF Report)

Westinghouse Electric Company is a nuclear reactor vendor headquartered in the U.S. that is developing advanced reactor technology for the U.S. and global markets. Westinghouse has been relying on the neutronics Argonne Reactor Codes (ARC) executed through the NEAMS Workbench and its PyARC module that are developed under the DOE-NE Nuclear Energy Advanced Modeling and Simulation (NEAMS) and Advanced Reactor Technology (ART) – Fast Reactor programs. Through this user experience, Westinghouse identified several enhancements that would benefit the ARC codes’ usability by the US industry and therefore its commercialization potential. The enhancements were proposed to deliver both improvements in workflow and analysis capabilities to better support effective fast reactor core design and analysis to the nuclear industry. The PyARC workflow was extended in this project by integrating non-neutronic ARC codes DASSH and NUBOW-3D. The Ducted Assembly Steady-State Heat equation (DASSH) code is developed at ANL to perform steady-state thermal hydraulic sub-channel analysis in liquid metal fast reactor assemblies to determine optimized coolant flow and temperature distributions, which in this project was updated and validated for lead fast reactor (LFR) applications. The interface between REBUS and NUBOW-3D were improved in this project to assess the impact of the core restraint design and thermal induced expansion effects on the reactivity of the core, and to model the deformations of the fuel assemblies induced by temperature and irradiation. Finally, the ARC models that were extensively verified and validated through various SFR-based modeling benchmarks are extended in this project through code-to-code comparison on relevant LFR-specific neutronics benchmarks against Monte-Carlo neutronic solutions. Overall, this work enables verification of the capability of the ARC codes for a wide range of Generation-IV reactor designs. The outcome of this project is the release of a comprehensive modeling toolkit of validated, robust and efficient codes, as well as their user interface, that enables industry to perform a wide range of fast reactor analyses for design and licensing of their concepts.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

A study on the impact of using a subchannel resolution for modeling of large break loss of coolant accidents

The nuclear industry is investigating the feasibility of transitioning from 18- to 24-month fuel cycles because of the positive impact it would have on the operational costs for the current fleet of light-water reactors. A challenge to making this change is the increased risk of fuel fragmentation, relocation, and dispersal (FFRD) due to the known potential for ceramic fuel to pulverize into fine particles at the higher discharge burnups. Previous work has been performed by the Nuclear Energy Advanced Modeling and Simulation program to assess FFRD risk in high-burnup cores using the BISON fuel performance code and a coarse mesh thermal hydraulics (T/H) solution for a loss-of-coolant accident (LOCA) using the TRACE system T/H code. Because of the importance of the T/H solution for FFRD assessment, this study seeks to investigate the impact of using higher-fidelity subchannel techniques for modeling of the LOCA transient. CTF was used to model a subregion of a high-burnup core that was depleted by the Virtual Environment for Reactor Applications (VERA) multiphysics core simulator. Both coarse-mesh and pin-resolved models were created in CTF, and a consistent coarse-mesh TRACE model was also developed to allow for benchmarking the code results. Further, a large-break loss-of-coolant accident (LBLOCA) reflood transient was simulated using these three models, and results were compared. Results showed some consistent differences between the CTF and TRACE coarse models, including a higher peak cladding temperature (PCT) prediction in CTF and later quenching in CTF; however, the transient clad temperature behavior was similar, and these differences are likely due to post-critical heat flux heat transfer modeling differences and minimum film boiling temperature model differences. The pin-resolved results indicate that the PCT in the lumped model is often under-predicted by as much as 70 °C and that PCT occurs at a different location than the high-power pin in the assembly. The lumped model predicts a difference of 10 °C or less between the average and hot pins in the assembly, whereas the pin-resolved model predicts a range of over 100 °C. These results indicate that higher-fidelity T/H results may have an impact on predicted core behavior during LOCA, which may be important to consider when assessing FFRD risk.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2025

Mesoscale Modeling for Restructuring and Fragmentation in High Burnup UO 2

This report summarizes the mesoscale modeling conducted in fiscal year 2025 under the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, focusing on the microstructural evolution and restructuring in high burnup UO 2 nuclear fuel and its impact on fuel fragmentation. We developed a pioneering phase-field model to simulate restructuring behavior across different regions of high burnup fuel, including the dark zone and rim region. A grand-potential-based phase-field model is employed to concurrently evaluate subgrain formation and the growth of fission gas bubbles within the fuel. An energy-based subgrain formation criterion was introduced to simulate the restructuring process. The effects of temperature and burnup rate were studied to capture how each of these parameters influences the characteristics of the restructured fuel. Subgrain formation was observed to initiate around existing fission gas bubbles and proceed toward triple junctions, grain boundaries, and grain interiors. Under a given subgrain formation rate, the rate of restructuring increases with rising fuel temperature. The restructuring occurs faster with higher burnup rate. A restructuring bias was observed within the microstructure, due to the variation in defect accumulation when comparing different grains. Microstructures corresponding to the dark zone and rim region can be obtained by parameterizing the model with the appropriate defect production rate, as determined based on the burnup rate and temperature. The predicted microstructures are consistent with experimental observations of the restructured regions. Based on the mesoscale simulations, a mechanistic model for restructuring and grain size evolution was implemented in BISON. Thus, this work provides a first-of-its-kind restructuring model for different regions of high-burnup fuel to BISON. It was shown that the model predicts appropriate grain size evolution along fuel radius as those observed in experiments. This model enables BISON to predict the effect of restructuring on the fission gas release. Finally, the phase-field fracture simulation with dark zone specific microstructures were presented to provide the fragmentation criteria for the dark zone. This work introduces a first-of-its-kind restructuring model for high burnup fuel, significantly enhancing BISON's predictive capabilities.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Integrated Molten Salt Reactor Modeling Capabilities in NEAMS Thermal Hydraulics Tools

The DOE Nuclear Energy Advanced Modeling and Simulation (NEAMS) program supports a full range of computational thermal fluids analysis capabilities and code developments for a broad range of advanced reactor concepts. The research and development approach under the thermal fluids technical area synergistically combines three length and time scales in a hierarchical multi-scale approach. To enable multi-scale thermal fluids capability using these codes, a key joint effort has been underway to develop an integrated system- and engineering-scale thermal fluids analysis capability, through integration of SAM and Pronghorn codes, both based on the MOOSE framework.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Reliability estimation of an advanced nuclear fuel using coupled active learning, multifidelity modeling, and subset simulation

Tristructural isotropic (TRISO)-coated particle fuel is a robust nuclear fuel and determining its reliability is critical for the success of advanced nuclear technologies. However, TRISO failure probabilities are small and the associated computational models are expensive. Here we used coupled active learning, multifidelity modeling, and subset simulation to estimate the failure probabilities of TRISO fuels using several 1D and 2D models. With multifidelity modeling, we replaced expensive high-fidelity (HF) model evaluations with information fusion from two low-fidelity (LF) models. For the 1D TRISO models, we considered three multifidelity modeling strategies: only Kriging, Kriging LF prediction plus Kriging correction, and deep neural network (DNN) LF prediction plus Kriging correction. While the results across these multifidelity modeling strategies compared satisfactorily, strategies employing information fusion from two LF models called the HF model least often. Next, for the 2D TRISO model, we considered two multifidelity modeling strategies: DNN LF prediction plus Kriging correction (data-driven) and 1D TRISO LF prediction plus Kriging correction (physics-based). The physics-based strategy, as expected, consistently required the fewest calls to the HF model. However, the data-driven strategy had a lower overall simulation time since the DNN predictions are instantaneous, and the 1D TRISO model requires a non-negligible simulation time.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Development of a Representative Molten Chloride Fast Reactor Model to Assess the Impact of Nuclear Data

The SCALE code system was employed to conduct a preliminary investigation of nuclear data impacts for a fast spectrum molten chloride salt reactor. A computationally effective depletion model that is representative of the reactor system was successfully developed and used to conduct fuel depletion simulations. Development of this model draws from the SLICE method that was developed at Oak Ridge National Laboratory to enable generation of fuel compositions for an advanced reactor core at equilibrium operation. Eigenvalue uncertainty calculations using the ENDF/B-VII.1 nuclear data library were performed for the reactor in the fresh fuel state and an irradiated fuel state. It was determined that the primary driver of eigenvalue uncertainty was the uncertainty in the 235U (n, 𝛾) cross section. Uncertainty calculation results from this study were compared to results available for a different fast system, a sodium-cooled fast reactor, to confirm similarities and identify differences with respect to nuclear data impacts between the two fast advanced reactor systems.

Hirji, Rakim [Georgia Institute of Technology]↗
DOE OSTI2023

Adaptive, Active Learning, and Multifidelity Monte Carlo Methods in the MOOSE Stochastic Tools Module

MOOSE is an open-source computational platform for constructing multi-physics models and executing them in a massively parallel fashion. It has a stochastic tools module (STM) for forward/inverse uncertainty quantification (UQ) and surrogate modeling. This presentation details some recent developments to the STM with respect to the implementation of adaptive, active learning, and multifidelity Monte Carlo methods for forward UQ of computational models. Specifically, the adaptive Monte Carlo methods include Markov Chain Monte Carlo (MCMC)-driven algorithms like adaptive importance sampling and parallelized subset simulation for statistical QoI estimation, rare events analysis, and stochastic gradient-free optimization. The active learning methods include Gaussian Process (GP) surrogates and their training via Adam optimization, design of acquisition functions, and integration with samplers like Monte Carlo, adaptive importance, and parallelized subset simulation. These active learning methods are also designed to work in a batch mode, wherein, the required calls to the full computational model are executed in parallel whenever a user-specified batch size is met. The multifidelity methods in STM are broadly divided into two categories: hierarchical, where a defined hierarchy exists among the low-fidelity models, and peer, where all the low-fidelity models are treated equally. A GP surrogate is used to learn the differences between the low- and high-fidelity models in both multifidelity categories, and acquisition functions from the active learning classes are used to decide whether to rely on a low-fidelity model or call the expensive high-fidelity model. Alongside the software description and usage, applications are also presented to nuclear engineering computational models including a TRISO nuclear fuel particle, a reactor pressure vessel, and a heat-pipe microreactor.

97 MATHEMATICS AND COMPUTING↗