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At least 235 records · Page 13

SIERRA Code Coupling Module: Arpeggio User Manual (V.5.26)

The SNL Sierra Mechanics code suite is designed to enable simulation of complex multiphysics scenarios. The code suite is composed of several specialized applications which can operate either in standalone mode or coupled with each other. Arpeggio is a supported utility that enables loose coupling of the various Sierra Mechanics applications by providing access to Framework services that facilitate the coupling. More importantly Arpeggio orchestrates the execution of applications that participate in the coupling. This document describes the various components of Arpeggio and their operability. The intent of the document is to provide a fast path for analysts interested in coupled applications via simple examples of its usage.

97 MATHEMATICS AND COMPUTING↗

Multiphysics Modeling of Microreactors with NEAMS codes, and Validation Based on KRUSTY Reactivity Insertion

The NEAMS Multiphysics Applications team continues to assess code usability and functionality for microreactor design and safety analyses, while demonstrating that NEAMS tools capture both steady-state and transient behavior across distinct microreactor concepts. In FY2025, the team advanced full-core, high-fidelity, multiphysics models that solve more complex problems and strengthen verification/validation for several microreactor systems: heat-pipe microreactor (HPMR), gas-cooled microreactor (GCMR), and the KRUSTY experiment. These models employ the MOOSE MultiApp/Transfers architecture with Griffin for neutronics, BISON for heat conduction/thermomechanics, Sockeye for heat pipes, SAM/THM for coolant channels and loops, and SWIFT for hydride behavior, with meshes generated via the MOOSE Reactor Module. The graphite models available in the Grizzly code were also investigated for future analyses. For the HPMR, a Na-HPMR variant was constructed to align with recently validated heat-pipe experiments and Sockeye’s LCVF capability, enabling mechanistic heat-pipe transients and startup modeling. The Na-HPMR will serve as the primary model for HPMR investigations in upcoming tasks. The load-following and single heat-pipe failure scenarios (Griffin/BISON/Sockeye), which were previously modeled for the K-HPMR, were replicated for the Na-HPMR, showing strong negative temperature feedback and highly localized thermal effects, respectively, while the startup case captured vapor-front progression and heat-removal activation. Solid mechanics was added to the previously built K-HPMR full-core model in BISON, showing minimal impact on steady-state reactivity yet enabling stress-field predictions that prepare the path for full-core TRISO performance analyses. For the GCMR, automated steady-state and four transient scenarios were executed using Griffin/BISON/SAM/SWIFT. Results confirm robust inherent safety: power collapses promptly in loss-of-cooling events, the inlet-temperature drop settles to a new equilibrium, and a single-channel blockage yields only a ~30 K local fuel-temperature rise with <0.4% power decrease. SWIFT-predicted hydrogen redistribution affects reactivity during both steady-state and transient conditions, underscoring its importance. A Brayton-cycle balance of plant (BOP) model in SAM/THM demonstrated stable startup behavior, and xenon-driven reactivity during load following was analyzed. To improve TRISO-compact temperature fidelity, a fast multiscale Heat Source Decomposition (HSD) treatment was implemented. Against heterogeneous benchmarks, HSD reduces underprediction of kernel temperatures and lowers predicted peak powers in reactivity-insertion transients compared to previous homogenized models. KRUSTY warm-critical validation progressed from FY2024 baselines: the 15Ȼ insertion shows excellent agreement in peak power (~2% high) and temperature trends, and the 30Ȼ case was automated via a feedback controller that maintained power near 3 kW for ~150 s with close agreement to data. The successful modeling of the warm critical tests has laid a strong foundation for simulating more complex nuclear system tests in the years ahead. Throughout FY2025, developer feedback was provided (e.g., MOOSE batch mesh generation, distributed pre-split meshes, Griffin sweeper on displaced meshes), several new models were contributed to the Virtual Test Bed, and an OECD-NEA WPRS multiphysics benchmark based on the HPMR was initiated to enable broader cross-comparison and best-practice development with the nuclear community at large.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

SIMD Programming for the SMASH Shock Physics Code

Many modern CPUs that are available to the NNSA as mission computing resources support vector instruction sets. Making good use of vector instructions, referred to as “vectorization”, is often critical to getting the best performance from these CPUs. While other codes choose to rely on compiler auto-vectorization, the SMASH shock physics code chooses to leverage APIs for explicit vectorization. These APIs are similar to directly calling the CPU vendor’s vector intrinsics, with the additional benefit of being vendor-agnostic. This document explains what the SIMD APIs are and how to use them in developing SMASH.

97 MATHEMATICS AND COMPUTING↗

SIERRA Code Coupling Module: Arpeggio User Manual - Version 5.28

The SNL Sierra Mechanics code suite is designed to enable simulation of complex multiphysics scenarios. The code suite is composed of several specialized applications which can operate either in standalone mode or coupled with each other. Arpeggio is a supported utility that enables loose coupling of the various Sierra Mechanics applications by providing access to Framework services that facilitate the coupling. More importantly Arpeggio orchestrates the execution of applications that participate in the coupling. This document describes the various components of Arpeggio and their operability. The intent of the document is to provide a fast path for analysts interested in coupled applications via simple examples of its usage.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

SIERRA Code Coupling Module: Arpeggio User Manual - Version 5.30

The SNL Sierra Mechanics code suite is designed to enable simulation of complex multiphysics scenarios. The code suite is composed of several specialized applications which can operate either in standalone mode or coupled with each other. Arpeggio is a supported utility that enables loose coupling of the various Sierra Mechanics applications by providing access to Framework services that facilitate the coupling. More importantly Arpeggio orchestrates the execution of applications that participate in the coupling. This document describes the various components of Arpeggio and their operability. The intent of the document is to provide a fast path for analysts interested in coupled applications via simple examples of its usage.

97 MATHEMATICS AND COMPUTING↗

The Sparks tracking code

This note introduces a new tracking code, Sparks, built on the foundations laid by hemod4 and designed for fast tracking of large ensembles of single particles over thousands of turns. The code is intended for the rapid evaluation of nonlinear lattice behavior through observables such as detuning, Poincaré sections, and smear, providing a computationally efficient alternative to large-scale dynamic aperture studies during lattice design and optimization.

43 PARTICLE ACCELERATORS↗

Stability optimization of energetic particle driven modes in nuclear fusion devices: the FAR3d gyro-fluid code

The development of reduced models provide efficient methods that can be used to perform short term experimental data analysis or narrow down the parametric range of more sophisticated numerical approaches. Reduced models are derived by simplifying the physics description with the goal of retaining only the essential ingredients required to reproduce the phenomena under study. This is the role of the gyro-fluid code FAR3d, dedicated to analyze the linear and nonlinear stability of Alfvén Eigenmodes (AE), Energetic Particle Modes (EPM) and magnetic-hydrodynamic modes as pressure gradient driven mode (PGDM) and current driven modes (CDM) in nuclear fusion devices. Such analysis is valuable for improving the plasma heating efficiency and confinement; this can enhance the overall device performance. The present review is dedicated to a description of the most important contributions of the FAR3d code in the field of energetic particles (EP) and AE/EPM stability. FAR3d is used to model and characterize the AE/EPM activity measured in fusion devices as LHD, JET, DIII-D, EAST, TJ-II and Heliotron J. In addition, the computational efficiency of FAR3d facilitates performing massive parametric studies leading to the identification of optimization trends with respect to the AE/EPM stability. This can aid in identifying operational regimes where AE/EPM activity is avoided or minimized. This technique is applied to the analysis of optimized configurations with respect to the thermal plasma parameters, magnetic field configuration, external actuators and the effect of multiple EP populations. In addition, the AE/EPM saturation phase is analyzed, taking into account both steady-state phases and bursting activity observed in LHD and DIII-D devices. The nonlinear calculations provide: the induced EP transport, the generation of zonal structures as well as the energy transfer towards the thermal plasma and between different toroidal/helical families. Finally, FAR3d is used to forecast the AE/EPM stability in operational scenarios of future devices as ITER, CFETR, JT60SA and CFQS as well as possible approaches to optimization with respect to variations in the most important plasma parameters.

Alfv én Eigenmodes↗

Validation of the SCALE/Polaris-PARCS Code Procedure with the ENDF/B-VII.1 AMPX 56-Group Library: Pressurized Water Reactor

This study was conducted to validate the SCALE/Polaris v6.3.0–PARCS v3.4.2 code procedure with the Evaluated Nuclear Data File (ENDF)/B-VII.1 AMPX 56-group library for pressurized water reactor (PWR) analysis, by comparing simulated results with measured data for critical experiments and operating PWRs. Uncertainties of the SCALE/Polaris–PARCS code procedure for PWR analysis were evaluated in the validation for the PWR key nuclear parameters such as critical boron concentrations, reactivity, control bank work, temperature coefficients, and pin and assembly power peaking factors.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Entity—Hardware-agnostic Particle-in-cell Code for Plasma Astrophysics. II. General Relativistic Module

Black hole (BH) environments often host plasmas that are fully collisionless or contain intrinsically collisionless regions, including relativistic jets and coronae, where particle energization is ubiquitous. Capturing the physics of these systems requires numerical methods capable of modeling relativistic, magnetized, collisionless plasmas in strong gravitational fields. In this work, we introduce the general relativistic module for Entity—the first open-source, coordinate-agnostic, performance-portable, particle-in-cell code. The code enables fast axisymmetric simulations of collisionless plasmas around BHs on any modern high-performance computing architecture (both GPUs and CPUs).

Galishnikova, Alisa [Flatiron Institute, New York,↗

ACDC (Automated Campbell Diagram Code) [SWR-26-042]

This application provides a web-based graphical user interface to generating Campbell Diagrams and visualizing mode shapes for OpenFAST turbine models. Determining the aeroelastic stability and dynamic characteristics of wind turbines is a critical step in turbine design and analysis. Historically, extracting natural frequencies and mode shapes from OpenFAST—the industry-standard whole-turbine simulation code—has been a fragmented and tedious process. It required manual model configuration, command-line linearization execution, and complex post-processing via proprietary scripts to handle rotating-frame dynamics. To address these workflow bottlenecks, we present the Automated Campbell Diagram Code (ACDC), an open-source graphical software tool developed by the National Laboratory of the Rockies (NLR) under the DOE-funded Distributed Wind Aeroelastic Modeling (dWAM) project. ACDC streamlines the end-to-end linearization and stability analysis workflow into a single, intuitive cross-platform application. The software guides users through OpenFAST model configuration, definition of operating points, and the automated execution of steady-state trim and linearization simulations. Under the hood, ACDC automates the complex mathematical post-processing steps required for rotating systems, including Multi-Blade Coordinate (MBC) transformations, eigenanalysis, and advanced modal tracking utilizing the Modal Assurance Criterion (MAC) and spectral clustering. Finally, ACDC processes these results to automatically generate Campbell diagrams and features a robust 3D visualization engine to animate full-system mode shapes. By eliminating the reliance on external post-processing environments and manual data manipulation, ACDC significantly accelerates dynamic analysis and lowers the barrier to entry for wind energy researchers and engineers.

Summerville, Brent [National Laboratory of the Roc↗

Data and Code for: Observation-constrained agroecosystem model inversion reveals continental-scale variation of winter wheat traits

This repository contains the simulation outputs and processing scripts associated with the study of winter wheat traits across the United States, utilizing the Ecosys agroecosystem model. The dataset includes model results for both rainfed and irrigated winter wheat systems, supporting the findings presented in the manuscript titled "Observation-constrained agroecosystem model inversion reveals continental-scale variation of winter wheat traits." Data includes the original Ecosys simulation outputs (archived in .db format within the compressed .zip files) and extracted analysis data (stored in .pkl files for efficient processing). Python code for data processing and figure generation is provided in a Jupyter notebook. External Observational Datasets should refer to the following official repositories for the input and validation data used in this study. The eddy covariance data from the AmeriFlux network (https://ameriflux.lbl.gov/). Climate-forcing data of NLDAS-2 from NASA LDAS (https://ldas.gsfc.nasa.gov/nldas/nldas-2-forcing-data). Soil data from the Gridded Soil Survey Geographic Database (gSSURGO), available at (https://www.nrcs.usda.gov/resources/data-and-reports/gridded-soil-survey-geographic-gssurgo-database). Crop yields, planting and harvest dates from the USDA public databases (https://quickstats.nass.usda.gov/; https://webapp.rma.usda.gov/apps/actuarialinformationbrowser/CropCriteria.aspx). Satellite-derived SLOPE GPP data from ORNL DAAC (https://daac.ornl.gov/cgi-bin/dsviewer.pl?ds_id=1786). Land use and crop progress information from the USDA Crop Data Layer and Crop Progress and Condition Gridded Layers (https://www.nass.usda.gov/Research_and_Science/). The Ecosys model code is available online at https://github.com/jinyun1tang/ECOSYS.

Wheat↗

Walnut v1.2 Code Abstract

Abstract for publication for copyright assertion for Walnut v1.2 software code to satisfy prime contract requirements. HQ approval to assert copyright on this code was granted to NNSS on 9/30/2024

47 OTHER INSTRUMENTATION↗

ASME Design Code Rule Changes for Nuclear Graphite

The American Society of Mechanical Engineers Boiler Pressure and Vessel Code (ASME BPVC) Section III, Division 5, Article HHA-3000 outlines graphite core component and graphite core assembly design guidelines. Graphite core components are defined as ?components manufactured from graphite that are installed to form a graphite core assembly within the reactor pressure vessel of a high temperature, graphite moderated fission reactor.? (p. 413) Graphites? inherent defect distributions do not allow for deterministic material reliability. Rather, graphite has variable strength distributions which change by grade. Article HHA-3000 outlines two semi-probabilistic methods, the full and simplified assessments, which set design load limit targets for each of three component structural reliability classes. The Design Task Group was officially recognized as a specialized task group within ASME November of 2023, though we?ve been collaborating since 2022. The purpose of the Design Task Group is to correct, clarify, and make HHA-3000 function as intended. The Design Task Group will sunset once we?ve achieved our objectives. The Design Task Group was specifically told to not write new Code. While there may be more precise and more accurate methods to determine reliability targets, the current methods are conservative, relatively simple to implement, and have thus far been considered satisfactory for setting design reliability targets. Much of the ground-work to write proposal files and background documents for records to make the changes needed to achieve our objective have been completed. The Design Task Group has documented much of their work through papers, presentations, and memorandums. Three memorandums in which INL team members had substantial contributions are found in the Appendices: FEA Modeling for the Baseline Program, Evaluating the Effects on Margin of Updating the Threshold and Shape Parameters in the Full Assessment, and Interpretations of the Full and Simplified Assessments in ASME BPVC. Most of the on-going work to achieve the Design Task Group?s objective will be addressing comments on existing records and moving records through the balloting process. The Design Task Group met bi-weekly mostly through the end of FY2023. Since February 2024, the Design Task Group has mostly been completed with solving and documenting the technical issues associated with the assessments. Unless new tasks are identified, the remaining work of the Design Task Group will be political and editorial.

97 MATHEMATICS AND COMPUTING↗

Reductive Analysis with Compiler-Guided Large Language Models for Input-Centric Code Optimizations

Input-centric program optimization aims to optimize code by considering the relations between program inputs and program behaviors. Despite its promise, a long-standing barrier for its adoption is the difficulty of automatically identifying critical features of complex inputs. This paper introduces a novel technique, reductive analysis through compiler-guided Large Language Models (LLMs), to solve the problem through a synergy between compilers and LLMs. It uses a reductive approach to overcome the scalability and other limitations of LLMs in program code analysis. The solution, for the first time, automates the identification of critical input features without heavy instrumentation or profiling, cutting the time needed for input identification by 44× (or 450× for local LLMs), reduced from 9.6 hours to 13 minutes (with remote LLMs) or 77 seconds (with local LLMs) on average, making input characterization possible to be integrated into the workflow of program compilations. Optimizations on those identified input features show similar or even better results than those identified by previous profiling-based methods, leading to optimizations that yield 92.6% accuracy in selecting the appropriate adaptive OpenMP parallelization decisions, and 20-30% performance improvement of serverless computing while reducing resource usage by 50-60%.

Input-Centric Optimization↗

Revisiting Source Convergence Diagnostics in the KENO Monte Carlo Neutron Transport Codes [Abstract]

Monte Carlo criticality transport codes, which rely on the power iteration procedure, are a fundamental tool for nuclear criticality safety practitioners in assessing the neutron multiplication factor (k eff ) for problems involving fissile material. In these calculations, ensuring the convergence of both the fission source distributions and the k eff estimate for accurate results is crucial. However, a converged k eff estimate does not necessarily mean the fission source distribution is also converged because the fission source and flux distribution may continue to evolve even after k eff convergence. Therefore, most Monte Carlo transport criticality codes now offer various diagnostic tests to assess fission source convergence in addition to the k eff convergence by analyzing the trends of these quantities over multiple generations.

AZURE↗

Multiphysics Demonstration of Temperature-Driven Assembly Bowing in SFRs using MOOSE-Based Codes

Core bowing is an important passive safety mechanism in liquid metal cooled fast reactors. When the core restraint system is properly designed, temperature and flux gradients influence assemblies in the core to bow into less reactive configurations during accident scenarios, resulting in negative reactivity feedback. Prediction of core bowing involves complex interplay of radiation transport, impacts of fluid flow and heat transfer on duct temperature, and mechanical responses to the induced temperature and flux gradients. Under the U.S. Department of Energy Office of Nuclear Energy’s Advanced Modeling and Simulation (NEAMS) Program [1], an integrated multiphysics approach is being developed to model the core bowing phenomena in liquid metal-cooled fast reactors with the Multiphysics Object Oriented Simulation Environment (MOOSE) [2]. In this methodology, the MOOSE-based reactor physics code Griffin [3] will solve the neutron transport equation and determine the power distribution. With the detailed power distribution from Griffin, the subchannel analysis codes MOOSE-Subchannel [4] and Pronghorn [5] are utilized to calculate the assembly temperature distribution. MOOSE’s Solid Mechanics [6] and Contact [7] Modules are leveraged to calculate the thermal expansion and duct bowing displacement with the duct wall temperature from thermal hydraulics calculation. In this work, an initial one-way coupling demonstration of the integrated multiphysics approach has been performed on a seven-assembly problem based on the sodium-cooled fast reactor ABR-1000 design [8]. The neutronics calculation with Griffin is not yet involved in the current simulation. MOOSE-Subchannel and Pronghorn evaluate fluid and solid temperature based on a fixed power distribution. In addition, one-way coupling is utilized in this coupled calculation, via Pronghorn passing the duct temperature data to the MOOSE Solid Mechanics calculation. An assessment of the Solid Mechanics module was performed in parallel to verify duct bowing behavior with duct-to-duct contact phenomenon [9]. The displacement from MOOSE Solid Mechanics is not yet transferred back and utilized in the Pronghorn and MOOSE-Subchannel calculation. This model will be available on the National Reactor Innovation Center (NRIC) Virtual Test Bed (VTB) repository [10]. Future stages of this work will involve solving problems of increasing complexity as well as adding more physics (e.g. reactor physics) to the integrated workflow to reach the end goal of modeling the core bowing phenomenon with an integrated multiphysics workflow.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

Sockeye Code Validation Against UNIST Heat Pipe - Poster - Internship 2025

Sockeye is an engineering level code being developed under the MOOSE framework for modeling heat pipes. A heat pipe is a sealed tube with a wick structure filled with a working fluid that transfers heat efficiently and passively via phase change of the working fluid. Heat applied to the evaporator end creates a pressure gradient which causes vapor to migrate to the condenser end where the vapor deposits its energy and condenses. Capillary force generated by the wick structure then draws the liquid back to the evaporator. A validation study was performed to compare the Sockeye code against data produced at the Ulsan National Institute of Standards and Technology for a slightly overfilled sodium heat pipe. The heat pipe was operated under natural convection cooling and a decreasing inactive length was observed. The experiment was modeled in Sockeye using the condenser pool model, the front non-condensable gas (NCG) model, and the mixture NCG model separately to reproduce the inactive length phenomenon. Also, a new capability was implemented in MOOSE to allow for conjugate heat transfer from the condenser based on the Churchill-Chu correlation for natural convection. The condenser pool model showed an increasing inactive length, demonstrating that the behavior was likely not caused by a pool of excess liquid. The front NCG model was able to show good agreement with the experiment, but it suffered convergence issues at the front. Finally, the mixture NCG model gave good results when the axial mesh was sufficiently refined. This work culminated in additions to the Sockeye documentation and a contribution to a journal article that will be published later. This poster is a summary of my work which I can take back to my university for presentation.

42 - ENGINEERING↗

COR-0011 Rev 6 MARVEL Project Code of Record

This Code of Record identifies the codes, standards, and procedures necessary to design, develop, construct, and startup the Microreactor Applications Research Validation and Evaluation (MARVEL) Project at the Materials and Fuel Complex (MFC) Transient Reactor Test (TREAT) Facility and the Idaho National Laboratory (INL). The MARVEL Project is an INL test microreactor funded by the United States Department of Energy (DOE) via the Microreactor Program (MRP). The goal of the project is to establish an operational nuclear applications test bed that can generate combined heat and power to enable integration and R&D with end-user technologies, as well as allow microreactor technologists to test next-generation control systems. The microreactor is a thermal reactor utilizing Uranium Zirconium Hydride (UZrH) fuel with review and authorization by the Department of Energy Idaho Operations Office (DOE-ID) for National Environmental Policy Act (NEPA) compliance, safety review, and supplemental readiness assessments for startup and operation. To enable rapid deployment, the MARVEL reactor will reside in the Transient Reactor Test (TREAT) Facility and utilize the existing operating Category B reactor facility, approved facility safety basis, operating crews, and recent re-start experience.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗