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At least 307 records · Page 17

Status of the NEAMS and ARC neutronic fast reactor tools integration to the NEAMS Workbench

The Workbench initiative was launched in FY-2017 within the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program to facilitate the transition from conventional tools to high-fidelity tools. The Workbench provides a common user interface for model creation, real-time validation, execution, output processing, and visualization for integrated codes. The integration of the Argonne Reactor Computation (ARC) suite of codes into the NEAMS Workbench was initiated in FY-2017.

97 MATHEMATICS AND COMPUTING↗

URBANopt: An Open-Source Software Development Kit for Community and Urban District Energy Modeling: Preprint

Urban building modeling tools are developing rapidly; these tools use emerging simulation workflows for specific urban environmental design tasks, such as assessing the impacts of energy efficiency technologies at a district scale. However, with the emergence of new environmental design tasks, addressing all possible use cases and tasks is challenging and cannot be covered by a single tool. Urban-scale analysis at this level of complexity often requires linking multiple emerging tools, rather than using a single tool, to adequately evaluate a variety of possible fields in urban environmental design. To achieve this, flexible platforms are needed to support multiple input formats (e.g., geometric and non-geometric building properties), enabling the mapping of such inputs to underlying simulation engines. This paper provides an overview of the open-source URBANopt Software Development Kit (SDK) for modeling high-performance buildings and energy systems at a district scale. URBANopt's flexible SDK is composed of several modules that can be customized to integrate with other tools and generate new workflows to perform urban environmental design tasks, such as capturing interactions between individual buildings, district energy systems, distributed energy resources, and the electric distribution grid. We describe the functionality of the core SDK modules in URBANopt (called Core Gem, GeoJSON Gem, and Scenario Gem) and discuss the flexibility of these modules as a means of integration with a variety of tools. We also document and demonstrate technical details of writing and combining new modules to create customized workflows. Finally, we present a case study that uses the URBANopt SDK to model a hypothetical mixed-use urban project and simulate various scenarios to meet district energy performance goals.

buildings↗

Continued Verification of MOOSE Structural Mechanics Tools for Modeling Core Bowing Phenomena in Fast Reactors

Under the U.S. Department of Energy Office of Nuclear Energy’s Advanced Modeling and Simulation (NEAMS) Program, an integrated multiphysics approach is being developed to model the core bowing phenomena important to liquid metal-cooled fast reactors. Core bowing is an important passive safety mechanism whereby increased power (which leads to temperature and flux gradients) influences the core to bow into less reactive configurations when the restraint system is properly designed. The phenomenon includes a complex interplay of radiation transport, duct temperature calculations involving fluid flow and heat transfer, and thermo-mechanical responses to the induced temperature and flux gradients. Structural material properties are also important to determining inelastic response to longer term flux gradients which cause irradiation creep and swelling. While core bowing provides a strong negative reactivity feedback when the restraint system is designed properly, it also results in additional forces between assemblies which increase the loads required to extricate them during refueling or control rod movement. Therefore, the restraint system must be designed with these tradeoffs in mind. The first stage of the work, which commenced in FY21 and continues through FY22, assesses thermo-mechanical modeling tools for producing core bowing predictions consistent with conventional tools. The Multiphysics Object Oriented Simulation Environment (MOOSE) Tensor Mechanics and Contact Modules are employed. This status report describes work on additional thermo-mechanical benchmark verification problems with increased complexity from the examples demonstrated in FY21. Several benchmark verification examples were selected from the IAEA verification and validation report. These examples involve clusters of ducts representative of a sector of a hexagonal reactor core which bow into each other and cause contact and load pad elevations, as well as single ducts subjected to irradiation fields undergoing swelling and subsequent bowing. The MOOSE-based results were compared to both IAEA benchmark participants’ results, analytic equations as available, and NUBOW-3D, a beam model code developed by Argonne National Laboratory. In every case, the MOOSE results agreed with other simulations results, providing additional verification basis of the tools for this particular physics application.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Enabling Dynamic Probabilistic Risk Assessment of Physical Security Using EMRALD and MAAP

The optimization of physical security in nuclear power plants requires sophisticated methodologies that integrate operator actions and plant behavior through advanced simulation tools. To address this, Idaho National Laboratory [JL2.1]has developed the Modeling and Analysis for Safety and Security using the Dynamic EMRALD Framework (MASS-DEF) methodology, an approach that integrates force-on-force simulations, dynamic probabilistic risk assessment, and thermal-hydraulics modeling [JL3.1]to enhance security planning while reducing costs. We developed a tool that produces reduced order models using thermal hydraulic simulations from the Modular Accident Analysis Program (MAAP) [1]. These models can quickly evaluate reactor core behavior during attack simulations, and in so doing, address two barriers of traditional methods: (1) MAAP simulations are computationally intensive, and (2) attack scenarios must be run in a secure environment, which complicates analysis and validation. By precomputing scenario outcomes for a small number of modified parameters, the reduced order model significantly decreases the computational cost and enables offsite review of the results.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

Predicting the evolution of biomass bulk density through feedstock preprocessing: Discrete element modeling, regression analysis, and pilot-scale validation

Bulk density is an important material property of biomass feedstocks, influencing handling, storage, transport costs, and conversion efficiency. In this study, predictive regression models for loose and tapped bulk densities of Alamo and Cave-in-Rock switchgrass are developed using a comprehensive dataset generated via calibrated bonded-sphere discrete element method (DEM) simulations. Here, a key contribution of this study is the use of a DEM-based approach, which correlates density with moisture content and particle size distribution parameters and enables analysis across a continuous particle size range, overcoming limitations of purely experimental data. For comparison, regression models are also developed using only experimental data from pilot-scale runs at the Biomass Feedstock National User Facility at Idaho National Laboratory. Validation against pilot-scale data showed reasonable prediction accuracy for both model types, particularly for smaller particle sizes (post-secondary grinding). While the experimental model showed slightly better performance matching the validation data in some cases, the DEM-based model benefits from a much larger dataset, reduced predictor multicollinearity, and continuous parameter coverage, highlighting the utility of validated simulation models for developing robust predictive tools for biomass preprocessing applications.

09 - BIOMASS FUELS↗

PyNetUQ

SAND2021-3242 O PyNetUQ is a Python library for network uncertainty propagation. Custom interface classes for components are modeled individually with potentially distinct simulation tools. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Tencer, John↗

Combined Environments: Driving multiple loads on Z

Pulsed power drivers such as the Z generator of Sandia National Laboratories typically deliver high current (>20MA) to single experiments. This project is intended to develop and assess ways to simultaneously drive multiple targets on a single pulsed power driver (specifically a neutron and an x-ray producing target driven in a single experiment). The combined x-ray/neutron environment produced will then be used to investigate potential synergistic effects in integrated circuits. A pre-requisite for being able to design and study multiple targets on Z is first adapting simulation tools to be able to model them effectively. This will enable us to assess the tradeoffs between the different ways multiple targets can be combined, and to better understand how existing and future pulsed power machines can be used to generate combined testing environments. This report is limited to documenting the initial development of a parallel load modeling capability that is presently being applied to design experiments to produce combined neutron/x-ray environments on Z.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Materials genome innovation for computational software (magics) center

Functional layered material (LM) architectures will dominate nanomaterials science in this century. We have developed theory, modeling, simulation, and software and data tools that enhance understanding and AI guide synthesis, enable characterization of complex structures, and improve capabilities in the predictive design and growth of LMs. Research at the Center has focused on: Computational synthesis and characterization: AI guided synthesis and experimental synthesis of stacked LMs with tailored properties via optimized chemical vapor deposition (CVD) growth and liquid-phase exfoliation; study defects, edges, grain boundaries, wrinkling of atomic layers and their effects on chemical, mechanical, electrical, and optical properties. Far-from-equilibrium processes: Joint experimental and simulation based probe of electronic processes with NAQMD and ultrafast X-ray free-electron laser (XFEL) and ultrafast electron diffraction (UED) facilities at Stanford. Experimentally validate NAQMD by ultrafast electron diffraction and X-ray spectroscopy studies of structural and excited state dynamics, shape fluctuations, and phonon dynamics. Scalable software: Simulation engines for desktop-to-exascale platforms using low-overhead, linear-scaling QMD algorithms; divide-conquer-recombine NAQMD with electronic excitations; extended-Lagrangian reactive molecular dynamics (RMD), machine learning (ML) based neural-network quantum molecular dynamics (NNQMD), and super-state accelerated molecular dynamics (AMD) and kinetic Monte Carlo codes; thermal and electrical transport software; and design 3D architectures of LMs with desired functionality using scalable software. Distribution of software and data, and training: Software and simulation-experimental data generated within the Center are distributed to the materials science community via Berkeley Materials Project (MP) framework. We have also organized three workshops for software distribution and training at USC (Nov. 2017, Mar. 2018) and Gaithersburg, MD (Nov. 2018) to train researchers, with the last one in focused on underrepresented groups, in collaboration with Howard University which is one of the largest HBCUs. The Center supported a total of 46 personnel and 6 undergraduate students. These include 14 faculty, 11 postdoctoral research associates, 20 graduate research assistants, and mentored 6 undergraduate students. This resulted in the publications of 63 research papers that include 46 publications on Reactive and Quantum Dynamics Simulations, 13 publications on Machine Learning for Quantum Materials, and 4 publications on Quantum Computing.

2D Materials↗

Guided Resilience Self Assessment Application

Reliable electricity access is vital for everything from hospitals to national security. When grid disturbances occur, it is crucial to minimize the amount of time it takes to recover. Grid resiliency considers both the preparation for and recovery from high-impact low-frequency disturbances (HILF) such as weather events and cyber attacks. The Department of Energy (DOE) Wind Energy Technologies Office (WETO) funds the multi-laboratory Microgrids, Infrastructure Resilience, and Advanced Control Launchpad (MIRACL) project to investigate technologies to support and grow distributed wind. Researchers at Idaho National Laboratory (INL) contribute to resilience and cybersecurity efforts for the project, and have produced a resilience framework to evaluate system resilience based on individual system specifications. In order to make this framework easy for anyone to apply, I have coded a web application that allows users to input their power system qualities, goals, and perceived risks and then receive suggestions on how to improve their grid resiliency. The web application follows the seven steps in the planning stage of the framework process, allowing the user to input information about their grid and select from common goals, metrics, and hazards, as well as add their own. The application currently provides information about how to complete each step, requiring minimal prior knowledge of the framework. Future work for this application will include allowing the user to submit line drawings of their system and incorporate modeling tools so that the hazard simulations of applying the framework is completed for the user.

97 MATHEMATICS AND COMPUTING↗

Lignin Utilization

Valorization of lignin has massive potential economic and sustainability benefits for the lignocellulosic biorefinery. However, challenges remain to realize lignin conversion to coproducts, especially related to selective, high yield depolymerization to monomers and quantitative analytics on lignin, the latter of which is critical for accurate process modeling. Towards these goals, the Lignin Utilization project focuses on catalytic lignin deconstruction chemistries for C-O and C-C bond cleavage, development of analytical chemistry techniques to quantitatively characterize lignin, and syntheses of requisite model compounds for understanding lignin transformations. This work is done with and supports multiple BETO projects, including the Biological Lignin Valorization (BLV) project, the Separations Consortium, and others. Outcomes of Lignin Utilization for analytics and synthesis include 1) development of new mass spectrometry (MS) methods to characterize lignin dimers/oligomers in process streams, 2) deployment of a computational-experimental tool (with Biochemical Process Modeling and Simulation) to identify lignin-derived compounds with high fidelity from MS, and 3) delivery of >40 unique compounds. From a catalysis perspective, we have developed new oxidative approaches to cleave C-O and C-C bonds and produce >50% bio-available aromatic monomers for biological funneling for the BLV project and have developed recoverable bases for base-catalyzed deconstruction of lignin.

BIOMASS FUELS↗

Internship Presentation: Integrating Safety and Cybersecurity: Security-by-Design with SOWT Analysis for Reactor Testing

This study covers leveraging reactor testing facilities that are primarily designed with a focus on safety to enhance cybersecurity testing. By incorporating reactor security-by-design with reactor safety-by-design principles and adopting defense-in-depth strategies that emphasize both safety and security, the research evaluates applicable cyber tools, models, and solutions. This includes simulating specific cyber-attack scenarios using reactor simulators and performing SWOT (Strengths, Weaknesses, Opportunities, Threats) analysis to improve the cybersecurity of reactor systems.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗

Improving Residential Building Simulations Through Large-Scale Empirical Validation

Residential building energy simulations are increasingly used for energy-efficient building design, codes and standards analysis, home certifications and ratings, utility programs, and technology assessments. Various software tools exist to perform residential building simulations, and these tools often use different models, inputs, and assumptions. This leads to inconsistencies that can undermine confidence in the predicted results. Validation of these tools can increase confidence by ensuring their accuracy and consistency. One way to validate simulation tools is through empirical testing, which compares predicted energy usage to measured utility billing data. This paper describes the process of data collection, data standardization, and empirical validation, and illustrates its use with our residential EnergyPlus (R)-based software. The data and process can be extended to other simulation tools and contribute to improving residential building simulations more broadly.

empirical validation↗

An Energy Calculator for Simple Commercial Buildings

According to the EIA, simple commercial buildings account for 97% of total commercial building stock. However, most simple commercial buildings for example small- to mid-sized offices, retail, schools and warehouses do not benefit from the data-driven decision-making capabilities of whole-building energy modeling. The high cost of custom modeling limits the use of energy modeling of simple buildings for new construction or retrofit measures. Lack of tools providing helpful information on interactive savings estimates creates difficulties in meeting aggressive decarbonization and energy efficiency goals for simple building designers and utility program managers. This paper reviews a beta phase Simple Building Calculator with the ability to generate relatively accurate and interactive modeling results based on a limited but robust set of inputs. It can evaluate whole-building or single measure savings in new or existing buildings, compare measure package choices, or provide simplified performance modeling for energy codes and utility incentives. The tool combines physical (annual whole building prototype simulation) and statistical modeling techniques to predict annual energy performance. It supports a variety of building characteristics for envelope, HVAC, and lighting with parameters ranging from vintage to max tech configurations, as well as support for single-zone and simple multi-zone HVAC systems. The Simple Building Calculator was designed to provide immediate feedback for otherwise computationally intensive tasks like measure comparison, development of multiple measure package combinations, or verification that measures meet efficiency targets—all with the goal of providing a tool for quick annual energy simulation of simple commercial buildings.

Hart, Reid↗

An Extensible High Energy Density Modeling Tool for Extreme Regimes

The overreaching goal of the project is to develop a simulation capability to model an entire High Energy Density (HED) target heated by an X-ray Free Electron Laser (XFEL) beam including the surrounding material with a focus on target material associated with subsequent shots. Our primary objective is to study target fratricide problems, where radiation/debris from the current shot degrade the target for subsequent shots. This work will have a large impact on research being conducted at HED facilities where the quality of data is directly related to the effective repetition rate of the driver, which is often limited by target fratricide problems. This project focuses on a stream of closely spaced droplet targets that are appropriate for new very high repetition rate sources such as the ~1 MHz LCLS-II upgraded XFEL. The capability of the PISALE (Pacific Island Structured-AMR with ALE) code is extended to model this class of problems. We summarize the capability and improvements made to the HED branch of the PISALE code. We discuss our simulations of target fratricide for small (5 micron) hydrogen droplets heated by an XFEL beam at SLAC. We also compare simulations of the initial dynamics of larger (50 micron) water droplets, heated by the same XFEL beam, with experimental data. We briefly discuss training, dissemination, and related activities associated with this project.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

2025 Intern Poster - Abbigail Short

The OSCC Coupling Shaft Handling Fixture, known as the "Puppy Dog Tool," was originally designed by hand in 1976. The initial design was difficult to read and replicate, lacking 3D modeling for simulations and testing. To modernize the tool, the original drawings were reviewed and recreated in Autodesk Inventor with increased spacing for clarity. Key improvements included adding a hook, modifying the top plate and main body connection, and introducing a guiding wall for the clamp. These changes enhanced durability and usability, preventing bending and facilitating easier assembly. The updated design preserved the tool's functionality while making it more robust and user-friendly for high-precision operations.

99 - GENERAL AND MISCELLANEOUS↗

ParFlow Sand Tank: A tool for groundwater exploration

The ParFlow Sand Tank model is an open source application designed to allow users to interactively simulate and visualize groundwater movement through the subsurface. The app is designed for both research and education; teaching hydrogeology concepts and making it easy explore and run sophisticated groundwater simulations. Our goal is to support increased accessibility and usability of research grade hydrology tools for research and teaching. The Sand Tank application simulates groundwater and surface water fluxes as well as contaminant transport in real time using the integrated physical hydrology model ParFlow (Kollet & Maxwell, 2006; Maxwell & Miller, 2005; Osei-Kuffuor et al., 2014) and the particle tracking code EcoSlim (Maxwell et al., 2019). ParFlow is a numerical hydrology model that simulates spatially distributed groundwater and surface water flow. It is a well established research tool with more than 90 publications documenting its development use to advance our understanding of groundwater dynamics and groundwater surface water interactions from the hillslope to the continental scale e.g. (Condon et al., 2020; Condon & Maxwell, 2019; Maxwell & Condon, 2016). It is designed for efficient parallel computation and has been run on many platforms spanning from laptops to supercomputers. However, one of the challenges of ParFlow is that it requires significant training and hydrologic expertise to develop simulations. The Sand Tank application makes this model accessible to anyone for education and exploration. Our application uses ParFlow for its simulation backend and ParaView for the data loading and processing. The communication infrastructure relies on the ParaViewWeb framework. We use model templates deployed in Docker images to setup the Sand Tank framework. Users can build the application locally or interact with it through our web deployment. When interacting with a template users can interactively change model parameters like subsurface processes or pump/inject water into the subsurface and watch the system respond to their changes in real time as the simulation runs. Additionally, our template setup will allow more advanced users to build custom templates of increasing complexity for both research and educational purposes.

54 ENVIRONMENTAL SCIENCES↗

Multiphysics Simulations of MSRE with NEAMS Thermal Hydraulics Tools

This report documents the benchmarks being developed and simulations performed using tools and codes developed under the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, utilizing MSRE experimental data. In FY23, three main work scopes were investigated under the NEAMS MSR work package at ANL. The first scope investigated the Griffin-SAM coupling model for simulating the pump startup transient experiment of MSRE. The analyses start with a simple model (single-channel, single-lattice), gradually adding more details (multi-channel, full-core) into the model. The results show that the reactivity loss curve is very sensitive to the axial boundary conditions and the radial core discretization. The simple model can predict a similar reactivity trend as that of the more sophisticated model, which is likely due to error cancellation. Accurately modeling the axial boundary condition may further improve the reactivity trend but would require significant efforts to generate the mesh of the MSRE inlet and upper plenum. The core channel radial discretization for the Griffin-SAM coupled model also depends on the flow distribution. Given the complex geometry in the inlet plenum, the flow distribution needed to be calculated from CFD analysis, which was performed using the NekRS code. This analysis employed a MSRE CAD model developed by Copenhagen Atomics. The CAD model was disassembled to keep the inlet plenum region only, which was subsequently cleaned and modified so that the mesh generated is under the memory limit. The results are merged to a few radial regions to show that the flow rate is highest in the central region. This would be useful for future improvement of the Griffin-SAM coupling model of the MSRE core. The last task investigated is tritium transport modeling using the standalone SAM code. This task aimed to initiate the effort to demonstrate and validate the tritium transport model implemented in SAM. The preliminary investigation employed an MSRE model consisting of the primary loop. Three tritium transport pathways were examined including the retention in the graphite, the permeation through the HX tube wall, and the removal from the off-gas system. The results compare well with the MSRE data, but improvements are still needed on the initial conditions (i.e., the present state may not have reached equilibrium), the boundary conditions, the off-gas system modeling, and a better numerical strategy to reach the equilibrium state.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Using Hydrodynamic Similarity as a Verification Method for Impact Cratering Simulations in the FLAG Hydrocode

Hydrodynamic codes (hydrocodes) are common tools for modeling hypervelocity impacts to provide insight into the physical phenomenon. Hydrocodes can simulate impacts from micrometer to kilometer spatial scales and reach impact velocities difficult to achieve in experimental settings. However, numerical models are approximations, and demonstrating that a numerical method is capable of providing physical results for these models is essential. In this work, we employ a hydrocode verification technique that leverages hydrodynamic similarity, a mathematical property of the conservation equations of fluid mechanics that form the basis for hydrocode models. Using the FLAG hydrocode, we simulate aluminum (Al) and basalt projectiles and targets at spatial scales spanning 7 orders of magnitude (hundreds of micrometers to kilometers). These materials were chosen because Al-6061 is a common material in spacecraft and satellites and basalt is a useful approximation of rocky astronomical bodies. Our results show that hydrodynamic similarity holds for each material model used and across spatial scales. We show that under certain conditions hydrodynamic similarity can apply in the presence of gravity and that similarity does not hold in the presence of strength models. We conclude that the FLAG hydrocode preserves important mathematical properties of fluid dynamics in hypervelocity impacts of Al-6061 and basalt.

79 ASTRONOMY AND ASTROPHYSICS↗