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At least 487 records · Page 27

Development for Integrated System-Level Analysis Capabilities in SAM for Molten Salt Reactors

In recent years, there has been renewed interest in Molten Salt Reactors (MSRs) for their potential advantages compared to reactors that rely on solid fuel. In response to such interest, many methods and codes have been developed to capture the unique features of MSRs. Among them, the System Analysis Module (SAM) is a modern system analysis tool that provides fast-running, modest-fidelity, whole-plant transient analysis capabilities, essential for fast-turnaround design scoping and engineering analyses of advanced reactor concepts. For liquid-fuel MSRs, the complex physics and chemistry involved in MSR operation—such as reactor kinetics, fluid flow, heat transfer, and salt composition dynamics—pose significant challenges for system-level modeling. Specific modeling capabilities are needed for system-level transient simulation. This paper presents recent advancements in SAM capability enhancements for system-level modeling of MSRs, focusing on improved simulation fidelity, computational efficiency, and multi-physics integration. Key enhancements include the development of species transport, Delayed Neutron Precursor (DNP) drift, modified Point Kinetics Equations (PKE), decay heat modeling, key fission product behavior, salt corrosion, and thermal-hydraulic coupling, as well as code robustness and performance enhancements for MSR applications. The code enhancement allows for better predictive accuracy in safety analysis, transient behavior, and operational optimization, thus supporting the design and licensing of next-generation MSRs. Results from case studies are presented to demonstrate the benefits of these enhancements in accurately capturing key reactor transient behaviors.

Hu, Rui (ORCID:0000000237712920)↗

SCALE Modeling of the Sodium Cooled Fast-Spectrum Advanced Burner Test Reactor

This report documents the modeling and simulation of a sodium-cooled fast reactor (SFR) as part of a U.S. Nuclear Regulatory Commission–sponsored project to assess the modeling and simulation capabilities for accident progression, source term, and consequence analysis for advanced reactor technologies with the Oak Ridge National Laboratory code SCALE and the Sandia National Laboratories (SNL) code MELCOR. Based on publicly available benchmark specifications, a fully heterogeneous 3D SCALE model of the 250 MWth Advanced Burner Test Reactor (ABTR) was developed to demonstrate SCALE’s capabilities for full-core reactivity analysis, fuel inventory prediction, and decay heat analysis of an SFR. The benchmark specifications contain modeling details for the ABTR core at the beginning of equilibrium cycle (BOEC) at operating conditions; they were derived from a 2006 preconceptual design report produced by Argonne National Laboratory. The ABTR was designed to demonstrate reactor-based transmutation of transuranics, that is, to “burn” transuranics recovered from light-water reactor (LWR) spent fuel. The ABTR’s fuel is designed to operate in 4 month cycles using uranium/transuranic (U/TRU) metallic fuel, with a TRU content of approximately 20%, at a conversion ratio of approximately 0.6. Various reactivity calculations were performed with SCALE for the ABTR and, where possible, compared with results available in the open literature. Additionally, SCALE was used to perform a full-core depletion calculation over the 4 month cycle to obtain the nuclide inventory at the end of equilibrium cycle (EOEC). These nuclide inventories, decay heat, power profiles, and reactivity feedback coefficients at EOEC represent the initial conditions for analyzing severe accident scenarios with MELCOR.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

A Power Application Developer’s Guide to the Common Information Model: An Introduction for Power Systems Engineers and Application Developers – CIM17v40

A key issue in creating the next generation of energy management system (EMS) and advanced distribution management system (ADMS) platforms will be the ability to represent and exchange power system network model data in a consistent manner. To this end, the Common Information Model (CIM) stands out as the only standardized vocabulary (or ontology) for defining power system network models and asset data in a comprehensive, consistent manner across the generation-transmission-distribution boundary. The CIM is freely available to use and extend. The CIM is maintained by the UCAiug (informally known as the CIM User’s Group) under an Apache 2.0 license. The CIM Users Group collaborates with the IEC and other standards communities for the development of technical and informative specifications. Although portions of the information model are referred to by the corresponding IEC standards naming, it is not necessary to purchase any of the IEC standards to use the CIM information model. This document provides a roadmap for power system engineers and application developers not familiar with semantic modeling to start using the CIM for modeling, simulation, optimization, and development of advanced power applications. The key classes needed for defining power system topology and equipment are explained systematically. Key focus areas include modeling of lines, transformers, generators, switching equipment, loads, and distributed energy resources (DERs).

97 MATHEMATICS AND COMPUTING↗

The design and operation of a planet emitted and albedo radiation simulator

A simulator is described, which provides a dynamic simulation of planetary albedo and planet-emitted thermal radiation. The simulator was designed for model tests of advanced thermal control concepts, the development of space hardware, and flight qualification of small payloads. The simulator was designed to be used in a vacuum chamber equipped with liquid nitrogen cold walls and a solar simulator. The simulator consists of two major components: a gimbaled model support system and an array of quartz infrared lamps. Tests indicate that the apparatus will satisfactorily simulate the secondary radiation on a 0.92-meter spherical body in near-earth orbits. Calculations indicate that other shapes can be accommodated without structural modifications.

Sweet, G. E.↗

Solving Navier-Stokes Equations with Advanced Turbulence Models on Three-Dimensional Unstructured Grids

USM3D is a widely-used unstructured flow solver for simulating inviscid and viscous flows over complex geometries. The current version (version 5.0) of USM3D, however, does not have advanced turbulence models to accurately simulate complicated flows. We have implemented two modified versions of the original Jones and Launder k-epsilon two-equation turbulence model and the Girimaji algebraic Reynolds stress model in USM3D. Tests have been conducted for two flat plate boundary layer cases, a RAE2822 airfoil and an ONERA M6 wing. The results are compared with those of empirical formulae, theoretical results and the existing Spalart-Allmaras one-equation model.

Wang, Qun-Zhen↗

Simulation model of a twin-tail, high performance airplane

The mathematical model and associated computer program to simulate a twin-tailed high performance fighter airplane (McDonnell Douglas F/A-18) are described. The simulation program is written in the Advanced Continuous Simulation Language. The simulation math model includes the nonlinear six degree-of-freedom rigid-body equations, an engine model, sensors, and first order actuators with rate and position limiting. A simplified form of the F/A-18 digital control laws (version 8.3.3) are implemented. The simulated control law includes only inner loop augmentation in the up and away flight mode. The aerodynamic forces and moments are calculated from a wind-tunnel-derived database using table look-ups with linear interpolation. The aerodynamic database has an angle-of-attack range of -10 to +90 and a sideslip range of -20 to +20 degrees. The effects of elastic deformation are incorporated in a quasi-static-elastic manner. Elastic degrees of freedom are not actively simulated. In the engine model, the throttle-commanded steady-state thrust level and the dynamic response characteristics of the engine are based on airflow rate as determined from a table look-up. Afterburner dynamics are switched in at a threshold based on the engine airflow and commanded thrust.

Buttrill, Carey S.↗

Development of a Griffin model of the advanced test reactor

In the pursuit of a higher fidelity deterministic simulation capability of the Advanced Test Reactor, it is important to have a fast yet accurate deterministic neutronics model. Here, to achieve this, we employed an advanced two-step method. The first step involves generating homogenized cross sections using OpenMC, a cutting-edge Monte Carlo neutron transport code. OpenMC offers excellent modular capabilities, allowing for easy component integration and flexibility in incorporating new designs into the model. The second step involves deterministic transport calculations, which are performed using Griffin, a reactor physics application based on the Multiphysics Object-Oriented Simulation Environment (MOOSE). To ensure the accurate spatial resolution and assignment of material cross sections, a Cubit-generated mesh for the Advanced Test Reactor is utilized as an intermediate step between the OpenMC and Griffin models; Griffin utilizes the mesh for its finite element solution, while OpenMC material identifications are written to the mesh file to be used in Griffin material assignments. Additionally, a Python-based script converts the cross sections generated by OpenMC into the ISOXML format required by Griffin. Initial comparisons using the Griffin diffusion solver indicated good agreement between the neutron multiplication factors obtained from the standalone OpenMC model and the Griffin model, with differences of less than 10 pcm in the 2D geometry configuration; it was later determined that this agreement was likely due to compensating effect and was more likely on the order of –700 pcm relative to the OpenMC solution. However, in three-dimensional calculations, an unacceptably large error (almost 8,000 pcm) was found in the Griffin solution with the diffusion solver. Subsequent calculations using Griffin’s discrete ordinates solver demonstrated substantially improved agreement, within 116 pcm of the OpenMC solution used to generate the cross sections for Griffin. Building on this capability, future work will seek to perform more detailed validation calculations. The ultimate goal is to evaluate both transient and multiphysics simulations of the reactor.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Stone Content Influence on Land Surface Model Simulation of Soil Moisture and Evapotranspiration at Reynolds Creek Watershed

Considerable advancement in spatiotemporal resolution of remote sensing and ground-based measurements has enabled refinement of parameters used in land surface models for simulating surface water fluxes. However, land surface modeling capabilities are still inadequate for accurate representation of subsurface properties and processes, which continue to limit the accuracy of land surface model simulation. Our objective in this study was to examine the performance of the variously parameterized Noah-Multiphysics (Noah-MP) land surface model and to improve simulations of evapotranspiration (ET) and soil moisture dynamics in stony soils using verification from eddy covariance ET and in-situ soil moisture data. Meteorological and eddy covariance data from the Lower Sheep sub-catchment within the Reynolds Creek Experimental Watershed in Southwestern Idaho were employed to drive Noah-MP and to assess simulation results. We evaluated the performance of Noah-MP considering four different scenarios: (1) A one-layer soil profile with Noah-MP default soil hydraulic parameters, followed by five-layer soil profiles using -(2) Noah-MP default soil hydraulic parameters -(3) soil hydraulic parameters derived from a pedotransfer function using field observations, and -(4) hydraulic parameters from (3) which also accounted for stone content in each layer. Each modeling experiment was forced with the same set of initial conditions, atmospheric input and vegetation parameters. Our results indicated that enhanced representation of soil profile properties and stone content information noticeably improve the Noah-MP land surface model simulation of soil moisture content and evapotranspiration.

Land surface models, Soil hydrology, Noah-MP, Evap↗

Recent Advanced Reactor Multiphysics Model Highlights in the Virtual Test Bed (VTB)

The Virtual Test Bed (VTB) host over 30 distinct simulations that showcase state-of-the art capabilities across the national lab complex. An update on the status of models on the VTB is summarized here, along with a more detailed overview of select recent new capabilities to showcase. All of the major advanced reactor types are represented in the VTB. The first example consists of a multiphysics simulation to track the transport of species in Molten Salt Reactors using depletion, advection, and thermochemical calculations. The second consists of a coupled neutronic and thermal hydraulic simulation to validate a gas cooled reactor. The third consist of pebble-bed equilibrium model for a fluoride high-temperature reactor. The fourth is a high-fidelity neutronic and thermal hydraulic model of a liquid metal reactor assembly. And lastly the fifth consists of transient multiphysics simulations of heat pipe microreactors.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

28 NREL Stratus - Enabling Workflows to Fuse Data Streams, Modeling, Simulation, and Machine Learning: Preprint

Integrating cloud services into advanced computing facilities provides significant new capabilities over focusing solely on traditional high performance computing (HPC) workloads. This brings complementary capabilities as well as enabling new focused roles for HPC. They are especially potent for workflows that fuse data streams, modeling and simulation ('modsim') and machine learning. A key challenge to adopting a hybrid edge-cloud-HPC model is to align optimal capability, data, and user intent on the right resources for each step in a workflow.?The NREL Stratus service provides a basis for this: Stratus layers capabilities needed to make?cloud services accessible to a lab-based scientific community on commercial offerings, and; currently supports upwards of 200 projects ranging from IOT integration to traditional modeling and simulation. This provides a real-world inventory of scientific workflow elements. A growing knowledge base enables placing these elements appropriately between the edge, cloud, and traditional HPC. This paper outlines a vision via reference architecture and the application of that architecture in a typical workflow highlighting multiple components: sensor data intake, cleaning and transforming (edge/cloud suitable); generation of synthetic data through modsim, computationally heavy ML training and hyperparameter optimization (HPC suitable), and; inference and deployment (cloud ideal). Every step in such a workflow involves a cost-benefit analysis regarding the data movement, computational efficiency, availability, latency, and resource capabilities. The reference architecture and examples outlined allow for understanding new opportunities in the context of emerging workflows that combine IOT, cloud, and HPC to bolster scientific productivity.

AI↗

Simulations of Cryogenic Line Chilldown with Advanced Sub-Grid Wall Boiling Models

A meso-scale model developed at MIT [2][11] for boiling processes in water was adapted for cryogens and demonstrated for chilldown of propellant transfer lines in both liquid nitrogen and hydrogen. The sub-grid boiling model accurately captures the contributions to heat transfer from the generation of bubble nuclei, growth, and interaction of the bubbles in the microlayer as well as quenching of the boiling surface following bubble departure. It was adapted for cryogenic fluids using thermodynamic scaling concepts taking into account non-dimensional pressures and temperatures that are scaled by the corresponding critical values for the fluid. The boiling model was demonstrated for line chilldown in liquid nitrogen (Darr et al. [6]). The predicted wall temperature at which quenching occurs was close to the test data while the slope of the temperature curve after quenching is initiated, showing a steeper variation than the test data. Simulations were also performed for liquid hydrogen by simulating experiments of Hartwig et al. [7]. Chilldown times in liquid hydrogen are much more rapid due to higher heat transfer in the film boiling regime and accounting for the higher turbulence levels were found to be important. Furthermore, at the much lower fluid temperatures in liquid hydrogen flows, accounting for the variable thermal properties of the solid material is critical and has a dramatic impact on the quench times. The need for additional studies to better understand the evolution of the quench front in liquid hydrogen was noted.

Computational Fluid Dynamics↗

Simulations of Cryogenic Line Chilldown with Advanced Sub-Grid Wall Boiling Models

A meso-scale model developed at MIT [2][11] for boiling processes in water was adapted for cryogens and demonstrated for chilldown of propellant transfer lines in both liquid nitrogen and hydrogen. The sub-grid boiling model accurately captures the contributions to heat transfer from the generation of bubble nuclei, growth, and interaction of the bubbles in the microlayer as well as quenching of the boiling surface following bubble departure. It was adapted for cryogenic fluids using thermodynamic scaling concepts taking into account non-dimensional pressures and temperatures that are scaled by the corresponding critical values for the fluid. The boiling model was demonstrated for line chilldown in liquid nitrogen (Darr et al. [6]). The predicted wall temperature at which quenching occurs was close to the test data while the slope of the temperature curve after quenching is initiated, showing a steeper variation than the test data. Simulations were also performed for liquid hydrogen by simulating experiments of Hartwig et al. [7]. Chilldown times in liquid hydrogen are much more rapid due to higher heat transfer in the film boiling regime and accounting for the higher turbulence levels were found to be important. Furthermore, at the much lower fluid temperatures in liquid hydrogen flows, accounting for the variable thermal properties of the solid material is critical and has a dramatic impact on the quench times. The need for additional studies to better understand the evolution of the quench front in liquid hydrogen was noted.

Computational Fluid Dynamics↗

Implementation of Advanced Two Equation Turbulence Models in the USM3D Unstructured Flow Solver

USM3D is a widely-used unstructured flow solver for simulating inviscid and viscous flows over complex geometries. The current version (version 5.0) of USM3D, however, does not have advanced turbulence models to accurately simulate complicated flow. We have implemented two modified versions of the original Jones and Launder k-epsilon "two-equation" turbulence model and the Girimaji algebraic Reynolds stress model in USM3D. Tests have been conducted for three flat plate boundary layer cases, a RAE2822 airfoil and an ONERA M6 wing. The results are compared with those from direct numerical simulation, empirical formulae, theoretical results, and the existing Spalart-Allmaras one-equation model.

Wang, Qun-Zhen↗

Advancing the Predictability of Water Cycle Phenomena via the Application of AI to Model Ensemble Simulations and Observations

AI has the power to identify new pathways to extended predictability of the water cycle via its application to model ensembles together with accompanying observations. We discuss both scientific and technological aspects of this challenge, and address the parts of the MODEX approach involving “Model simulations, evaluation, analysis, and benchmarking” and “Identification of key knowledge gaps”. The widespread incorporation of AI into model analysis will significantly advance Earth system predictability and our predictive capabilities.

54 ENVIRONMENTAL SCIENCES↗

Measured noise of a scale model high speed propeller at simulated takeoff/approach conditions

A model high-speed advanced propeller, SR-7A, was tested in the NASA Lewis 9x15 foot anechoic wind tunnel at simulated takeoff/approach conditions of 0.2 Mach number. These tests were in support of the full-scale Propfan Text Assessment (PTA) flight program. Acoustic measurements were taken with fixed microphone arrays and with an axially translating microphone probe. Limited aerodynamic measurements were also taken to establish the propeller operating conditions. Tests were conducted with the propeller alone and with three down-stream wing configurations. The propeller was run over a range of blade setting angles from 32.0 deg. to 43.6 deg., tip speeds from 183 to 290 m/sec (600 to 950 ft/sec), and angles of attack from -10 deg. to +15 deg. The propeller alone BPF tone noise was found to increase 10 dB in the flyover plane at 15 deg. propeller axis angle of attack. The installation of the straight wing at minimum spacing of 0.54 wing chord increased the tone noise 5 dB under the wing of 10 deg. propeller axis angle of attack, while a similarly spaced inboard upswept wing only increased the tone noise 2 dB.

Woodward, Richard P.↗

Self-consistent equilibrium and transport simulations for NSTX-U plasmas enhanced via machine learning surrogate models

The Control-Oriented Transport SIMulator (COTSIM) is an advanced equilibrium and transport code designed for simulating tokamak discharges at computational speeds suitable for control applications. COTSIM’s modular framework enables users to select models that balance accuracy with speed according to specific needs, allowing the code to operate from fast to faster-than-real-time performance levels. This work presents recent enhancements to COTSIM’s predictive accuracy for NSTX-U scenarios, achieved by integrating neural-network-based surrogate models and self-consistent equilibrium calculations. To improve source deposition predictions, a surrogate model for NUBEAM has been incorporated. Additionally, a surrogate model for the Multi-Mode Module (MMM) now supports predictions of anomalous thermal, momentum, and particle diffusivities—key factors for modeling the evolution of temperature and rotation. Each surrogate model was specifically trained for the NSTX-U operational regime to enhance COTSIM’s accuracy while maintaining computational efficiency. Moreover, COTSIM now couples fixed-boundary equilibrium solvers with its transport solvers, enabling self-consistent predictions of plasma profiles and equilibrium evolution over the discharge. Simulation results demonstrate strong agreement between COTSIM and TRANSP predictions for NSTX-U discharges. These substantial advancements expand COTSIM’s utility in model-based control applications for NSTX-U. Potential applications include simultaneous optimization of equilibrium and transport scenarios, integration into digital twins, real-time profile estimation (e.g., temperature and rotation) from limited or noisy measurements, and advanced feedback-based scenario control.

Equilibrium and transport modeling↗