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DOE OSTI2025

Advancing the STS Neutron Moderator Design with an Automated Optimization Workflow and Unstructured Mesh Modeling

With the Second Target Station approaching its final design phase, a detailed neutronics evaluation of its critical components is necessary. Optimizing the dimensions of the two cold-source moderators that are at the heart of this facility presents a multi-objective optimization problem for which an accurate geometric description is crucial. We have applied a fully automated optimization workflow in which a detailed unstructured mesh geometry is automatically generated with Attila4MC, starting from a parametrized CREO geometry followed by preprocessing with SpaceClaim. With this geometry, a MCNP run is performed to calculate the brightness metrics, which are subsequently provided to the optimization algorithm in DAKOTA that provides new parameters and drives the optimization loop until convergence. In this paper, we show the results of the analysis that are used for the final design of the cylindrical and tube moderator. The optimization simulations provide a refinement to and confirmation of the conclusions of the previous design iteration. Additional to the optimization, a sensitivity study is performed to study the effect of minor geometry changes, which is important for the final engineering design. In conclusion, with these studies, we demonstrate that the automated workflow and high-fidelity unstructured mesh modeling are efficient tools for a thorough design evaluation.

DAKOTA↗

NASA NTRSDate not supplied

Aerothermodynamic Analysis of a Flexible Thermal Protection System under Reentry Loads

The Carryall Block 1 reentry vehicle being developed by Outpost Space utilizes a strut supported semirigid deployable heatshield. This consists of a flexible thermal protection system, a heat-resistant fabric stack, stretched over actuated spars. The advantages of a deployable heatshield include reduced heat loading and earlier deceleration in the trajectory. However, the nature of the flexible thermal protection system necessitates considering the loaded shape of the heat shield. The flexible thermal protection system will deflect under reentry loads leading to areas of higher heating rates as well as a reduced axial coefficient as compared to the nominal shape. The Carryall Block 1 is analyzed using NASA’s FUN3D and DPLR CFD solvers with a deflected shape based on the catenary equations. The aerodynamic results are found to be within a percent for both solvers and both structured and unstructured mesh types. Fluid Structure Interaction (FSI) analysis is currently a work in progress, using file I/O to communicate between FUN3D and LS-DYNA, a commercial nonlinear structural solver. Challenges in deforming the geometry, mesh, and initial results are presented here.

thermal protection system↗

DOE OSTI2025

Coupled beam-target-moderator optimization for the Second Target Station

To support the design of the Second Target Station, that aims to provide the world’s highest peak brightness of cold neutrons, studies that optimize the dimensions of the target and moderators are invaluable. In this work, we investigate the influence of the target dimensions and beam profile on the performance and optimal size of the moderators. We perform optimization runs with detailed MCNP6.2 simulations using high-fidelity unstructured mesh geometries generated from parametrized CAD models. We demonstrate that small changes in target height do not influence the moderator performance if the beam dimensions are chosen adequately. We quantify the effect of beam footprint and target width on the moderator performance and show that the optimal moderator dimensions are insensitive to limited changes in target and beam profile.

Dakota↗

DOE OSTI2025

Solving sparse finite element problems on neuromorphic hardware

The finite element method (FEM) is one of the most important and ubiquitous numerical methods for solving partial differential equations (PDEs) on computers for scientific and engineering discovery. Applying the FEM to larger and more detailed scientific models has driven advances in high-performance computing for decades. Here we demonstrate that scalable spiking neuromorphic hardware can directly implement the FEM by constructing a spiking neural network that solves the large, sparse, linear systems of equations at the core of the FEM. We show that for the Poisson equation, a fundamental PDE in science and engineering, our neural circuit achieves meaningful levels of numerical accuracy and close to ideal scaling on modern, inherently parallel and energy-efficient neuromorphic hardware, specifically Intel’s Loihi 2 neuromorphic platform. We illustrate extensions to irregular mesh geometries in both two and three dimensions as well as other PDEs such as linear elasticity. Our spiking neural network is constructed from a recurrent network model of the brain’s motor cortex and, in contrast to black-box deep artificial neural network-based methods for PDEs, directly translates the well-understood and trusted mathematics of the FEM to a natively spiking neuromorphic algorithm.

Applied mathematics↗

DOE OSTI2025

SEFOR Core I-E

This repository contains the VTB model developed for the Southwest Experimental Fast Oxide Reactor (SEFOR) core configuration I-E using the NEAMS tools. The MOOSE Reactor Module was employed to set up the geometry mesh, MC2-3 was applied to generate multigroup cross sections at various temperatures, and Griffin was used to calculate the k-eff values of Core I-E across these temperature conditions. To validate the deterministic results from Griffin, reference solutions were obtained with the Monte Carlo code Shift. The reactivity feedback was then derived and compared against SEFOR experimental data from isothermal tests in order to assess the performance of Griffin. Reproducing these results requires licensed access to several code systems, including Shift, Griffin, and MC2-3. Instructions for obtaining and accessing these codes can be found at the following locations: https://www.ornl.gov/scale/releases for SCALE/Shift, https://mooseframework.inl.gov/ncrc/applications/ncrc_root_griffin.html for Griffin, and https://www.anl.gov/nse/mc23 for MC2-3.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

NASA NTRS1972

Analysis of the transient response of shell structures by numerical methods.

This paper examines some basic considerations underlying dynamic shell response analysis and the impact of these considerations upon the practical aspects of solution by numerical methods. Emphasis is placed on the solution of linear problems. The present states of development of the finite difference and finite element methods are reviewed, and techniques for the treatment of temporal variation are discussed. An examination is made of the frequency parameters characteristic of thin shell theory, applied excitations, and spatial mesh geometries, and the significance of these parameters with respect to computational convergence is illustrated.

Geers, T. L.↗

NASA NTRS1991

Shock capturing schemes for multidimensional flow

Progress made in the development of a genuinely multidimensional finite volume algorithm for problems in inviscid gas dynamics is presented. The approach entails: (1) the reconstruction of flowfield data using a planar wave pattern in which the strengths and orientations of the component waves are derived independently of the mesh geometry; and (2) the development of a flux formula which provides a numerical approximation to the flux at a finite volume cell face during the passage of waves which are in general oblique to the face. Several algorithms are outlined, and the most recent developments are included. The results of several numerical cases are also included.

Parpia, Ijaz H.↗

NASA NTRS2011

Ultra-Sensitive Transition-Edge Sensors (TESs) for Far-IR/Submm Space-Borne Spectroscopy

We have built surface micromachined thin-film metallized Si(x)N(y) optical absorbers for transition-edge sensors (TESs) suitable for the Background - Limited far-IR/Submm Spectrograph (BLISS). BLISS is a broadband (38 micrometers - 433 micrometers), grating spectrometer consisting of five wavebands each with a modest resolution of R (is) approx. 1000. Because BLISS requires the effective noise equivalent power (NEP) of the TES to be below 10 (exp 19) W/Hz(exp 1/2), our TESs consist of four long (1000 micrometers), narrow (0.4 micrometers ), and thin (0.25 micrometers ) Si(x) N(y) support beams that reduce the thermal conductance G between the substrate and the optical absorber. To reduce the heat capacity of the absorber and make the response time tau fast enough for BLISS, our absorbers are patterned into a mesh geometry with a fill factor of less than 10%. We use a bilayer of Ti/Au to make the effective impedance of the absorber match the impedance of the incoming radiation for each band. Measurements of the response time of the metallized absorbers to heat pulses show that their heat capacity exceeds the predictions of the Debye model. Our results are suggestive that the surface of the low pressure chemical vapor deposition (LPCVD) Si(x)N(y) used in the absorbers' construction is the source of microstates that dominate the heat capacity.

far-IR spectrometer↗

NASA NTRSDate not supplied

Plume Impingement Software Module for Real-Time Proximity Operations

Successfully executing proximity operations in space, such as docking or in-orbit servicing, requires sophisticated spacecraft design that accounts for induced environments. As a chaser vehicle’s attitude control thrusters fire, they create rarefied plumes that can impact the target vehicle, with the potential to overload components, exceed thermal limits, and spin the target vehicle out of control. High-fidelity simulations of the thruster plume impingement environment require the direct simulation Monte Carlo (DSMC) method, but DSMC is too computationally expensive to simulate proximity operations that involve thousands of thruster firings. For this analysis to be tractable, engineering models of the plume flowfield and impingement events are used to simulate these trajectories [1]. Currently, on-orbit plume impingement environments are modeled through an inefficient open-loop analysis cycle where the vehicle’s flight controller and plume impingement teams iterate on the trajectories until they pass the target vehicle’s plume requirements. As complex on-orbit missions evolve and become more frequent, lengthy design cycles will become operational bottlenecks. To address this gap, this work develops an advanced plume impingement module capable of operating at real-time scale that can be integrated with existing mission planning tools and onboard flight systems. The plume module leverages state-of-the-art plume simulation techniques [2] to deliver fast, physics-based impingement predictions in a software architecture that can be tailored to diverse proximity operations scenarios. A prototype of this plume impingement module is built to demonstrate the feasibility of real-time performance. This prototype completes plume impingement calculations in microseconds per target geometry mesh point. The software serves as a foundational capability for plume-aware trajectory design, operational risk assessment, and future autonomous decision-making systems.

Plume Impingement↗

NASA NTRS2019

Geometry Modeling for Unstructured Mesh Adaptation

The quantification and control of discretization error is critical to obtaining reliable simulation results. Adaptive mesh techniques have the potential to automate discretization error control, but have made limited impact on production analysis workflow. Recent progress has matured a number of independent implementations of flow solvers, error estimation methods, and anisotropic mesh adaptation mechanics. However, the poor integration of initial mesh generation and adaptive mesh mechanics to typical sources of geometry has hindered adoption of adaptive mesh techniques, where these geometries are often created in Mechanical Computer- Aided Design (MCAD) systems. The difficulty of this coupling is compounded by two factors: the inherent complexity of the model (e.g., large range of scales, bodies in proximity, details not required for analysis) and unintended geometry construction artifacts (e.g., translation, uneven parameterization, degeneracy, self-intersection, sliver faces, gaps, large tolerances be- tween topological elements, local high curvature to enforce continuity). Manual preparation of geometry is commonly employed to enable fixed-grid and adaptive-grid workflows by reducing the severity and negative impacts of these construction artifacts, but manual process interaction inhibits workflow automation. Techniques to permit the use of complex geometry models and reduce the impact of geometry construction artifacts on unstructured grid workflows are models from the AIAA Sonic Boom and High Lift Prediction are shown to demonstrate the utility of the current approach.

Park, Michael A.↗

NASA NTRS2023

Predicting Two-Dimensional Airfoil Performance Using Graph Neural Networks

Computer simulations require the use of meshes to simulate geometries. These meshes capture important geometric features of the design and can be used in machine learning modeling. This report explores the use of graph neural networks (GNNs) to learn features from two-dimensional (2D) airfoil designs represented as a set of nodes connected using edges. This type of network is common in aerospace applications: most geometries are represented as a mesh in order to perform analysis. The objective of this work is to use GNNs to predict the performance of 2D airfoils generated using the program XFOIL. The predicted performance parameters include bulk quantities such as coefficients of lift (C L ), drag (C d , C dp ), moment (C m ), and node-specific quantities such as coefficient of pressure (C p ). In this report, a spline convolutional graph-based neural network is compared with deep learning neural networks to predict both bulk and node-specific quantities. The findings indicate the GNNs are able to predict bulk quantities quite well; however, when the number of outputs is increased, the deep neural network (DNN) proves to be better in its prediction capability. Two different normalization strategies were compared in the training of both GNNs and DNNs: minmax and standard deviation. In both types of networks, standard deviation scaling proved to be the best.

machine learning↗

NASA NTRS1990

Euler and Navier-Stokes computations for two-dimensional geometries using unstructured meshes

A general purpose unstructured mesh solver for steady-state two-dimensional inviscid and viscous flows is described. The efficiency and accuracy of the method are enhanced by the simultaneous use of adaptive meshing and an unstructured multigrid technique. A method for generating highly stretched triangulations in regions of viscous flow is outlined, and a procedure for implementing an algebraic turbulence model on unstructured meshes is described. Results are shown for external and internal inviscid flows and for turbulent viscous flow over a multi-element airfoil configuration.

Mavriplis, D. J.↗

NASA NTRS1989

Euler and Navier-Stokes computations for airfoil geometries using unstructured meshes

Mavriplis, D. J.↗

NASA NTRSDate not supplied

Automation of Overset Structured Mesh Generation onBoundary Representation Geometries

A scheme is presented for the automatic generation of structured overset meshes ongeometries that are defined by Boundary Representation (BRep) solids. The surface meshsystem consists of face, edge and node meshes corresponding to the three respective basicBRep entity types. A cut-cell method is introduced to improve robustness of the on-geometrydetermination test for a face mesh grid point. A geometric component tagging scheme is utilizedto enhance local grid point distribution on a configuration with a large range of geometricscales. A cap grid topology is automatically utilized around the trailing edge of wing and tailtips to enhance mesh quality and to enable more effective surface coverage. Robustness of thehyperbolic surface marching method is improved by replacing the point projection scheme witha walking scheme. Relaxation of surface grid spacing at concave corners enables automatedhigh quality hyperbolic volume mesh creation. Domain connectivity is automatically performedon the surface mesh system. A variety of test cases are presented including a re-entry capsule,two models of the Juncture Flow Experiment wing-body, five rotorcraft concept vehicles, andvarious components of the High-Lift Common Research Model from the High-Lift PredictionWorkshop 4.

TTT↗

NASA NTRS1991

The aerodynamic characteristics of vortex ingestion for the F/A-18 inlet duct

A Reduced Navier-Stokes (RNS) solution technique was successfully combined with the concept of partitioned geometry and mesh generation to form a very efficient 3D RNS code aimed at the analysis-design engineering environment. Partitioned geometry and mesh generation is a pre-processor to augment existing geometry and grid generation programs which allows the solver to (1) recluster an existing gridlife mesh lattice, and (2) perturb an existing gridfile definition to alter the cross-sectional shape and inlet duct centerline distribution without returning to the external geometry and grid generator. The present results provide a quantitative validation of the initial value space marching 3D RNS procedure and demonstrates accurate predictions of the engine face flow field, with a separation present in the inlet duct as well as when vortex generators are installed to supress flow separation. The present results also demonstrate the ability of the 3D RNS procedure to analyze the flow physics associated with vortex ingestion in general geometry ducts such as the F/A-18 inlet. At the conditions investigated, these interactions are basically inviscid like, i.e., the dominant aerodynamic characteristics have their origin in inviscid flow theory.

Anderson, Bernhard H.↗

NASA NTRS1991

The aerodynamic characteristics of vortex ingestion for the F/A-18 inlet duct

A Reduced Navier-Stokes (RNS) solution technique was successfully combined with the concept of partitioned geometry and mesh generation to form a very efficient 3-D RNS code aimed at the analysis-design engineering environment. Partitioned geometry and mesh generation is a pre-processor to augment existing geometry and grid generation programs which allows the solver to (1) recluster an existing gridlife mesh lattice, and (2) perturb an existing gridfile definition to alter the cross-sectional shape and inlet duct centerline distribution without returning to the external geometry and grid generator. The present results provide a quantitative validation of the initial value space marching 3-D RNS procedure and demonstrates accurate predictions of the engine face flow field, with a separation present in the inlet duct as well as when vortex generators are installed to suppress flow separation. The present results also demonstrate the ability of the 3-D RNS procedure to analyze the flow physics associated with vortex ingestion in general geometry ducts such as the F/A-18 inlet. At the conditions investigated, these interactions are basically inviscid like, i.e., the dominant aerodynamic characteristics have their origin in inviscid flow theory.

Anderson, Bernhard H.↗

DOE OSTI2025

FY25 MOOSE Usability Improvements: 3D Meshing Capabilities, Initiation of Geometry Support for Monte Carlo Tools, and Enhancement of MOOSE/Workbench User Input Interactions

Usability improvements have been made to MOOSE and Workbench in FY25 to enhance usability and user workflows. Assorted enhancement have been made to MOOSE’s intrinsic meshing capabilities in order to enable more flexible and complex meshing of nuclear reactor systems, in particular for 3D applications. Mesh generators have been added to perform operations such as batch mesh generation, surface mesh generation, and creation of 3D transition layers. These mesh generation capabilities make it much easier to generate high quality non-extruded 3D meshes. Additionally, work to integrate Monte Carlo reactor physics simulations into MOOSE-based multi-physics workflows has reached another milestone with the implementation of the Constructive Solid Geometry (CSG) base framework. This framework lays the foundation for mesh generators to offer the user a generic CSG output option (as opposed to a finite element mesh). To support users, workshop on the MOOSE Reactor Module was delivered which featured hands-on examples using the NEAMS Workbench on INL’s High Performance Computing system. Recent updates to the NEAMS Workbench, WASP, and the MOOSE language server have introduced several improvements aimed at making MOOSE-based simulation setup and input management faster, more accurate, and easier to use. Key capabilities that have been added include multi-tab-stop autocompletion, visual input diagnostics, developer-directed data visualizations, upgraded ParaView integration, and Workspace-level file tracking. Together, these changes make it easier for users to build, validate, and manage complex MOOSE-based simulation models — especially those involving reusable components, included files, and datasets. The improvements are designed to save time, reduce input errors, and help users get to a successful simulation run faster, with more confidence in the results.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

NASA NTRS2012

Liquid Acquisition Device Design Sensitivity Study

In-space propulsion often necessitates the use of a capillary liquid acquisition device (LAD) to assure that gas-free liquid propellant is available to support engine restarts in microgravity. If a capillary screen-channel device is chosen, then the designer must determine the appropriate combination screen mesh and channel geometry. A screen mesh selection which results in the smallest LAD width when compared to any other screen candidate (for a constant length) is desirable; however, no best screen exists for all LAD design requirements. Flow rate, percent fill, and acceleration are the most influential drivers for determining screen widths. Increased flow rates and reduced percent fills increase the through-the-screen flow pressure losses, which drive the LAD to increased widths regardless of screen choice. Similarly, increased acceleration levels and corresponding liquid head pressures drive the screen mesh selection toward a higher bubble point (liquid retention capability). After ruling out some screens on the basis of acceleration requirements alone, candidates can be identified by examining screens with small flow-loss-to-bubble point ratios for a given condition (i.e., comparing screens at certain flow rates and fill levels). Within the same flow rate and fill level, the screen constants inertia resistance coefficient, void fraction, screen pore or opening diameter, and bubble point can become the driving forces in identifying the smaller flow-loss-to-bubble point ratios.

VanDyke, M. K.↗