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DOE OSTI2022

Utah FORGE Phase 3 Native State Model: 2022 Update

This is the Phase 3 native state model update. The Phase 3 numerical model represents a significant subsurface volume below the FORGE site footprint. The model domain of 4.0 km x 4.0 km x 4.2 km is located approximately between depths of 4000 to 4200 meters below land surface. This data archive consists of 10 files, 4 of which are simulation input files and the remaining 6 are simulation output files. There is an included readme.txt file that contains details on each of the data files. The input files include meshes, FALCON code inputs, tabulated data of water properties, temperature values, and model boundaries. The output files include simulation outfiles and point data of modeled material properties.

15 GEOTHERMAL ENERGY↗

NASA NTRS1995

Visualization of stratospheric ozone depletion and the polar vortex

Direct analysis of spacecraft observations of stratospheric ozone yields information about the morphology of annual austral depletion. Visual correlation of ozone with other atmospheric data illustrates the diurnal dynamics of the polar vortex and contributions from the upper troposphere, including the formation and breakup of the depletion region each spring. These data require care in their presentation to minimize the introduction of visualization artifacts that are erroneously interpreted as data features. Non geographically registered data of differing mesh structures can be visually correlated via cartographic warping of base geometries without interpolation. Because this approach is independent of the realization technique, it provides a framework for experimenting with many visualization strategies. This methodology preserves the fidelity of the original data sets in a coordinate system suitable for three-dimensional, dynamic examination of atmospheric phenomena.

Treinish, Lloyd A.↗

NASA NTRS1995

Navier-Stokes Aerodynamic Simulation of the V-22 Osprey on the Intel Paragon MPP

The paper will describe the Development of a general three-dimensional multiple grid zone Navier-Stokes flowfield simulation program (ENS3D-MPP) designed for efficient execution on the Intel Paragon Massively Parallel Processor (MPP) supercomputer, and the subsequent application of this method to the prediction of the viscous flowfield about the V-22 Osprey tiltrotor vehicle. The flowfield simulation code solves the thin Layer or full Navier-Stoke's equation - for viscous flow modeling, or the Euler equations for inviscid flow modeling on a structured multi-zone mesh. In the present paper only viscous simulations will be shown. The governing difference equations are solved using a time marching implicit approximate factorization method with either TVD upwind or central differencing used for the convective terms and central differencing used for the viscous diffusion terms. Steady state or Lime accurate solutions can be calculated. The present paper will focus on steady state applications, although time accurate solution analysis is the ultimate goal of this effort. Laminar viscosity is calculated using Sutherland's law and the Baldwin-Lomax two layer algebraic turbulence model is used to compute the eddy viscosity. The Simulation method uses an arbitrary block, curvilinear grid topology. An automatic grid adaption scheme is incorporated which concentrates grid points in high density gradient regions. A variety of user-specified boundary conditions are available. This paper will present the application of the scalable and superscalable versions to the steady state viscous flow analysis of the V-22 Osprey using a multiple zone global mesh. The mesh consists of a series of sheared cartesian grid blocks with polar grids embedded within to better simulate the wing tip mounted nacelle. MPP solutions will be shown in comparison to equivalent Cray C-90 results and also in comparison to experimental data. Discussions on meshing considerations, wall clock execution time, load balancing, and scalability will be provided.

Vadyak, Joseph↗

NASA NTRS1989

Using Patran and Supertab as pre- and postprocessors to COSMIC/NASTRAN

Patran and Supertab are interactive computer graphics pre- and postprocessors that can be used to generate NASTRAN bulk data decks and to visualize results from a NASTRAN analysis. Both of the programs are in use at the Numerical Structural Mechanics Branch of the David Taylor Research Center (DTRC). Various aspects of Patran and Supertab are discussed including: geometry modeling, finite element mesh generation, bulk data deck creation, results translation and visualization, and the user interface. Some advantages and disadvantages of both programs will be pointed out.

Lipman, Robert R.↗

DOE OSTI2019

A data-driven framework for error estimation and mesh-model optimization in system-level thermal-hydraulic simulation

We report over the past decades, several computer codes have been developed for simulation and analysis of thermal-hydraulics and system response in nuclear reactors under operating, abnormal transient, and accident conditions. However, simulation errors and uncertainties still inevitably exist even while these codes have been extensively assessed and used. In this work, a data-driven framework (Optimal Mesh/Model Information System, OMIS) is formulated and demonstrated to estimate simulation error and suggest optimal selection of computational mesh size (i.e., nodalization) and constitutive correlations (e.g., wall functions and turbulence models) for low-fidelity, coarse-mesh thermal-hydraulic simulation, in order to achieve accuracy comparable to that of high-fidelity simulation. Using results from high-fidelity simulations and experimental data with many fast-running low-fidelity simulations, an error database is built and used to train a machine learning model that can determine the relationship between local simulation error and local physical features. This machine learning model is then used to generate insight and help correct low-fidelity simulations for similar physical conditions. The OMIS framework is designed as a modularized six-step procedure and accomplished with state-of-the-art methods and algorithms. A mixed-convection case study was performed to illustrate the entire framework.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2016

Trigger Detection for Adaptive Scientific Workflows Using Percentile Sampling

The increasing complexity of both scientific simulations and high-performance computing system architectures are driving the need for adaptive workflows, in which the composition and execution of computational and data manipulation steps dynamically depend on the evolutionary state of the simulation itself. Consider, for example, the frequency of data storage. Critical phases of the simulation should be captured with high frequency and with high fidelity for postanalysis; however, we cannot afford to retain the same frequency for the full simulation due to the high cost of data movement. We can instead look for triggers, indicators that the simulation will be entering a critical phase, and adapt the workflow accordingly. In this paper, we present a methodology for detecting triggers and demonstrate its use in the context of direct numerical simulations of turbulent combustion using S3D. We show that chemical explosive mode analysis (CEMA) can be used to devise a noise-tolerant indicator for rapid increase in heat release. However, exhaustive computation of CEMA values dominates the total simulation, and thus is prohibitively expensive. To overcome this computational bottleneck, we propose a quantile sampling approach. Our sampling-based algorithm comes with provable error/confidence bounds, as a function of the number of samples. Most importantly, the number of samples is independent of the problem size, and thus our proposed sampling algorithm offers perfect scalability. Our experiments on homogeneous charge compression ignition and reactivity controlled compression ignition simulations show that the proposed method can detect rapid increases in heat release, and its computational overhead is negligible. Our results will be used to make dynamic workflow decisions regarding data storage and mesh resolution in future combustion simulations.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1985

Diffraction Analysis of Mesh Deployable Reflector Antennas

A formulation and many representative numerical results for mesh reflector antennas are presented. The reflection coefficient matrix for the prescribed mesh configuration was determined and the local coordinate system of the mesh cells at each point on the curved reflector surface was accentuated. A novel strip aperture model was used to formulate the transmission coefficient matrix for a variety of mesh cell configurations. Numerical data are tailored to the dimensions of a conceptually designed land mobile satellite system (LMSS) which employs a large mesh deployable offset parabolic antenna. Results are shown for an offset parabolic reflector with mesh surfaces similar to the mesh surface of tracking and data relay satellite system (TDRSS).

Rahmat-Samii, Y.↗

NASA NTRS2017

Experimental Investigation of Shrouding on Meshed Spur Gear Windage Power Loss

Windage power loss in high-speed gearboxes results in efficiency losses and increased heating due to drag on the gear teeth. Test results for meshed spur gear windage power loss are presented at ambient oil inlet temperatures, both with and without shrouding. The rate of windage power loss is observed to increase above a gear surface speed of 10,000 feet per minute (51 meters per second), similar to results presented in the literature. Shrouding is observed to become more effective above 15,000 feet per minute (76 meters per second), decreasing power loss by 10 percent at 25,000 feet per minute (127 meters per second). The need for gearbox oil drain slots limits the effectiveness of shrouding in reducing windage power loss. Windage power loss is observed to decrease with increasing gearbox temperatures and to increase with oil flow. Windage power losses for unshrouded meshed spur gears are 7 times greater than losses determined from unshrouded single spur gear tests. A 6- to 12-times increase in windage power loss is observed in the shrouded meshed spur gear data compared with shrouded single spur gear data. Based on this preliminary study, additional research is suggested to determine the effect of oil drain slot configurations, axial and radial shroud clearances, and higher gear surface speeds on windage power loss. Additional work is also suggested to determine the sensitivity of windage power loss to oil temperature and oil flow. Windage power loss for meshed spur gears tested in both the shrouded and unshrouded configurations is shown to be more than double versus windage power loss for the same spur gears run individually in the same shroud configurations. Further study of the physical processes behind these results is needed to optimize gearbox shrouds for minimum windage power loss.

drag↗

DOE OSTI2026

Field and Model Data Associated with the Manuscript “Drivers of Streamflow Intermittency in Humid Regions: 1. Evaluating Above- and Below-ground Controls of Flow Persistence in a Forested Catchment”

This package contains field data, modeling files, and scripts supporting the investigation of the drivers of streamflow intermittency in a forested catchment. It includes the field data collected from electrical resistivity tomography (ERT) surveys, ground penetrating radar (GPR), continuous self-potential (SP) monitoring, electromagnetic (EM) imaging, groundwater and stilling well. In addition, it contains the data and results of the coupled water- and electrical-flow model developed using the COMSOL Multiphysics and Advanced Terrestrial Simulator (ATS), as well as software files and Jupyter notebooks used to process the data and generate figures in the manuscript submitted for peer review. The data archive is organized in the following directories: 1) Climate Includes hourly precipitation and daily evapotranspiration time series (2024 – 2025) provided as CSV files, alongside a text file detailing dataset units. 2) Coupled_model Contains two subfolders: Synthetic and Field_Application subfolder. Synthetic subfolder contains the ATS XML input script (can be opened using any code editor) for the four synthetic hydrological cases tested (Connected and gaining, Connected and losing, Disconnected and losing, and dry stream). It also includes other experimental cases to test the influence of precipitation and concentration gradient. For each synthetic case, the flow model simulation is executed using the ATS XML scripts and the included Python script (generate_data_set.py) to convert ATS output to COMSOL-ready input. COMSOL Multiphysics template (.mph can be opened with the commercial software COMSOL and requires a license) is executed using the ATS output data to simulate the potential field. It also includes the Synthetic_model_plot.ipynb (can be opened using any code editor) to visualize the SP result and generate manuscript figures. The data subfolder contains mesh files to run both the ATS (.exo and .stl files can be viewed using Paraview; .h5 files can be opened using HDFView software and h5py Python package) and COMSOL models. Field_Application subfolder contains two subfolders: ES_MDA_inversion and Final_Model. ES_MDA_inversion contains the Python script (.py can be opened using any code editor) and SP observation data used to run the Ensemble Smoother with Multiple Data Assimilation (ES-MDA) inversion sequence to get the optimal model parameters. The Final_model subfolder contains the ATS XML input scripts, data files, output data for the two SP sites. The same workflow steps outlined for the Synthetic subfolder apply here. It also contains the Jupyter notebook (Plot_final_calib.ipynb) to visualize the results of the modeled SP, stream-groundwater exchange and moisture content. 3) Discharge Includes the electrical conductivity (EC) time series (provided as CSV files) from salt slug injections. It also includes the Jupyter notebook (Discharge_process.ipynyb) used to estimate discharge. All discharge measurements collated into rating_curve_processed.csv 4) EM Contains the CSV file of the EM data from the DUALEM-42, including spatial coordinates (x, y, z), apparent conductivity, and in-phase measurements at 2 m coil separations for horizontal coplanar (HCP) and perpendicular (PRP) geometries. 5) ERT Contains raw resistivity data (provided as CSV files), spatial location of each of the electrodes (provided as CSV files), and files used for the resistivity inversion (.resipy can be opened with the open-source ResIPy software). 6) GPR Includes GPR field datasets collected at 100 MHz and 250 MHz antenna frequencies, along with the processing/interpretation project file (GPR_process.gpz can be viewed using EKKO_Project 6, a commercial software by Sensors & Software that requires a license). 7) Slug_test Includes the slug test data at all the groundwater wells provided as CSV files, as well as the Jupyter notebook (Slug_test.ipynb) for calculating hydraulic conductivity. 8) SP Contains the SP data collected in field at the two SP sites (one in the perennial reach and the other in the intermittent reach), provided as DAT files. 9) Well_data Contains two subfolders: 1) Raw, which provides unprocessed pressure, electrical conductivity and temperature timeseries downloaded from the loggers in all the groundwater and stilling wells, and 2) Processed, which contains sorted, QA/QC timeseries data for each well. The data archive also contains data_process.ipynb, a Jupyter notebook used for field data analysis and generating figures (plotting well, SP, climate, and discharge data, as well as calculating head gradient at sites with nested groundwater wells). It also includes DTW.ipynb, a Jupyter notebook containing the code for the dynamic time warping (DTW) with sliding window to evaluate SP signal synchronicity.

ATS↗

NASA NTRS1992

Mapping unstructured grid computations to massively parallel computers

Investigated here is this mapping problem: assign the tasks of a parallel program to the processors of a parallel computer such that the execution time is minimized. First, a taxonomy of objective functions and heuristics used to solve the mapping problem is presented. Next, we develop a highly parallel heuristic mapping algorithm, called Cyclic Pairwise Exchange (CPE), and discuss its place in the taxonomy. CPE uses local pairwise exchanges of processor assignments to iteratively improve an initial mapping. A variety of initial mapping schemes are tested and recursive spectral bipartitioning (RSB) followed by CPE is shown to result in the best mappings. For the test cases studied here, problems arising in computational fluid dynamics and structural mechanics on unstructured triangular and tetrahedral meshes, RSB and CPE outperform methods based on simulated annealing. Much less time is required to do the mapping and the results obtained are better. Compared with random and naive mappings, RSB and CPE reduce the communication time two fold for the test problems used. Finally, we use CPE in two applications on a CM-2. The first application is a data parallel mesh-vertex upwind finite volume scheme for solving the Euler equations on 2-D triangular unstructured meshes. CPE is used to map grid points to processors. The performance of this code is compared with a similar code on a Cray-YMP and an Intel iPSC/860. The second application is parallel sparse matrix-vector multiplication used in the iterative solution of large sparse linear systems of equations. We map rows of the matrix to processors and use an inner-product based matrix-vector multiplication. We demonstrate that this method is an order of magnitude faster than methods based on scan operations for our test cases.

Hammond, Steven Warren↗

DOE OSTI2023

Ume: Unstructured Mesh Explorations

Ume is an open-source collection of data structures for unstructured computational meshes and some simple algorithms that operate on them. These algorithms mimic the memory access patterns of a common class of operations found in several of the computational physics simulation codes developed at Los Alamos National Laboratory. The intent is that Ume can be used by hardware vendors to understand the memory traffic created by complex codes in a simplified environment, and to explore new means of optimization for that traffic. Ume is provided as a source-code C++ library and includes several applications that demonstrate the use of that library.

Henning, Paul↗

NASA NTRS1993

Dynamic mesh adaption for triangular and tetrahedral grids

The following topics are discussed: requirements for dynamic mesh adaption; linked-list data structure; edge-based data structure; adaptive-grid data structure; three types of element subdivision; mesh refinement; mesh coarsening; additional constraints for coarsening; anisotropic error indicator for edges; unstructured-grid Euler solver; inviscid 3-D wing; and mesh quality for solution-adaptive grids. The discussion is presented in viewgraph form.

Rupak Biswas↗

DOE OSTI2016

Improving performance of two-group interfacial area transport equation models using genetic algorithms and high resolution experimental data

In the two-fluid transport model, the coupling of mass, momentum and energy transfer between phases is highly dependent on interfacial area transfer terms. Several research efforts in the past have been focused on the development of an interfacial area transport equation model (IATE), in order to eliminate the drawbacks of static flow regime maps currently used in best-estimate thermal-hydraulic system codes. The IATE attempts to model the dynamics that are involved in two phase flows by accounting for the different interaction mechanisms affecting bubble transport in the flow. In general, current IATE models perform poorly in high void fraction flow regimes. As both models depend on closure relations that require empirically determined coefficients, a genetic algorithm is implemented to study their optimization. The preliminary study indicates that improvements are achievable by application of the genetic algorithm. Optimization of coefficients for an entire set of high-resolution wire mesh sensor (WMS) data provided a single set of optimal coefficients. The application of WMS-optimized coefficients to external tests improved IATE performance for similar hydraulic diameters and provided a neutral change in performance for significantly smaller/larger hydraulic diameters. This is a crucial outcome as an optimized set of coefficients that provide significant improvement for a subset of experimental data - is shown to benefit performance in external data for which the coefficients are not specifically optimized. (authors)

42 ENGINEERING↗

NASA NTRS1997

Out-of-Core Streamline Visualization on Large Unstructured Meshes

It's advantageous for computational scientists to have the capability to perform interactive visualization on their desktop workstations. For data on large unstructured meshes, this capability is not generally available. In particular, particle tracing on unstructured grids can result in a high percentage of non-contiguous memory accesses and therefore may perform very poorly with virtual memory paging schemes. The alternative of visualizing a lower resolution of the data degrades the original high-resolution calculations. This paper presents an out-of-core approach for interactive streamline construction on large unstructured tetrahedral meshes containing millions of elements. The out-of-core algorithm uses an octree to partition and restructure the raw data into subsets stored into disk files for fast data retrieval. A memory management policy tailored to the streamline calculations is used such that during the streamline construction only a very small amount of data are brought into the main memory on demand. By carefully scheduling computation and data fetching, the overhead of reading data from the disk is significantly reduced and good memory performance results. This out-of-core algorithm makes possible interactive streamline visualization of large unstructured-grid data sets on a single mid-range workstation with relatively low main-memory capacity: 5-20 megabytes. Our test results also show that this approach is much more efficient than relying on virtual memory and operating system's paging algorithms.

Ueng, Shyh-Kuang↗

DOE OSTI2015

An Update on NiCE Support for BISON

The Nuclear Energy Advanced Modeling and Simulation program (NEAMS) from the Department of Energy s Office of Nuclear Energy has funded the development of a modeling and simulation workflow environment to support the various codes in its nuclear energy scientific computing toolkit. This NEAMS Integrated Computational Environment (NiCE) provides extensible tools and services that enable efficient code execution, input generation, pre-processing visualizations, and post-simulation data analysis and visualization for a large portion of the NEAMS Toolkit. A strong focus for the NiCE development team throughout FY 2015 has been support for the Multiphysics Object Oriented Simulation Environment (MOOSE) and the NEAMS nuclear fuel performance modeling application built on that environment, BISON. There is a strong desire in the program to enable and facilitate the use of BISON throughout nuclear energy research and industry. A primary result of this desire is the need for strong support for BISON in NiCE. This report will detail improvements to NiCE support for BISON. We will present a new and improved interface for interacting with BISON simulations in a variety of ways: (1) improved input model generation, (2) embedded mesh and solution data visualizations, and (3) local and remote BISON simulation launch. We will also show how NiCE has been extended to provide support for BISON code development.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2019

Mesh Generation for Microstructures

A parallel, adaptive overlay grid procedure is proposed for use in generating all-hex meshes for stochastic (SVE) and representative (RVE) volume elements in computational materials modeling. The mesh generation process is outlined including several new advancements such as data filtering to improve mesh quality from voxelated and 3D image sources, improvements to the primal contouring method for constructing material interfaces and pillowing to improve mesh quality at boundaries. We show specific examples in crystal plasticity and syntactic foam modeling that have benefitted from the proposed mesh generation procedure and illustrate results of the procedure with several practical mesh examples.

36 MATERIALS SCIENCE↗

NASA NTRS2019

Automatic Incorporation of Flaws into Cad and FEA Models Based On Measured NDE Data

Automatic incorporation of non-destructive evaluation (NDE) data into CAD and finite element (FE) models for structural analysis is essential for accurate residual-life and strength analyses of composite structures. Currently, two significant but independent challenges exist for incorporating NDE data in such analyses: interpretation of the NDE signals to locate and characterize the structural defects and the incorporation of that information into structural analysis tools. The first challenge will be addressed through linear inversion of calculated synthetic responses generated by a simulation engine to evaluate flaw size, location, and other characteristics. The second challenge will be addressed by building on prior and parallel defect modeling efforts to integrate suitable flaw models into the CAD/finite-element representation of a specimen. Ultrasonic NDE information is usually represented using C-Scans of time-of-flight or intensity information. Other modalities such as thermography and computed tomography (CT) could also be used to characterize the structure. This information will first be projected into material coordinates and then aligned with the specimen’s finite element mesh. The NDE data can then be incorporated by inserting flaw geometry into the CAD and FE analysis model and automatic modification of local material properties and boundary conditions. This process will enable the use of structural analysis tools even for practical modalities such as ultrasound and thermography which may not directly give accurate-enough geometric information to fully define the flaw. The full flaw characteristics will be inferred using prior expert and modeling knowledge to categorize flaw signatures. Outputs for this project will include demonstrated methods for creating structural analysis geometric models that incorporate flaw characterization information; these models can then be used directly in popular commercial FEA software. In addition, the primary deliverable for the project will include a software that will be able to automatically incorporate different kinds of flaws into an existing FE models. The models will be generated in standard file formats to enable direct import into the analysis software.

Adarsh Krishnamurthy↗

DOE OSTI2026

Reactive Transport Modeling with Physics-Informed Machine Learning for Critical Minerals Applications

This study presents a physics-informed neural network (PINN) framework for reactive transport modeling for simulating fast bimolecular reactions in porous media. Accurate characterization of cAhemical interactions and product formation in surface and subsurface environments is essential for advancing critical mineral extraction and related geoscience applications. The proposed methodology sequentially addresses the flow and diffusion–reaction subproblems. The flow field is computed using a mixed formulation, while the diffusion–reaction system is modeled via two uncoupled tensorial diffusion equations reformulated in terms of chemical invariants. PINNs are employed to solve the governing equations, enabling data-efficient, mesh-free prediction of chemical concentration fields. The framework is validated through a series of benchmark problems involving flow in heterogeneous porous media. Initial verification is conducted using patch tests for the flow field, followed by validation of the transport problem with emphasis on preserving non-negativity of concentrations. The complete fast bimolecular reaction scenario is then solved, yielding spatial distributions of reactants and product species. Results demonstrate that the PINNs-based approach effectively captures sharp, mixing-limited reaction fronts and dispersive mixing behavior, offering reliable predictions of reactive plume evolution. These capabilities are crucial for evaluating long-term subsurface behavior in applications such as fluid storage, energy extraction, and efficient extraction of critical minerals.

42 ENGINEERING↗