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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Implementation of Charged Particle Behavior in Discrete Element Method (DEM) Simulations

To understand the behavior of charged lunar regolith when perturbed by lunar landers, it is important to couple the grain dynamics with mechanical and electrical particle interactions. To accomplish this, improvements have been made to a discrete element method (DEM) software package to include both short- and long-range interactions between spherical particles. Short-range interactions rely on contact between the particles, such as electrical conduction and triboelectric charge transfer driven by work functions. Long-range interactions act at a distance between every pairing of particles, such as electrostatic forces and gravitational forces. Results from simulations between a few particles are compared with theory to verify these added behaviors prior to scaling up to more complex scenarios. The radii, initial charges, electrical conductivities, work functions, and separation of the particles are varied and the resultant charges as well as the time required to reach the final state are determined.

Electrostatics↗
NASA NTRS1999

The Shuttle Radar Topography Mission: A Global DEM

Digital topographic data are critical for a variety of civilian, commercial, and military applications. Scientists use Digital Elevation Models (DEM) to map drainage patterns and ecosystems, and to monitor land surface changes over time.

Digital↗
DOE OSTI2026

A filter-dependent granular temperature model from large-scale CFD-DEM data

The computational study of strongly-coupled, gas–solid flows at scales relevant to most environmental and engineering applications requires the use of ‘coarse-grained’ methodologies such as the two-fluid model, particle-in-cell approach or the multiphase Reynolds Averaged Navier–Stokes equations. While these strategies enable computations at desirable length- and time-scales, they rely heavily on models to capture important flow physics that occur at scales smaller than the mesh. To date, the models that do exist are based on a limited set of flow conditions, such as very dilute particle phase. To this end, we leverage a large-scale repository of CFD-DEM data to develop filter-size dependent models for the mean variance in particle volume fraction, a quantity commonly used to assess the degree of clustering, and the granular temperature, a key quantity for accurately predicting gas–solid flows. In conclusion, because of its filter-size dependence, the granular temperature model can be directly translated to coarse-grained approaches and tied directly to grid size.

AMReX↗
DOE OSTI2025

Remote sensing images, DEM, and point clouds associated with “Accuracy evaluation of cost-effective 3D reconstruction approaches for hydrobiogeochemical processes in non-perennial stream riverbeds”

This data package is associated with the publication “Accuracy evaluation of cost-effective 3D reconstruction approaches for hydrobiogeochemical processes in non-perennial stream riverbeds” published in Frontiers in Environmental Science, Environmental Informatics and Remote Sensing (Bao et al., 2026; doi: 10.3389/fenvs.2026.1725258). This data package includes the drone photos for a section of Umtanum Creek in Washington, Unted States. The photos were used to reconstruct the 3-dimensional (3D) digital elevation model (DEM) of the riverbed for the investigated stream section. The reconstruction results from four approaches are provided: (1) unoccupied aerial vehicle (UAV, colloquially known as drone) imagery-based Structure-from-Motion (SfM), (2) a machine learning-based 3D reconstruction model, Visual Geometry Grounded Deep Structure from Motion (VGGSfM), (3) Visual Geometry Grounded Transformer for long sequence of images (VGGT-Long), and (4) handheld smartphone LiDAR scanning. The ground truth measurements by tripod-mounted optical level kit and ground control points GPS locations for evaluating the accuracy of the four reconstruction approaches are also provided in this data package. A preliminary version of this data package was published in October 2025 at the time of manuscript submission. It was updated in March 2026, at the time of manuscript acceptance, to include additional metadata (this readme, data dictionary, and file level metadata). The data did not change. For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. In addition to a readme, this data package also includes a file-level metadata (FLMD) file that describes each file and a data dictionary (DD) that describes all column/row headers and variable definitions. This dataset is comprised of (1) 8 folders; (2) the detailed flight configuration html files; (3) field metadata; (4) a readme; (5) a data dictionary; and (6) file-level metadata. The folders “2024_10_18_d01” and “2024_10_18_d02” contain the original drone photos for the two drone flights (d01 and d02) on October 18, 2024. The reconstruction results from each of the approaches are in the folders called “ODM_SfM”, “VGGSfM”, “VGGTLong”, and “LiDAR”. The ground truth measurements are in the folder called “optical_level_kit”. Lastly, results comparing the different approaches are in the folder called “comparisons”. All files are .csv, .html, .jpg, .obj, .txt, and .npy. For information on using the .obj and .npy files, see the readme files within the same folder as the files.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Granular Temperature Modeling with Large-Scale CFD-DEM Data

The granular temperature is a measure of solids-phase fluctuating kinetic energy in particle-laden gas-solid flows. This report focuses on reduced-order models of granular temperature in triply-periodic cluster induced turbulent flow. The granular temperature data was generated by post-processing large-scale CFD-DEM simulations that were carried out as part of an ALCC awarded study. The algebraic model of Tang et al, originally fit to DNS data, was found to be amenable to the present data. The results of several regression analyses are presented building on the original expression. This work was performed in part through the National Nuclear Security Administration (NNSA) Minority Serving Institutions Internship Program (MSIIP).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1990

Revealing topographic lineaments through IHS enhancement of DEM data

Intensity-hue-saturation (IHS) processing of slope (dip), aspect (dip direction), and elevation to reveal subtle topographic lineaments which may not be obvious in the unprocessed data are used to enhance digital elevation model (DEM) data from northwestern Nevada. This IHS method of lineament identification was applied to a mosiac of 12 square degrees using a Cray Y-MP8/864. Square arrays from 3 x 3 to 31 x 31 points were tested as well as several different slope enhancements. When relatively few points are used to fit the plane, lineaments of various lengths are observed and a mechanism for lineament classification is described. An area encompassing the gold deposits of the Carlin trend and including the Rain in the southeast to Midas in the northwest is investigated in greater detail. The orientation and density of lineaments may be determined on the gently sloping pediment surface as well as in the more steeply sloping ranges.

Murdock, Gary↗
NASA NTRS2000

BOREAS Regional DEM in Raster Format and AEAC Projection

This data set is based on the GTOPO30 Digital Elevation Model (DEM) produced by the United States Geological Survey EROS Data Center (USGS EDC). The BOReal Ecosystem-Atmosphere Study (BOREAS) region (1,000 km x 1000 km) was extracted from the GTOPO30 data and reprojected by BOREAS staff into the Albers Equal-Area Conic (AEAC) projection. The pixel size of these data is 1 km. The data are stored in binary, image format files.

Knapp, David↗
NASA NTRS2006

Forecasting of Storm-Surge Floods Using ADCIRC and Optimized DEMs

Increasing the accuracy of storm-surge flood forecasts is essential for improving preparedness for hurricanes and other severe storms and, in particular, for optimizing evacuation scenarios. An interactive database, developed by WorldWinds, Inc., contains atlases of storm-surge flood levels for the Louisiana/Mississippi gulf coast region. These atlases were developed to improve forecasting of flooding along the coastline and estuaries and in adjacent inland areas. Storm-surge heights depend on a complex interaction of several factors, including: storm size, central minimum pressure, forward speed of motion, bottom topography near the point of landfall, astronomical tides, and, most importantly, maximum wind speed. The information in the atlases was generated in over 100 computational simulations, partly by use of a parallel-processing version of the ADvanced CIRCulation (ADCIRC) model. ADCIRC is a nonlinear computational model of hydrodynamics, developed by the U.S. Army Corps of Engineers and the US Navy, as a family of two- and three-dimensional finite-element-based codes. It affords a capability for simulating tidal circulation and storm-surge propagation over very large computational domains, while simultaneously providing high-resolution output in areas of complex shoreline and bathymetry. The ADCIRC finite-element grid for this project covered the Gulf of Mexico and contiguous basins, extending into the deep Atlantic Ocean with progressively higher resolution approaching the study area. The advantage of using ADCIRC over other storm-surge models, such as SLOSH, is that input conditions can include all or part of wind stress, tides, wave stress, and river discharge, which serve to make the model output more accurate. To keep the computational load manageable, this work was conducted using only the wind stress, calculated by using historical data from Hurricane Camille, as the input condition for the model. Hurricane storm-surge simulations were performed on an eight-node Linux computer cluster. Each node contained dual 2-GHz processors, 2GB of memory, and a 40GB hard drive. The digital elevation model (DEM) for this region was specified using a combination of Navy data (over water), NOAA data (for the coastline), and optimized Interferometric Synthetic Aperture Radar data (over land). This high-resolution topographical data of the Mississippi coastal region provided the ADCIRC model with improved input with which to calculate improved storm-surge forecasts.

Valenti, Elizabeth↗
NASA NTRS2018

Combining Sparsity DEM Inversions with Event Tracking for AIA Data

We introduce a modified version of the ASGARD code (Automated Selection and Grouping of events in A/A Regional Data). Originally written to detect and group brightenings ("events") in the AIA EUV channels, it now includes the sparsity DEM inversion method and instead detects emission measure enhancements in different temperature bins. Ultimately, the goal is to automatically determine heating and cooling rates in different coronal structures.

Bethge, Christian↗
DOE OSTI2024

Asynchronous GPU-based DEM solver embedded in commercial CFD software with polyhedral mesh support

A novel graphical processing unit-based discrete element method solver is introduced to improve stability, performance, and provide seamless integration into commercial or open-source computational fluid dynamics software. A key innovation is eliminating a need for network communication between solvers, which was previously required for cross-platform coupling. This is accomplished by a direct coupling method that employs dynamic-linked libraries. Furthermore, the solver optimizes memory usage by streamlining the particle-cell search algorithm by eliminating the cells' searching grid. This ensures the solver is compatible with a wide range of mesh types, providing high geometric flexibility. The approach simplifies the simulation process by directly incorporating computational fluid dynamics mesh information into the discrete element method solver. The performance analysis indicates about sixteen times boost in computational speed compared to benchmark central processing unit-based solvers. Finally, the solver's compatibility with polyhedral meshes, a vital advantage for complex geometries, is tested against a referenced study regarding the simulation of an immersed-tube fluidized bed.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS2022

Trade Study of DEM Software

Review of Open-source Discrete Element Method Softwares: Three open-source solutions have been investigated for integration into OceanWATERS: Yade, EsysParticle, and ProjectChrono.

DEM↗
DOE OSTI2025

A rheological model for loose sands with insights from DEM

A rheological model for loose granular media is developed to capture both solid-like and fluid-like responses during shearing. The proposed model is built by following the mathematical structure of an extended Kelvin–Voigt model, where an elastic spring and plastic slider act in parallel to a viscous damper. This arrangement requires the partition of the total stress into rate-independent and rate-dependent stress components. To model the solid-like behavior, a simple frictional plasticity model is adopted without modifications, thus contributing to the rate-independent stress. Instead, the fluid-like or rate-dependent stress is further decomposed into deviatoric and volumetric parts, by proposing a new formulation based on a combination of the μ(I) relation, originally developed under pressure-controlled shear, with a pressure-shear rate relation derived under volume-controlled shear. The proposed formulation allows the model to capture both the increase in the friction coefficient and the enhanced dilation at high shear rates. High-fidelity simulation data, obtained from discrete element method and multiscale modelling, are used to evaluate the performance of the proposed constitutive model. The model provides accurate results under both drained and undrained simple shear paths across a wide range of shear rates. Furthermore, it successfully reproduces at much lower computational cost the flowslide mobility computed through multiscale simulations, which is primarily regulated by the shear rate dependence of the material properties during the dynamic runout stage.

Elasticity↗
DOE OSTI2024

Simulation of Microcapsule Transport in Fractured Media Using Coupled CFD‐DEM

Geothermal energy is sustainable and gaining momentum as a solution to energy crises and environmental issues. However, challenges like production temperature and thermal breakthrough can impact geothermal project efficiency. One innovative solution to alleviate the thermal breakthrough is to inject polymer-based materials that are encapsulated in microcapsules into fractures to modify fracture permeability and prevent preferential flow. In our study, we utilized a coupled computational fluid dynamics and discrete element method to simulate the transport of microcapsules under various scenarios controlled by microcapsule size, microcapsule concentration, and fracture roughness. For a smooth fracture, the results indicate that small microcapsules can travel through a smooth fracture regardless of their concentrations. Large microcapsules can transport through a smooth fracture when present in lower concentrations. However, medium and mixed-size microcapsules tend to cause the sealing of a smooth fracture, irrespective of their concentrations. For a rough fracture, the transport of microcapsules is complicated by their interactions with the rough fracture walls. The presence of two sealing positions in a rough fracture adds further complexity to this transport phenomenon. The size and concentration of microcapsules control one sealing location, while the rough fracture walls determine the other sealing location. The rough walls substantially affect microcapsule transport, rendering the role of microcapsule size and concentration less significant. The simulation results suggest that complex fracture surfaces significantly elevate the occurrence of sealing behavior. To mitigate sealing behavior within more complex fractures, it would be beneficial to use smaller and lower concentrations of microcapsules.

15 GEOTHERMAL ENERGY↗