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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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NASA NTRS1996

Segmentation of Unstructured Datasets

Datasets generated by computer simulations and experiments in Computational Fluid Dynamics tend to be extremely large and complex. It is difficult to visualize these datasets using standard techniques like Volume Rendering and Ray Casting. Object Segmentation provides a technique to extract and quantify regions of interest within these massive datasets. This thesis explores basic algorithms to extract coherent amorphous regions from two-dimensional and three-dimensional scalar unstructured grids. The techniques are applied to datasets from Computational Fluid Dynamics and from Finite Element Analysis.

Bhat, Smitha↗

NASA NTRS1999

Parallel Visualization of Large-Scale Aerodynamics Calculations: A Case Study on the Cray T3E

This paper reports the performance of a parallel volume rendering algorithm for visualizing a large-scale, unstructured-grid dataset produced by a three-dimensional aerodynamics simulation. This dataset, containing over 18 million tetrahedra, allows us to extend our performance results to a problem which is more than 30 times larger than the one we examined previously. This high resolution dataset also allows us to see fine, three-dimensional features in the flow field. All our tests were performed on the Silicon Graphics Inc. (SGI)/Cray T3E operated by NASA's Goddard Space Flight Center. Using 511 processors, a rendering rate of almost 9 million tetrahedra/second was achieved with a parallel overhead of 26%.

Ma, Kwan-Liu↗

NASA NTRS2002

Entrainment-Zone Restratification and Flow Structures in Stratified Shear Turbulence

Late-time dynamics and morphology of a stratified turbulent shear layer are examined using 1) Reynolds-stress and heat-flux budgets, 2) the single-point structure tensors introduced by Kassinos et al. (2001), and 3) flow visualization via 3D volume rendering. Flux reversal is observed during restratification in the edges of the turbulent layer. We present a first attempt to quantify the turbulence-mean-flow interaction and to characterize the predominant flow structures. Future work will extend this analysis to earlier times and different values of the Reynolds and Richardson numbers.

Reif, B. Anders Pettersson↗

NASA NTRS2003

Structural Anomalies Detected in Ceramic Matrix Composites Using Combined Nondestructive Evaluation and Finite Element Analysis (NDE and FEA)

Most reverse engineering approaches involve imaging or digitizing an object and then creating a computerized reconstruction that can be integrated, in three dimensions, into a particular design environment. The rapid prototyping technique builds high-quality physical prototypes directly from computer-aided design files. This fundamental technique for interpreting and interacting with large data sets is being used here via Velocity2 (an integrated image-processing software, ref. 1) using computed tomography (CT) data to produce a prototype three-dimensional test specimen model for analyses. A study at the NASA Glenn Research Center proposes to use these capabilities to conduct a combined nondestructive evaluation (NDE) and finite element analysis (FEA) to screen pretest and posttest structural anomalies in structural components. A tensile specimen made of silicon nitrite (Si3N4) ceramic matrix composite was considered to evaluate structural durability and deformity. Ceramic matrix composites are being sought as candidate materials to replace nickel-base superalloys for turbine engine applications. They have the unique characteristics of being able to withstand higher operating temperatures and harsh combustion environments. In addition, their low densities relative to metals help reduce component mass (ref. 2). Detailed three-dimensional volume rendering of the tensile test specimen was successfully carried out with Velocity2 (ref. 1) using two-dimensional images that were generated via computed tomography. Subsequent, three-dimensional finite element analyses were performed, and the results obtained were compared with those predicted by NDE-based calculations and experimental tests. It was shown that Velocity2 software can be used to render a three-dimensional object from a series of CT scan images with a minimum level of complexity. The analytical results (ref. 3) show that the high-stress regions correlated well with the damage sites identified by the CT scans and the experimental data. Furthermore, modeling of the voids collected via NDE offered an analytical advantage that resulted in more accurate assessments of the material s structural strength. The top figure shows a CT scan image of the specimen test section illustrating various hidden structural entities in the material and an optical image of the test specimen considered in this study. The bottom figure represents the stress response predicted from the finite element analyses (ref .3 ) for a selected CT slice where it clearly illustrates the correspondence of the high stress risers due to voids in the material with those predicted by the NDE. This study is continuing, and efforts are concentrated on improving the modeling capabilities to imitate the structural anomalies as detected.

Abdul-Aziz, Ali↗

NASA NTRS2011

Terahertz Computed Tomography of NASA Thermal Protection System Materials

A terahertz axial computed tomography system has been developed that uses time domain measurements in order to form cross-sectional image slices and three-dimensional volume renderings of terahertz-transparent materials. The system can inspect samples as large as 0.0283 cubic meters (1 cubic foot) with no safety concerns as for x-ray computed tomography. In this study, the system is evaluated for its ability to detect and characterize flat bottom holes, drilled holes, and embedded voids in foam materials utilized as thermal protection on the external fuel tanks for the Space Shuttle. X-ray micro-computed tomography was also performed on the samples to compare against the terahertz computed tomography results and better define embedded voids. Limits of detectability based on depth and size for the samples used in this study are loosely defined. Image sharpness and morphology characterization ability for terahertz computed tomography are qualitatively described.

Roth, D. J.↗

NASA NTRS2011

A Novel Automated Method for Analyzing Cylindrical Computed Tomography Data

A novel software method is presented that is applicable for analyzing cylindrical and partially cylindrical objects inspected using computed tomography. This method involves unwrapping and re-slicing data so that the CT data from the cylindrical object can be viewed as a series of 2-D sheets in the vertical direction in addition to volume rendering and normal plane views provided by traditional CT software. The method is based on interior and exterior surface edge detection and under proper conditions, is FULLY AUTOMATED and requires no input from the user except the correct voxel dimension from the CT scan. The software is available from NASA in 32- and 64-bit versions that can be applied to gigabyte-sized data sets, processing data either in random access memory or primarily on the computer hard drive. Please inquire with the presenting author if further interested. This software differentiates itself in total from other possible re-slicing software solutions due to complete automation and advanced processing and analysis capabilities.

Roth, D. J.↗

DOE OSTI2021

Visualization of Jet Impingement and Ignition in a Piston-Cylinder Chamber

The transportation sector accounts for almost a third of the United States energy consumption. We are developing predictive simulations of the complex in-cylinder processes of internal combustion engines to improve performance and decrease pollutant emissions. Using volume rendering, we provide a first look at the jet impingement and ignition inside a piston-cylinder chamber. Through the visualization, we were able to construct a complete 3D picture of the jet impingement on the piston-bowl walls leading to the formation of pockets of auto-ignition of fuel-air mixture. These auto-ignition pockets subsequently lead to flame stabilization releasing the chemical energy for conversion to useful work. A detailed physical picture of flame stabilization as provided by the visualization techniques presented in this study help in the design next-generation internal combustion engines.

91 SC - Advanced Scientific Computing Reseach (ASC↗

NASA NTRS1997

A Parallel Pipelined Renderer for the Time-Varying Volume Data

This paper presents a strategy for efficiently rendering time-varying volume data sets on a distributed-memory parallel computer. Time-varying volume data take large storage space and visualizing them requires reading large files continuously or periodically throughout the course of the visualization process. Instead of using all the processors to collectively render one volume at a time, a pipelined rendering process is formed by partitioning processors into groups to render multiple volumes concurrently. In this way, the overall rendering time may be greatly reduced because the pipelined rendering tasks are overlapped with the I/O required to load each volume into a group of processors; moreover, parallelization overhead may be reduced as a result of partitioning the processors. We modify an existing parallel volume renderer to exploit various levels of rendering parallelism and to study how the partitioning of processors may lead to optimal rendering performance. Two factors which are important to the overall execution time are re-source utilization efficiency and pipeline startup latency. The optimal partitioning configuration is the one that balances these two factors. Tests on Intel Paragon computers show that in general optimal partitionings do exist for a given rendering task and result in 40-50% saving in overall rendering time.

Chiueh, Tzi-Cker↗

DOE OSTI2023

NeRVI: Compressive neural representation of visualization images for communicating volume visualization results

We present NeRVI, a new deep-learning approach that compresses a large collection of visualization images generated from time-varying data for communicating volume visualization results. Based on an image-based implicit neural representation, our approach represents tens of thousands of high-resolution rendering images parametrized by different parameters via a hybrid model of multilayer perceptrons and convolutional neural networks. Here, our model predicts images and corresponding masks, and the masks are utilized for loss computation and network training to capture fine structural details and small components. In conjunction with model quantization and weight encoding, NeRVI yields highly compact compressive neural representations while preserving the image fidelity well. We demonstrate the effectiveness of NeRVI with isosurface rendering and direct volume rendering images generated from multiple data sets and compare NeRVI with other state-of-the-art deep learning-based (InSituNet, SIREN, NeRF, and NeRV) methods. Quantitative and qualitative results show that NeRVI provides an alternative solution that augments domain scientists' ability to manage, represent, and communicate scientific visualization output.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1998

Efficient Encoding and Rendering of Time-Varying Volume Data

Visualization of time-varying volumetric data sets, which may be obtained from numerical simulations or sensing instruments, provides scientists insights into the detailed dynamics of the phenomenon under study. This paper describes a coherent solution based on quantization, coupled with octree and difference encoding for visualizing time-varying volumetric data. Quantization is used to attain voxel-level compression and may have a significant influence on the performance of the subsequent encoding and visualization steps. Octree encoding is used for spatial domain compression, and difference encoding for temporal domain compression. In essence, neighboring voxels may be fused into macro voxels if they have similar values, and subtrees at consecutive time steps may be merged if they are identical. The software rendering process is tailored according to the tree structures and the volume visualization process. With the tree representation, selective rendering may be performed very efficiently. Additionally, the I/O costs are reduced. With these combined savings, a higher level of user interactivity is achieved. We have studied a variety of time-varying volume datasets, performed encoding based on data statistics, and optimized the rendering calculations wherever possible. Preliminary tests on workstations have shown in many cases tremendous reduction by as high as 90% in both storage space and inter-frame delay.

CODING↗

NASA NTRSDate not supplied

Space Needle Returns

STEP is imported into Engineering Sketch Pad. Some bodies where slightly scaled and translated in OpenCSM to create a manifold solid for the downstream meshing process. The braces at the base and columns around the core are omitted because their solids are malformed or created nonmanifold intersections. EGADS provides an initial tessellation of the surface. refine adapted the surface mesh to a curvature and feature size metric. TetGen initially filled the volume. The TetGen mesh is adapted to the Spalding Law of the Wall u+ with refine to provide the initial mesh for flow solution. Solution-based mesh adaptation is performed where FUN3D-FV computes the flow solution with the Reynolds-averaged Navier-Stokes equations coupled to the Spalart-Allmaras turbulence model. The freestream Mach number is 4 approaching 40° from the central axis of the Space Needle. The volume and surface mesh is adapted with refine to reduce estimated interpolation error in Mach number via the multiscale metric. The adapted mesh implicitly resolves the boundary layers, shocks, and expansions. The surface mesh is shown for the lee side with a slice through the volume on the left. Computational schlieren in the lower right shows density variations. A slice of the mesh is colored with Mach number in the upper right where mesh with freestream Mach number is not rendered. The volume mesh contains 64 million vertices. A NASA worm logo is sketched and extruded into a solid in OpenCSM. The worm is unioned to the Space Needle roof to produce the inset mesh image.

mesh↗

DOE OSTI2024

Attribute-Aware RBFs: Interactive Visualization of Time Series Particle Volumes Using RT Core Range Queries

Smoothed-particle hydrodynamics (SPH) is a mesh-free method used to simulate volumetric media in fluids, astrophysics, and solid mechanics. Visualizing these simulations is problematic because these datasets often contain millions, if not billions of particles carrying physical attributes and moving over time. Radial basis functions (RBFs) are used to model particles, and overlapping particles are interpolated to reconstruct a high-quality volumetric field; however, this interpolation process is expensive and makes interactive visualization difficult. Existing RBF interpolation schemes do not account for color-mapped attributes and are instead constrained to visualizing just the density field. To address these challenges, we exploit ray tracing cores in modern GPU architectures to accelerate scalar field reconstruction. We use a novel RBF interpolation scheme to integrate per-particle colors and densities, and leverage GPU-parallel tree construction and refitting to quickly update the tree as the simulation animates over time or when the user manipulates particle radii. We also propose a Hilbert reordering scheme to cluster particles together at the leaves of the tree to reduce tree memory consumption. Finally, we reduce the noise of volumetric shadows by adopting a spatially temporal blue noise sampling scheme. Our method can provide a more detailed and interactive view of these large, volumetric, time-series particle datasets than traditional methods, leading to new insights into these physics simulations.

Particle Volumes↗

DOE OSTI2026

Expanding Access to Science Participation: A FAIR Framework for Petascale Data Visualization and Analytics

The massive data generated by scientists daily serve as both a major catalyst for new discoveries and innovations, as well as a significant roadblock that restricts access to the data. Here, our paper introduces a new approach to removing Big Data barriers and democratizing access to petascale data for the broader scientific community. Our novel data fabric abstraction layer allows user-friendly querying of scientific information while hiding the complexities of dealing with file systems or cloud services. We enable FAIR (Findable, Accessible, Interoperable, and Reusable) access to datasets such as NASA’s petascale climate datasets. Our paper presents an approach to managing, visualizing, and analyzing petabytes of data within a browser on equipment ranging from the top NASA supercomputer to commodity hardware like a laptop. Our novel data fabric abstraction utilizes state-of-the art progressive compression algorithms and machine-learning insights to power scalable visualization dashboards for petascale data. The result provides users with the ability to identify extreme events or trends dynamically, expanding access to scientific data and further enabling discoveries. We validate our approach by improving the ability of climate scientists to visually explore their data via three fully interactive dashboards. We further validate our approach by deploying the dashboards and simplified training materials in the classroom at a minority-serving institution. These dashboards, released in simplified form to the general public, contribute significantly to a broader push to democratize the access and use of climate data.

Computer science↗

NASA NTRS2013

Heat Melt Compaction as an Effective Treatment for Eliminating Microorganisms from Solid Waste

One of the technologies being tested at NASA Ames Research Center (ARC) for the Advance Exploration Systems program and as part of the logistics and repurposing project is heat melt compaction (HMC) of solid waste. Reduces volume, removes water and renders a biologically stable and safe product. The HMC compacts and reduces the trash volume as much as 90o/o greater than the current manual compaction used by the crew.The project has three primary goals or tasks. 1. Microbiological analysis of HMC hardware surfaces before and after operation. 2. Microbiological and physical characterizations of heat melt tiles made from trash at different processing times and temperatures. 3. Long term storage and stability of HMC trash tiles or "Do the bugs grow back?"

Hummerick, Mary P.↗

DOE OSTI2024

The Central Role of Oxo Clusters in Zirconium‐Based Esterification Catalysis

Oxo clusters are a unique link between oxide nanocrystals and Metal‐Organic Frameworks (MOFs), representing the limit of downscaling each of the respective crystals. Herein, the superior catalytic activity of clusters, compared to zirconium MOF UiO‐66 and nanocrystals is shown. Focus is on esterification reactions given their general importance in consumer products and the challenge of converting large substrates. Oxo clusters have a higher surface‐to‐volume ratio than nanocrystals, rendering them more active. For large substrates, for example, oleic acid, MOF UiO‐66 has negligible catalytic activity while clusters provide almost quantitative conversion, a fact we ascribe to limited diffusion of large substrates through the MOF pores. Clusters do not suffer from limited mass transfer and we also obtain high conversion in solvent‐free reactions with sterically hindered alcohols (hexanol, 2‐ethyl hexanol, benzyl alcohol, and neopentyl alcohol). The cluster catalyst can be recovered and shows identical activity when reused. The structural integrity of the cluster is confirmed using X‐ray total scattering and pair distribution function analysis. Moreover, when homogeneous zirconium alkoxides are used as catalysts, the same oxo cluster is retrieved, showing that oxo clusters are the active catalytic species, even in previously assumed homogeneously catalyzed reactions.

Pulparayil Mathew, Jikson↗

DOE OSTI2024

DEM simulation of the compression of crushable sand: does the initial particle shape matter?

Advances in DEM modeling, combined with high-resolution X-ray tomography, opened the way for computer models based on virtual replicas of the particles which preserve nearly all facets of their geometry. This leads to simulation advantages, but also high computational costs. Here we tackle a question stemming from this trend: how accurate should particle models be to ensure accuracy? We address this question for the case of the compression of crushable sand. LS-DEM was used to generate three models of Ottawa sand (exact replicas, ellipsoids, and spheres) from digital images of its grains. Compression-induced crushing was simulated for all sets by tracking evolving size and shape distribution. The results confirm that exact replicas provide the closest match of the measurements. However, intermediate degrees of rendering (e.g. ellipsoids preserving volume and aspect ratio of the real grains) led to satisfactory results only marginally different from those of exact replicas. In conclusion, these findings provide an example of the protocols that may be followed to identify the optimal degree of particle approximation which should be regarded as mandatory to achieve a conscious, sustainable use of computational resources.

58 GEOSCIENCES↗

NASA NTRS2012

Heat Melt Compaction as an Effective Treatment for Eliminating Microorganisms from Solid Waste

One of the technologies being tested at Ames Research Center as part of the logistics and repurposing project is heat melt compaction (HMC) of solid waste to reduce volume, remove water and render a biologically stable and safe product. Studies at Kennedy Space Center have focused on the efficacy of the heat melt compaction process for killing microorganisms in waste and specific compacter operation protocols, i.e., time and temperature, required to achieve a sterile, stable product. The work reported here includes a controlled study to examine the survival and potential re-growth of specific microorganisms over a 6-month period of storage after heating and compaction. Before heating and compaction, ersatz solid wastes were inoculated with Bacillus amyloliquefaciens and Rhodotorula mucilaginosa, previously isolated from recovered space shuttle mission food and packaging waste. Compacted HMC tiles were sampled for microbiological analysis at time points between 0 and 180 days of storage in a controlled environment chamber. In addition, biological indicator strips containing spores of Bacillus atrophaeus and Ceo bacillus stearothermophilus were imbedded in trash to assess the efficacy of the HMC process to achieve sterilization. Analysis of several tiles compacted at 180 C for times of 40 minutes to over 2 hours detected organisms in all tile samples with the exception of one exposed to 180 C for approximately 2 hours. Neither of the inoculated organisms was recovered, and the biological indicator strips were negative for growth in all tiles indicating at least local sterilization of tile areas. The findings suggest that minimum time/temperature combination is required for complete sterilization. Microbial analysis of tiles processed at lower temperatures from 130 C-150 C at varying times will be discussed, as well as analysis of the bacteria and fungi present on the compactor hardware as a result of exposure to the waste and the surrounding environment. The two organisms inoculated into the waste were among those isolated and identified from the HMC surfaces indicating the possibility of cross contamination.

Hummerick, Mary P.↗

NASA NTRS2013

Heat Melt Compaction as an Effective Treatment for Eliminating Microorganisms from Solid Waste

One of the technologies being tested at Ames Research Center as part of the logistics and repurposing project is heat melt compaction (HMC) of solid waste to reduce volume, remove water and render a biologically stable and safe product. Studies at Kennedy Space Center have focused on the efficacy of the heat melt compaction process for killing microorganisms in waste and specific compacter operation protocols, i.e., time and temperature required to achieve a sterile, stable product. The work. reported here includes a controlled study to examine the survival and potential re-growth of specific microorganisms over a 6-month period of storage after heating and compaction. Before heating and compaction, ersatz solid wastes were inoculated with Bacillus amyloliquefaciens and Rhodotorula mucilaginosa, previously isolated from recovered space shuttle mission food and packaging waste. Compacted HMC tiles were sampled for microbiological analysis at time points between 0 and 180 days of storage in a controlled environment chamber. In addition, biological indicator strips containing spores of Bacillus atrophaeus and Geobacillus stearothermophilus were imbedded in trash to assess the efficacy of the HMC process to achieve sterilization. Analysis of several tiles compacted at 180deg C for times of 40 minutes to over 2 hours detected organisms in all tile samples with the exception of one exposed to 180deg C for approximately 2 hours. Neither of the inoculated organisms was recovered, and the biological indicator strips were negative for growth in all tiles indicating at least local sterilization of tile areas. The findings suggest that minimum time/temperature combination is required for complete sterilization. Microbial analysis of tiles processed at lower temperatures from 130deg C-150deg C at varying times will be discussed, as well as analysis of the bacteria and fungi present on the compactor hardware as a result of exposure to the waste and the surrounding environment. The two organisms inoculated into the waste were among those isolated and identified from the HMC surfaces indicating the possibility of cross contamination.

Hummerick, Mary P.↗