SEARCH · Search NASA

Results for “Mesh Networks”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 163 records · Page 9

All sources NASA NTRS DOE OSTI

NASA NTRS1998

Navigation of the space VLBI mission-HALCA

In February 1997, the Japanese Space Agency ISAS launched the first space VLBI satellite, HALCA, with an 8 meter diameter wire mesh antenna and radio astronomy receivers capable of observing at 1.6, 4.8, and 22 Ghz. In a 560 by 21000 km orbit with a 6 hour period and 31 degree inclination, it observes celestial radio sources in conjunction with a world wide network of ground radio telescopes as part of an international collaborative effort which includes facilities in Japan, the U.S., Canada, Australia, and Europe. JPL is providing tracking and navigation support using a dedicated subnet of 11 meter antennas as well as co-observations using the DSN 70 meter antennas. This paper describes the spacecraft dynamics model and orbit determination strategies developed to meet the stringent trajectory accuracy requirements for generating predictions for the transfer of a stable uplink frequency to the spacecraft and for determining reconstructed orbits for delivery to the NRAO VLBI correlator and the international VLBI science community.

You, Tung Han↗

DOE OSTI2024

Chapter 4: Physically informed deep learning networks for simulating microstructure evolution of 3D polycrystals

As discussed in the previous chapter, high energy diffraction microscopy (HEDM) is used to study the micromechanical evolution of a material during in situ loading. HEDM experiments have been used to verify crystal plasticity (CP) simulations [119, 91, 90, 120], for experimental planning, material design, and to further analyze experimental results. However, Fast Fourier transform-based CP (CP-FFT) or finite element-based CP (CP-FE) methods are often too slow to be used in real-time during an experiment. CP-FFT is faster than CP-FE simulations due to the absence of meshing, but can still take hours to simulate the response of a single volume depending on the size and number of strain steps [127]. Reducing computation time would create a larger exploration space in planning and design, and enable faster analysis of experimental results and real-time feedback during an experiment. This research expands upon previous works to develop a workflow for predicting the full-field evolution of a 3D polycrystal. The workflow is simplified from previous works to predict only orientation and elastic strain tensors (from which stress tensors are calculated). The network is physically informed through loss functions and network architecture for a more robust model. The orientation predictions are informed about the cubic crystal symmetry of the material by incorporating disorientation and misorientation information into the network architecture and loss. The Von Mises stress is used to enforce the correct stress-strain trends in the strain tensor predictions. Additional total strain steps from the elastic and elastoplastic region are included to better capture the stress-strain evolution at smaller total strain steps. Material and hardening parameters are additional inputs into the networks to further inform the network and to study the network’s ability to predict different materials other than those used for training.

36 MATERIALS SCIENCE↗

NASA NTRS1997

Computer Supported Indexing: A History and Evaluation of NASA's MAI System

Computer supported indexing systems may be categorized in several ways. One classification scheme refers to them as statistical, syntactic, semantic or knowledge-based. While a system may emphasize one of these aspects, most systems actually combine two or more of these mechanisms to maximize system efficiency. Statistical systems can be based on counts of words or word stems, statistical association, and correlation techniques that assign weights to word locations or provide lexical disambiguation, calculations regarding the likelihood of word co-occurrences, clustering of word stems and transformations, or any other computational method used to identify pertinent terms. If words are counted, the ones of median frequency become candidate index terms. Syntactical systems stress grammar and identify parts of speech. Concepts found in designated grammatical combinations, such as noun phrases, generate the suggested terms. Semantic systems are concerned with the context sensitivity of words in text. The primary goal of this type of indexing is to identify without regard to syntax the subject matter and the context-bearing words in the text being indexed. Knowledge-based systems provide a conceptual network that goes past thesaurus or equivalent relationships to knowing (e.g., in the National Library of Medicine (NLM) system) that because the tibia is part of the leg, a document relating to injuries to the tibia should he indexed to LEG INJURIES, not the broader MeSH term INJURIES, or knowing that the term FEMALE should automatically be added when the term PREGNANCY is assigned, and also that the indexer should be prompted to add either HUMAN or ANIMAL. Another way of categorizing indexing systems is to identify them as producing either assigned- or derived-term indexes.

Silvester, June P.↗

NASA NTRS2004

Compact, Lightweight Dual- Frequency Microstrip Antenna Feed for Future Soil Moisture and Sea Surface Salinity Missions

The development of a compact, lightweight, dual frequency antenna feed for future soil moisture and sea surface salinity (SSS) missions is described. The design is based on the microstrip stacked-patch array (MSPA) to be used to feed a large lightweight deployable rotating mesh antenna for spaceborne L-band (approx. 1 GHz) passive and active sensing systems. The design features will also enable applications to airborne sensors operating on small aircrafts. This paper describes the design of stacked patch elements, 16-element array configuration and power-divider beam forming network The test results from the fabrication of stacked patches and power divider were also described.

sea surface salinity↗

NASA NTRS2012

High-Thermal-Conductivity Fabrics

Heat management with common textiles such as nylon and spandex is hindered by the poor thermal conductivity from the skin surface to cooling surfaces. This innovation showed marked improvement in thermal conductivity of the individual fibers and tubing, as well as components assembled from them. The problem is centered on improving the heat removal of the liquid-cooled ventilation garments (LCVGs) used by astronauts. The current design uses an extensive network of water-cooling tubes that introduces bulkiness and discomfort, and increases fatigue. Range of motion and ease of movement are affected as well. The current technology is the same as developed during the Apollo program of the 1960s. Tubing material is hand-threaded through a spandex/nylon mesh layer, in a series of loops throughout the torso and limbs such that there is close, form-fitting contact with the user. Usually, there is a nylon liner layer to improve comfort. Circulating water is chilled by an external heat exchanger (sublimator). The purpose of this innovation is to produce new LCVG components with improved thermal conductivity. This was addressed using nanocomposite engineering incorporating high-thermalconductivity nanoscale fillers in the fabric and tubing components. Specifically, carbon nanotubes were added using normal processing methods such as thermoplastic melt mixing (compounding twin screw extruder) and downstream processing (fiber spinning, tubing extrusion). Fibers were produced as yarns and woven into fabric cloths. The application of isotropic nanofillers can be modeled using a modified Nielsen Model for conductive fillers in a matrix based on Einstein s viscosity model. This is a drop-in technology with no additional equipment needed. The loading is limited by the ability to maintain adequate dispersion. Undispersed materials will plug filtering screens in processing equipment. Generally, the viscosity increases were acceptable, and allowed the filled polymers to still be processed.The novel feature is that fabrics do not inherently possess good thermal conductivity. In fact, fabrics are used for thermal insulation, not heat removal. The technology represents the first material that is a wearable fabric, based on company textiles and materials that will significantly conduct heat.

Chibante, L. P. Felipe↗

NASA NTRSDate not supplied

Assessment of the Fluid Network for the Effusion Holes in a RQL (Rich-burn, Quick-quench, Lean-burn) Gas Turbine Combustor

The transient processes involving lean blowout (LBO) in a RQL combustor such as the single cup combustor in the National Jet Fuels Combustion Program (NJFCP) referee rig are simulated with the reduced mechanisms based on Hybrid Chemistry for three different fuels, A2, C1 and C4. Experiments conducted in the NJFCP referee rig established a stable flame at a global equivalence ratio of 0.096 (the near LBO condition) as the starting condition for LBO tests performed with all A and C fuels. Simulations of the approach to LBO verify that a stable flame is established at the near-LBO condition for each fuel before reducing fuel flow rate (and thus equivalence ratio) in a stepwise manner. Main conclusions are: (1) For A2 fuel the equivalence ratio for LBO is 0.081 (2) For C1 fuel the equivalence ratio for LBO is 0.087 or 0.085depended on different step-down transition paths. (3) For C4 fuel the equivalence ratio for LBO is 0.087 or 0.084 depended on types of mesh or boundary conditions. (4) The fuel relative difference from LES on LBO for C1 fuel relative to A2 fuel is 7.40% or 4.94% versus 7.83% from the experimental data. (5) The fuel relative difference from LES on LBO for C4 fuel relative to A2 is 6.17% or 7.69% versus 5.21% from the experimental data

Lean blow out↗

NASA NTRSDate not supplied

Assessment of the Fluid Network for the Effusion Holes in a RQL (Rich-burn, Quick-quench, Lean-burn) Gas Turbine Combustor

The transient processes involving lean blowout (LBO) in a RQL combustor such as the single cup combustor in the National Jet Fuels Combustion Program (NJFCP) referee rig are simulated with the reduced mechanisms based on Hybrid Chemistry for three different fuels, A2, C1 and C4. Experiments conducted in the NJFCP referee rig established a stable flame at a global equivalence ratio of 0.096 (the near LBO condition) as the starting condition for LBO tests performed with all A and C fuels. Simulations of the approach to LBO verify that a stable flame is established at the near-LBO condition for each fuel before reducing fuel flow rate (and thus equivalence ratio) in a stepwise manner. Main conclusions are: (1) For A2 fuel the equivalence ratio for LBO is 0.081 (2) For C1 fuel the equivalence ratio for LBO is 0.087 or 0.085 depended on different step-down transition paths. (3) For C4 fuel the equivalence ratio for LBO is 0.087 or 0.084 depended on types of mesh or boundary conditions. (4) The fuel relative difference from LES on LBO for C1 fuel relative to A2 fuel is 7.40% or 4.94% versus 7.83% from the experimental data. (5) The fuel relative difference from LES on LBO for C4 fuel relative to A2 is 6.17% or 7.69% versus 5.21% from the experimental data.

Lean Blow out↗

DOE OSTI2025

Mesh-like structure integrated core-shell-shell nanocomposites for enhanced stability and performance in carbon capture

Carbon capture is essential for mitigating climate change, yet most sorbents struggle to combine high capacity with chemical stability. Here we report core-shell-shell (CSS) nanocomposites that integrate adsorption efficiency with exceptional robustness. The design couples a metal-organic framework (MOF) core, which enriches local CO 2 concentration, with a polyamine shell that is reorganized into a porous, ordered network through entanglement with an outer covalent organic framework (COF) shell. This hierarchical architecture enables dual amine functionalization via sequential “click” and Schiff-base reactions, achieving a CO 2 uptake of 3.4 mmol g −1 at 1 bar. The COF outer layer also acts as a protective barrier, suppressing humidity interference and doubling cycling stability under simulated flue gas. Remarkably, the nanocomposites maintain structural integrity after one week in strongly acidic (3 M HNO 3 ) or basic (NaOH, pH=14) environments, underscoring their chemical resilience. By uniting high capacity, cycling durability, and environmental tolerance, this CSS strategy offers a versatile platform for next-generation carbon capture materials.

Yang, Sizhuo [Lawrence Berkeley National Laborator↗

DOE OSTI2024

DS-GL: Advancing Graph Learning via Harnessing the Power of Nature within Dynamic Systems

With the rapid digitization of the world, an increasing number of real-world applications are turning to nonEuclidean data, modeled as graphs. Due to their intrinsic high complexity and irregularity, learning from graph data demands tremendous computational power. Recently, CMOS-compatible Ising machines, i.e., dynamic systems composed of CMOS components, have emerged as a new approach that harnesses the inherent power of natural annealing within dynamic systems to efficiently resolve binary optimization problems and have been adopted for traditional graph computation, such as max-cut. However, when performing complex Graph Learning (GL) tasks, Ising machines face significant hurdles: (i) they are inherently binary and thus ill-suited for real-valued problems; (ii) their expensive all-to-all coupling network that guarantees effective natural annealing poses daunting scalability concerns. To address these challenges, this paper proposes a nature-powered graph learning framework dubbed DS-GL, which is the first effort to transform the process of solving graph learning problems into the natural annealing process within a parameterized dynamic system embodied as a CMOS chip. To tackle the two major hurdles, DS-GL first augments the Ising machine architecture to modify the self-reaction term of its Hamiltonian function from linear to quadratic, effectively serving as an energy regulator. This adjustment maintains the system’s original physical interpretation while enabling it to process continuous, real-valued data. Second, to address the scaling issue, DS-GL further upgrades the real-valued dense Ising machine by decomposing it into a mesh-based multi-PE dynamic system that supports efficient distributed spatial-temporal co-annealing across different PEs through sparse interconnects. By exploiting the inherent sparsity and component structures in real-world graphs, DS-GL is able to map complex graph learning tasks onto the scalable dynamic system while maintaining high accuracy. Evaluations with three diverse GL applications across six real-world datasets, including traffic flow and COVID-19 prediction, show that DS-GL can deliver from 102× to 106× speedups and 500× energy reduction over Graph Neural Networks on GPUs, with 5% - 20% accuracy enhancement.

Song, Ruibing↗

NASA NTRS1997

RIACS

Topics considered include: high-performance computing; cognitive and perceptual prostheses (computational aids designed to leverage human abilities); autonomous systems. Also included: development of a 3D unstructured grid code based on a finite volume formulation and applied to the Navier-stokes equations; Cartesian grid methods for complex geometry; multigrid methods for solving elliptic problems on unstructured grids; algebraic non-overlapping domain decomposition methods for compressible fluid flow problems on unstructured meshes; numerical methods for the compressible navier-stokes equations with application to aerodynamic flows; research in aerodynamic shape optimization; S-HARP: a parallel dynamic spectral partitioner; numerical schemes for the Hamilton-Jacobi and level set equations on triangulated domains; application of high-order shock capturing schemes to direct simulation of turbulence; multicast technology; network testbeds; supercomputer consolidation project.

Oliger, Joseph↗

DOE OSTI2026

Scaling kinetic Monte-Carlo simulations of grain growth with combined convolutional and graph neural networks

Graph neural networks (GNN) have emerged as a promising machine learning method for microstructure simulations such as grain growth. However, accurate modeling of realistic grain boundary networks requires large simulation cells, which GNN has difficulty scaling up to. To alleviate the computational costs and memory footprint of GNN, we suggest a hybrid architecture combining a convolutional neural network (CNN) based bijective autoencoder to compress the spatial dimensions, and a GNN that evolves the microstructure in the latent space of reduced spatial sizes. Our results demonstrate that the new design significantly reduces computational costs with using fewer message passing layer (from 12 down to 3) compared with GNN alone. The reduction in computational cost becomes more pronounced as the spatial size increases, indicating strong computational scalability. For the largest mesh evaluated (160 3 ), our method reduces memory usage and runtime in inference by 117× and 115×, respectively, compared with GNN-only baseline. More importantly, it shows higher accuracy and stronger spatiotemporal capability than the GNN-only baseline, especially in long-term testing. Such combination of scalability and accuracy is essential for simulating realistic material microstructures over extended time scales. The improvements can be attributed to the bijective autoencoder’s ability to compress information losslessly from spatial domain into a high dimensional feature space, thereby producing more expressive latent features for the GNN to learn from, while also contributing its own spatiotemporal modeling capability. Training data are generated from stochastic grain growth simulations, providing realistic variability for learning robust microstructure evolution. Comprehensive system validation confirms that the model is accurate, robust, and scalable.

36 MATERIALS SCIENCE↗

NASA NTRS1991

Performance effects of irregular communications patterns on massively parallel multiprocessors

A detailed study of the performance effects of irregular communications patterns on the CM-2 was conducted. The communications capabilities of the CM-2 were characterized under a variety of controlled conditions. In the process of carrying out the performance evaluation, extensive use was made of a parameterized synthetic mesh. In addition, timings with unstructured meshes generated for aerodynamic codes and a set of sparse matrices with banded patterns on non-zeroes were performed. This benchmarking suite stresses the communications capabilities of the CM-2 in a range of different ways. Benchmark results demonstrate that it is possible to make effective use of much of the massive concurrency available in the communications network.

Saltz, Joel↗

NASA NTRS1991

Performance effects of irregular communications patterns on massively parallel multiprocessors

Saltz, Joel↗

NASA NTRS1987

Impact of solids on composite materials

The failure modes of composite materials as a result of low velocity impact were investigated by simulating the impact with a finite element analysis. An important facet of the project is the modeling of the impact of a solid onto cylindrical shells composed of composite materials. The model under development will simulate the delamination sustained when a composite material encounters impact from another rigid body. The computer equipment was installed, the computer network tested, and a finite element method model was developed to compare results with known experimental data. The model simulated the impact of a steel rod onto a rotating shaft. Pre-processing programs (GMESH and TANVEL) were developed to generate node and element data for the input into the three dimensional, dynamic finite element analysis code (DYNA3D). The finite element mesh was configured with a fine mesh near the impact zone and a coarser mesh for the impacting rod and the regions surrounding the impacting zone. For the computer simulation, five impacting loads were used to determine the time history of the stresses, the scribed surface areas, and the amount of ridging. The processing time of the computer codes amounted from 1 to 4 days. The calculated surface area were within 6-12 percent, relative error when compated to the actual scratch area.

Bronson, Arturo↗

NASA NTRS1989

Krylov methods preconditioned with incompletely factored matrices on the CM-2

The performance is measured of the components of the key interative kernel of a preconditioned Krylov space interative linear system solver. In some sense, these numbers can be regarded as best case timings for these kernels. Sweeps were timed over meshes, sparse triangular solves, and inner products on a large 3-D model problem over a cube shaped domain discretized with a seven point template. The performance of the CM-2 is highly dependent on the use of very specialized programs. These programs mapped a regular problem domain onto the processor topology in a careful manner and used the optimized local NEWS communications network. The rather dramatic deterioration in performance was documented when these ideal conditions no longer apply. A synthetic workload generator was developed to produce and solve a parameterized family of increasingly irregular problems.

Berryman, Harry↗

DOE OSTI2026

CHESS 2025: Orthorectified airborne RGB imagery from NEON AOP surveys

This dataset provides Level 1 (L1) and Level 3 (L3) orthorectified Red-Green-Blue (RGB) imagery collected for the 2025 Colorado Headwaters Ecological Spectroscopy Study (CHESS). This high-resolution imagery is a photographic record of red, green, and blue visible light from sunlight reflected off of the Earth’s surface. The data comprise full-color images of the ground surface and are primarily intended to provide context to imaging spectroscopy and light detection and ranging (LiDAR) data. The data were acquired over three study domains in the Upper Gunnison river basin: the upper East River watershed (CRBU); Almont Triangle and Taylor Canyon (ALMO); and Upper Taylor River watershed (UPTA) between 2025-06-13 and 2025-07-15. RGB images were acquired using the PhaseOne IXM-RS150F high-resolution digital camera onboard the National Ecological Observatory Network (NEON) Airborne Observation Platform (AOP). The package data include both an L1 product comprising one camera frame per file and an L3 mosaic aligned to the Universal Transverse Mercator (UTM) Zone 13N grid and the World Geodetic System (WGS) 84 projection. Both products are provided in geotif (.tif) format at 0.1 m ground resolution. The bulk of the imagery was collected during the main CHESS field campaign from June 13 to July 15, 2025. Additional images of a portion of the Upper Taylor (UPTA) domain were collected on September 18, 2025, to fill gaps in imagery identified after the main campaign was complete. RGB camera imagery is not radiometrically calibrated, and therefore pixel values should not be exploited for scientific analysis. Pixel values have undergone a manual adjustment to enhance feature identification. The imagery is rigorously geolocated which does allow for reliable geometric information to be retrieved. To generate the orthorectified imagery, the NEON AOP camera captured visible spectrum in red, green, and blue bands. The raw images were then processed using NEON’s camera orthorectification workflow. A boresight calibration flight was made to build a complete camera, distortion, and alignment model. Color balance/white balance and exposure correction were applied to the raw RGB images. The corrected images were orthorectified by ray-tracing image pixels to a lidar-derived digital surface model (DSM) mesh using the refined camera model, outputting orthorectified raster pixels on a regular grid. Flightline-level data were mosaicked by selecting per-pixel contributions from overlapping orthorectified images using line-of-sight (LOS) zenith angle minimization to reduce edge distortions. CHESS Project Description: The Colorado Headwaters Ecological Spectroscopy Study (CHESS) comprised a multi-week airborne remote sensing and field observation campaign in the Upper Gunnison Basin, Colorado, conducted in June and July of 2025. Airborne remote sensing was conducted by the National Ecological Observatory Network Airborne Observation Platform (NEON AOP), concurrent with a field campaign run by the Rocky Mountain Biological Laboratory (RMBL), the Lawrence Berkeley National Laboratory (LBNL) and SLAC National Accelerator Laboratory Watershed Function Science Focus Area (SFA), and NASA-JPL (Jet Propulsion Laboratory) Earth Surface Mineral Dust Source Investigation (EMIT) program. Between June 10 and July 18, 2025, the NEON AOP flight team collected high-resolution aerial imaging spectroscopy and Light Detection and Ranging (LiDAR) data over three domains: the Upper East River (CRBU), Almont Triangle (ALMO), and the Upper Taylor Basin (UPTA). In coordination with the flights, a field campaign acquired ground-truth observations, including observations of vegetation composition, foliar traits, forest demography, and subsurface properties in 18 core sampling areas within the domains. Additional surface water observations were taken at over 380 point locations. All CHESS campaign datasets can be found within the CHESS ESS-DIVE data portal: https://data.ess-dive.lbl.gov/portals/chess. Funding Acknowledgement: Field and remote-sensing data acquisition was performed under a grant from the National Aeronautics and Space Administration (80NSSC24K1005). This work was also supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.

2018 NEON and 2025 CHESS Campaigns↗

NASA NTRS2001

Parallel Processing of Adaptive Meshes with Load Balancing

Many scientific applications involve grids that lack a uniform underlying structure. These applications are often also dynamic in nature in that the grid structure significantly changes between successive phases of execution. In parallel computing environments, mesh adaptation of unstructured grids through selective refinement/coarsening has proven to be an effective approach. However, achieving load balance while minimizing interprocessor communication and redistribution costs is a difficult problem. Traditional dynamic load balancers are mostly inadequate because they lack a global view of system loads across processors. In this paper, we propose a novel and general-purpose load balancer that utilizes symmetric broadcast networks (SBN) as the underlying communication topology, and compare its performance with a successful global load balancing environment, called PLUM, specifically created to handle adaptive unstructured applications. Our experimental results on an IBM SP2 demonstrate that the SBN-based load balancer achieves lower redistribution costs than that under PLUM by overlapping processing and data migration.

Das, Sajal K.↗

NASA NTRS1999

Computer Aided Modeling to Determine the Effectiveness of Resistive Exercises as Countermeasures for Bone Mineral Density Loss

Due to the loss of gravitational loading, astronauts have a tendency to lose bone mineral density in their lumbar spine and lower extremities on orbit. NASA requires astronauts to perform exercises during space flight to help reduce the amount of demineralization. To test these exercises on earth, 17 week bed rest studies are conducted that consist of specific diet and exercise regimes. Developing a finite element model of these exercises will help to quantify the stress distribution imposed by of each of these exercises. To help develop this model, MRI images are acquired from individuals participating in the bed rest studies. The MRIs can be used to create a subject specific model of each individual for testing. The MRIs are processed in the Magnetic Resonance Imaging Data Transfer System program to develop a three-dimensional finite element model of the femur for evaluation. Modifications were made to the MRIDTS that simplified the model creation process. These modifications made it possible to construct two separate models of different portions of a bone simultaneously and then later connect them manually. This helped alleviate the warping problem associated with the drastic changes in geometry found in some body parts, such as the joints. The code was also modified to incorporate material properties of various bone components into the model. Interior meshing was also incorporated into the program to allow for both the cortical shell and the entire bone to be modeled. A prototype model of the right femur of an adult female is being constructed and tested to determine the feasibility of finite element analysis as a tool for evaluating exercise effectiveness. The model is being run through the ANSYS finite element program on the Alabama Super Computer Network. After the model is validated, models of bedrest subjects can be generated to investigate exercise countermeasures.

Murphy, Benjamin M.↗