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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 685 records · Page 38

All sources NASA NTRS DOE OSTI

NASA NTRS2010

Applications of Modeling and Simulation for Flight Hardware Processing at Kennedy Space Center

The Boeing Design Visualization Group (DVG) is responsible for the creation of highly-detailed representations of both on-site facilities and flight hardware using computer-aided design (CAD) software, with a focus on the ground support equipment (GSE) used to process and prepare the hardware for space. Throughout my ten weeks at this center, I have had the opportunity to work on several projects: the modification of the Multi-Payload Processing Facility (MPPF) High Bay, weekly mapping of the Space Station Processing Facility (SSPF) floor layout, kinematics applications for the Orion Command Module (CM) hatches, and the design modification of the Ares I Upper Stage hatch for maintenance purposes. The main goal of each of these projects was to generate an authentic simulation or representation using DELMIA V5 software. This allowed for evaluation of facility layouts, support equipment placement, and greater process understanding once it was used to demonstrate future processes to customers and other partners. As such, I have had the opportunity to contribute to a skilled team working on diverse projects with a central goal of providing essential planning resources for future center operations.

Marshall, Jennifer L.↗

NASA NTRS2019

Earth Science and Remote Sensing Data Portal Earth Science and Remote Sensing Geospatial Data Portal

The Earth Science and Remote Sensing (ESRS) Data Portal, managed by the ESRS Unit at NASA's Johnson Space Center, is a web GIS environment built on Esri's ArcGIS Enterprise platform. Its current intent is to visualize, analyze, and distribute geospatial data to our internal organization and the communities of Houston and Galveston. Applications on the ESRS Data Portal include a Regional Remote Sensing web app, story maps developed for astronaut training, and a web scene for visualizing LiDAR.

Jagge, Amy M.↗

DOE OSTI2018

Chloride induced reinforcement corrosion behavior in self-healing concrete with encapsulated polyurethane

Cracks in reinforced concrete structures accelerate the ingress of chlorides and therefore cause a higher risk for corrosion. In this research, autonomous healing of cracks by encapsulated polyurethane was investigated as a possible method to reduce reinforcement corrosion. Reinforced concrete beams were exposed weekly to a chloride solution and electrochemical parameters were measured to determine the influence of the self-healing mechanism on the corrosion process. The rebars were visually examined afterwards. For the cracked beams an active state of corrosion was detected within an exposure period of 10 weeks and clear pitting corrosion was observed on the rebars. Autonomous crack healing with low viscosity polyurethane could significantly reduce the corrosion in the propagation stage. For these specimens no visual damage to the rebars was detected. In conclusion, the application of self-healing concrete with a low viscosity polyurethane is able to enhance the durability of reinforced concrete structures in marine environments.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Demonstrating the viability of Lagrangian in situ reduction on supercomputers

Performing exploratory analysis and visualization of large-scale time-varying computational science applications is challenging due to inaccuracies that arise from under-resolved data. In recent years, Lagrangian representations of the vector field computed using in situ processing are being increasingly researched and have emerged as a potential solution to enable exploration. However, prior works have offered limited estimates of the encumbrance on the simulation code as they consider “theoretical” in situ environments. Further, the effectiveness of this approach varies based on the nature of the vector field, benefitting from an in-depth investigation for each application area. With this study, an extended version of Sane et al. (2021), we contribute an evaluation of Lagrangian analysis viability and efficacy for simulation codes executing at scale on a supercomputer. We investigated previously unexplored cosmology and seismology applications as well as conducted a performance benchmarking study by using a hydrodynamics mini-application targeting exascale computing. Here, to inform encumbrance, we integrated in situ infrastructure with simulation codes, and evaluated Lagrangian in situ reduction in representative homogeneous and heterogeneous HPC environments. To inform post hoc accuracy, we conducted a statistical analysis across a range of spatiotemporal configurations as well as a qualitative evaluation. Additionally, our study contributes cost estimates for distributed-memory post hoc reconstruction. In all, we demonstrate viability for each application — data reduction to less than 1% of the total data via Lagrangian representations, while maintaining accurate reconstruction and requiring under 10% of total execution time in over 90% of our experiments.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Phase segregation dynamics in mixed-halide perovskites revealed by plunge-freeze cryo-electron microscopy

Mixed-halide lead perovskites, with photoexcited charge-carrier properties suitable for high-efficiency photovoltaics, hold significant promise for high-efficiency tandem solar cells. However, phase segregation under illumination, where an iodide-rich phase forms carrier trap states, remains a barrier to application. This study employs plunge-freeze cryoelectron microscopy to visualize nanoscale phase segregation dynamics in CsPb(Br x I 1–x ) 3 films. By rapidly freezing the illuminated samples, we preserve transient photoexcited ion distributions for high-resolution structural and compositional analysis at the nanoscale. Cryogenic scanning transmission electron microscopy (STEM) techniques (electron energy loss spectroscopy [EELS] and 4D-STEM) captured the dynamics of photo-induced iodine migration from grain boundaries to centers, identified the buildup of anisotropic strain, and captured the heterogeneous evolution of this process within a single grain. These findings provide insight into microscopic phase segregation mechanisms and their dynamics, enhancing our understanding of mixed-halide perovskite photostability.

42 ENGINEERING↗

DOE OSTI2022

Classification of computed thermal tomography images with deep learning convolutional neural network

Thermal tomography (TT) is a computational method for the reconstruction of depth profile of the internal material defects from Pulsed Infrared Thermography (PIT) nondestructive evaluation. Here, the PIT method consists of recording material surface temperature transients with a fast frame infrared camera, following thermal pulse deposition on the material surface with a flashlamp and heat diffusion into material bulk. TT algorithm obtains depth reconstructions of thermal effusivity, which has been shown to provide visualization of the subsurface internal defects in metals. In many applications, one needs to determine the defect shape and orientation from reconstructed effusivity images. Interpretation of TT images is non-trivial because of blurring, which increases with depth due to the heat diffusion-based nature of image formation. We have developed a deep learning convolutional neural network (CNN) to classify the size and orientation of subsurface material defects in TT images. CNN was trained with TT images produced with computer simulations of 2D metallic structures (thin plates) containing elliptical subsurface voids. The performance of CNN was investigated using test TT images developed with computer simulations of plates containing elliptical defects, and defects with shapes imported from scanning electron microscopy images. CNN demonstrated the ability to classify radii and angular orientation of elliptical defects in previously unseen test TT images. We have also demonstrated that CNN trained on the TT images of elliptical defects is capable of classifying the shape and orientation of irregular defects.

42 ENGINEERING↗

DOE OSTI2020

Tetrahedral Trees: A Family of Hierarchical Spatial Indexes for Tetrahedral Meshes

In this work, we address the problem of performing efficient spatial and topological queries on large tetrahedral meshes with arbitrary topology and complex boundaries. Such meshes arise in several application domains, such as 3D Geographic Information Systems (GISs), scientific visualization, and finite element analysis. To this aim, we propose Tetrahedral trees, a family of spatial indexes based on a nested space subdivision (an octree or a kD-tree) and defined by several different subdivision criteria. We provide efficient algorithms for spatial and topological queries on Tetrahedral trees and compare to state-of-the-art approaches. Our results indicate that Tetrahedral trees are an improvement over R*-trees for querying tetrahedral meshes; they are more compact, faster in many queries, and stable at variations of construction thresholds. They also support spatial queries on more general domains than topological data structures, which explicitly encode adjacency information for efficient navigation but have difficulties with domains with a non-trivial geometric or topological shape.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Scribe Network API v.1.0.0

SAND2023-07864O Scribe Network API is an add-on tool for Scribe3D software. Scribe Network API documents tabletop exercises in trainings and plays back simulated videos of the scenarios and responses. Users can apply the software to compiled projects, or to a simple visual studio project solution package. The software runs a web application that relays information between computers using Scribe3D through a web application, or web app. The web app involves a representational state transfer (REST) application programming interface that handles sending and receiving Scribe save files and an SQL server that stores the save files. This follow-on package allows users to facilitate a networked tabletop exercise. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Noel, Todd↗

DOE OSTI2026

mvBayes

SAND2026-16980O mvBayes implements multivariate Bayesian regression using MATLAB and decomposes a multivariate or functional response into components based on a user-specified orthogonal basis. This allows for independent modeling of each component with any chosen univariate Bayesian regression model. This tool includes methods for prediction and visualization, facilitating the evaluation of Bayesian surrogate models through the application of Bayesian theory and Markov Chain Monte Carlo (MCMC) sampling techniques. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Tucker, J. Derek [Sandia National Lab. (SNL-CA), L↗

DOE OSTI2025

Self-supervised physics-informed generative networks for phase retrieval from a single X-ray hologram

X-ray phase contrast imaging significantly improves the visualization of structures with weak or uniform absorption, broadening its applications across a wide range of scientific disciplines. Propagation-based phase contrast is particularly suitable for time- or dose-critical in vivo/in situ/operando (tomography) experiments because it requires only a single intensity measurement. However, the phase information of the wave field is lost during the measurement and must be recovered. Conventional algebraic and iterative methods often rely on specific approximations or boundary conditions that may not be met by many samples or experimental setups. In addition, they require manual tuning of reconstruction parameters by experts, making them less adaptable for complex or variable conditions. Here we present a self-learning approach for solving the inverse problem of phase retrieval in the near-field regime of Fresnel theory using a single intensity measurement (hologram). A physics-informed generative adversarial network is employed to reconstruct both the phase and absorbance of the unpropagated wave field in the sample plane from a single hologram. Unlike most state-of-the-art deep learning approaches for phase retrieval, our approach does not require paired, unpaired, or simulated training data. This significantly broadens the applicability of our approach, as acquiring or generating suitable training data remains a major challenge due to the wide variability in sample types and experimental configurations. The algorithm demonstrates robust and consistent performance across diverse imaging conditions and sample types, delivering quantitative, high-quality reconstructions for both simulated data and experimental datasets acquired at beamline P05 at PETRA III (DESY, Hamburg), operated by Helmholtz-Zentrum Hereon. Furthermore, it enables the simultaneous retrieval of both phase and absorption information.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Compiler and Runtime Approaches to Enable Large-Scale Irregular Programs. Final report, July 2013 - July 2019

While regular algorithms, characterized by operations on dense matrices and arrays, have long been the mainstay of scientific, high-performance computing, irregular algorithms, which feature unpredictable accesses to pointer-based data structures, are becoming increasingly common in high performance computing, arising in graph analysis, data mining and visualization, among other domains. Unfortunately, the defining characteristics of irregular applications, their dynamic, unpredictable, data-dependent access patterns and data layouts, make achieving high performance on large scale systems difficult. Scaling applications to peta- and exa-scale requires carefully controlling communication and data movement and placement, an inherently difficult task when access patterns and data layouts are unpredictable! Most irregular applications that attain high performance must be painstakingly hand-written and hand-tuned, with few common principles or paradigms uniting various implementations and easing future development. Despite the increasing importance of irregular applications, there is little programmer knowledge, and even less compiler ability, devoted to optimizing them. This project aims to solve these problems. By allowing programmers to write irregular applications in high level forms, with at most a few annotations highlighting key structural properties, programmers can focus on developing their algorithms and methods. The compiler and run-time system can take on the tedious task of optimizing the application for execution at large scales, and can automatically provide efficient implementations. This will provide portability and ease maintenance for existing irregular applications, but, more importantly, open up whole new domains of computational science to large-scale, high-performance simulation codes.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1976

Evaluation of advanced microelectronic fluxless solder-bump contacts for hybrid microcircuits

Technology for interconnecting monolithic integrated circuit chips with other components is investigated. The advantages and disadvantages of the current flip-chip approach as compared to other interconnection methods are outlined. A fluxless solder-bump contact technology is evaluated. Multiple solder-bump contacts were formed on silicon integrated circuit chips. The solder-bumps, comprised of a rigid nickel under layer and a compliant solder overlayer, were electroformed onto gold device pads with the aid of thick dry film photomasks. Different solder alloys and the use of conductive epoxy for bonding were explored. Fluxless solder-bump bond quality and reliability were evaluated by measuring the effects of centrifuge, thermal cycling, and high temperature storage on bond visual characteristics, bond electrical continuity, and bond shear tests. The applicability and suitability of this technology for hybrid microelectronic packaging is discussed.

Mandal, R. P.↗

NASA NTRS1986

Magnetic field directional discontinuities - Characteristics between 0.46 and 1.0 AU

Based on Mariner 10 data, a statistical survey and an application of the Sonnerup-Cahill variance procedure to a visual identification with 1.2-s averages for time intervals corresponding to the equally spaced heliocentric distances of 1.0, 0.72 and 0.46 AU, are employed to study the characteristics of directional discontinuities (DDs) in the interplanetary magnetic field. Analysis using two methods demonstrated that the ratio of tangential discontinuities (TDs) to rotational discontinuities (RDs) decreased with decreasing radial distance. Decreases in average discontinuity thickness of 41 percent between 1.0 and 0.72 AU, and 56 percent between 1.0 and 0.46 AU, were found for both TDs and RDs, in agreement with Pioneer 10 data between 1 and 5 AU. Normalization of the individual DD thicknesses with respect to the estimated local proton gyroradius (R sub L) gave a nearly constant average thickness at the three locations, 36 + or - 5 R sub L, for both RDs and TDs.

Lepping, R. P.↗

NASA NTRS1986

Millimeter-wave imaging sensor

A scanning 3-mm radiometer system has been built and used on a helicopter to produce moderate-resolution (0.5 deg) images of the ground. This millimeter-wave sensor can be used for a variety of remote-sensing applications and produces images through clouds, smoke, and dust when visual and IR sensors are not usable. The system is described and imaging results are presented.

Wilson, W. J.↗

NASA NTRS1988

Personnel occupied woven envelope robot

The Personnel Occupied Woven Envelope Robot (POWER) provides an alternative to extravehicular activity (EVA) of space suited astronauts and/or use of long slender manipulator arms such as are used in the Shuttle Remote Manipulator System. POWER provides the capability for a shirt sleeved astronaut to perform such work by entering a control pod through air locks at both ends of an inflated flexible bellows (access tunnel). The exoskeleton of the tunnel is a series of six degrees of freedom (Six-DOF) articulated links compressible to 1/6 of their fully extended length. The operator can maneuver the control pod to almost any location within about 50 m of the base attachment to the space station. POWER can be envisioned as a series of hollow Six-DOF manipulator segments or arms wherein each arm grasps the shoulder of the next arm. Inside the hollow arms ia a bellow-type access tunnel. The control pod is the fist of the series of linked hollow arms. The fingers of the fist are conventional manipulator arms under direct visual control of the nearby operator in the pod. The applications and progress to date of the POWER system is given.

Wessling, Francis↗

NASA NTRS1988

Naked-eye acquisition of visible near-earth satellites

This paper develops visual sighting criteria for observing artificial near-earth satellites with the naked eye, and summarizes the mathematics needed to predict visibility efficiently from a set of mean orbital elements. It reports on a successful application of the sighting criteria and visibility-prediction mathematics, and shows that successful visual acquisition depends as much upon the observer's skill in recognizing the constellations as it does upon accurate visibility predictions.

Mansfield, Roger L.↗

NASA NTRS1991

MacPASCO - A Macintosh-based, interactive graphic preprocessor for structural analysis and sizing

MacPASCO, an interactive, graphic preprocessor for panel design is described. MacPASCO creates input for PASCO, an existing computer code for structural analysis and optimization of longitudinal stiffened composite panels. By using a graphical user interface, MacPASCO simplifies the specification of panel geometry and reduces user input errors, thus making the modeling and analysis of panel designs more efficient. The user draws the initial structural geometry on the computer screen, then uses a combination of graphic and text inputs to: refine the structural geometry, specify information required for analysis such as panel load conditions, and define design variables and constraints for minimum-mass optimization. Composite panel design is an ideal application because the graphical user interface can: serve as a visual aid, eliminate the tedious aspects of text-based input, and eliminate many sources of input errors.

Lucas, S. H.↗

NASA NTRS1991

Flow visualization

Flow visualization techniques are reviewed, with particular attention given to those applicable to liquid helium flows. Three techniques capable of obtaining qualitative and quantitative measurements of complex 3D flow fields are discussed including focusing schlieren, particle image volocimetry, and holocinematography (HCV). It is concluded that the HCV appears to be uniquely capable of obtaining full time-varying, 3D velocity field data, but is limited to the low speeds typical of liquid helium facilities.

Weinstein, Leonard M.↗