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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Program Overview Laboratory Directed Research and Development FY2020 (Annual Report)

Throughout this year’s report, we highlight how the LDRD program invests in ideas that make the world a safer place. We review key accomplishments and performance indicators, and we share snapshots of some of our talented staff. I also encourage you to visit our LDRD website and learn more about the 244 projects that we supported during fiscal year 2020. Looking to the future, I am confident that LDRD investments will continue to help LLNL remain at the forefront of innovative research.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Towards Three-Dimensional Neutron Imaging with Light-field Technology

A broad range of applications in nuclear safeguards and security can benefit from compact, fast neutron imagers with large angular acceptance. However, accurate 3D multi-vertex reconstruction in a monolithic detector remains a significant barrier to realization. Current approaches, such as the centroiding approach and the use of shadow masks, have not yet resulted in a successful demonstration in a light-starved environment. This project explored the use of cutting-edge technology—a light field camera—which inherently preserves both the spatial and directional information of incident light. Such technology can, in principle, resolve multi-vertex events and offer accurate position reconstruction in 3D with relatively simple readout electronics. Since the project's inception in May 2023, we have built an experimental setup to calibrate and characterize a commercial light-field camera (Lytro Illum). We assessed its 3D event reconstruction capability in a relatively low-light intensity environment by analyzing the cross-correlation of a series of 2D images of a characterized tunable light source taken at various distances. A sub-cm resolution, lower than typical neutron interaction separations in a compact scintillator volume, was observed with the LED light source, suggesting the promising capability of its nominal optics design to provide the adequate resolution required for a compact monolithic neutron directional detector. However, using a light-field-based readout for a neutron camera requires incorporating an ultra-low-noise light sensor, which is beyond the scope of this project. We also initiated the development of a 3D light-field-based reconstruction algorithm tailored to sparse scenes, as expected from particle interactions in a scintillator medium. Additionally, we demonstrated the capability of the algorithm to replicate the ground truth. Finally, we began the development of a neutron directional detector simulation to determine the performance criteria for light-field-based reconstruction that allows for good neutron directional reconstruction. This Feasibility Study has led to a successful follow-up project under the DNN R&D innovation portfolio starting May 2024.

42 ENGINEERING↗
DOE OSTI2020

On the Convergence of Physics Informed Neural Networks for Linear Second-Order Elliptic and Parabolic Type PDEs

Physics informed neural networks (PINNs) are deep learning based techniques for solving partial differential equations (PDEs) encountered in computational science and engineering. Guided by data and physical laws, PINNs find a neural network that approximates the solution to a system of PDEs. Such a neural network is obtained by minimizing a loss function in which any prior knowledge of PDEs and data are encoded. Despite its remarkable empirical success in one, two or three dimensional problems, there is little theoretical justification for PINNs. As the number of data grows, PINNs generate a sequence of minimizers which correspond to a sequence of neural networks. We want to answer the question: Does the sequence of minimizers converge to the solution to the PDE? We consider two classes of PDEs: linear second-order elliptic and parabolic. By adapting the Schauder approach and the maximum principle, we show that the sequence of minimizers strongly converges to the PDE solution in C 0 . Furthermore, we show that if each minimizer satisfies the initial/boundary conditions, the convergence mode becomes H 1 . Computational examples are provided to illustrate our theoretical findings. To the best of our knowledge, this is the first theoretical work that shows the consistency of PINNs.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1987

Tribology theory versus experiment

Tribology, the study of friction and wear of materials, has achieved a new interest because of the need for energy conservation. Fundamental understanding of this field is very complex and requires a knowledge of solid-state physics, material science, chemistry, and mechanical engineering. This paper is meant to be didactic in nature and outlines some of the considerations needed for a tribology research program. The approach is first to present a simple model, a field emission tip in contact with a flat surface, in order to elucidate important considerations, such as contact area, mechanical deformations, and interfacial bonding. Then examples from illustrative experiments are presented. Finally, the current status of physical theories concerning interfacial bonding are presented.

Ferrante, John↗
NASA NTRSDate not supplied

NASA BPS Reduced Gravity Integrated Computational Materials Engineering (ICME) Study

The Biological and Physical Sciences (BPS) Division of NASA’s Science Mission Directorate (SMD), and its predecessors, has sponsored extensive flight and ground experiments yielding benchmark datasets in many materials science research areas including thermophysical properties and solidification microstructure formation and evolution. The subject study sought to motivate and focus BPS’s engagement within the broader Integrated ICME community to understand the phenomena underlying material processing, structure, and properties in the microgravity environment of space and to support future space exploration efforts.

Louise Littles↗
DOE OSTI2023

A Novel Experimental Approach to Understand the Transport of Nanodrugs

Nanoparticle-based drugs offer attractive advantages like targeted delivery to the diseased site and size and shape-controlled properties. Therefore, understanding the particulate flow of the nanodrugs is important for effective delivery, accurate prediction of required dosage, and developing efficient drug delivery platforms for nanodrugs. In this study, the transport of nanodrugs including flow velocity and deposition is investigated using three model metal oxide nanodrugs of different sizes including iron oxide, zinc oxide, and combined Cu-Zn-Fe oxide synthesized via a modified polyol approach. The hydrodynamic size, size, morphology, chemical composition, crystal phase, and surface functional groups of the water-soluble nanodrugs were characterized via dynamic light scattering, transmission electron microscopy, scanning electron microscopy-energy dispersive X-ray, X-ray diffraction, and fourier transform infrared spectroscopy, respectively. Two different biomimetic flow channels with customized surfaces are developed via 3D printing to experimentally monitor the velocity and deposition of the different nanodrugs. A diffusion dominated mechanism of flow is seen in size ranges 92 nm to 110 nm of the nanodrugs, from the experimental velocity and mass loss profiles. The flow velocity analysis also shows that the transport of nanodrugs is controlled by sedimentation processes in the larger size ranges of 110–302 nm. However, the combined overview from experimental mass loss and velocity trends indicates presence of both diffusive and sedimentation forces in the 110–302 nm size ranges. It is also discovered that the nanodrugs with higher positive surface charges are transported faster through the two test channels, which also leads to lower deposition of these nanodrugs on the walls of the flow channels. The results from this study will be valuable in realizing reliable and cost-effective in vitro experimental approaches that can support in vivo methods to predict the flow of new nanodrugs.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Self-mixing in microtubule-kinesin active fluid from nonuniform to uniform distribution of activity

Active fluids have applications in micromixing, but little is known about the mixing kinematics of systems with spatiotemporally-varying activity. To investigate, UV-activated caged ATP is used to activate controlled regions of microtubule-kinesin active fluid and the mixing process is observed with fluorescent tracers and molecular dyes. At low Péclet numbers (diffusive transport), the active-inactive interface progresses toward the inactive area in a diffusion-like manner that is described by a simple model combining diffusion with Michaelis-Menten kinetics. At high Péclet numbers (convective transport), the active-inactive interface progresses in a superdiffusion-like manner that is qualitatively captured by an active-fluid hydrodynamic model coupled to ATP transport. Results show that active fluid mixing involves complex coupling between distribution of active stress and active transport of ATP and reduces mixing time for suspended components with decreased impact of initial component distribution. This work will inform application of active fluids to promote micromixing in microfluidic devices.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Simultaneous inference of the compressibility and inelastic response of tantalum under extreme loading

We study the deformation of tantalum under extreme loading conditions. Experimental velocity data are drawn from both ramp loading experiments on Sandia’s Z-machine and gas gun compression experiments. The drive conditions enable the study of materials under pressures greater than 100 GPa. We provide a detailed forward model of the experiments including a model of the magnetic drive for the Z-machine. Utilizing these experiments, we simultaneously infer several different types of physically motivated parameters describing equation of state, plasticity, and anelasticity via the computational device of Bayesian model calibration. Characteristics of the resulting calculated posterior distributions illustrate relationships among the parameters of interest via the degree of cross correlation. The calibrated velocity traces display good agreement with the experiments up to experimental uncertainty as well as improvement over previous calibrations. Examining the Z-shots and gun-shots together and separately reveals a trade-off between accuracy and transferability across different experimental conditions. Implications for model calibration, limitations from model form, and suggestions for improvements are discussed.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

What is in a name: Defining “high entropy” oxides

High entropy oxides are emerging as an exciting new avenue to design highly tailored functional behaviors that have no traditional counterparts. Study and application of these materials are bringing together scientists and engineers from physics, chemistry, and materials science. The diversity of each of these disciplines comes with perspectives and jargon that may be confusing to those outside of the individual fields, which can result in miscommunication of important aspects of research. In this Perspective, we provide examples of research and characterization taken from these different fields to provide a framework for classifying the differences between compositionally complex oxides, high entropy oxides, and entropy stabilized oxides, which is intended to bring a common language to this emerging area. We highlight the critical importance of understanding a material’s crystallinity, composition, and mixing length scales in determining its true definition.

36 MATERIALS SCIENCE↗
DOE OSTI2024

A Pseudoreversible Normalizing Flow for Stochastic Dynamical Systems with Various Initial Distributions

Here, we present a pseudoreversible normalizing flow method for efficiently generating samples of the state of a stochastic differential equation (SDE) with various initial distributions. The primary objective is to construct an accurate and efficient sampler that can be used as a surrogate model for computationally expensive numerical integration of SDEs, such as those employed in particle simulation. After training, the normalizing flow model can directly generate samples of the SDE’s final state without simulating trajectories. The existing normalizing flow model for SDEs depends on the initial distribution, meaning the model needs to be retrained when the initial distribution changes. The main novelty of our normalizing flow model is that it can learn the conditional distribution of the state, i.e., the distribution of the final state conditional on any initial state, such that the model only needs to be trained once and the trained model can be used to handle various initial distributions. This feature can provide a significant computational saving in studies of how the final state varies with the initial distribution. Additionally, we propose to use a pseudoreversible network architecture to define the normalizing flow model, which has sufficient expressive power and training efficiency for a variety of SDEs in science and engineering, e.g., in particle physics. We provide a rigorous convergence analysis of the pseudoreversible normalizing flow model to the target probability density function in the Kullback–Leibler divergence metric. Numerical experiments are provided to demonstrate the effectiveness of the proposed normalizing flow model.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1972

The Skylab experiment program.

Description of planned Skylab experiments in the general fields of life sciences, solar physics, earth observations, astrophysics, engineering, and technology. Each experiment is outlined in terms of its specific purpose, supporting hardware, relevant functions to be performed by an astronaut, and data recovery measures. Major support facilities described include the scientific airlock, the articulated mirror system, the extendable boom, and the film vault.

Schneider, W. C.↗
NASA NTRS1988

Applications of surface analysis and surface theory in tribology

Tribology, the study of adhesion, friction and wear of materials is a complex field which requires a knowledge of solid state physics, surface physics, chemistry, material science and mechanical engineering. It has been dominated, however, by the more practical need to make equipment work. With the advent of surface analysis and advances in surface and solid state theory, a new dimension has been added to the analysis of interactions at tribological interfaces. In this paper the applications of tribological studies and their limitations are presented. Examples from research at the NASA Lewis Research Center are given. Emphasis is on fundamental studies involving the effects of monolayer coverage and thick films on friction and wear. A summary of the current status of theoretical calculations of defect energetics is presented. In addition, some new theoretical techniques which enable simplified quantitative calculations of adhesion, fracture and friction are discussed.

Ferrante, John↗
NASA NTRS1989

Applications of surface analysis and surface theory in tribology

Tribology, the study of adhesion, friction and wear of materials, is a complex field which requires a knowledge of solid state physics, surface physics, chemistry, material science, and mechanical engineering. It has been dominated, however, by the more practical need to make equipment work. With the advent of surface analysis and advances in surface and solid-state theory, a new dimension has been added to the analysis of interactions at tribological interfaces. In this paper the applications of tribological studies and their limitations are presented. Examples from research at the NASA Lewis Research Center are given. Emphasis is on fundamental studies involving the effects of monolayer coverage and thick films on friction and wear. A summary of the current status of theoretical calculations of defect energetics is presented. In addition, some new theoretical techniques which enable simplified quantitative calculations of adhesion, fracture, and friction are discussed.

Ferrante, John↗
NASA NTRS2012

NASA Thesaurus: Hierarchical Listing with Definitions; Rotated Term Display - Volumes 1 and 2

The NASA Thesaurus contains the authorized subject terms by which the documents in the NASA STI Databases are indexed and retrieved. The scope of this controlled vocabulary includes not only aerospace engineering, but all supporting areas of engineering and physics, the natural space sciences (astronomy, astrophysics, planetary science), Earth sciences, and to some extent, the biological sciences. Volume 1 - Hierarchical Listing With Definitions contains over 18,400 subject terms, 4,300 definitions, and more than 4,500 USE cross references. The Hierarchical Listing presents full hierarchical structure for each term along with 'related term' lists, and can serve as an orthographic authority. Volume 2 - Rotated Term Display is a ready-reference tool which provides over 52,700 additional 'access points' to the thesaurus terminology. It contains the postable and nonpostable terms found in the Hierarchical Listing arranged in a KWIC (key-word-in-context) index.

Source record↗
NASA NTRS2012

NASA Thesaurus Data File

The NASA Thesaurus contains the authorized NASA subject terms used to index and retrieve materials in the NASA Aeronautics and Space Database (NA&SD) and NASA Technical Reports Server (NTRS). The scope of this controlled vocabulary includes not only aerospace engineering, but all supporting areas of engineering and physics, the natural space sciences (astronomy, astrophysics, planetary science), Earth sciences, and the biological sciences. The NASA Thesaurus Data File contains all valid terms and hierarchical relationships, USE references, and related terms in machine-readable form. The Data File is available in the following formats: RDF/SKOS, RDF/OWL, ZThes-1.0, and CSV/TXT.

Source record↗
NASA NTRS1989

CSM research: Methods and application studies

Computational mechanics is that discipline of applied science and engineering devoted to the study of physical phenomena by means of computational methods based on mathematical modeling and simulation, utilizing digital computers. The discipline combines theoretical and applied mechanics, approximation theory, numerical analysis, and computer science. Computational mechanics has had a major impact on engineering analysis and design. When applied to structural mechanics, the discipline is referred to herein as computational structural mechanics. Complex structures being considered by NASA for the 1990's include composite primary aircraft structures and the space station. These structures will be much more difficult to analyze than today's structures and necessitate a major upgrade in computerized structural analysis technology. NASA has initiated a research activity in structural analysis called Computational Structural Mechanics (CSM). The broad objective of the CSM activity is to develop advanced structural analysis technology that will exploit modern and emerging computers, such as those with vector and/or parallel processing capabilities. Here, the current research directions for the Methods and Application Studies Team of the Langley CSM activity are described.

Knight, Norman F., Jr.↗