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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 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
NASA NTRS2008

Eurasian Reindeer Pastoralism in a Changing Climate: Indigenous Knowledge and NASA Remote Sensing

It is intended that Reindeer Mapper/EALAT will be able to provide reindeer herders with an efficient tool for managing the real-time movements and migrations of their herds through enabling improved efficiency in linking different members of the herder settlements or communities and providing real-time local, satellite or other data (e.g., ice melt in lakes and rivers, weather events), thus enabling real time adjustments to herd movements to avoid problems such as changing weather/climate conditions, freeze-thaw "lock-out" problems, or take advantage of availability of better pasturelands along migration routes. The system is being designed to incorporate local data to allow users to bring their own data into the system for analysis in addition to the data provided by the system itself. With the local information of the population, up to date environmental data and habitat characteristics, the system could generate maps depicting important features of interest for reindeer managers. One of the products derived from the planned Reindeer Mapper system will be a web-based graphic display that allows analysts to quickly pinpoint areas of interest such as those with large concentrations of reindeer and provide surrounding environmental information. The system could be automatically updated with near-real-time information such as hourly precipitation and snowfall rate and accumulation, daily surface and air temperatures, and vegetation cover conditions. The system could bring attention to the proximity of human and animal populations as part of the need for control response. A local GIS will bring these many layers together with several supporting models, showing only a straightforward graphic of the real-time situation in the field. Because the system proposed will be operating in the Internet environment, it should be virtually accessible from any network computers and wireless remote access from the field. The International Center for Reindeer Husbandry in Kautokeino, Norway, is providing regional and international coordination of and access to data sets and expertise, and will act as overall clearinghouse for EALAT information.

Maynard, N. G.↗
DOE OSTI2023

Direct prediction of inelastic neutron scattering spectra from the crystal structure*

Abstract Inelastic neutron scattering (INS) is a powerful technique to study vibrational dynamics of materials with several unique advantages. However, analysis and interpretation of INS spectra often require advanced modeling that needs specialized computing resources and relevant expertise. This difficulty is compounded by the limited experimental resources available to perform INS measurements. In this work, we develop a machine-learning based predictive framework which is capable of directly predicting both one-dimensional INS spectra and two-dimensional INS spectra with additional momentum resolution. By integrating symmetry-aware neural networks with autoencoders, and using a large scale synthetic INS database, high-dimensional spectral data are compressed into a latent-space representation, and a high-quality spectra prediction is achieved by using only atomic coordinates as input. Our work offers an efficient approach to predict complex multi-dimensional neutron spectra directly from simple input; it allows for improved efficiency in using the limited INS measurement resources, and sheds light on building structure-property relationships in a variety of on-the-fly experimental data analysis scenarios.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

A Comparison of Novel Woodstove Catalytic Combustors to Improve Low Temperature Light off and Catalyst Stability at High Temperatures and Corrosive Environments, Including Stability of Catalytic Combustors used in Coastal Environments

Wood heaters with catalytic combustors often emit higher levels of particulate matter (PM) and volatile organic compounds (VOCs) at startup before the catalytic combustor is at operational temperature. This project aims to advance wood heater catalytic combustor technology by studying degradation mechanisms in failed field catalysts and using those insights to develop an improved catalytic combustor. Findings will provide critical insights into the degradation mechanisms of wood heater catalytic combustors and inform the design of catalysts that deliver improved efficiency, durability, and performance compared to current commercial products. The outcomes of this project will not only improve catalytic combustor technology but also contribute to operational guidelines to extend catalyst lifetimes.

99 GENERAL AND MISCELLANEOUS↗
NASA NTRS1979

Thin cells for space

Research and pilot line production efforts directed towards the fabrication of high efficiency ultrathin silicon solar cells (50 micrometers) are reported. Conventional ultrathin cells with air-mass-zero (AM0) efficiencies exceeding 14% and coplanar back contact cells with AM0 efficiencies up to 11.7% were developed. The primary mechanisms limiting efficiency were determined in both types of cells, and they are discussed within the context of further improving efficiency. Results of pilot line production of conventional ultrathin cells are also presented. Average AM0 efficiencies of 12% were readily achieved for 2000 cell production runs.

Storti, G.↗
NASA NTRS1990

Statistical analysis of static shape control in space structures

The article addresses the problem of efficient analysis of the statistics of initial and corrected shape distortions in space structures. Two approaches for improving efficiency are considered. One is an adjoint technique for calculating distortion shapes: the second is a modal expansion of distortion shapes in terms of pseudo-vibration modes. The two techniques are applied to the problem of optimizing actuator locations on a 55 m radiometer antenna. The adjoint analysis technique is used with a discrete-variable optimization method. The modal approximation technique is coupled with a standard conjugate-gradient continuous optimization method. The agreement between the two sets of results is good, validating both the approximate analysis and optimality of the results.

Burdisso, Ricardo A.↗
NASA NTRS1990

Continuation of research into software for space operations support: Conversion of the display manager to X Windows/Motif, volume 2

NASA is currently using a set of applications called the Display Builder and Display Manager. They run on Concurrent systems and heavily depend on the Graphic Kernel System (GKS). At this time however, these two applications would more appropriately be developed in X Windows, in which a low X is used for all actual text and graphics display and a standard widget set (such as Motif) is used for the user interface. Use of the X Windows will increase performance, improve the user interface, enhance portability, and improve reliability. Prototype of X Window/Motif based Display Manager provides the following advantages over a GKS based application: improved performance by using a low level X Windows, display of graphic and text will be more efficient; improved user interface by using Motif; Improved portability by operating on both Concurrent and Sun workstations; and Improved reliability.

Collier, Mark D.↗
NASA NTRS2003

Evaluation of Genetic Algorithm Concepts Using Model Problems: Multi-Objective Optimization - Part 2

A genetic algorithm approach suitable for solving multi-objective optimization problems is described and evaluated using a series of simple model problems. Several new features including a binning selection algorithm and a gene-space transformation procedure are included. The genetic algorithm is suitable for finding pareto optimal solutions in search spaces that are defined by any number of genes and that contain any number of local extrema. Results indicate that the genetic algorithm optimization approach is flexible in application and extremely reliable, providing optimal results for all optimization problems attempted. The binning algorithm generally provides pareto front quality enhancements and moderate convergence efficiency improvements for most of the model problems. The gene-space transformation procedure provides a large convergence efficiency enhancement for problems with non-convoluted pareto fronts and a degradation in efficiency for problems with convoluted pareto fronts. The most difficult problems --multi-mode search spaces with a large number of genes and convoluted pareto fronts-- require a large number of function evaluations for GA convergence, but always converge.

Holst, Terry L.↗
NASA NTRS2006

Managing the On-Board Data Storage, Acknowledgement and Retransmission System for Spitzer

The Spitzer Space Telescope has a two-phase downlink system. Recorded data are transmitted during one telecom session. Then commands are sent during the next session to delete those data that were received on the ground and to retransmit those data that were missed. We must build science sequences that are as efficient as possible to make the best use of our supply of liquid helium. One way to improve efficiency is to use only the minimum time needed during telecom sessions to transmit the predicted volume of data. But, we must also not fill the on-board storage and must allow enough time margin to retransmit missed data. We describe tools and procedures that allow us to build science sequences that are single-fault tolerant in this regard and that allow us to recover quickly and safely from anomalies that affect the receipt or acknowledgment (i.e. deletion) of data.

on-board storage↗
NASA NTRS2008

Photocatalytic Coatings for Exploration and Spaceport Design

This project developed self-cleaning photocatalytic coatings that remove contamination without human intervention. The coatings chemically remove organic contaminants and leave no residue. The photocatalyst will not negatively affect other coating properties, especially corrosion resistance. Titanium dioxide, TiO2, is an extremely popular photocatalyst because of its chemical stability, nontoxicity, and low cost. TiO2 is commonly used in the photocatalytic oxidation of organic matter or pollutants in the gas and liquid phases. However, TiO2 does have some drawbacks. It has limited light absorption because of its large band-gap and suffers from a photonic efficiency of less than 10 percent for organic degradation. Dopants can lower the band-gap and improve efficiency. Since the photocatalytically active form of TiO2 is a nanocrystalline powder, it can be difficult to make a robust coating with enough catalyst loading to be effective. Photocatalysts become active when certain light energy is absorbed. When photons with an energy greater than the band-gap, Eg, (wavelengths shorter than 400 nm) impinge upon the surface of the TiO2, an electron-hole pair is formed. The electron-hole pair oxidizes adsorbed substances either directly or via reactive intermediates that form on the surface, such as hydroxyl radicals (OH) or superoxide ions (O2-). Several factors can influence the band-gap energy of TiO2, two of which are crystal structure and impurities. TiO2 exists as three crystal structures brookite, anatase, and rutile that can be controlled via heat treatment. Anatase is the most photocatalytically active crystal form of TiO2. Doping TiO2 with impurities can alter its band-gap energy, as well as its effectiveness as a catalyst. Depending on their size, dopant atoms can occupy either the substitutional or interstitial lattice positions. Atoms that are relatively large will assume the interstitial positions and create a much greater energy disturbance in the crystal than will smaller atoms that take on the substitutional positions. This energy disturbance narrows the band-gap and thus allows photons with longer wavelengths and smaller energies (such as those in the visible-light spectrum) to create electron-hole pairs. Raman spectroscopy was performed for the purpose of determining the crystal structure and the degree of crystallinity of the TiO2 particles. Reflectance measurements indicated the wavelengths of light absorbed by the different catalysts.

Source record↗
DOE OSTI2021

De-noising drift chambers in CLAS12 using convolutional auto encoders

Modern Nuclear Physics experimental setups run experiments with higher beam intensity resulting in increased noise in detector components used for particle track reconstruction. Increased uncorrelated signals (noise) result in decreased particle reconstruction efficiency. In this paper, we investigate the usage of Machine Learning, specifically Convolutional Neural Network Auto-Encoders (CAE), for de-noising raw hits from drift chambers in the CLAS12 detector. To the best of our knowledge, this is the first time CAE is employed to perform such an operation in this field. During the de-noising phase, it is important to remove as much noise as possible while retaining the valid hits to avoid losing crucial information about the experiment. Here, we show that using CAE, it is possible to remove noise hits while retaining up to 94% of valid tracks for a beam current of 110nA while for lower beam currents (45-55nA), we get up to 98% efficiency. Studies on experimental conditions with increasing noise show that CAE performs better than conventional tracking algorithms in isolating hits belonging to tracks. Specifically, the de-noising algorithm results in tracking efficiency improvements greater than 15%, in real data production procedures with nominal conditions, and up to two times better efficiency in synthetically generated data with high luminosity conditions (90-110nA), indicating that machine learning can lead to significantly shorter times for conducting physics experiments.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Comparative study of machine learning techniques for post-combustion carbon capture systems

Computational analysis of countercurrent flows in packed absorption columns, often used in solvent-based post-combustion carbon capture systems (CCSs), is challenging. Typically, computational fluid dynamics (CFD) approaches are used to simulate the interactions between a solvent, gas, and column's packing geometry while accounting for the thermodynamics, kinetics, heat, and mass transfer effects of the absorption process. These simulations can then be used explain a column's hydrodynamic characteristics and evaluate its CO 2 -capture efficiency. However, these approaches are computationally expensive, making it difficult to evaluate numerous designs and operating conditions to improve efficiency at industrial scales. In this work, we comprehensively explore the application of statistical ML methods, convolutional neural networks (CNNs), and graph neural networks (GNNs) to aid and accelerate the scale-up and design optimization of solvent-based post-combustion CCSs. We apply these methods to CFD datasets of countercurrent flows in absorption columns with structured packings characterized by several geometric parameters. We train models to use these parameters, inlet velocity conditions, and other model-specific representations of the column to estimate key determinants of CO 2 -capture efficiency without having to simulate additional CFD datasets. We also evaluate the impact of different input types on the accuracy and generalizability of each model. We discuss the strengths and limitations of each approach to further elucidate the role of CNNs, GNNs, and other machine learning approaches for CO 2 -capture property prediction and design optimization.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1980

High efficiency SPS klystron design

The most likely compact configuration to realize both high efficiency and high gain is a 5-6 cavity design focused by an electromagnet. An outline of a potential klystron configuration is given. The selected power output of 70 kW CW resulted from a maximum assumed operating voltage of 40 kV. The basic klystron efficiency cannot be expected to exceed 70-75% without collector depression. Although impressive gains were achieved in raising the basic efficiency from 50% to 70% or so with a multi-stage collector, the estimated efficiency improvement due to 5-stage collector at the 75% level is only about 8% resulting in an overall efficiency of about 83%.

Nalos, E. J.↗
NASA NTRS2006

Managing the On-Board Data Storage, Acknowledgment and Retransmission System for Spitzer

The Spitzer Space Telescope has a two-phase downlink system. Data are transmitted during one telecom session. Then commands are sent during the next session to delete those data that were received and to retransmit those data that were missed. We must build sequences that are as efficient as possible to make the best use of our finite supply of liquid helium, One way to improve efficiency is to use only the minimum time needed during telecom sessions to transmit the predicted volume of data. But, we must also not fill the onboard storage and must allow enough time margin to retransmit missed data. We describe tools and procedures that allow us to build observatory sequences that are single-fault tolerant in this regard and that allow us to recover quickly and safely from anomalies that affect the receipt or acknowledgment of data.

Spitzer↗
DOE OSTI2022

Machine learning with knowledge constraints for process optimization of open-air perovskite solar cell manufacturing

Perovskite photovoltaics (PV) have achieved rapid development in the past decade in terms of power conversion efficiency of small-area lab-scale devices; however, successful commercialization still requires further development of low-cost, scalable, and high-throughput manufacturing techniques. One of the critical challenges of developing a new fabrication technique is the high-dimensional parameter space for optimization, but machine learning (ML) can readily be used to accelerate perovskite PV scaling. Herein, we present an ML-guided framework of sequential learning for manufacturing process optimization. We apply our methodology to the Rapid Spray Plasma Processing (RSPP) technique for perovskite thin films in ambient conditions. With a limited experimental budget of screening 100 process conditions, we demonstrated an efficiency improvement to 18.5% as the best-in-our-lab device fabricated by RSPP, and we also experimentally found 10 unique process conditions to produce the top-performing devices of more than 17% efficiency, which is 5 times higher rate of success than the control experiments with pseudo-random Latin hypercube sampling. Our model is enabled by three innovations: (a) flexible knowledge transfer between experimental processes by incorporating data from prior experimental data as a probabilistic constraint; (b) incorporation of both subjective human observations and ML insights when selecting next experiments; (c) adaptive strategy of locating the region of interest using Bayesian optimization first, and then conducting local exploration for high-efficiency devices. Furthermore, in virtual benchmarking, our framework achieves faster improvements with limited experimental budgets than traditional design-of-experiments methods (e.g., one-variable-at-a-time sampling). This framework shows the capability of incorporating researchers’ domain knowledge into the ML-guided optimization loop; therefore, it has the potential to facilitate the wider adoption of ML in scaling to perovskite PV manufacturing.

14 SOLAR ENERGY↗
DOE OSTI2024

Linac_Gen: Integrating Machine Learning and Particle-in-Cell Methods for Enhanced Beam Dynamics at Fermilab

Here, we introduce Linac_Gen, a tool developed at Fermilab, which combines machine learning algorithms with Particle-in-Cell methods to advance beam dynamics in linacs. Linac_Gen employs techniques such as Random Forest, Genetic Algorithms, Support Vector Machines, and Neural Networks, achieving a tenfold increase in speed for phase-space matching in Linacs over traditional methods, through the use of genetic algorithms. Crucially, Linac_Gen's adept handling of 3D field maps elevates the precision and realism in simulating beam instabilities and resonances, marking a key advancement in the field. Benchmarked against established codes, Linac_Gen demonstrates not only improved efficiency and precision in beam dynamics studies but also in the design and optimization of Linac systems, as evidenced in its application to Fermilab's PIP-II Linac project. This work represents a notable advancement in accelerator physics, marrying ML with PIC methods to set new standards for efficiency and accuracy in accelerator design and research. Linac_Gen exemplifies a novel approach in accelerator technology, offering substantial improvements in both theoretical and practical aspects of beam dynamics.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Linac_Gen: integrating machine learning and particle-in-cell methods for enhanced beam dynamics at Fermilab

Here, we introduce Linac_Gen, a tool developed at Fermilab, which combines machine learning algorithms with Particle-in-Cell methods to advance beam dynamics in linacs. Linac_Gen employs techniques such as Random Forest, Genetic Algorithms, Support Vector Machines, and Neural Networks, achieving a tenfold increase in speed for phase-space matching in linacs over traditional methods through the use of genetic algorithms. Crucially, Linac_Gen's adept handling of 3D field maps elevates the precision and realism in simulating beam instabilities and resonances, marking a key advancement in the field. Benchmarked against established codes, Linac_Gen demonstrates not only improved efficiency and precision in beam dynamics studies but also in the design and optimization of linac systems, as evidenced in its application to Fermilab's PIP-II linac project. This work represents a notable advancement in accelerator physics, marrying ML with PIC methods to set new standards for efficiency and accuracy in accelerator design and research. Linac_Gen exemplifies a novel approach in accelerator technology, offering substantial improvements in both theoretical and practical aspects of beam dynamics.

43 PARTICLE ACCELERATORS↗
NASA NTRS1989

Recent advances in Runge-Kutta schemes for solving 3-D Navier-Stokes equations

A thin-layer Navier-Stokes has been developed for solving high Reynolds number, turbulent flows past aircraft components under transonic flow conditions. The computer code has been validated through data comparisons for flow past isolated wings, wing-body configurations, prolate spheroids and wings mounted inside wind-tunnels. The basic code employs an explicit Runge-Kutta time-stepping scheme to obtain steady state solution to the unsteady governing equations. Significant gain in the efficiency of the code has been obtained by implementing a multigrid acceleration technique to achieve steady-state solutions. The improved efficiency of the code has made it feasible to conduct grid-refinement and turbulence model studies in a reasonable amount of computer time. The non-equilibrium turbulence model of Johnson and King has been extended to three-dimensional flows and excellent agreement with pressure data has been obtained for transonic separated flow over a transport type of wing.

Vatsa, Veer N.↗
DOE OSTI2023

SAM Code Development for Source Term Modeling in Fluoride-salt-cooled High-temperature Reactors

The SAM code is under development and supported by DOE-NE’s Nuclear Energy Advanced Modeling and Simulation program as a modern system-level modeling and simulation tool for advanced non-light water reactor safety analyses. These advanced reactor concepts incorporate novel and improved approaches to achieve safety and economic feasibility. Many concepts leverage higher operating temperatures for improved efficiency with a variety of coolants and structural materials to support those needs. Such design choices may also pose unique radiological source term risks. There are continuous efforts to incorporate new physics and phenomena relevant to advanced reactor concepts, including capabilities to enable system-level source term modeling. The Pebble-Bed Fluoride-salt-cooled High-temperature Reactor (PB-FHR) is a promising candidate among advanced nuclear reactor concepts with its improved passive safety characteristics and high thermal efficiency. In addition to past efforts to support the development and utilization of SAM for PB-FHR safety analysis, the species transport modeling capabilities in SAM have been extended to simulate source term phenomena in concepts like the PB-FHR. The PB-FHR concept utilizes pebble-form TRISO fuel and FLiBe salt coolant to provide robust barriers to the release of almost all fission products and radiological source terms. However, tritium poses a unique radiological risk due to its significant production from neutron interactions with 6 Li and 9 Be in the FLiBe as well as its high mobility at elevated temperatures where it can permeate through structural metals. Secondly, the use of graphite at elevated temperatures poses the risk of oxidation damage to any structural components or fuel pebbles that are exposed to accidental air ingress. This report summarizes progress made in modeling these phenomena in SAM, which leverages the system-level multi-physics thermal hydraulic simulation to support an effective engineering-scale source term modeling capability. A tritium transport model is developed to simulate the various transport pathways in FHR and MSR concepts and is presented through verification and validation examples as well as demonstrations simulating experimental test loops and reference plant FHR models. A graphite oxidation model is also introduced to calculate local oxidation rates and is presented with initial validation results.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗