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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 1,513 records · Page 84
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Application of a deep learning semantic segmentation model to helium bubbles and voids in nuclear materials

Imaging nanoscale radiation-induced defects using the transmission electron microscope (TEM) is a key factor in the successful implementation of materials for nuclear energy structural applications. Analyzing each defect in a TEM micrograph is currently a manual task. To identify the defects in a single image can take anywhere from 15 min to an hour and a project can require the analysis of anywhere from tens to ≥ 100 images. Here, we use artificial intelligence (AI) models to automate this task. For simplification, we evaluated images with only a single type of defect; helium bubbles. Additionally, we performed semantic segmentation of these helium bubble defects in electron microscopy images of irradiated FeCrAl alloys using a deep learning DefectSegNet model. This model, which was previously used to classify crystal defects, is inspired by the classic DenseNet and U-Net image segmentation models. It claims high spatial resolution, but has poor performance at object boundaries. Our paper improves the DefectSegNet model’s application by adding two new features. First, the DefectSegNet model is applied not only to perform calculation pixel-wise but also object (or feature) wise. Because object-wise metrics are directly relevant to our final goal of detecting bubbles, whereas pixel-wise classification is only an intermediate step, it is an important part of our study. Second, a distance map loss (DML) function has been added to increase its performance at object boundaries. It is crucial to accurately represent defects boundaries, especially bubbles, in order to track the bubble-induced swelling caused by irradiation. The boundary-focused DML function is also compared to other loss functions like Cross-entropy, Weighted Binary Cross Entropy (WBCE), Dice and Intersection over Union (IOU). Finally, by incorporating new features, we found a marked improvement on segmentation quality and better shape preservation at the boundaries and areas of the bubbles.

42 ENGINEERING↗
DOE OSTI2021

Photoelectrochemically Self Improving Si/GaN Photocathode: Figure 2d Raw Data

After 10 hrs of chronoamperometry (CA) photoconductive atomic force microscopy (PC-AFM) measurements were conducted on Si/GaN samples using a commercial AFM system (Bruker Dimension Icon). PeakForce TUNA mode was used to acquire the morphology and current simultaneously. A PtIr conductive probe with spring constant of 2.8 Nm-1 was used for the scanning. A white light source was used to illuminate the surface during the acquisition. Line scan extracting the topography and photocurrent from this 10 hour CA tested Si/GaN sample. The topography mapping is 2 × 2 µm2. No sample bias was applied and this photoconductive AFM measurement was performed under white light front illumination with an angle.

photocathode↗
DOE OSTI2023

Uncertainty quantification in scientific machine learning: Methods, metrics, and comparisons

Neural networks (NNs) are currently changing the computational paradigm on how to combine data with mathematical laws in physics and engineering in a profound way, tackling challenging inverse and ill-posed problems not solvable with traditional methods. However, quantifying errors and uncertainties in NN-based inference is more complicated than in traditional methods. This is because in addition to aleatoric uncertainty associated with noisy data, there is also uncertainty due to limited data, but also due to NN hyperparameters, overparametrization, optimization and sampling errors as well as model misspecification. Although there are some recent works on uncertainty quantification (UQ) in NNs, there is no systematic investigation of suitable methods towards quantifying the total uncertainty effectively and efficiently even for function approximation, and there is even less work on solving partial differential equations and learning operator mappings between infinite-dimensional function spaces using NNs. In this work, we present a comprehensive framework that includes uncertainty modeling, new and existing solution methods, as well as evaluation metrics and post-hoc improvement approaches. Further, to demonstrate the applicability and reliability of our framework, we present an extensive comparative study in which various methods are tested on prototype problems, including problems with mixed input-output data, and stochastic problems in high dimensions. In the Appendix, we include a comprehensive description of all the UQ methods employed. Further, to help facilitate the deployment of UQ in Scientific Machine Learning research and practice, we present and develop in [1] an open-source Python library (github.com/Crunch-UQ4MI/neuraluq), termed NeuralUQ, that is accompanied by an educational tutorial and additional computational experiments.

11 physics-informed neural networks↗
DOE OSTI2023

Carbon Coating Influence on the Formation of Percolating Electrode Networks for Silicon Anodes

Previous studies have demonstrated that chemical vapor deposition carbon coating on silicon (Si@C) can enhance the electrochemical performance of lithium-ion batteries with Si-based anodes. However, the underlying mechanisms contributing to this improvement have not been fully explored. Here, we address this knowledge gap by applying a suite of characterization methods to evaluate Si@C anodes prepared by reducing acetylene on ball-milled Si particles. Raman mapping measurements show that the C coating (<5 nm thick) enables a homogeneous Si and carbon distribution during the slurry casting process, thereby promoting Si utilization during cycling. The coating’s microstructure and morphology were evaluated using X-ray photoelectron spectroscopy (XPS), scanning transmission electron microscopy, and neutron reflectivity experiments. Electrochemical impedance spectroscopy measurements upon cycling indicate that carbon coating also reduces the overall resistance as benchmarked against bare Si anodes. Galvanostatic cycling in half-cell studies revealed higher initial Coulombic efficiency and specific capacities with increasing carbon coating time. However, solid electrolyte interphase (SEI) investigations using XPS showed that the coated and uncoated samples have very similar characteristics, suggesting that the SEI may only play a minor role in enhancing the performance of Si@C. Full-cell evaluation of the Si electrodes was consistent with half-cell results relating to performance and SEI properties, further supporting the conclusion that electronic and ionic percolation, enabled by effective electrode manufacturing, are the dominant factors contributing to the favorable performance of Si@C.

25 ENERGY STORAGE↗
DOE OSTI2026

A unifying equation for fermentation sustainability across the titer-rate-yield landscape

Industrial fermentation is central to the sustainable production of fuels and chemicals, yet commercial viability of emerging technologies hinges on improving fermentation titer, rate, and yield (TRY). How these metrics shape system cost remains difficult to generalize due to complex interactions among feedstocks, fermentation, separations, catalytic upgrading, waste management, and facility design. Here, we systematically map theoretical fermentation performance spaces (formed by all potential TRY combinations) for 32 representative biomanufacturing facilities—spanning distinct choices for feedstocks, fermentation regimes and products, separations, and catalytic upgrading—by simulating and evaluating them (via techno-economic analysis, TEA) under uncertainty (600,000 Monte Carlo simulations) and across TRY combinations (7500 TRY combinations for each of 32 configurations). Across this wide design and thermodynamic simulation space, we find the relationship between fermentation TRY and system cost is captured by a simple, generalizable mathematical equation (R 2 of 0.992 − 1.000 across our simulations; 0.954 − 1.000 when validated against prior studies that used different tools). We use this equation to elucidate key drivers that shape cost sensitivity to fermentation performance, generating widely applicable insights. By demonstrating a unifying relationship governs the impact of fermentation on biomanufacturing economics, this work establishes a foundation for agile, holistically predictive, resource-efficient strategies to prioritize fermentation research and development needs and accelerate commercialization of emerging biomanufacturing technologies.

applied mathematics↗
DOE OSTI2023

Evaluating E. coli genome‐scale metabolic model accuracy with high‐throughput mutant fitness data

Abstract The Escherichia coli genome‐scale metabolic model (GEM) is an exemplar systems biology model for the simulation of cellular metabolism. Experimental validation of model predictions is essential to pinpoint uncertainty and ensure continued development of accurate models. Here, we quantified the accuracy of four subsequent E. coli GEMs using published mutant fitness data across thousands of genes and 25 different carbon sources. This evaluation demonstrated the utility of the area under a precision–recall curve relative to alternative accuracy metrics. An analysis of errors in the latest (iML1515) model identified several vitamins/cofactors that are likely available to mutants despite being absent from the experimental growth medium and highlighted isoenzyme gene‐protein‐reaction mapping as a key source of inaccurate predictions. A machine learning approach further identified metabolic fluxes through hydrogen ion exchange and specific central metabolism branch points as important determinants of model accuracy. This work outlines improved practices for the assessment of GEM accuracy with high‐throughput mutant fitness data and highlights promising areas for future model refinement in E. coli and beyond.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Misr: Miniature Ignition Screening Rapid Compression Machine for Kinetic Measurements of Novel Fuels (Final Report)

High throughput ignition screening would be useful for evaluating fuels before scaled production. One method for doing this involves generating a map of ignition delay times over different conditions for each fuel blend. Constant condition ignition delay time maps can be used to estimate ignition for engines in prescribed thermodynamic trajectories. A Miniaturized Ignition Screening Rapid Compression Machine (MISR) has been developed and built at the University of Illinois Chicago (UIC) intending to generate those constant condition ignition delay time maps for low temperature chemistry relevant conditions. Some design features include a bellows-actuated driver section, which is lighter compared to other RCM designs, an adjustable brake section, and full optical access. The setup was designed to achieve reaction conditions (T > 600K and P < 100 bar with repetition rates of about 8 seconds per experiment). These conditions were meant to be relevant to low-to-intermediate temperature auto-ignition and for generation of data for developing relevant chemical kinetics models or ignition maps. Because of the compression characteristics and the heat loss characteristics of the MISR, the apparatus currently tests higher temperatures over shorter test times than what would be desirable, however there are some pathways to improved compression characteristics as detailed in this report. A detailed description of the MISR design and its operating mechanism is discussed. The team faced several challenges and setbacks in the construction and commissioning of the MISR, and those are highlighted, along with the modifications that were performed to get the MISR operational. To demonstrate the performance characteristics of the MISR, limited ignition delay experiments were conducted for ethanol fuel at different equivalence ratios (Φ), and those results were usable, but again test a higher temperature and shorter ignition delay time than initially intended.

02 PETROLEUM↗
DOE OSTI2024

Practical applications of machine-learned flows on gauge fields

Normalizing flows are machine-learned maps between different lattice theories which can be used as components in exact sampling and inference schemes. Ongoing work yields increasingly expressive flows on gauge fields, but it remains an open question how flows can improve lattice QCD at state-of-the-art scales. We discuss and demonstrate two applications of flows in replica exchange (parallel tempering) sampling, aimed at improving topological mixing, which are viable with iterative improvements upon presently available flows.

Abbott, Ryan↗
NASA NTRS1975

Study to develop improved spacecraft snow survey methods using Skylab/EREP data

The author has identified the following significant results. Of the four black and white S190A camera stations, snowcover is best defined in the two visible spectral bands, due in part to their better resolution. The overall extent of the snow can be mapped more precisely, and the snow within shadow areas is better defined in the visible bands. Of the two S190A color products, the aerial color photography is the better. Because of the contrast in color between snow and snow-free terrain and the better resolution, this product is concluded to be the best overall of the six camera stations for detecting and mapping snow. Overlapping frames permit stereo viewing, which aids in distinguishing clouds from the underlying snow. Because of the greater spatial resolution of the S190B earth terrain camera, areal snow extent can be mapped in greater detail than from the S190A photographs. The snow line elevation measured from the S190A and S190B photographs is reasonable compared to the meager ground truth data available.

Barnes, J. C.↗
NASA NTRS1978

Future directions in experimental gamma ray astronomy

Better vehicles and instruments are needed if gamma ray spectroscopy in astrophysics and cosmology is to advance. A gamma ray observatory will (1) permit long-term observations of selected sources to measure their variability and to achieve high sensitivity; (2) measure periods in days or weeks; and (3) assess the entire sky to observe various predicted sources, to measure the energy spectrum, and to map the isotropy of the cosmic ray background over larger collecting areas (of the order of a square meter). Conventional and unconventional instruments must cover the energy range from 0.1 MeV to 20 MeV with improved sensitivity. Angular resolution must be improved one degree or more to study discrete X-ray sources in the galactic center. Actively collimated detectors, improved double Compton instruments, and gamma ray correlators to actively synthesize the absolute energy spectrum of the sky protons are discussed as well as the need for scientific balloons.

Haymes, R. C.↗
NASA NTRS1981

Technology development of the Space Transportation System mission and terrestrial applications of satellite technology

The Space Transportation System (STS) is discussed, including the launch processing system, the thermal protection subsystem, meteorological research, sound supression water system, rotating service structure, improved hypergol or removal systems, fiber optics research, precision positioning, remote controlled solid rocket booster nozzle plugs, ground operations for Centaur orbital transfer vehicle, parachute drying, STS hazardous waste disposal and recycle, toxic waste technology and control concepts, fast analytical densitometry study, shuttle inventory management system, operational intercommunications system improvement, and protective garment ensemble. Terrestrial applications are also covered, including LANDSAT applications to water resources, satellite freeze forecast system, application of ground penetrating radar to soil survey, turtle tracking, evaluating computer drawn ground cover maps, sparkless load pulsar, and coupling a microcomputer and computing integrator with a gas chromatograph.

Source record↗
NASA NTRS1984

Improved design of subcritical and supercritical cascades using complex characteristics and boundary-layer correction

The method of complex characteristics and hodograph transformation for the design of shockless airfoils was extended to design supercritical cascades with high solidities and large inlet angles. This capability was achieved by introducing a conformal mapping of the hodograph domain onto an ellipse and expanding the solution in terms of Tchebycheff polynomials. A computer code was developed based on this idea. A number of airfoils designed with the code are presented. Various supercritical and subcritical compressor, turbine and propeller sections are shown. The lag-entrainment method for the calculation of a turbulent boundary layer was incorporated to the inviscid design code. The results of this calculation are shown for the airfoils described. The elliptic conformal transformation developed to map the hodograph domain onto an ellipse can be used to generate a conformal grid in the physical domain of a cascade of airfoils with open trailing edges with a single transformation. A grid generated with this transformation is shown for the Korn airfoil. Previously announced in STAR as N83-24474

Sanz, J. M.↗
NASA NTRS1992

Transverse Mercator Projection Via Elliptic Integrals

Improved method of construction of U.S. Army's universal transverse Mercator grid system based on Gauss-Kruger transverse Mercator projection and on use of elliptic integrals of second kind. Method can be used to map entire northern or southern hemisphere with respect to single principal meridian.

Wallis, David E.↗
NASA NTRS1993

Optimization Of A Computational Grid

In improved method of generation of computational grid, grid-generation process decoupled from definition of geometry. Not necessary to redefine boundary. Instead, continuous boundaries in physical domain specified, and then grid points in computational domain mapped onto continuous boundaries.

Pearce, Daniel G.↗
NASA NTRS1994

Precise GPS orbits for geodesy

The Global Positioning System (GPS) has become, in recent years, the main space-based system for surveying and navigation in many military, commercial, cadastral, mapping, and scientific applications. Better receivers, interferometric techniques (DGPS), and advances in post-processing methods have made possible to position fixed or moving receivers with sub-decimeter accuracies in a global reference frame. Improved methods for obtaining the orbits of the GPS satellites have played a major role in these achievements; this paper gives a personal view of the main developments in GPS orbit determination.

Colombo, Oscar L.↗
NASA NTRS1998

Incorporating Manual and Autonomous Code Generation

Code can be generated manually or using code-generated software tools, but how do you interpret the two? This article looks at a design methodology that combines object-oriented design with autonomic code generation for attitude control flight software. Recent improvements in space flight computers are allowing software engineers to spend more time engineering the applications software. The application developed was the attitude control flight software for an astronomical satellite called the Microwave Anisotropy Probe (MAP). The MAP flight system is being designed, developed, and integrated at NASA's Goddard Space Flight Center. The MAP controls engineers are using Integrated Systems Inc.'s MATRIXx for their controls analysis. In addition to providing a graphical analysis for an environment, MATRIXx includes an autonomic code generation facility called AutoCode. This article examines the forces that shaped the final design and describes three highlights of the design process: (1) Defining the manual to autonomic code interface; (2) Applying object-oriented design to the manual flight code; (3) Implementing the object-oriented design in C.

McComas, David↗
NASA NTRS1997

Analysis of Vegetation and Atmospheric Correction Indices for Landsat Images

Vegetation and Atmospheric Indices are mathematical combinations of remote sensing bands which are useful in distinguishing the various values of the spectral reflectance. In this paper we study how the applications of various atmospherically corrected indices and vegetation indices can aide in retrieving the amount of surface reflectance from a remotely sensed image. Specifically, this paper studies and compares three vegetation indices and one atmospherically resistant index. These indices include the Normalized Difference Vegetation Index (NDVI), the Soil Adjusted Vegetation Index (SAVI), the Green Vegetation Index (GVI), and the Atmospherically Resistant Vegetation Index (ARVI), respectively. The algorithms attempt to estimate the optical characteristics of Thematic Mapper (TM) imagery. It will be shown that the NDVI algorithm followed by the ARVI correcting algorithm provided significant improvements in the tonal qualities of the retrieved images. The results are presented on 1987 TM images over the Kennedy Space Center (KSC) and are compared with a set of United States Geological Survey (U.S.G.S) maps.

Bush, Tasha R.↗
NASA NTRS2004

High-Resolution Displacement Sensor Using a SQUID Array Amplifier

Improvement in the measurement of displacement has profound implications for both exploration technologies and fundamental physics. For planetary exploration, the new SQUID-based capacitive displacement sensor will enable a more sensitive gravity gradiometer for mapping the interior of planets and moons. A new concept of a superfluid clock to be reported by Penanen and Chui at this workshop is also based on a high-resolution displacement sensor. Examples of high-impact physics projects that can benefit from a better displacement sensor are: detection of gravitational waves, test of the equivalence principle, search for the postulated "axion" particle, and test of the inverse square law of gravity. We describe the concept of a new displacement sensor that makes use of a recent development in the Superconducting Quantum Interference Device (SQUID) technology. The SQUID array amplifier, invented by Welty and Martinis (IEEE Trans. Appl. Superconductivity 3, 2605, 1993), has about the same noise as a conventional SQUID; however, it can work at a much higher frequency of up to 5 MHz. We explain how the higher bandwidth can be translated into higher resolution using a bridge-balancing scheme that can simultaneously balance out both the carrier signal at the bridge output and the electrostatic force acting on the test mass.

Chui, Talso↗