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At least 433 records · Page 24

Thermal Data-driven Model Reduction for Enhanced Battery Health Monitoring

Electric aviation faces a major challenge of avoiding potentially catastrophic consequences of the battery’s thermal runaway while keeping the weight of the battery low. Detection of early warning signals of battery failures requires accurate monitoring of the battery’s health throughout its lifespan. However, identifying the parameters of the battery from field data is notoriously difficult. We investigate this problem within the framework of modeling the temperature dynamics of a Li-ion cell during tests simulating loading in electric aircraft flights. It is found that the parameters of a higher-fidelity physics-based thermal model cannot be identified from the simulated flight data. To resolve this issue, we reduce the higher-fidelity thermal model to a model with fewer parameters. The resulting reduced-order model can predict temperature dynamics accurately and is identifiable throughout the cell’s lifespan which allows using the model’s parameters to monitor the state-of-health of the aging cell and detect anomalies in thermal behavior.

Li ion batteries↗

Toward equitable environmental exposure modeling through convergence of data, open, and citizen sciences: an example of air pollution exposure modeling amidst increasing wildfire smoke

Exposure modeling is critical in environmental epidemiology and human health but may face challenges (e.g., skewed data, unequal error, context-insensitive validation, and computational demands). Modeling decisions reflect the intended use of the models and the values that modelers prioritize. We aimed to provide a conceptual framework and machine learning (ML) modeling protocols that address these issues. With 500m-gridded hourly PM 2.5 and O 3 levels in Illinois before, during, and after the 2023 Canadian wildfire season as a motivating example, we conducted modeling experiments to evaluate modeling methods, guided by three domains we propose based on theories of science: 1) Data Diversity, leveraging open and citizen science data to enhance inclusivity, parsimony, and representativeness; 2) Equitable Accuracy, ensuring fairly distributed uncertainties across subpopulations; and 3) Sustainable Modeling, balancing accuracy with reducing computational demands to promote accessibility for under-resourced researchers. Here, we found that ML with publicly available data can achieve high accuracy. Depending on methods, performance may vary substantially, even with identical input data. Large but skewed data may reduce performance. Misuse of cross-validation protocols can underestimate prediction error; although we observed R 2 s of ∼98 %, the modeled estimates varied significantly, indicating the need for careful model validation. By using new modeling protocols including representativeness-considered training and validation data and a new loss function, we achieved high agreement between estimates and ground-based measurements (e.g., R 2 = ∼90 % for PM 2.5 ; ∼80 % for O 3 ), equally distributed errors across sociodemographic strata and urban–rural divides, and reduction in computation time—from several weeks or months to a few days.

Exposure assessment↗

Lunar Floor-Fractured Craters: Classification, Distribution and Implications for Magmatism and Shallow Crustal Structure

Floor-fractured craters (FFCs) are a class of lunar craters defined by their distinctly shallow, often plate-like floors, and combinations of radial, con-centric, and polygonal floor-fractures; a variety of other interior features are often observed, such as moats, ridges, small dark-haloed pits, and patches of mare material. They were first classified by Schultz [1] , who recognized eight overall types of floor-fractured crater. These eight subtypes have widely differing appearances, a factor that could provide insight into formation mechanisms (different manifestations of the same mechanism, or indicators of varying formation mechanisms). Two formation mechanisms for FFCs were initially proposed: 1) magmatic intrusion [1], in which magma rising toward the surface in dikes encountered low-density breccia lenses beneath crater floors and spread laterally to form sills, raising and fracturing the crater floor. 2) viscous relaxation [2], in which the properties of the crust permitted viscous flow in the vicinity of the crater, causing long-wavelength relaxation of the topography and uplift and fracturing of the crater floor. Critical to distinguishing between these two end-member hypotheses and identifying others is a quantitative assessment of the topography of FFCs and knowledge of their regional and local settings. The purpose of this study is to use newly available Lunar Reconnaissance Orbiter (LRO) Lunar Orbiter Laser Altimeter (LOLA) altimeter and Lunar Reconnaissance Orbiter Camera (LROC) image data to provide an updated global catalog of the locations, classes, morphometric and morphologic characteristics of all lunar floor-fractured craters. We use the excellent 8-class system initially described in Schultz [1] as a starting point for classification and the enhanced LOLA/LROC data sets to examine and categorize all FFCs; we found evidence for a new FFC class, discernably different from the previously existing types. Our approach, and the global categorization of all FFCs, permits the spatial distribution of each FFC-subtype to be plotted and assessed allowing for further investigation into FFC formation mechanisms. Upon completion, the data set will be made available on our web site at http://www.planetary.brown.edu/html_pages/data.htm.

Jozwiak, L. M.↗

On the brittle-ductile behavior of iron meteorites - New experimental constraints

Impact trials were performed at the NASA vertical gun range to study low-temperature brittle-ductile transitions in meteoritic, steel and iron targets. The trials were performed to enhance the data base underlying the concept of formation of planetesimals in collisional coagulation. Impact velocities of 1.6-5.5 km/sec were used, as were temperatures from 100-300 K. Spallation was observed in the tests with meteorite samples, even at room temperature, and brittleness was enhanced at temperature below 200 C. Net mass losses were induced at the higher impact velocities. It is suggested that iron meteorite agglomerations could form in the inner solar region during nebular condensation, but would not form in farther-out regions such as the asteroid belt. The protoplanets could have an iron core, with metallicity decreasing with radius from the core, which may have happened with the earth.

Matsui, T.↗

Structure of the St. Francois Mountains and surrounding lead belt, S. E. Missouri: Inferences from thermal IR and other data sets

Day-IR, day-visible, and night-IR image data sets were analyzed. All three images were contrast enhanced, using a linear stretch. The night-IR image was destriped using a box-car filtering approach. Apparent thermal inertia images were generated from the data. The enhanced data and the apparent thermal inertia image were also registered and overlayed onto shaded relief images depicting topography and onto a colored version of the Missouri geologic map. The combination of the apparent thermal inertial image and the shaded relief map proved to have the greatest discriminability in terms of portraying linear features. The reason seems to be that the vegetation canopy on the Ozark Plateau is different topography, tend to emphasize subtle topographic effects.

Arvidson, R. E.↗

Development of X-33/X-34 Aerothermodynamic Data Bases: Lessons Learned and Future Enhancements

A synoptic of programmatic and technical lessons learned in the development of aerothermodynamic data bases for the X-33 and X-34 programs is presented in general terms and from the perspective of the NASA Langley Research Center Aerothermodynamics Branch. The format used is that of the "aerothermodynamic chain," the links of which are personnel, facilities, models/test articles, instrumentation, test techniques, and computational fluid dynamics (CFD). Because the aerodynamic data bases upon which the X-33 and X-34 vehicles will fly are almost exclusively from wind tunnel testing, as opposed to CFD, the primary focus of the lessons learned is on ground-based testing. The period corresponding to the development of X-33 and X-34 aerothermodynamic data bases was challenging, since a number of other such programs (e.g., X-38, X-43) competed for resources at a time of downsizing of personnel, facilities, etc., outsourcing, and role changes as NASA Centers served as subcontractors to industry. The impact of this changing environment is embedded in the lessons learned. From a technical perspective, the relatively long times to design and fabricate metallic force and moment models, delays in delivery of models, and a lack of quality assurance to determine the fidelity of model outer mold lines (OML) prior to wind tunnel testing had a major negative impact on the programs. On the positive side, the application of phosphor thermography to obtain global, quantitative heating distributions on rapidly fabricated ceramic models revolutionized the aerothermodynamic optimization of vehicle OMLs, control surfaces, etc. Vehicle designers were provided with aeroheating information prior to, or in conjunction with, aerodynamic information early in the program, thereby allowing trades to be made with both sets of input; in the past only aerodynamic data were available as input. Programmatically, failure to include transonic aerodynamic wind tunnel tests early in the assessment phase led to delays in the optimization phase, as OMLs required modification to provide adequate transonic aerodynamic performance without sacrificing subsonic and hypersonic performance. Funding schedules for industry, based on technical milestones, also presented challenges to aerothermodynamics seeking optimum flying characteristics across the subsonic to hypersonic speed regimes and minimum aeroheating. This paper is concluded with a brief discussion of enhancements in ground-based testing/CFD capabilities necessary to partially/fully satisfy future requirements.

Miller, C. G.↗

Orbit determination of highly elliptical Earth orbiters using improved Doppler data-processing modes

A navigation error covariance analysis of four highly elliptical Earth orbits is described, with apogee heights ranging from 20,000 to 76,800 km and perigee heights ranging from 1,000 to 5,000 km. This analysis differs from earlier studies in that improved navigation data-processing modes were used to reduce the radio metric data. For this study, X-band (8.4-GHz) Doppler data were assumed to be acquired from two Deep Space Network radio antennas and reconstructed orbit errors propagated over a single day. Doppler measurements were formulated as total-count phase measurements and compared to the traditional formulation of differenced-count frequency measurements. In addition, an enhanced data-filtering strategy was used, which treated the principal ground system calibration errors affecting the data as filter parameters. Results suggest that a 40- to 60-percent accuracy improvement may be achievable over traditional data-processing modes in reconstructed orbit errors, with a substantial reduction in reconstructed velocity errors at perigee. Historically, this has been a regime in which stringent navigation requirements have been difficult to meet by conventional methods.

Estefan, J. A.↗

Experimental Investigation of Flow Orientation Effects on Cryogenic Flow Boiling

Cryogenic flow boiling physics is of paramount importance for future cryogenic space applications employing Cryogenic Fluid Management (CFM) technologies. This experimental study investigates the two-phase flow and heat transfer performance of LN 2 flow boiling across five distinct flow orientations: vertical upflow, vertical downflow, horizontal flow, 45° inclined upflow, and 45° inclined downflow. The study employed the steady- state heating method within a circular heated tube featuring an 8.5-mm inner diameter and a 680-mm heated length. High-speed video recordings were utilized to capture two-phase flow patterns and interfacial behaviors across various flow orientations. The experiments covered a wide range of operating conditions, including mass velocities ranging from 351.80 to 1572.77 kg/m 2 s and inlet pressures from 297.14 to 1032.97 kPa, primarily with near-saturated inlet subcooling. Distinct two-phase flow patterns and regime transitions were identified for each flow orientation. Symmetrical flow patterns were evident in vertical orientations, whereas non-vertical orientations exhibited asymmetric flow stratifications, primarily influenced by the buoyancy force in a terrestrial gravity environment. Bubble dynamic parameters were quantified, and bubble collision and dispersion phenomena were visualized. Analyzing heat transfer performance based on local flow boiling curves and variations in heat transfer coefficients (HTCs), it was observed that vertical upflow demonstrated the most enhanced heat transfer performance, while vertical downflow exhibited the lowest. As mass velocity exceeded 830 kg/ m 2 s, the differences in heat transfer among orientations became less distinct, emphasizing the role of flow inertia in mitigating the influence of flow orientation. A direct comparison of microgravity HTC data from a recent study by the authors against the 1-𝘨 e HTC data indicated enhanced heat transfer performance in microgravity for flow orientation configurations in terrestrial gravity. However, this enhancement progressively diminished as the heat flux increased. Distinct HTC trends were observed as mass velocity increased for different flow orientations and gravity levels.

Cryogens↗

Analysis, Repair, and Management of the Total Ozone Mapping Spectrometer Database

In the ensuing period we were able to demonstrate that the origin of these filamentous patterns resulted from the action of synoptic-scale vortical velocity field on the global-scale background gradient of ozone concentration in the meridional direction. Hyperbolic flow patterns between long-lived atmospheric vortices bring together air parcels from different latitudes, thus creating large gradients along the separatrices leaving the hyperbolic (stagnation) point. This result is further confirmed by the KL analysis of the ozone field in the equatorial region, where the background concentration gradient vanishes. The spectral slope in this region has been found to lie close to -1, in agreement with Batchelor's prediction. Another outcome of this result is that it at least provides indirect evidence about the kinetic energy spectrum of the atmospheric turbulence in the range of scales approximately 200 to 2000 km. Namely, Batchelor's analysis is based on the assumption that the velocity field is large-scale, that is the kinetic energy spectrum decays as O(k(sup -3)) or steeper. Since the scalar spectrum is confirmed, this also supports this form of the kinetic energy spectrum. The study of equatorial regions of TOMS data revealed the efficiency of the KL method is in detecting and separating a wave-like measurement artifact inherently present in the dataset due to the non-perfect correction for cross-track bias. Just two to three eigenfunctions represent the error, which makes it possible to enhance the data by reconstituting it from the data by eliminating the subspace of artifactual eigenfunctions. This represents a highly efficient means for achieving an improved rendering of the data. This has been implemented on the database. A wide range of techniques and algorithms have been developed for the repair and extension of the TOMS database.

Sirovich, Lawrence↗

PubChemLite Plus Collision Cross Section (CCS) Values for Enhanced Interpretation of Nontarget Environmental Data

Finding relevant chemicals in the vast (known) chemical space is a major challenge for environmental and exposomics studies leveraging nontarget high resolution mass spectrometry (NT-HRMS) methods. Chemical databases now contain hundreds of millions of chemicals, yet many are not relevant. This article details an extensive collaborative, open science effort to provide a dynamic collection of chemicals for environmental, metabolomics, and exposomics research, along with supporting information about their relevance to assist researchers in the interpretation of candidate hits. The PubChemLite for Exposomics collection is compiled from ten annotation categories within PubChem, enhanced with patent, literature and annotation counts, predicted partition coefficient (logP) values, as well as predicted collision cross section (CCS) values using CCSbase. Monthly versions are archived on Zenodo under a CC-BY license, supporting reproducible research, and a new interface has been developed, including historical trends of patent and literature data, for researchers to browse the collection. This article details how PubChemLite can support researchers in environmental and exposomics studies, describes efforts to increase the availability of experimental CCS values, and explores known limitations and potential for future developments. The data and code behind these efforts are openly available.

PubChem↗

Downscaling MODIS Land Surface Temperature for Urban Public Health Applications

This study is part of a project funded by the NASA Applied Sciences Public Health Program, which focuses on Earth science applications of remote sensing data for enhancing public health decision-making. Heat related death is currently the number one weather-related killer in the United States. Mortality from these events is expected to increase as a function of climate change. This activity sought to augment current Heat Watch/Warning Systems (HWWS) with NASA remotely sensed data, and models used in conjunction with socioeconomic and heatrelated mortality data. The current HWWS do not take into account intra-urban spatial variation in risk assessment. The purpose of this effort is to evaluate a potential method to improve spatial delineation of risk from extreme heat events in urban environments by integrating sociodemographic risk factors with estimates of land surface temperature (LST) derived from thermal remote sensing data. In order to further improve the consideration of intra-urban variations in risk from extreme heat, we also developed and evaluated a number of spatial statistical techniques for downscaling the 1-km daily MODerate-resolution Imaging Spectroradiometer (MODIS) LST data to 60 m using Landsat-derived LST data, which have finer spatial but coarser temporal resolution than MODIS. In this paper, we will present these techniques, which have been demonstrated and validated for Phoenix, AZ using data from the summers of 2000-2006.

Al-Hamdan, Mohammad↗

Downscaling MODIS Land Surface Temperature for Urban Public Health Applications

This study is part of a project funded by the NASA Applied Sciences Public Health Program, which focuses on Earth science applications of remote sensing data for enhancing public health decision-making. Heat related death is currently the number one weather-related killer in the United States. Mortality from these events is expected to increase as a function of climate change. This activity sought to augment current Heat Watch/Warning Systems (HWWS) with NASA remotely sensed data, and models used in conjunction with socioeconomic and heatrelated mortality data. The current HWWS do not take into account intra-urban spatial variation in risk assessment. The purpose of this effort is to evaluate a potential method to improve spatial delineation of risk from extreme heat events in urban environments by integrating sociodemographic risk factors with estimates of land surface temperature (LST) derived from thermal remote sensing data. In order to further improve the consideration of intra-urban variations in risk from extreme heat, we also developed and evaluated a number of spatial statistical techniques for downscaling the 1-km daily MODerate-resolution Imaging Spectroradiometer (MODIS) LST data to 60 m using Landsat-derived LST data, which have finer spatial but coarser temporal resolution than MODIS. In this paper, we will present these techniques, which have been demonstrated and validated for Phoenix, AZ using data from the summers of 2000-2006.

Al-Hamdan, Mohammad↗

Single Primary Heat Extraction and Removal Emulator (SPHERE) Long Duration Testing

For the development of heat-pipe cooled microreactors, it is crucial to thoroughly understand the characteristics and functioning of heat pipes across a wide spectrum of operating conditions. Passive heat removal and its long-term performance stability are critical factors in this context. Enhanced experimental data is vital for evaluating the operational lifespan of alkali metal heat pipes. Idaho National Laboratory (INL) has successfully conducted an extended duration test on a high-performance sodium-filled heat pipe, closely monitoring the axial temperature profile, power supplied by the heaters, and heat removed by a gas-gap calorimeter. The results from this testing provide valuable data that are instrumental in supporting heat pipe validation efforts. Specifically, this data aids in the development and validation of Sockeye, the Multiphysics Object-Oriented Simulation Environment (MOOSE) tool under the US-DOE NEAMS program designed for heat pipe modeling. By comparing experimental results with Sockeye’s predictions, the tool's accuracy and reliability can be assessed and improved, thereby enhancing its capability to simulate heat pipe operations under various conditions.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

Astromaterials Curation Online Resources for Principal Investigators

The Astromaterials Acquisition and Curation office at NASA Johnson Space Center curates all of NASA's extraterrestrial samples, the most extensive set of astromaterials samples available to the research community worldwide. The office allocates ~1500 individual samples to researchers and students each year and has served the planetary research community for 45+ years. The Astromaterials Curation office provides access to its sample data repository and digital resources to support the research needs of sample investigators and to aid in the selection and request of samples for scientific study. These resources can be found on the Astromaterials Acquisition and Curation website at https://curator.jsc.nasa.gov. To better serve our users, we have engaged in several activities to enhance the data available for astromaterials samples, to improve the accessibility and performance of the website, and to address user feedback. We havealso put plans in place for continuing improvements to our existing data products.

Todd, Nancy S.↗

Mesoscale and severe storms (Mass) data management and analysis system

Progress on the Mesoscale and Severe Storms (MASS) data management and analysis system is described. An interactive atmospheric data base management software package to convert four types of data (Sounding, Single Level, Grid, Image) into standard random access formats is implemented and integrated with the MASS AVE80 Series general purpose plotting and graphics display data analysis software package. An interactive analysis and display graphics software package (AVE80) to analyze large volumes of conventional and satellite derived meteorological data is enhanced to provide imaging/color graphics display utilizing color video hardware integrated into the MASS computer system. Local and remote smart-terminal capability is provided by installing APPLE III computer systems within individual scientist offices and integrated with the MASS system, thus providing color video display, graphics, and characters display of the four data types.

Hickey, J. S.↗

TinyTPC: A TEST STAND FOR LAr DOPING

TinyTPC is a small scale liquid-argon time projection chamber (LArTPC) that studies how photosensitive dopants can improve the energy resolution of low energy events in LArTPCs. Bench tests to resolve high voltage breakdown issues and to improve the low voltage system readout are described. Experimental data with a radioactive source of Th-228 for the calibration of the pixelated readout and the characterization of TinyTPC's energy resolution is explained. Provisional results from the addition of isobutylene (photosensitive dopant) and xenon (wavelength shifter) to liquid-argon (LAr) are also presented. Further steps to improve voltage system and enhance the data collection are discussed.

Rodriguez Thorne, Paloma↗

Development of X-33/X-34 Aerothermodynamic Data Bases: Lessons Learned and Future Enhancements

A synoptic of programmatic and technical lessons learned in the development of aerothermodynamic data bases for the X-33 and X-34 programs is presented in general terms and from the perspective of the NASA Langley Research Center Aerothermodynamics Branch. The format used is that of the aerothermodynamic chain, the links of which are personnel, facilities, models/test articles, instrumentation, test techniques, and computational fluid dynamics (CFD). Because the aerodynamic data bases upon which the X-33 and X-34 vehicles will fly are almost exclusively from wind tunnel testing, as opposed to CFD, the primary focus of the lessons learned is on ground-based testing.

Miller, C. G.↗

Advancing the Frontiers of Deep Learning for Low-Dose 3D Cone-Beam CT Reconstruction

X-ray computed tomography (CT) is an important noninvasive medical imaging modality for studying the structural details of internal organs. Image reconstruction in CT is an inverse problem of recovering an object's internal structure from the absorption profile of X-ray beams (sinogram) measured using a detector. The classical variational approach for CT reconstruction minimizes an energy functional using an appropriate iterative algorithm. Motivated by the success of deep learning (DL), researchers have begun to leverage training data and enhanced computing capabilities in recent years to produce high-fidelity reconstructed images. Nonetheless, much of the academic research in DL algorithms for CT has focused primarily on the two-dimensional setting (with simplified forward operators and noise model) for proofs-of-concept, and a comprehensive benchmarking of various classical and data-driven CT reconstruction approaches has not beenundertaken. The key objective of our CT reconstruction grand challenge was to promote methodological advancements for both classical and DL-based approaches for clinical CT with a reasonably accurately simulated 3D CT forward operator and noise model. We have utilized the publicly available LIDC-IDRI dataset and simulated sinograms and FDK images corresponding to two dose levels (clinical- and low-dose, constituting two tracks of the challenge) starting from the normal-dose images as the ground truth. In this paper, we summarize the motivation, context, and results of our challenge, and highlight the future research directions in DL for clinical CT.

X-ray tomography↗