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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 1,657 records · Page 92
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Cerebral perfusion computed tomography deconvolution via structure tensor total variation regularization

Purpose: Cerebral perfusion computed tomography (PCT) imaging as an accurate and fast acute ischemic stroke examination has been widely used in clinic. Meanwhile, a major drawback of PCT imaging is the high radiation dose due to its dynamic scan protocol. The purpose of this work is to develop a robust perfusion deconvolution approach via structure tensor total variation (STV) regularization (PD-STV) for estimating an accurate residue function in PCT imaging with the low-milliampere-seconds (low-mAs) data acquisition. Methods: Besides modeling the spatio-temporal structure information of PCT data, the STV regularization of the present PD-STV approach can utilize the higher order derivatives of the residue function to enhance denoising performance. To minimize the objective function, the authors propose an effective iterative algorithm with a shrinkage/thresholding scheme. A simulation study on a digital brain perfusion phantom and a clinical study on an old infarction patient were conducted to validate and evaluate the performance of the present PD-STV approach. Results: In the digital phantom study, visual inspection and quantitative metrics (i.e., the normalized mean square error, the peak signal-to-noise ratio, and the universal quality index) assessments demonstrated that the PD-STV approach outperformed other existing approaches in terms of the performance of noise-induced artifacts reduction and accurate perfusion hemodynamic maps (PHM) estimation. In the patient data study, the present PD-STV approach could yield accurate PHM estimation with several noticeable gains over other existing approaches in terms of visual inspection and correlation analysis. Conclusions: This study demonstrated the feasibility and efficacy of the present PD-STV approach in utilizing STV regularization to improve the accuracy of residue function estimation of cerebral PCT imaging in the case of low-mAs.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Novel Analysis and Visualization of Chemical Events for Public Health Surveillance

Pacific Northwest National Laboratory hosted an intern-based web application development contest in the summer of 2016 centered around developing novel chemical surveillance applications to aid in health situational awareness. Making up the three teams were three graduate students (n=9) from various US schools majoring in non-public health domains, such as computer science and user design. The interns successfully developed three applications that demonstrated a value-add to chemical surveillance—ChemAnalyzer (text analytics), RetroSpect (retrospective analysis of chemical events),and ToxicBusters (geo-based trend analytics). These applications will be the basis for the first chemical surveillance application to be incorporated into the DTRA Biosurveillance Ecosystem (BSVE).Pacific Northwest National Laboratory (PNNL), on behalf the Defense Threat Reduction Agency (DTRA; project number CB10190), hosts an annual intern- based web app development contest. Previous competitions have focused on mobile biosurveillance. The 2016 competition pivoted away from biosurveillance to focus on addressing challenges within the field of chemical surveillance and increasing public health chemical situational awareness. The result of the app will be integrated within the DTRA BSVE. PNNL hosted nine graduate interns for a 10-week period in the summer of 2016 as participants in a summer web application development contest. Students were drawn from such fields as software engineering and user experience and design and placed into three teams of three students. The challenge presented to the interns was to design and develop a fully-functional web application that would address a critical need within the chemical surveillance community. The interns developed their own ideas (vetted by PNNL and DTRA), discovered and integrated their own data sources, and produced their own visualizations and analytics, independent of any assistance outside of that provided in an advisory capacity. The competition end with a judging event with a panel of subject matter experts and cash awards were distributed to the teams. Each team produced a unique application. Although there was mild overlap between some of the ideas, the applications were developed independently and each reflected the unique contributions of the teams. ChemAnalyzer is a text-analytics platform designed to facilitate more data-driven decision, given a corpus of text data about a chemical event. Their platform provided the ability to automatically identify and highlight key words in documents related to chemical events. The keywords are drawn from an ontology installed with the system, as well as any user-identified keywords. The ChemAnalyzer team finished in third place. The RetroSpect team developed a visual analytic tool for performing retrospective analysis and monitoring of chemical events. Their app provided the ability to search and analyze past events, as well as visualization of state and county information for the recorded chemical events. The RetroSpect team finished in second place. The Toxic busters team - the winners of the competition - created a geo-based situational awareness tool for tracking chemical events. Their app featured an updateable map overlay, search functionality for finding specific or related events, incident and city/state/national-level statistics and trends, as well as news and social media integration based on keywords related to chemical surveillance. Each of the apps developed by the teams provides value to an analyst tasked with monitoring chemical events. The apps integrated unique data sources to provides a full picture of a chemical event, and its effects upon the surrounding population. This integrated analytics provides a valuable benefit over existing workflows, where analysts must monitor news, social, and other information sources manually for real-time information. The apps developed by these interns are designed to enable identification and analysis of the incident as quickly as possible, allowing for more timely assessments of the incident and its impacts. The web app development contest provided a unique opportunity for students to learn about the emerging needs in chemical surveillance as it relates to health situational awareness. Students were drawn from a variety of fields and were tasked with developing novel web apps addressing some of the most pressing challenges in the field of chemical surveillance. The ideas generated by the students will help form the basis for future chemical surveillance application development to be integrated with the DTRABSVE.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Block Island Acoustic Propagation Modeling Data

This dataset contains acoustic propagation model outputs, computational subroutines, and analysis tools for underwater sound propagation in the Block Island region, including parabolic equation (PE) model results, visualization products, and comprehensive modeling software tools.

17 WIND ENERGY↗
NASA NTRS1994

Parallelization and visual analysis of multidimensional fields: Application to ozone production, destruction, and transport in three dimensions

Atmospheric modeling is a grand challenge problem for several reasons, including its inordinate computational requirements and its generation of large amounts of data concurrent with its use of very large data sets derived from measurement instruments like satellites. In addition, atmospheric models are typically run several times, on new data sets or to reprocess existing data sets, to investigate or reinvestigate specific chemical or physical processes occurring in the earth's atmosphere, to understand model fidelity with respect to observational data, or simply to experiment with specific model parameters or components.

Schwan, Karsten↗
DOE OSTI2023

Driving mode analysis—How uncertain functional inputs propagate to an output

Abstract Driving mode analysis elucidates how correlated features of uncertain functional inputs jointly propagate to produce uncertainty in the output of a computation. Uncertain input functions are decomposed into three terms: the mean functions, a zero‐mean driving mode, and zero‐mean residual. The random driving mode varies along a single direction, having fixed functional shape and random scale. It is uncorrelated with the residual, and under linear error propagation, it produces an output variance equal to that of the full input uncertainty. Finally, the driving mode best represents how input uncertainties propagate to the output because it minimizes expected squared Mahalanobis distance amongst competitors. These characteristics recommend interpretation of the driving mode as the single‐degree‐of‐freedom component of input uncertainty that drives output uncertainty. We derive the functional driving mode, show its superiority to other seemingly sensible definitions, and demonstrate the utility of driving mode analysis in an application. The application is the simulation of neutron transport in criticality experiments. The uncertain input functions are nuclear data that describe how Pu reacts to bombardment by neutrons. Visualization of the driving mode helps scientists understand what aspects of correlated functional uncertainty have effects that either reinforce or cancel one another in propagating to the output of the simulation.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1991

Debris/Ice/TPS Assessment and Photographic Analysis for Shuttle Mission STS-37

A Debris/Ice/TPS assessment and photographic analysis was conducted for Space Shuttle Mission STS-37. Debris inspections of the flight elements and launch pad were performed before and after launch. Ice/frost conditions on the External Tank were assessed by the use of computer programs, nomographs, and infrared scanner data during cryogenic loading of the vehicle followed by on-pad visual inspection. High speed photography of launch was analyzed to identify ice/debris sources and evaluate potential vehicle damage and/or inflight anomalies. The debris/ice/TPS conditions and photographic analysis of Mission STS-37 are documented, along with their overall effect on the Space Shuttle Program.

Katnik, Gregory N.↗
DOE OSTI2021

Visual Impact Assessment of the Energetic Materials Complex Construction Project on Manhattan Project–Era Historic Properties, the TA-06-0037 Concrete Bowl, and the TA-22-0001 Quonset Hut

Concern for potential visual effects to historic Manhattan Project–era properties emerged early in the planning and consultation phase for the upcoming Energetic Materials Complex (EMC) construction project. In initial discussions with project managers and design team members, resource managers became aware of the need to consider potential impacts to the viewsheds of two nearby properties that are eligible for inclusion in the Manhattan Project National Historical Park (MAPR). Resource managers recognized that viewshed characteristics important to the integrity of the Concrete Bowl (Technical Area [TA-]06-0037) and the Quonset Hut (TA-22-0001) conceivably faced the prospect of lasting and irreversible visual impacts. A strategy to gather necessary data soon emerged. The approach presented to the New Mexico State Historic Preservation Officer (SHPO) on April 7, 2021, combined gathering baseline information from field visits with a geographic information system (GIS)-supported viewshed analysis. Accordingly, results from the viewshed analysis would help resource managers determine if a more comprehensive visual impact assessment (VIA) would be needed. If necessitated by the outcome of the GIS viewshed analysis, initial consultation with the SHPO specified the production of a VIA that would explore any potential visual adverse impacts to the Concrete Bowl and the Quonset Hut. Cultural resources and GIS specialists with the Laboratory performed a viewshed analysis shortly after consultation with the SHPO. The analysis indicated a high likelihood that at least one of the two Manhattan Project–era properties would experience at least a minimal level of visual impact and that a VIA would be needed. The resulting analysis provides a description of the undertaking, an account of the properties affected along with an evaluation of historical significance, an examination of potential visual impacts, and a determination of effect to the identified historic properties.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

Deep-learning methods for contrast enhancement and artifact reduction in cryo-electron tomography: a systematic analysis of the state of the art and proposed improvements

Cryo-electron tomography (cryo-ET) has emerged as the preferred technique for visualizing the organization of macromolecular complexes in situ and resolving their structures at subnanometre resolution [Tegunov et al. (2021)View full citation, Nat. Methods, 18, 186–193]. Despite improvements in data quality as a result of advances in detector technology, microscope stability and stage precision, the analysis and interpretation of tomograms remains challenging due to a low signal-to-noise ratio and reconstruction artifacts stemming from experimental constraints in specimen tilt during data collection resulting in a missing wedge in the Fourier space. Recently, self-supervised deep-learning methods have been proposed for contrast enhancement and reduction of resolution anisotropy in reconstructed tomograms. Here, we evaluate several state-of-the-art deep-learning methods which aim to improve the interpretability of cryo-ET reconstructions, with a focus on their performance on downstream tasks of template matching, sub­tomogram averaging and segmentation. We propose new training architectures and a loss function based on Fourier shell correlation that show improved performance over the standard U-Net with L1/L2 losses. We demonstrate our analysis on four diverse experimental datasets: purified 80S ribosomes, in situ Chlamydomonas reinhardtii, immature HIV-1 virus-like particles and INS-1E cells.

contrast enhancement↗
DOE OSTI2021

Tracking the evolution of processes occurring in silicon anodes in lithium ion batteries by 3D visualization of relaxation times

An unconventional electroanalytical method has been used for tracking processes in silicon anodes in lithium ion batteries: a 3D visualization of relaxation times. Impedance data of the electrodes were collected at different potentials and different cycles during cyclic voltammetry, and were treated by means of the Distribution of Relaxation Times (DRT) method. A 3D visualization of the results allowed to identify the formation of a solid electrolyte interphase on the anode, composed of two layers with different relaxation times. Such findings are not possible by conventional analysis of impedance data by modeling with equivalent circuits, nor by simple DRT alone. Additionally, it was possible to observe that the characteristic relaxation time of the lithiation of the Si anode becomes smaller upon cycling, indicating that the material experiences structural transformations that allow it to lithiate faster. The result is relevant to motivate the use of micron-sized particles in the anode.

25 ENERGY STORAGE↗
DOE OSTI2024

Improving I/O-aware Workflow Scheduling via Data Flow Characterization and trade-off Analysis

The scientific computing paradigm has transitioned from compute-intensive to I/O-intensive and memory-intensive in the past decade, especially when data-driven science has become common practice. Numerous empirical I/O-aware scheduling optimizations have been developed by incorporating I/O capacity and bandwidth as constraints into scheduling. Unfortunately, there is a lack of data flow (I/O) characterization tool and an understanding of trade-offs between concurrency, locality, and I/O bandwidth. To bridge the gap, this work 1) presents a set of descriptors to characterize, organize, and visualize I/O profiles, including flow size, I/O bandwidth, and operation count, which group data flows by I/O types, tasks, and files; 2) proposes an I/O Roofline model-based trade-off analysis to find the optimal trade-off between flow operational intensity, concurrency, and flow performance. The I/O descriptors generate useful insights into complicated I/O behaviors, suggesting distinct concurrency, storage, and scheduling to be used by types, tasks, and files. The proposed trade-off analysis guides scheduling decisions that generate resource assignment with the best flow parallelism. We evaluate our I/O-aware scheduling methodology on a highly I/O-intensive workflow–1000 Genomes. The experimental results demonstrate speedups of up to 2.4× compared to the state-of-the- art methods.

Guo, Luanzheng [BATTELLE (PACIFIC NW LAB)]↗
NASA NTRS2021

Maine Ecological Forecasting: Using NASA Earth Observations to Assess Federally Endangered Atlantic Salmon Habitat in Maine

Atlantic salmon (Salmo salar) is a species of anadromous fish that was historically prevalent throughout the New England region. Overfishing and habitat loss caused a severe decline in the salmon population, restricting North America’s remaining wild Atlantic salmon to rivers in Maine. Land use and land cover (LULC) change and factors associated with temperature and precipitation are important for understanding the suitability of freshwater habitat for juvenile salmon. In collaboration with the Maine Department of Marine Resources and the Downeast Salmon Federation, the team utilized NASA Earth observations to aid partners in understanding how these factors change in relation to critical salmon habitat. Landsat 5 Thematic Mapper (TM) and Landsat 8 Operational Land Imager (OLI) imagery was analyzed to assess changes in LULC between 1985 and 2021. Terra Moderate Resolution Imaging Spectroradiometer (MODIS) and Integrated Multi-satellite Retrievals for Global Precipitation Measurement (GPM IMERG) data were used to determine land surface temperature and precipitation, respectively; between 2000 and 2020. Lastly, temperature and precipitation anomaly maps visualized deviation from the 20-year climatic average for each pixel. LULC analysis for 1985 to 2020 showed a loss of forest cover throughout critical salmon habitat although gains in forested area were also observed. Assessment of mean summer land surface temperature revealed an increase in temperature from 2000 to 2020 and anomaly maps highlighted areas experiencing abnormally high or low summer precipitation and temperature. These results and the underlying data were packaged for the partner organizations to inform future conservation efforts.

Michael Corley↗
NASA NTRS2006

Spatial and Temporal Coherence of SeaWiFS Chlorophyll Concentration Anomalies in the North Atlantic Bloom (1998-2005) Examined with Giovanni

The availability of climatological chlorophyll-a concentration data products from the SeaWiFS mission spanning the eight-year mission period allowed the creation of a climatological anomaly analysis function in Giovanni, the GES DISC Interactive Online Visualization and ANalysis Infrastructure. This study utilizes the Giovanni anomaly analysis function to examine mesoscale anomalies in the North Atlantic Ocean during the springtime North Atlantic Bloom. This examination indicates that areas exhibiting positive anomalies and areas exhibiting negative anomalies are coherent over significant spatial scales, with relatively abrupt boundaries between areas with positive and negative anomalies. Year-to-year variability in anomaly "intensity" can be caused by either variability in the temporal occurrence of the bloom peak or by variability in the peak chlorophyll concentration in a particular area. The study will also discuss the feasibility of combining chlorophyll anomaly analysis with other data types.

Acker, James G.↗
DOE OSTI2017

Measured extent of agricultural expansion depends on analysis technique

Concern is rising that ecologically important, carbon-rich natural lands in the United States are losing ground to agriculture. We investigate how quantitative assessments of historical land use change to address this concern differ in their conclusions depending on the data set used. We examined land use change between 2006 and 2014 in 20 counties in the Prairie Pothole Region using the Cropland Data Layer, a modified Cropland Data Layer, data from the National Agricultural Imagery Program, and in-person ground-truthing. The Cropland Data Layer analyses overwhelmingly returned the largest amount of land use change with associated error that limits drawing conclusions from it. Analysis with visual imagery estimated a fraction of this land use change. Clearly, analysis technique drives understanding of the measured extent of land use change; different techniques produce vastly different results that would inform land management policy in strikingly different ways. As a result, best practice guidelines are needed.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Dataset for Biorefinery-specific feedstock price variability, Part 1: Corn stover

This dataset was utilized in a report to highlight parameters that affect near-term sustainable supply of corn stover and forest resources at $56 and $74 per dry ton delivered. While the report focus is restricted to 2018, the modeling runs are available from 2016-2022. In the 2016 Billion-ton Report (BT16), two stover cases were presented. In this dataset, we vary technical levels of those assumptions to measure stover supply response and to evaluate the major determinants of stover supply. In each of these cases, the supply is modeled first at the farmgate at prices up to $80 per dry ton for five deterministic scenarios. Building on this dataset, a supplementary dataset of delivered supply was modeled for 800k dry ton per year capacity facilities in two facility siting approaches. Results were summarized across delivered supply curves for twelve scenarios. The resulting supply curves are highly elastic, resulting in a range of potential supplies across scenarios at specified prices. Interactive visualization of these data allows exploration into any specified nth plant supply sensitivity to key variables and spatial distribution of stover resources. The analysis is economic supply risk and doesn’t account for disruptions from competing demands, namely livestock feed and bedding markets. Scenario ending in _BC3080 is a reference scenario consistent with BT16 Basecase (BC1), but with corn stover price isolation. Scenario ending in _OHB080 includes high operational efficiency constraints for corn stover. Scenario ending in _OLB080 includes low operational efficiency constraints for corn stover. Scenario ending in _PLB080 includes low opportunity cost. Scenario ending in _PHB080 includes high opportunity cost. No Land Rental costs are applied to these scenarios. All scenarios were under an exogenous price simulation using POLYSYS (v2017).

Agricultural residues, biomass resources, 2018, bi↗
DOE OSTI2021

GENESPACE R Package (GENESPACE) v1.0

In short, the GENESPACE pipeline conducts analysis of orthology networks, constrained within syntenic regions. Since analyses are limited to local tests conducted within syntenic blocks, GENESPACE is agnostic to ploidy, duplicated regions, inversions or other whole-genome chromosomal complexities that are common across many evolutionary lineages. This advantage allows for evolutionary tests in polyploids (e.g. switchgrass, manuscript in review), species with ancient, but retained whole-genome duplications (e.g. pecan, manuscript in prep), high levels of tandem array proliferation (e.g. eukalypts, manuscript in review) and many other factors that can confound comparative genomic analyses. The major advances of GENESPACE are three-fold: First, this is the first R package to integrate visualization and analysis of large-scale comparative genomics. R, which offers a high-level environment for graphical and statistical exploration of data, is often speed- and memory-limited and not used for computationally intensive tasks such as comparative genomics. The highly efficient C++ scripts used in GENESPACE (via data.table) permit a much faster and computationally lightweight implementation of comparative genomics than is currently available. Second, the pipeline itself is novel. To the best of our knowledge, no other program accomplishes synteny-constrained and ploidy-agnostic comparative genomics. Since nearly all plants and many animals have a history of whole-genome duplications, this is a major and necessary advance to the field. Third, GENESPACE offers high-level and intuitive multi-genome graphical outputs. The dotplots and 'riparian' plots produced herein, which are produced entirely through original R code, are publication-ready and easily customizable.

Schmutz, Jeremy↗
DOE OSTI2026

Adapt: A Weather Radar Data Analysis and Nowcasting Platform for Informed Adaptive Scanning

SF-26-021 Adapt is a data processing platform for real-time data analysis, short term prediction of targets convective cells and tracking for archived data. It provides tools for downloading, processing, segmenting, projecting, analyzing, and visualizing storm cell data from weather radar. The pipeline includes cell detection, motion estimation using optical flow, cell property extraction, and persistence to NetCDF and SQLite/Parquet for guiding adaptive scanning.

Raut, Bhupendra Ashokrao [Argonne National Laborat↗
DOE OSTI2018

Challenges in Eye Tracking for Dynamic User-Driven Workflows

This three-year Laboratory Directed Research and Development (LDRD) project aimed at developing a developed prototype data collection system and analysis techniques to enable the measurement and analysis of user-driven dynamic workflows. Over 3 years, our team developed software, algorithms, and analysis technique to explore the feasibility of capturing and automatically associating eye tracking data with geospatial content, in a user-directed, dynamic visual search task. Although this was a small LDRD, we demonstrated the feasibility of automatically capturing, associating, and expressing gaze events in terms of geospatial image coordinates, even as the human "analyst" is given complete freedom to manipulate the stimulus image during a visual search task. This report describes the problem under examination, our approach, the techniques and software we developed, key achievements, ideas that did not work as we had hoped, and unsolved problems we hope to tackle in future projects.

42 ENGINEERING↗
DOE OSTI2021

Exploring Explicit Uncertainty for Binary Analysis (EUBA)

Reverse engineering (RE) analysts struggle to address critical questions about the safety of binary code accurately and promptly, and their supporting program analysis tools are simply wrong sometimes. The analysis tools have to approximate in order to provide any information at all, but this means that they introduce uncertainty into their results. And those uncertainties chain from analysis to analysis. We hypothesize that exposing sources, impacts, and control of uncertainty to human binary analysts will allow the analysts to approach their hardest problems with high-powered analytic techniques that they know when to trust. Combining expertise in binary analysis algorithms, human cognition, uncertainty quantification, verification and validation, and visualization, we pursue research that should benefit binary software analysis efforts across the board. We find a strong analogy between RE and exploratory data analysis (EDA); we begin to characterize sources and types of uncertainty found in practice in RE (both in the process and in supporting analyses); we explore a domain-specific focus on uncertainty in pointer analysis, showing that more precise models do help analysts answer small information flow questions faster and more accurately; and we test a general population with domain-general sudoku problems, showing that adding "knobs" to an analysis does not significantly slow down performance. This document describes our explorations in uncertainty in binary analysis.

97 MATHEMATICS AND COMPUTING↗