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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 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

An open science resource for establishing reliability and reproducibility in functional connectomics

Efforts to identify meaningful functional imaging-based biomarkers are limited by the ability to reliably characterize inter-individual differences in human brain function. Although a growing number of connectomics-based measures are reported to have moderate to high test-retest reliability, the variability in data acquisition, experimental designs, and analytic methods precludes the ability to generalize results. The Consortium for Reliability and Reproducibility (CoRR) is working to address this challenge and establish test-retest reliability as a minimum standard for methods development in functional connectomics. Specifically, CoRR has aggregated 1,629 typical individuals’ resting state fMRI (rfMRI) data (5,093 rfMRI scans) from 18 international sites, and is openly sharing them via the International Data-sharing Neuroimaging Initiative (INDI). To allow researchers to generate various estimates of reliability and reproducibility, a variety of data acquisition procedures and experimental designs are included. Similarly, to enable users to assess the impact of commonly encountered artifacts (for example, motion) on characterizations of inter-individual variation, datasets of varying quality are included.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Estimating Sediment Settling Velocities from a Theoretically Guided Data-Driven Approach

Sediment settling velocities are commonly estimated from analytical or process-based approaches. These approaches have theoretical constraints due to the incompletely resolved settling physics. A parametric data-driven approach was recently proposed without theoretical constraints, but it is limited by its mathematical assumptions. To overcome these limitations, here we apply a machine learning algorithm to an aggregated sediment settling experimental database and develops a nonparametric data-driven model to estimate the noncohesive sediment settling velocity in water. A cross-comparison against five process-based equations and a parametric data-driven equation demonstrates the higher accuracy and better consistency of the new model in estimating sediment settling velocities under various physical regimes. The new model also shows an easily implemented self-update capability by assimilating theoretical data derived from the process-based equations. The updated model, incorporating experimental and theoretical data of sediment settling processes, further improves the accuracy and reduces the uncertainty in estimating sediment settling velocities. This study demonstrates the capability of machine learning in sediment transport study and illustrates an alternative framework for other hydraulic engineering challenges.

42 ENGINEERING↗
DOE OSTI2020

A Step-Down Test Procedure for Wavelet Shrinkage Using Bootstrapping

Wavelet thresholding (or shrinkage) attempts to remove the noises existing in the signals while preserving inherent pattern characteristics in the reconstruction of true signals. For data-denoising purpose, we present a new wavelet thresholding procedure which employs the step-down testing idea of identifying active contrasts in unreplicated fractional factorial experiments. The proposed method employs bootstrapping methods to a step-down test for thresholding wavelet coefficients. By introducing the concept of a false discovery error rate in testing wavelet coefficients, we shrink the wavelet coefficients with p -values higher than the error rate. The error rate controls the expected proportion of wrongly accepted coefficients among chosen wavelet coefficients. Bootstrap samples are used to approximate the p -value for computational efficiency. We also present some guidelines for selecting the values of hyper-parameters which affect the performance in the step-down thresholding procedure. Based on some common testing signals and an air-conditioner sounds example, the comparison of our proposed procedure with other thresholding methods in the literature is performed. The analytical results show that the proposed procedure has a potential in data-denoising and data-reduction in a variety of signal reconstruction applications.

42 ENGINEERING↗
NASA NTRS1989

Proceedings of the Scientific Data Compression Workshop

Continuing advances in space and Earth science requires increasing amounts of data to be gathered from spaceborne sensors. NASA expects to launch sensors during the next two decades which will be capable of producing an aggregate of 1500 Megabits per second if operated simultaneously. Such high data rates cause stresses in all aspects of end-to-end data systems. Technologies and techniques are needed to relieve such stresses. Potential solutions to the massive data rate problems are: data editing, greater transmission bandwidths, higher density and faster media, and data compression. Through four subpanels on Science Payload Operations, Multispectral Imaging, Microwave Remote Sensing and Science Data Management, recommendations were made for research in data compression and scientific data applications to space platforms.

Ramapriyan, H. K.↗
DOE OSTI2026

Ion-Specific Effects on PuO 2 Nanoparticle Aggregation and Dissolution in Concentrated Electrolytes

Hydrolytic PuO 2 nanoparticles (NPs) are a dominant aqueous Pu-bearing phase in high ionic strength nuclear wastes, yet their reactivity in nonideal brines remains poorly constrained. We quantify how electrolyte identity and concentration control PuO 2 NP aggregation and ligand-assisted dissolution in acidic, high salinity solutions (NaCl, NaNO 3 , NaClO 4 , Na 2 SO 4 , Na 2 C 2 O 4 up to 5 M). A multitechnique workflow combining liquid scintillation counting (operationally defined aqueous [Pu]), scattering/electrokinetic measurements (aggregate size and zeta potential), and spectroscopy (UV–vis, XPS, Raman) resolves electrolyte-dependent partitioning between colloidal and molecular Pu species. Weakly coordinating anions (ClO 4 – , Cl – , NO 3 – ) largely preserve the (aggregated) nanoparticulate fraction but generate distinct dissolved species at high concentration, i.e., Pu(IV)–nitrato complexes in NaNO 3 and Pu(VI)–chloro complexes in NaCl. In contrast, stronger ligands substantially perturb PuO 2 NP stability: sulfate promotes partial dissolution to Pu(IV)–sulfate complexes at low concentration but reduces aqueous [Pu] at higher sulfate levels via secondary Pu(IV) sulfate formation, whereas oxalate drives strong dissolution to aqueous Pu–oxalate complexes. Aged NPs show similar trends with reduced aqueous fractions and more dominant aggregation mechanisms. In conclusion, these spectroscopically constrained speciation data provide a foundation for incorporating PuO 2 NP reactivity into thermodynamic and reactive transport models for high salinity waste and brine environments.

Aggregation↗
DOE OSTI2022

A Framework for Inverse Prediction Using Functional Response Data

Inverse prediction models have commonly been developed to handle scalar data from physical experiments. However, it is not uncommon for data to be collected in functional form. When data are collected in functional form, it must be aggregated to fit the form of traditional methods, which often results in a loss of information. For expensive experiments, this loss of information can be costly. In this study, we introduce the functional inverse prediction (FIP) framework, a general approach which uses the full information in functional response data to provide inverse predictions with probabilistic prediction uncertainties obtained with the bootstrap. The FIP framework is a general methodology that can be modified by practitioners to accommodate many different applications and types of data. We demonstrate the framework, highlighting points of flexibility, with a simulation example and applications to weather data and to nuclear forensics. Results show how functional models can improve the accuracy and precision of predictions.

42 ENGINEERING↗
NASA NTRS1997

Colloids and Nucleation

The objectives of the work funded under this grant were to develop a microphotographic technique and use it to monitor the nucleation and growth of crystals of hard colloidal spheres. Special attention is given to the possible need for microgravity studies in future experiments. A number of persons have been involved in this work. A masters student, Keith Davis, began the project and developed a sheet illumination apparatus and an image processing system for detection and analysis. His work on a segmentation program for image processing was sufficient for his master's research and has been published. A post doctoral student Bernie Olivier and a graduate student Yueming He, who originally suggested the sheet illumination, were funded by another source but along with Keith made photographic series of several samples (that had been made by Keith Davis). Data extraction has been done by Keith, Bernie, Yueming and two undergraduates employed on the grant. Results are published in Langmuir. These results describe the sheet lighting technique as one which illuminates not only the Bragg scattering crystal, but all the crystals. Thus, accurate crystal counts can be made for nucleation rate measurements. The strange crystal length scale reduction, observed in small angle light scattering (SALS) studies, following the initial nucleation and growth period, has been observed directly. The Bragg scattering (and dark) crystal size decreases in the crossover region. This could be an effect due to gravitational forces or due to over- compression of the crystal during growth. Direct observations indicate a complex morphology for the resulting hard sphere crystals. The crystal edges are fairly sharp but the crystals have a large degree of internal structure. This structure is a result of (unstable) growth and not aggregation. As yet unpublished work compares growth exponents data with data obtained by SALS. The nucleation rate density is determined over a broad volume fraction range (0.505 to 0.575) and compared to classical nucleation rate calculations. The experimental nucleation rate density varies with volume fraction more slowly than expected theoretically. Gravity may influence nucleation because crystal nuclei are more dense than the surrounding fluid and may be gravitationally convected. The largest observed crystal size was near volume fraction 0.52. Near the freezing point, crystals should grow to large size because nuclei are sparse and there is plenty of room to grow without contacting other crystals. Near melting the opposite is true, with crystals growing into one another shortly after nucleation. The maximum crystal size seen near 0.52 volume fraction suggests that gravitational stresses are limiting crystal growth near freezing.

Ackerson, Bruce↗
NASA NTRS2011

Object-Based Mapping of the Circumpolar Taiga-Tundra Ecotone with MODIS Tree Cover

The circumpolar taiga tundra ecotone was delineated using an image-segmentation-based mapping approach with multi-annual MODIS Vegetation Continuous Fields (VCF) tree cover data. Circumpolar tree canopy cover (TCC) throughout the ecotone was derived by averaging MODIS VCF data from 2000 to 2005 and adjusting the averaged values using linear equations relating MODIS TCC to Quickbird-derived tree cover estimates. The adjustment helped mitigate VCF's overestimation of tree cover in lightly forested regions. An image segmentation procedure was used to group pixels representing similar tree cover into polygonal features (segmentation objects) that form the map of the transition zone. Each polygon represents an area much larger than the 500 m MODIS pixel and characterizes the patterns of sparse forest patches on a regional scale. Those polygons near the boreal/tundra interface with either (1) mean adjusted TCC values from5 to 20%, or (2) mean adjusted TCC values greater than 5% but with a standard deviation less than 5% were used to identify the ecotone. Comparisons of the adjusted average tree cover data were made with (1) two existing tree line definitions aggregated for each 1 degree longitudinal interval in North America and Eurasia, (2) Landsat-derived Canadian proportion of forest cover for Canada, and (3) with canopy cover estimates extracted from airborne profiling lidar data that transected 1238 of the TCC polygons. The adjusted TCC from MODIS VCF shows, on average, less than 12% TCC for all but one regional zone at the intersection with independently delineated tree lines. Adjusted values track closely with Canadian proportion of forest cover data in areas of low tree cover. A comparison of the 1238 TCC polygons with profiling lidar measurements yielded an overall accuracy of 67.7%.

Ranson, K. J.↗
DOE OSTI2014

DIRAQ: scalable in situ data- and resource-aware indexing for optimized query performance

Scientific data analytics in high-performance computing environments has been evolving along with the advancement of computing capabilities. With the onset of exascale computing, the increasing gap between compute performance and I/O bandwidth has rendered the traditional post-simulation processing a tedious process. Despite the challenges due to increased data production, there exists an opportunity to benefit from "cheap" computing power to perform query-driven exploration and visualization during simulation time. To accelerate such analyses, applications traditionally augment, post-simulation, raw data with large indexes, which are then repeatedly utilized for data exploration. However, the generation of current state-of-the-art indexes involves a compute- and memory-intensive processing, thus rendering them inapplicable in an in situ context. In this paper we propose DIRAQ, a parallel in situ, in network data encoding and reorganization technique that enables the transformation of simulation output into a query-efficient form, with negligible runtime overhead to the simulation run. DIRAQ's effective core-local, precision-based encoding approach incorporates an embedded compressed index that is 3---6 $$\times $$ ? smaller than current state-of-the-art indexing schemes. Its data-aware index adjustmentation improves performance of group-level index layout creation by up to 35 % and reduces the size of the generated index by up to 27 %. Moreover, DIRAQ's in network index merging strategy enables the creation of aggregated indexes that speed up spatial-context query responses by up to $$10\times $$ 10 ? versus alternative techniques. DIRAQ's topology-, data-, and memory-aware aggregation strategy results in efficient I/O and yields overall end-to-end encoding and I/O time that is less than that required to write the raw data with MPI collective I/O.

Computer Science↗
DOE OSTI2017

The POTRA domains of Toc75 exhibit chaperone-like function to facilitate import into chloroplasts

Protein trafficking across membranes is an essential function in cells; however, the exact mechanism for how this occurs is not well understood. In the endosymbionts, mitochondria and chloroplasts, the vast majority of proteins are synthesized in the cytoplasm as preproteins and then imported into the organelles via specialized machineries. In chloroplasts, protein import is accomplished by the TOC (translocon on the outer chloroplast membrane) and TIC (translocon on the inner chloroplast membrane) machineries in the outer and inner envelope membranes, respectively. TOC mediates initial recognition of preproteins at the outer membrane and includes a core membrane channel, Toc75, and two receptor proteins, Toc33/34 and Toc159, each containing GTPase domains that control preprotein binding and translocation. Toc75 is predicted to have a β-barrel fold consisting of an N-terminal intermembrane space (IMS) domain and a C-terminal 16-stranded β-barrel domain. Here we report the crystal structure of the N-terminal IMS domain of Toc75 from Arabidopsis thaliana , revealing three tandem polypeptide transport-associated (POTRA) domains, with POTRA2 containing an additional elongated helix not observed previously in other POTRA domains. Functional studies show an interaction with the preprotein, preSSU, which is mediated through POTRA2-3. POTRA2-3 also was found to have chaperone-like activity in an insulin aggregation assay, which we propose facilitates preprotein import. Furthermore, our data suggest a model in which the POTRA domains serve as a binding site for the preprotein as it emerges from the Toc75 channel and provide a chaperone-like activity to prevent misfolding or aggregation as the preprotein traverses the intermembrane space.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Ion Dynamics in Ionic-Liquid-Based Li-Ion Electrolytes Investigated by Neutron Scattering and Dielectric Spectroscopy

A detailed understanding of the diffusion mechanisms of ions in pure and doped ionic liquids remains an important aspect in the design of new ionic-liquid electrolytes for energy storage. Here, to gain more insight into the widely used imidazolium-based ionic liquids, the relationship between viscosity, ionic conductivity, diffusion coefficients, and reorientational dynamics in the ionic liquid 3-methyl-1-methylimidazolium bis(trifluoromethanesulfonyl)imide (DMIM-TFSI) with and without lithium bis(trifluoromethanesulfonyl)imide (Li-TFSI) was examined. The diffusion coefficients for the DMIM + cation and the role of ion aggregates were investigated by using the quasielastic neutron scattering (QENS) and neutron spin echo techniques. Two diffusion mechanisms are observed for the DMIM + cation with and without Li-TFSI, that is, translational and local. The data additionally suggest that Li + ion transport along with ion aggregates, known as the vehicle mechanism, may play a significant role in the ion diffusion process. These dielectric-spectroscopy investigations in a broad temperature and frequency range reveal a typical α–β-relaxation scenario. The α relaxation mirrors the glassy freezing of the dipolar ions, and the β relaxation exhibits the signatures of a Johari–Goldstein relaxation. In contrast to the translational mode detected by neutron scattering, arising from the decoupled faster motion of the DMIM + ions, the α relaxation is well coupled to the dc charge transport, that is, the average translational motion of all three ion species in the material. Finally, the local diffusion process detected by QENS is only weakly dependent on temperature and viscosity and can be ascribed to the typical fast dynamics of glass-forming liquids.

25 ENERGY STORAGE↗
DOE OSTI2021

Cryo-electron tomography provides topological insights into mutant huntingtin exon 1 and polyQ aggregates

Huntington disease (HD) is a neurodegenerative trinucleotide repeat disorder caused by an expanded poly-glutamine (polyQ) tract in the mutant huntingtin (mHTT) protein. The formation and topology of filamentous mHTT inclusions in the brain (hallmarks of HD implicated in neurotoxicity) remain elusive. Using cryo-electron tomography and subtomogram averaging, here we show that mHTT exon 1 and polyQ-only aggregates in vitro are structurally heterogenous and filamentous, similar to prior observations with other methods. Yet, we find filaments in both types of aggregates under ~2 nm in width, thinner than previously reported, and regions forming large sheets. In addition, our data show a prevalent subpopulation of filaments exhibiting a lumpy slab morphology in both aggregates, supportive of the polyQ core model. This provides a basis for future cryoET studies of various aggregated mHTT and polyQ constructs to improve their structure-based modeling as well as their identification in cells without fusion tags.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Data-driven agent-based modeling, with application to rooftop solar adoption

Agent-based modeling is commonly used for studying complex system properties emergent from interactions among many agents. We present a novel data-driven agent-based modeling framework applied to forecasting individual and aggregate residential rooftop solar adoption in San Diego county. Our first step is to learn a model of individual agent behavior from combined data of individual adoption characteristics and property assessment. We then construct an agent-based simulation with the learned model embedded in artificial agents, and proceed to validate it using a holdout sequence of collective adoption decisions. We demonstrate that the resulting agent-based model successfully forecasts solar adoption trends and provides a meaningful quantification of uncertainty about its predictions. We utilize our model to optimize two classes of policies aimed at spurring solar adoption: one that subsidizes the cost of adoption, and another that gives away free systems to low-income house- holds. We find that the optimal policies derived for the latter class are significantly more efficacious, whereas the policies similar to the current California Solar Initiative incentive scheme appear to have a limited impact on overall adoption trends.

Agent-based modeling↗
DOE OSTI2018

The future of Sinbad: learning from the best practices of ICSBEP - 24622

Two projects sanctioned by the Organisation for Economic Co-operation and Development (OECD) Nuclear Energy Agency (NEA) have over two decades of experience established comprehensive data sets in handbooks supporting criticality safety and reactor physics. The International Criticality Safety Benchmark Evaluation Project (ICSBEP), and later the International Reactor Physics Experiment Evaluation Project (IRPhEP) that was patterned after the success of the ICSBEP, serves as an example of quality and excellence in preserving our nuclear data heritage and establishing benchmark standards upon which current and future modeling, validation, and safety efforts can be supported. Many of the best practices and lessons learned from these benchmark projects can be adopted and adapted for use with the Shielding Integral Benchmark Archive and Database (SINBAD) to prepare higher quality shielding benchmark data to effectively expand the availability of qualified experimental data available to the nuclear community. The unique experiments performed and aggregated within SINBAD represent characteristic measurements, techniques, and applications not captured with the specificity of nuclear criticality safety or traditional reactor physics applications. Application of evaluated SINBAD benchmark data would challenge and enhance our current nuclear data and modeling and simulation strategies. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

A Mountain Glacier Perspective on the Bipolar Seesaw

A global record of mountain glacier terminations during the last deglaciation (∼19–11 ka) dated by a large, uncurated data set of cosmogenic-nuclide exposure ages highlights a statistically significant asynchrony in termination ages between the Northern and Southern Hemispheres. This interhemispheric offset in the timing of glacier terminations is consistent with previously correlated ice core records that show a systematic interhemispheric lag in the timing of abrupt climate events, with the Southern Hemisphere leading the Northern Hemisphere by ∼300–3,500 years. Our analysis (a) aggregates cosmogenic-nuclide exposure ages from a global data set of moraines to discern climatically driven peaks in moraine emplacement events, and (b) utilizes a Monte Carlo simulation based on a null hypothesis that moraine emplacement is interhemispherically synchronous to estimate the statistical significance of the observed offset. The observed lag of Northern Hemisphere emplacement events compared to the Southern Hemisphere is statistically significant and is consistent with the “bipolar seesaw” pattern observed in ice core records.

58 GEOSCIENCES↗
NASA NTRS1979

Forest Classification and Inventory System using Landsat, digital terrain, and ground sample data

Accurate timber inventory data for cost-effective forest management is the primary goal of a Forest Classification and Inventory System (FOCIS) designed to provide estimates of timber volume by species aggregated by compartments, townships, or other spatial management units. FOCIS uses Landsat spectral data, including a synthesized texture channel, and Forest Service ground sample data to produce timber volume-homogeneous classes through a two-step unsupervised clustering process. Registered digital terrain data, including derived slope angle and slope aspect channels, are used to predict species proportions through a trend surface model, again using ground sample data for model calibration. In the final stage of FOCIS, volume estimates and predicted species proportions are merged and aggregated to yield timber volumes by species within management areas.

Strahler, A. H.↗
NASA NTRS1989

Aggregation of ice crystals in cirrus

Results are given from analysis of the aggregation of thick plate, columnar, and bullet rosette ice crystals in cirrus. Data were obtained from PMS 2D-C images, oil coated slides, and aircraft meteorological measurements. Crystal size ranged from 100 to 900 microns in temperatures from -30 to -45 C. The results indicate that the ratio of the sizes of aggregating crystals and the difference of their terminal velocities are important in aggregation. The collection efficiency was calculated for the thick plate crystals from the same data.

Kajikawa, Masahiro↗
DOE OSTI2025

ARCH: Large-scale knowledge graph via aggregated narrative codified health records analysis

Objective: Electronic health record (EHR) systems contain a wealth of clinical data stored as both codified data and free-text narrative notes (NLP). The complexity of EHR presents challenges in feature representation, information extraction, and uncertainty quantification. Here, to address these challenges, we proposed an efficient Aggregated naRrative Codified Health (ARCH) records analysis to generate a large-scale knowledge graph (KG) for a comprehensive set of EHR codified and narrative features. Methods: Using data from 12.5 million Veterans Affairs patients, ARCH first derives embedding vectors and generates similarities along with associated p-values to measure the strength of relatedness between clinical features with statistical certainty quantification. Next, ARCH performs a sparse embedding regression to remove indirect linkage between features to build a sparse KG. Finally, ARCH was validated on various clinical tasks, including detecting known relationships between entity pairs, predicting drug side effects, disease phenotyping, as well as sub-typing Alzheimer’s disease patients. Results: ARCH produces high-quality clinical embeddings and KG for over 60,000 codified and narrative EHR concepts. The KG and embeddings are visualized in the R-shiny powered web-API.3 ARCH achieved high accuracy in detecting EHR concept relationships, with AUCs of 0.926 (codified) and 0.861 (NLP) for similar EHR concepts, and 0.810 (codified) and 0.843 (NLP) for related pairs. It detected drug side effects with a 0.723 AUC, which improved to 0.826 after fine-tuning. Using both codified and NLP features, the detection power increased significantly. Compared to other methods, ARCH has superior accuracy and enhances weakly supervised phenotyping algorithms’ performance. Notably, it successfully categorized Alzheimer’s patients into two subgroups with varying mortality rates. Conclusion: The proposed ARCH algorithm generates large-scale high-quality semantic representations and knowledge graph for both codified and NLP EHR features, useful for a wide range of predictive modeling tasks.

Electronic health records↗