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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 757 records · Page 42
All sourcesNASA NTRSDOE OSTI
NASA NTRS2014

The Uncertainty of Biomass Estimates from Modeled ICESat-2 Returns Across a Boreal Forest Gradient

The Forest Light (FLIGHT) radiative transfer model was used to examine the uncertainty of vegetation structure measurements from NASA's planned ICESat-2 photon counting light detection and ranging (LiDAR) instrument across a synthetic Larix forest gradient in the taiga-tundra ecotone. The simulations demonstrate how measurements from the planned spaceborne mission, which differ from those of previous LiDAR systems, may perform across a boreal forest to non-forest structure gradient in globally important ecological region of northern Siberia. We used a modified version of FLIGHT to simulate the acquisition parameters of ICESat-2. Modeled returns were analyzed from collections of sequential footprints along LiDAR tracks (link-scales) of lengths ranging from 20 m-90 m. These link-scales traversed synthetic forest stands that were initialized with parameters drawn from field surveys in Siberian Larix forests. LiDAR returns from vegetation were compiled for 100 simulated LiDAR collections for each 10 Mg · ha(exp -1) interval in the 0-100 Mg · ha(exp -1) above-ground biomass density (AGB) forest gradient. Canopy height metrics were computed and AGB was inferred from empirical models. The root mean square error (RMSE) and RMSE uncertainty associated with the distribution of inferred AGB within each AGB interval across the gradient was examined. Simulation results of the bright daylight and low vegetation reflectivity conditions for collecting photon counting LiDAR with no topographic relief show that 1-2 photons are returned for 79%-88% of LiDAR shots. Signal photons account for approximately 67% of all LiDAR returns, while approximately 50% of shots result in 1 signal photon returned. The proportion of these signal photon returns do not differ significantly (p greater than 0.05) for AGB intervals greater than 20 Mg · ha(exp -1). The 50m link-scale approximates the finest horizontal resolution (length) at which photon counting LiDAR collection provides strong model fits and minimizes forest structure uncertainty in the synthetic Larix stands. At this link-scale AGB greater than 20 Mg · ha(exp -1) has AGB error from 20-50% at the 95% confidence level. These results suggest that the theoretical sensitivity of ICESat-2 photon counting LiDAR measurements alone lack the ability to consistently discern differences in inferred AGB at 10 Mg · ha(exp -1) intervals in sparse forests characteristic of the taiga-tundra ecotone.

LiDAR↗
DOE OSTI2017

Electron Mobility and Trapping in Ferrihydrite Nanoparticles

Iron is the most abundant transition metal in the Earth's crust, and naturally occurring iron oxide minerals play a commanding role in environmental redox reactions. Although iron oxide redox reactions are well studied, their precise mechanisms are not fully understood. Recent work has shown that these involve electron transfer pathways within the solid, suggesting that overall reaction rates could be dependent on electron mobility. Initial ultrafast spectroscopy studies of iron oxide nanoparticles sensitized by fluorescein derivatives supported a model for electron mobility based on polaronic hopping of electron charge carriers between iron sites, but the constitutive relationships between hopping mobilities and interfacial charge transfer processes has remained obscured. We developed a coarse-grained lattice Monte Carlo model to simulate the collective mobilities and lifetimes of these photoinjected electrons with respect to recombination with adsorbed dye molecules for the essential nanophase ferrihydrite, and tested predictions made by the simulations using pump-probe spectroscopy. We acquired optical transient absorption spectra as a function of particle size and under a variety of solution conditions, and used cryogenic transmission electron microscopy to determine the aggregation state of the nanoparticles. We observed biphasic electron recombination kinetics over timescales that spanned picoseconds to microseconds, the slower regime of which was fit with a stretched exponential decay function. The recombination rates were weakly affected by nanoparticle size and aggregation state, suspension pH, and the injection of multiple electrons per nanoparticle. We conclude that electron mobility indeed limits the rate of interfacial electron transfer in these systems with the slowest processes relating to escape from deep traps, the presence of which outweighs the influence of environmental factors such as pH-dependent surface charge.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2022

Status of Lattice QCD Determination of Nucleon Form Factors and Their Relevance for the Few-GeV Neutrino Program

Calculations of neutrino–nucleus cross sections begin with the neutrino–nucleon interaction, making the latter critically important to flagship neutrino oscillation experiments despite limited measurements with poor statistics. Alternatively, lattice quantum chromodynamics (LQCD) can be used to determine these interactions from the Standard Model with quantifiable theoretical uncertainties. Recent LQCD results of g A are in excellent agreement with data, and results for the (quasi-)elastic nucleon form factors with full uncertainty budgets are expected within a few years. We review the status of the field and LQCD results for the nucleon axial form factor, F A ( Q 2 ), a major source of uncertainty in modeling sub-GeV neutrino–nucleon interactions. Results from different LQCD calculations are consistent but collectively disagree with existing models, with potential implications for current and future neutrino oscillation experiments. We describe a road map to solidify confidence in the LQCD results and discuss future calculations of more complicated processes, which are important to few-GeV neutrino oscillation experiments.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Copper Defects and Charge Collection in Cadmium Telluride Photovoltaic Devices

In CdTe photovoltaic devices, the CdTe layer must be doped with Cu to reduce its resistivity, increase carrier lifetime, and improve hole transport. However, the Cu concentration is typically very low around the interfaces and within the CdTe layer, making it difficult to determine the influence Cu has on charge transport at the nanoscale; Cu concentrations are difficult to detect due to low ionization probability of Cu atoms [1]. Here, we use synchrotron X-ray microscopy to probe the nanoscale distribution of Cu and correlate it to local charge collection in CdTe photovoltaic devices. We demonstrate Cu segregation around grain boundaries, and, using cross-section charge collection measurements and transport modelling, show recombination center concentration in the CdTe layer dictates the interface at which charge collection occurs. The work gives insights on how Cu distributes in CdTe photovoltaic systems, and an understanding of how these distributions affect charge transport.

Walker, Trumann↗
DOE OSTI2019

Self-Evolving Machine: A Continuously Improving Model for Molecular Thermochemistry

Because collecting precise and accurate chemistry data is often challenging, chemistry data sets usually only span a small region of chemical space, which limits the performance and the scope of applicability of data-driven models. To address this issue, we integrated an active learning machine with automatic ab initio calculations to form a self-evolving model that can continuously adapt to new species appointed by the users. In the present work, we demonstrate the self-evolving concept by modeling the formation enthalpies of stable closed-shell polycyclic species calculated at the B3LYP/6-31G(2df,p) level of theory. By combining a molecular graph convolutional neural network with a dropout training strategy, the model we developed can predict density functional theory (DFT) enthalpies for a broad range of polycyclic species and assess the quality of each predicted value. For the species which the current model is uncertain about, the automatic ab initio calculations provide additional training data to improve the performance of the model. For a test set composed of 2858 cyclic and polycyclic hydrocarbons and oxygenates, the enthalpies predicted by the model agree with the reference DFT values with a root-mean-square error of 2.62 kcal/mol. Finally, we found that a model originally trained on hydrocarbons and oxygenates can broaden its prediction coverage to nitrogen-containing species via an active learning process, suggesting that the continuous learning strategy is not only able to improve the model accuracy but is also capable of expanding the predictive capacity of a model to unseen species domains.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

PNNL DataHub NIAID Program Project: Modeling Host Responses to Understand Severe Human Virus Infections, Multi-Omic Viral Dataset Catalog Collection

The National Institute of Allergy and Infectious Diseases (NIAID) "Modeling Host Responses to Understand Severe Human Virus Infections" program project was a highly integrated and comprehensive systems biology research core, funded by the National Institute of Health (U19AI106772) from 2013-06-01 to 2018-05-31, investigating the complex host response to category A, B, and C priority pathogen infections. Resulting project deliverables include an extensive comprehensive collections of linked primary and secondary transformation viral experimental infection data. Here we provide a never before released comprehensive infectious disease collection of primary and secondary transformation multi-Omics data profiling a series of priority pathogen primary experimental studies for enhanced open access to viral Omics lifecycle datasets and project metadata. Using a highly integrated and multidisciplinary approach, linked primary data and metadata supporting secondary normalization datasets, provide critical information necessary for research reproducibility and long-term preservation. Enabling on-demand data access for research community consumption and developer reuse, serves to support new mechanistic insights and discoveries into host-pathogen interactions for aiding future biohazard data preparedness efforts in emergency response to global health crises involving viral infection.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2011

Tidally averaged circulation in Puget Sound sub-basins: Comparison of historical data, analytical model, and numerical model

Through extensive field data collection and analysis efforts conducted since the 1950s, researchers have established an understanding of the characteristic features of circulation in Puget Sound. The pattern ranges from the classic fjordal behavior in some basins, with shallow brackish outflow and compensating inflow immediately below, to the typical two-layer flow observed in many partially mixed estuaries with saline inflow at depth. An attempt at reproducing this behavior by fitting an analytical formulation to past data is presented, followed by the application of a three-dimensional circulation and transport numerical model. The analytical treatment helped identify key physical processes and parameters, but quickly reconfirmed that response is complex and would require site-specific parameterization to include effects of sills and interconnected basins. The numerical model of Puget Sound, developed using unstructured-grid finite volume method, allowed resolution of the sub-basin geometric features, including presence of major islands, and site-specific strong advective vertical mixing created by bathymetry and multiple sills. The model was calibrated using available recent short-term oceanographic time series data sets from different parts of the Puget Sound basin. The results are compared against (1) recent velocity and salinity data collected in Puget Sound from 2006 and (2) a composite data set from previously analyzed historical records, mostly from the 1970s. The results highlight the ability of the model to reproduce velocity and salinity profile characteristics, their variations among Puget Sound subbasins, and tidally averaged circulation. Sensitivity of residual circulation to variations in freshwater inflow and resulting salinity gradient in fjordal sub-basins of Puget Sound is examined.

58 GEOSCIENCES↗
DOE OSTI2025

Advancements in Constitutive Model Calibration: Leveraging the Power of Full‐Field DIC Measurements and In Situ Load Path Selection for Reliable Parameter Inference

Accurate material characterization and model calibration are essential for computationally supported high-consequence engineering decisions. Historically, characterization and calibration methods (1) use simplified test specimen geometries and global data, (2) cannot guarantee that sufficient characterization data are collected for a specific model of interest, (3) use deterministic methods that provide best-fit parameter values with no uncertainty quantification, and (4) are sequential, inflexible, and time-consuming. This work brings together several recent advancements into an improved workflow called interlaced characterization and calibration (ICC) that advances the state-of-the-art in constitutive model calibration. The ICC paradigm (1) employs tools to efficiently use full-field data to calibrate high-fidelity material models, (2) aligns the data needed with the data collected by adopting an optimal experimental design protocol, (3) quantifies parameter uncertainty through Bayesian inference and (4) incorporates these advancements into a quasi real-time feedback loop. The ICC framework is demonstrated here on the calibration of a material model using simulated full-field data for an aluminium cruciform specimen being deformed biaxially. The cruciform is actively driven through the myopically preferred load path using Bayesian optimal experimental design, which selects load steps that yield the maximum expected information gain (EIG). Principal component analysis (PCA) is performed on the model predictions of full-field displacements, and fast surrogate models are built to approximate the input-output relationships of the expensive finite element model. Furthermore, the tools developed and demonstrated here show that high-fidelity constitutive models can be efficiently and reliably calibrated with quantified uncertainty, thus supporting credible decision-making and potentially increasing the agility of solid mechanics modelling by enabling utilization of computational simulations at earlier stages of the design cycle.

Bayesian optimal experimental design↗
NASA NTRS1987

Measurement-based reliability/performability models

Measurement-based models based on real error-data collected on a multiprocessor system are described. Model development from the raw error-data to the estimation of cumulative reward is also described. A workload/reliability model is developed based on low-level error and resource usage data collected on an IBM 3081 system during its normal operation in order to evaluate the resource usage/error/recovery process in a large mainframe system. Thus, both normal and erroneous behavior of the system are modeled. The results provide an understanding of the different types of errors and recovery processes. The measured data show that the holding times in key operational and error states are not simple exponentials and that a semi-Markov process is necessary to model the system behavior. A sensitivity analysis is performed to investigate the significance of using a semi-Markov process, as opposed to a Markov process, to model the measured system.

Hsueh, Mei-Chen↗
DOE OSTI2022

Theoretical uncertainty quantification for heavy-ion fusion

Despite recent advances and focus on rigorous uncertainty quantification for microscopic models of quantum many-body systems, the uncertainty on the dynamics of those systems has been underexplored. To address this, we have used time-dependent Hartree-Fock to examine the model uncertainty for a collection of low-energy, heavy-ion fusion reactions. Fusion reactions at near-barrier energies represent a rich test-bed for the dynamics of quantum many-body systems owing to the complex interplay of collective excitation, transfer, and static effects that determine the fusion probability of a given system. The model uncertainty is sizable for many of the systems studied and the primary contribution arises from static properties that are ill-constrained, such as the neutron radius of neutron-rich nuclei. Furthermore, these large uncertainties motivate the use of information from reactions to better constrain existing models and to infer static properties from reaction data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

A theoretical study on quasifission and fusion–fission processes in heavy-ion collisions

Despite recent advances and focus on rigorous uncertainty quantification for microscopic models of quantum many-body systems, the uncertainty on the dynamics of those systems has been underexplored. To address this, we have used time-dependent Hartree-Fock to examine the model uncertainty for a collection of low-energy, heavy-ion fusion reactions. Fusion reactions at near-barrier energies represent a rich test-bed for the dynamics of quantum many-body systems owing to the complex interplay of collective excitation, transfer, and static effects that determine the fusion probability of a given system. The model uncertainty is sizable for many of the systems studied and the primary contribution arises from static properties that are ill-constrained, such as the neutron radius of neutron-rich nuclei. These large uncertainties motivate the use of information from reactions to better constrain existing models and to infer static properties from reaction data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1979

Collective plasma effects associated with the continuous injection model of solar flare particle streams

A modified continuous injection model for impulsive solar flares that includes self-consistent plasma nonlinearities based on the concept of marginal stability is presented. A quasi-stationary state is established, composed of a hot truncated electron Maxwellian distribution confined by acoustic turbulence on the top of the loop and energetic electron beams precipitating in the chromosphere. It is shown that the radiation properties of the model are in accordance with observations.

Vlahos, L.↗
NASA NTRS2002

Relationships Between the Bulk-Skin Sea Surface Temperature Difference, Wind, and Net Air-Sea Heat Flux

The primary purpose of this project was to evaluate and improve models for the bulk-skin temperature difference to the point where they could accurately and reliably apply under a wide variety of environmental conditions. To accomplish this goal, work was conducted in three primary areas. These included production of an archive of available data sets containing measurements of the skin and bulk temperatures and associated environmental conditions, evaluation of existing skin layer models using the compiled data archive, and additional theoretical work on the development of an improved model using the data collected under diverse environmental conditions. In this work we set the basis for a new physical model of renewal type, and propose a parameterization for the temperature difference across the cool skin of the ocean in which the effects of thermal buoyancy, wind stress, and microscale breaking are all integrated by means of the appropriate renewal time scales. Ideally, we seek to obtain a model that will accurately apply under a wide variety of environmental conditions. A summary of the work in each of these areas is included in this report. A large amount of work was accomplished under the support of this grant. The grant supported the graduate studies of Sandra Castro and the preparation of her thesis which will be completed later this year. This work led to poster presentations at the 1999 American Geophysical Union Fall Meeting and 2000 IGARSS meeting. Additional work will be presented in a talk at this year's American Meteorological Society Air-Sea Interaction Meeting this May. The grant also supported Sandra Castro during a two week experiment aboard the R/P Flip (led by Dr. Andrew Jessup of the Applied Physics Laboratory) to help obtain additional shared data sets and to provide Sandra with a fundamental understanding of the physical processes needed in the models. In a related area, the funding also partially supported Dr. William Emery and Daniel Baldwin in the preparation of their publication "Accuracy of in situ sea surface temperatures used to calibrate infrared satellite measurements". The remainder of this report is drawn from these publications and presentations.

Emery, William J.↗
DOE OSTI2013

Collective operations in a file system based execution model

A mechanism is provided for group communications using a MULTI-PIPE synthetic file system. A master application creates a multi-pipe synthetic file in the MULTI-PIPE synthetic file system, the master application indicating a multi-pipe operation to be performed. The master application then writes a header-control block of the multi-pipe synthetic file specifying at least one of a multi-pipe synthetic file system name, a message type, a message size, a specific destination, or a specification of the multi-pipe operation. Any other application participating in the group communications then opens the same multi-pipe synthetic file. A MULTI-PIPE file system module then implements the multi-pipe operation as identified by the master application. The master application and the other applications then either read or write operation messages to the multi-pipe synthetic file and the MULTI-PIPE synthetic file system module performs appropriate actions.

97 MATHEMATICS AND COMPUTING↗