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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 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Methodology Guidelines on Life Cycle Assessment of Photovoltaic Electricity: 3rd Edition

Life Cycle Assessment (LCA) is a structured, comprehensive method of quantifying material- and energy-flows and their associated emissions caused in the life cycle of goods and services. The ISO 14040 and 14044 standards provide the framework for LCA. However, this framework leaves the individual practitioner with a range of choices that can affect the results and thus the conclusions of an LCA study. The current IEA guidelines were developed to provide guidance on assuring consistency, balance, and quality to enhance the credibility and reliability of the results from LCAs on photovoltaic (PV) electricity generation systems. The guidelines represent a consensus among the authors - PV LCA experts in North America, Europe, and Asia - for assumptions made on PV performance, decisions on process input and emissions allocation, methods of analysis, and reporting of the results. Guidance is given on PV-specific parameters used as inputs in LCA and on choices and assumptions in life cycle inventory (LCI) data analysis and on implementation of modeling approaches. A consistent approach towards system modeling, the functional unit, the system boundaries, water use modeling and the allocation aspects enhances the credibility of PV electricity LCA studies and enables balanced LCA-based comparisons of different electricity producing technologies. The document discusses metrics like greenhouse gas emissions (GHG), cumulative energy demand (CED), acidification potential (AP), ozone depletion potential (ODP), human toxicity, ecotoxicity and ionizing radiation. Guidance is given for the definition of the energy payback time (EPBT), the nonrenewable energy payback time (NREPBT), and the impact mitigation potentials (IMP). The indicator energy return on investment (EROI) is described in a separate International Energy Agency (IEA) PV Power Systems (PVPS) Task 12 report (Raugei et al. 2015). The guidelines on the reporting and communication of the results serve the need for producing clear, comprehensive and transparent reports.

14 SOLAR ENERGY↗
DOE OSTI2015

Direct observation of oxygen-vacancy-enhanced polarization in a SrTiO{sub 3}-buffered ferroelectric BaTiO{sub 3} film on GaAs

The integration of functional oxide thin-films on compound semiconductors can lead to a class of reconfigurable spin-based optoelectronic devices if defect-free, fully reversible active layers are stabilized. However, previous first-principles calculations predicted that SrTiO{sub 3} thin films grown on Si exhibit pinned ferroelectric behavior that is not switchable, due to the presence of interfacial vacancies. Meanwhile, piezoresponse force microscopy measurements have demonstrated ferroelectricity in BaTiO{sub 3} grown on semiconductor substrates. The presence of interfacial oxygen vacancies in such complex-oxide/semiconductor systems remains unexplored, and their effect on ferroelectricity is controversial. Here, we use a combination of aberration-corrected scanning transmission electron microscopy and first-principles density functional theory modeling to examine the role of interfacial oxygen vacancies on the ferroelectric polarization of a BaTiO{sub 3} thin film grown on GaAs. We demonstrate that interfacial oxygen vacancies enhance the polar discontinuity (and thus the single domain, out-of-plane polarization pinning in BaTiO{sub 3}), and propose that the presence of surface charge screening allows the formation of switchable domains.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2014

Predicting oropharyngeal tumor volume throughout the course of radiation therapy from pretreatment computed tomography data using general linear models

Purpose: The purpose of this work was to develop and evaluate the accuracy of several predictive models of variation in tumor volume throughout the course of radiation therapy. Methods: Nineteen patients with oropharyngeal cancers were imaged daily with CT-on-rails for image-guided alignment per an institutional protocol. The daily volumes of 35 tumors in these 19 patients were determined and used to generate (1) a linear model in which tumor volume changed at a constant rate, (2) a general linear model that utilized the power fit relationship between the daily and initial tumor volumes, and (3) a functional general linear model that identified and exploited the primary modes of variation between time series describing the changing tumor volumes. Primary and nodal tumor volumes were examined separately. The accuracy of these models in predicting daily tumor volumes were compared with those of static and linear reference models using leave-one-out cross-validation. Results: In predicting the daily volume of primary tumors, the general linear model and the functional general linear model were more accurate than the static reference model by 9.9% (range: −11.6%–23.8%) and 14.6% (range: −7.3%–27.5%), respectively, and were more accurate than the linear reference model by 14.2% (range: −6.8%–40.3%) and 13.1% (range: −1.5%–52.5%), respectively. In predicting the daily volume of nodal tumors, only the 14.4% (range: −11.1%–20.5%) improvement in accuracy of the functional general linear model compared to the static reference model was statistically significant. Conclusions: A general linear model and a functional general linear model trained on data from a small population of patients can predict the primary tumor volume throughout the course of radiation therapy with greater accuracy than standard reference models. These more accurate models may increase the prognostic value of information about the tumor garnered from pretreatment computed tomography images and facilitate improved treatment management.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2018

Does Marine Surface Tension Have Global Biogeography? Addition for the OCEANFILMS Package

We apply principles of Gibbs phase plane chemistry across the entire ocean-atmosphere interface to investigate aerosol generation and geophysical transfer issues. Marine surface tension differences comprise a tangential pressure field controlling trace gas fluxes, primary organic inputs, and sea spray salt injections, in addition to heat and momentum fluxes. Mapping follows from the organic microlayer composition, now represented in ocean system models. Organic functional variations drive the microforcing, leading to (1) reduced turbulence and (by extension) laminar gas-energy diffusion; plus (2) altered bubble film mass emission into the boundary layer. Interfacial chemical behaviors are, therefore, closely reviewed as the background. We focus on phase transitions among two dimensional “solid, liquid, and gaseous” states serving as elasticity indicators. From the pool of dissolved organic carbon (DOC) only proteins and lipids appear to occupy significant atmospheric interfacial areas. The literature suggests albumin and stearic acid as the best proxies, and we distribute them through ecodynamic simulation. Consensus bulk distributions are obtained to control their adsorptive equilibria. We devise parameterizations for both the planar free energy and equation of state, relating excess coverage to the surface pressure and its modulus. Constant settings for the molecular surrogates are drawn from laboratory study and successfully reproduce surfactant solid-to-gas occurrence in compression experiments. Since DOC functionality measurements are rare, we group them into super-ecological province tables to verify aqueous concentration estimates. Outputs are then fed into a coverage, tension, elasticity code. The resulting two dimensional pressure contours cross a critical range for the regulation of precursor piston velocity, bubble breakage, and primary aerosol sources plus ripple damping. Concepts extend the water-air adsorption theory currently embodied in our OCEANFILMS aerosol emissions package, and the two approaches could be inserted into Earth System Models together. Uncertainties in the logic include kinetic and thermochemical factors operating at multiple scales.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Electron impact excitation of helium in Debye plasma

The probability, differential, and integral scattering cross sections of the 1{sup 1}S→2{sup 1}S and 1{sup 1}S→2{sup 1}P transitions of helium have been calculated in the first Born approximation. The projectile-target interactions depending on the temperature and the density of plasma are described by the Debye-Hückel model. Wave functions of the target before and after collision were modeled by non orthogonal Hartree-Fock orbitals. The wave functions parameters are calculated with the Ritz variational method. We improve our unscreened first Born approximation integral cross sections by using the BE-scaled (B stands for binding energy and E excitation energy) method. The second Born approximation has also been used to calculate the excitation cross sections in Debye plasma. Our calculations are compared to other theoretical and experimental results where applicable.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Development of Time Lapse VSP Integration Workflow: A Case Study at Farnsworth CO2-EOR Project

Abstract This study aims to develop a 4D Vertical Seismic Profile (VSP) integration workflow to improve the prediction of subsurface stress changes. The selected study site is a 5-spot pattern within the ongoing CO2-EOR operations at the Farnsworth Field Unit FWU in Ochiltree County, Texas. The specific pattern has undergone extensive geological and geomechanical characterization through the acquisition of 3D seismic data, geophysical well logs, and core. This workflow constrains a numerical hydromechanical model by applying a penalty function formed between "modeled" versus "observed" time-lapse compressional and shear seismic velocity changes. Analyses of geophysical logs and ultra-sonic measurements on core exhibit measurable sensitivities to changes in both fluid saturation and mean effective stress. These data are used to develop a site-specific rock physics model and stress-velocity relationship, which inform the numerical models used to generate the "modeled" portion of the penalty function. The "observed" portion of the penalty function is provided by a novel elastic full-waveform inversion of the available 3D baseline and three monitor surveys to produce high-quality estimates of time-lapse compressional and shear seismic velocity changes. The modeling workflow accounts sequentially for fluid substitution and stress impacts. Hydrodynamic and geomechanical properties of the 3D coupled numerical model are estimated through geostatistical integration of well log and core data with 3D seismic inversion products. Changes in seismic velocities due to fluid substitution are computed using the Biot-Gassmann workflow and site-specific rock physics. Stress impacts on time-lapse seismic velocity changes are modeled from the effective stress output of the hydromechanical model and are initially based on the velocity versus effective stress relationship extracted from core mechanical testing. Based on the principle of superposition of seismic wavefields, seismic velocity changes attributed to fluid substitution and that due to changes in mean effective stress are treated as linearly additive. The modeled results are upscaled using Backus averaging to reconcile scale discrepancies between the modeled and measured datasets to formulate the penalty function. This manuscript presents the forward modeling process and concludes that for the base case, the seismic velocity changes due to mean effective stress dominates over the seismic velocity changes attributed to fluid substitution because of the extensive range of the pressure perturbations. Successful minimization of this penalty function calibrates the coupled hydrodynamic geomechanical numerical model and affirms the suitability of acoustic time-lapse measurements such as 4D-VSP for geomechanical calibration.

02 PETROLEUM↗
DOE OSTI2011

Mathematical modelling of fungal growth and function

This contribution is based on the six presentations given at the Special Interest Group meeting on Mathematical modelling of fungal growth and function held during IMC9. The topics covered aspects of fungal growth ranging across several orders of magnitude of spatial and temporal scales from the biomechanics of spore ejection, vesicle trafficking and hyphal tip growth to the form and function of mycelial networks. Each contribution demonstrated an interdisciplinary approach to questions at specific scales. Collectively, they represented a significant advance in the multi-scale understanding offungal biology.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Multi-objective Bayesian alloy design using multi-task Gaussian processes

In design applications, correlations among material properties (such as the tendency for stronger materials to be less ductile) are often neglected. This approach is echoed in multi-objective optimization techniques which treat each performance characteristic as an independent objective, aiming to optimize scalar functions and find optimal Pareto fronts. However, this overlooks the statistical relationships between performance characteristics inherent in a material system. To address this, we propose the use of Bayesian optimization, a highly efficient black-box optimization algorithm known for constructing Gaussian processes (GPs) – uncorrelated surrogates - to model objective functions. Rather than evaluating multiple GPs for each objective function separately, we argue for a shift towards jointly modeling these objective functions, considering their statistical correlations. This integrated approach utilizes naturally occurring relationships among material properties, providing additional information to enhance the performance of the design framework. This requires the replacement of multiple independent GPs with a single multi-task GP, employing a correlation matrix to construct a multi-task kernel function, wherein each task corresponds to a single objective function. Here, we anticipate this refined methodology will better leverage material correlations, improving design optimization results.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Kinetic modeling of microbial growth, enzyme activity, and gene deletions: An integrated model of β-glucosidase function in Cellvibrio japonicus

Understanding the complex growth and metabolic dynamics in microorganisms requires advanced kinetic models containing both metabolic reactions and enzymatic regulation to predict phenotypic behaviors under different conditions and perturbations. Most current kinetic models lack gene expression dynamics and are separately calibrated to distinct media, which consequently makes them unable to account for genetic perturbations or multiple substrates. This challenge limits our ability to gain a comprehensive understanding of microbial processes towards advanced metabolic optimizations that are desired for many biotechnology applications. Here, we present an integrated computational and experimental approach for the development and optimization of mechanistic kinetic models for microbial growth and metabolic and enzymatic dynamics. Our approach integrates growth dynamics, gene expression, protein secretion, and gene-deletion phenotypes. We applied this methodology to build a dynamic model of the growth kinetics in batch culture of the bacterium Cellvibrio japonicus grown using either cellobiose or glucose media. The model parameters were inferred from an experimental data set using an evolutionary computation method. The resulting model was able to explain the growth dynamics of C. japonicus using either cellobiose or glucose media and was also able to accurately predict the metabolite concentrations in the wild-type strain as well as in β-glucosidase gene deletion mutant strains. We validated the model by correctly predicting the non-diauxic growth and metabolite consumptions of the wild-type strain in a mixed medium containing both cellobiose and glucose, made further predictions of mutant strains growth phenotypes when using cellobiose and glucose media, and demonstrated the utility of the model for designing industrially-useful strains. Importantly, the model is able to explain the role of the different β-glucosidases and their behavior under genetic perturbations. Here, this integrated approach can be extended to other metabolic pathways to produce mechanistic models for the comprehensive understanding of enzymatic functions in multiple substrates.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Seismic modeling with radial basis function-generated finite differences (RBF-FD) – a simplified treatment of interfaces

In a previous study of seismic modeling with radial basis function-generated finite differences (RBF-FD), we outlined a numerical method for solving 2-D wave equations in domains with material interfaces between different regions. The method was applicable on a mesh-free set of data nodes. It included all information about interfaces within the weights of the stencils (allowing the use of traditional time integrators), and was shown to solve problems of the 2-D elastic wave equation to 3rd-order accuracy. In the present paper, we discuss a refinement of that method that makes it simpler to implement. It can also improve accuracy for the case of smoothly-variable model parameter values near interfaces. We give several test cases that demonstrate the method solving 2-D elastic wave equation problems to 4th-order accuracy, even in the presence of smoothly-curved interfaces with jump discontinuities in the model parameters.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2011

Role of TNFR1 in lung injury and altered lung function induced by the model sulfur mustard vesicant, 2-chloroethyl ethyl sulfide

Lung toxicity induced by sulfur mustard is associated with inflammation and oxidative stress. To elucidate mechanisms mediating pulmonary damage, we used 2-chloroethyl ethyl sulfide (CEES), a model sulfur mustard vesicant. Male mice (B6129) were treated intratracheally with CEES (3 or 6 mg/kg) or control. Animals were sacrificed 3, 7 or 14 days later and bronchoalveolar lavage (BAL) fluid and lung tissue collected. Treatment of mice with CEES resulted in an increase in BAL protein, an indication of alveolar epithelial damage, within 3 days. Expression of Ym1, an oxidative stress marker also increased in the lung, along with inducible nitric oxide synthase, and at 14 days, cyclooxygenase-2 and monocyte chemotactic protein-1, inflammatory proteins implicated in tissue injury. These responses were attenuated in mice lacking the p55 receptor for TNF{alpha} (TNFR1-/-), demonstrating that signaling via TNFR1 is key to CEES-induced injury, oxidative stress, and inflammation. CEES-induced upregulation of CuZn-superoxide dismutase (SOD) and MnSOD was delayed or absent in TNFR1-/- mice, relative to WT mice, suggesting that TNF{alpha} mediates early antioxidant responses to lung toxicants. Treatment of WT mice with CEES also resulted in functional alterations in the lung including decreases in compliance and increases in elastance. Additionally, methacholine-induced alterations in total lung resistance and central airway resistance were dampened by CEES. Loss of TNFR1 resulted in blunted functional responses to CEES. These effects were most notable in the airways. These data suggest that targeting TNF{alpha} signaling may be useful in mitigating lung injury, inflammation and functional alterations induced by vesicants.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Interface-Induced Polarization in SrTiO 3 -LaCrO 3 Superlattices

Epitaxial interfaces and superlattices comprised of polar and non-polar perovskite oxides have generated a good deal of interest because of the variety of novel properties they possess. In this work, we examine superlattices comprised of SrTiO3 (STO) and LaCrO3 (LCO) layers; we demonstrate that the differing band alignment of the polar LCO layer and the non-polar STO layer produces a ferroelectric phase transition throughout the STO layers of the superlattice. Through x-ray absorption near edge spectroscopy and aberration-corrected scanning transmission electron microscopy we show that the Ti cations are displaced off-center in the TiO6 octahedra along the superlattice growth direction. We also demonstrate that a built-in potential gradient exists within the STO and LCO layers via in situ x-ray photoelectron spectroscopy measurements. Density functional theory models of the system are in excellent agreement with these results, predicting both the ferroelectric octahedral distortion and the built-in electric field. These results represent a new avenue for research in perovskite superlattices, as two non-ferroelectric phases are shown to induce a bulk ferroelectric response due to interfacial phenomena.

Complex oxides↗
DOE OSTI2010

Cascade Spectroscopy and Recent {Xi}* Photo-production Results from CLAS

Doubly-strange baryon resonances provide new insights into baryon structure. The standard QCD Lagrangian implies that for every N* and {Delta}* resonance, there should be a corresponding {Xi}(cascade resonance). This is due to the flavor symmetry of the strong force. Therefore, one can investigate baryon structure by observing aspects of the doubly-strange baryons like regularities such as parity doublets. At energies above approximately 1.5 GeV, the light-quark baryon resonances are broad and overlap while the cascades in this range are narrow and therefore more readily observed. An overview of the world cascade spectrum and a comparison to the lighter baryon spectra will be presented. Recent results from an on-going analysis from the G12 (5.4 GeV) photo-production experiment using the CLAS detector at JLab will be highlighted.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2017

Representation of radiative strength functions within a practical model of cascade gamma decay

A practical model developed at the Joint Institute for Nuclear Research (JINR, Dubna) in order to describe the cascade gamma decay of neutron resonances makes it possible to determine simultaneously, from an approximation of the intensities of two-step cascades, parameters of nuclear level densities and partial widths with respect to the emission of nuclear-reaction products. The number of the phenomenological ideas used isminimized in themodel version considered in the present study. An analysis of new results confirms what was obtained earlier for the dependence of dynamics of the interaction of fermion and boson nuclear states on the nuclear shape. From the ratio of the level densities for excitations of the vibrational and quasiparticle types, it also follows that this interaction manifests itself in the region around the neutron binding energy and is probably different in nuclei that have different parities of nucleons.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2017

Error modeling for surrogates of dynamical systems using machine learning: Machine-learning-based error model for surrogates of dynamical systems

A machine learning–based framework for modeling the error introduced by surrogate models of parameterized dynamical systems is proposed. The framework entails the use of high-dimensional regression techniques (eg, random forests, and LASSO) to map a large set of inexpensively computed “error indicators” (ie, features) produced by the surrogate model at a given time instance to a prediction of the surrogate-model error in a quantity of interest (QoI). This eliminates the need for the user to hand-select a small number of informative features. The methodology requires a training set of parameter instances at which the time-dependent surrogate-model error is computed by simulating both the high-fidelity and surrogate models. Using these training data, the method first determines regression-model locality (via classification or clustering) and subsequently constructs a “local” regression model to predict the time-instantaneous error within each identified region of feature space. We consider 2 uses for the resulting error model: (1) as a correction to the surrogate-model QoI prediction at each time instance and (2) as a way to statistically model arbitrary functions of the time-dependent surrogate-model error (eg, time-integrated errors). We then apply the proposed framework to model errors in reduced-order models of nonlinear oil-water subsurface flow simulations, with time-varying well-control (bottom-hole pressure) parameters. The reduced-order models used in this work entail application of trajectory piecewise linearization in conjunction with proper orthogonal decomposition. Moreover, when the first use of the method is considered, numerical experiments demonstrate consistent improvement in accuracy in the time-instantaneous QoI prediction relative to the original surrogate model, across a large number of test cases. When the second use is considered, results show that the proposed method provides accurate statistical predictions of the time- and well-averaged errors.

97 MATHEMATICS AND COMPUTING↗