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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 OSTI2020

Computationally Efficient Learning of Large Scale Dynamical Systems: A Koopman Theoretic Approach

In recent years there has been a considerable drive towards data-driven analysis, discovery and control of dynamical systems. To this end, operator theoretic methods, namely, Koopman operator methods have gained a lot of interest. In general, the Koopman operator is obtained as a solution to a least-squares problem, and as such, the Koopman operator can be expressed as a closed-form solution that involves the computation of Moore-Penrose inverse of a matrix. For high dimensional systems and also if the size of the obtained data-set is large, the computation of the Moore-Penrose inverse becomes computationally challenging. In this paper, we provide an algorithm for computing the Koopman operator for high dimensional systems in a time-efficient manner. We further demonstrate the efficacy of the proposed approach on two different systems, namely a network of coupled oscillators (with state-space dimension up to 2500) and IEEE 68 bus system (with state-space dimension 204 and up to 24,000 time-points).

Sinha, Subhrajit↗
DOE OSTI2022

libwfa: Wavefunction analysis tools for excited and open‐shell electronic states

Abstract An open‐source software library for wavefunction analysis, libwfa, provides a comprehensive and flexible toolbox for post‐processing excited‐state calculations, featuring a hierarchy of interconnected visual and quantitative analysis methods. These tools afford compact graphical representations of various excited‐state processes, provide detailed insight into electronic structure, and are suitable for automated processing of large data sets. The analysis is based on reduced quantities, such as state and transition density matrices (DMs), and allows one to distill simple molecular orbital pictures of physical phenomena from intricate correlated wavefunctions. The implemented descriptors provide a rigorous link between many‐body wavefunctions and intuitive physical and chemical models, for example, exciton binding, double excitations, orbital relaxation, and polyradical character. A broad range of quantum‐chemical methods is interfaced with libwfa via a uniform interface layer in the form of DMs. This contribution reviews the structure of libwfa and highlights its capabilities by several representative use cases. This article is categorized under: Software > Quantum Chemistry Theoretical and Physical Chemistry > Spectroscopy

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Aggregation and data analysis of corrosion studies in molten chloride and fluoride salts

Corrosion studies in molten fluoride and chloride salts were surveyed, and key data were aggregated into a single dataset. Studies were graphed by salt purity, temperature, sample material, container material, and experimental method (loop, capsule, crucible). To elucidate and quantify the factors that affect corrosion in molten salts, a data analysis using a newly-defined corrosion resistance score and a correlation analysis using techniques borrowed from machine learning were performed. It is shown that salt purity had the strongest correlation with corrosion rates in molten chlorides and fluorides. As a result, data analysis across varied works was inconsistent due to the lack of standardization among molten salt corrosion studies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Single Gaussian process method for arbitrary tokamak regimes with a statistical analysis

Abstract Gaussian process regression is a Bayesian method for inferring profiles based on input data. The technique is increasing in popularity in the fusion community due to its many advantages over traditional fitting techniques including intrinsic uncertainty quantification and robustness to over-fitting. This work investigates the use of a new method, the change-point method, for handling the varying length scales found in different tokamak regimes. The use of the Student’s t-distribution for the Bayesian likelihood probability is also investigated and shown to be advantageous in providing good fits in profiles with many outliers. To compare different methods, synthetic data generated from analytic profiles is used to create a database enabling a quantitative statistical comparison of which methods perform the best. Using a full Bayesian approach with the change-point method, Matérn kernel for the prior probability, and Student’s t-distribution for the likelihood is shown to give the best results.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Methods of particle manipulation and analysis

Methods described herein, in some embodiments, permit extraction of particle structural and/or surface charge data from gradient induced particle motion in channels. In one aspect, a method of manipulating particle motion comprises introducing a fluid into a channel, the fluid comprising particles, and driving particle accumulation to a preselected location in the channel by setting advective velocity of the fluid to offset diffusiophoretic mobility of the particles at the preselected location.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

An Anisotropic Local Method for Boundary Detection

Plan to submit this to the Journal of Statistical Analysis and Data Mining for their special issue on CoDA (Conference on Data Analysis, a meeting of analysts and scientists from the national labs)

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Methods of particle manipulation and analysis

Methods described herein, in some embodiments, permit extraction of particle structural and/or surface charge data from gradient induced particle motion in channels. In one aspect, a method of manipulating particle motion comprises introducing a fluid into a channel, the fluid comprising particles, and driving particle accumulation to a preselected location in the channel by setting advective velocity of the fluid to offset diffusiophoretic mobility of the particles at the preselected location.

Ault, Jesse↗
DOE OSTI2021

Creation of the VADER Code in SCALE [Abstract]

The VADER (Validation Analysis Data Evaluation Resource) is a new module in SCALE 6.3 that has been derived from the legacy USLSTATS program. VADER is a tool that allows the determination of bias and bias uncertainty for criticality safety computational methods. The older USLSTATS program, written in Java, existed outside of SCALE and provided tools to calculate only the confidence band with administrative margin (sometimes called USL-1) and the single-sided uniform width closed interval (USL-2). For normality testing it only offered a crude chi- squared normality test that had no user-configurable options and presented a simple pass/no-pass functionality.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Demonstration of Dimensional and Microstructural Postirradiation Examination Capabilities on MiniFuel Disk Specimens

This work demonstrates two new MiniFuel postirradiation examination (PIE) capabilities, laser profilometry and serial sectioning, for future use on alpha-U specimens for the upcoming Mini-99 irradiation campaign. Representative U–Mo disk specimens—3 mm in diameter and approximately 0.75 mm in thickness—were subjected to dimensional measurements using standard calipers, as well as a new Keyence CL-3000 series laser profilometry system designed to measure the surface of both sides of the disk simultaneously. The laser profilometry system captured thickness gradients across the specimens as large as 0.2 mm. Additionally, because of the limitations inherent to the use of calipers, caliper measurements consistently overestimated the initial volume of MiniFuel disk specimens compared to the laser profilometry method by up to 5%. However, the results show that optimal data collection and analysis procedures are crucial to avoiding significant artifacts during data collection that can lead to large errors (approximately 10%). Serial sectioning using a combination of ion milling and electron imaging was also demonstrated for the analysis of micron-sized control volumes. Nanometer- to micron-scale porosity was resolved on a representative U–Mo specimen before irradiation, even when the surface of the specimen appeared free of porosity. Future efforts to relate microstructural features (porosity, fission product distributions, and so on) to macroscale effects (dimensional changes, thermal conductivity degradation) require accurate characterization methods such as those demonstrated in this work. These advanced PIE capabilities will be applied to optimized alpha-U specimens for the upcoming Mini-99 neutron irradiation campaign.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2017

NanoSIMS for biological applications: Current practices and analyses

Secondary ion mass spectrometry (SIMS) has become an increasingly utilized tool in biologically relevant studies. Of these, high lateral resolution methodologies using the NanoSIMS 50/50L have been especially powerful within many biological fields over the past decade. Here, the authors provide a review of this technology, sample preparation and analysis considerations, examples of recent biological studies, data analyses, and current outlooks. Specifically, the authors offer an overview of SIMS and development of the NanoSIMS. The authors describe the major experimental factors that should be considered prior to NanoSIMS analysis and then provide information on best practices for data analysis and image generation, which includes an in-depth discussion of appropriate colormaps. Additionally, the authors provide an open-source method for data representation that allows simultaneous visualization of secondary electron and ion information within a single image. Finally, the authors present a perspective on the future of this technology and where they think it will have the greatest impact in near future.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

OrthoPhyl—streamlining large-scale, orthology-based phylogenomic studies of bacteria at broad evolutionary scales

Abstract There are a staggering number of publicly available bacterial genome sequences (at writing, 2.0 million assemblies in NCBI's GenBank alone), and the deposition rate continues to increase. This wealth of data begs for phylogenetic analyses to place these sequences within an evolutionary context. A phylogenetic placement not only aids in taxonomic classification but informs the evolution of novel phenotypes, targets of selection, and horizontal gene transfer. Building trees from multi-gene codon alignments is a laborious task that requires bioinformatic expertise, rigorous curation of orthologs, and heavy computation. Compounding the problem is the lack of tools that can streamline these processes for building trees from large-scale genomic data. Here we present OrthoPhyl, which takes bacterial genome assemblies and reconstructs trees from whole genome codon alignments. The analysis pipeline can analyze an arbitrarily large number of input genomes (>1200 tested here) by identifying a diversity-spanning subset of assemblies and using these genomes to build gene models to infer orthologs in the full dataset. To illustrate the versatility of OrthoPhyl, we show three use cases: E. coli/Shigella, Brucella/Ochrobactrum and the order Rickettsiales. We compare trees generated with OrthoPhyl to trees generated with kSNP3 and GToTree along with published trees using alternative methods. We show that OrthoPhyl trees are consistent with other methods while incorporating more data, allowing for greater numbers of input genomes, and more flexibility of analysis.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Final Scientific/Technical Report

A variety of calcifying organisms produce a transient or metastable amorphous calcium carbonate (ACC) precursor phase that is assembled and subsequently transformed into a crystalline biomineral, typically calcite or aragonite. The complex shapes, hierarchical structures, and unique physical properties of the biominerals that result from this calcification pathway have stimulated interest in adapting these concepts for the design and creation of bio-inspired functional materials in the laboratory. ACC also forms as a reactive precursor in diverse inorganic systems and is likely to play a much broader role in calcium carbonate formation. Knowledge of the structure, composition, and behavior of this metastable phase is critical for establishing a structural and mechanistic framework for calcium carbonate formation and its role in biogeochemical processes, including carbon cycling. Minor additives, such as magnesium, phosphorus, and organic macromolecules, are known to play important roles in controlling ACC stability, transformation kinetics, and selection of final crystalline polymorph. Molecular water also occurs in many types of ACC and is thought to play a structural role in its stability and transformation behavior. One of the major challenges that remain unresolved is identification of the structural basis for the role of these minor additives and molecular water. The absence of long-range order in ACC, and other amorphous phases, has posed a challenge for study by techniques commonly used for crystalline solids. Preliminary studies in our group show that the combination of two techniques, synchrotron X-ray-based pair distribution function (PDF) analysis and nuclear magnetic resonance (NMR) spectroscopy can provide entirely new insight to structural properties of synthetic ACC over length scales that are most relevant for understanding its transformation properties. Building on preliminary experiments, we propose a systematic study of synthesis, structure, and transformation behavior in abiotic systems. The work will specifically address the influence of phosphate as a minor additive. PDF analysis will utilize total X-ray scattering data collected at synchrotron facilities optimized for this method and will provide direct characterization of the short- and intermediate-range structure of ACC synthesized under controlled conditions. Parallel computational work using reverse Monte Carlo methods will allow structural models to be constructed for a more complete analysis of PDF results. NMR spectroscopy, using a variety of single- and double-resonance techniques, will provide information on H and CO3 components, including dynamical properties, and their relationship to stabilizing additives. PDF and NMR results will be complemented by parallel studies using X-ray absorption and FT-IR spectroscopy to allow direct comparison to previous studies. These techniques will be used to follow the transformation of different ACC samples, with specific additives, to crystalline phases under controlled condition (e.g., relative humidity). This work will provide the structural and mechanistic basis for understanding ACC stability, its transformation behavior, and the factors that govern polymorph selection. This new insight will directly benefit researchers in diverse fields, as well as adding to the framework of knowledge for understanding and controlling calcium carbonate formation in natural and engineered systems.

58 GEOSCIENCES↗
DOE OSTI2017

Effects of defects in composite wind turbine blades – Part 1: Characterization and mechanical testing

Abstract. The Montana State University Composite Material Technologies Research Group performed a study to ascertain the effects of defects that often result from the manufacture of composite wind turbine blades. The first step in this multiyear study was to systematically quantify and enter these defects into a database before embedding similar defects into manufactured coupons. Through the Sandia National Laboratories Blade Reliability Collaborative (BRC), it was determined that key defects to investigate were fiber waves and porosity. An inspection of failed commercial-scale wind turbine blades yielded metrics that utilized specific parameters to physically characterize a defect. Methods to easily and consistently discretize, measure, and assess these defects based on the identified parameters were established to allow for statistical analysis. Data relating flaw parameters to frequencies of occurrence were analyzed and found to fit within standard distributions. Additionally, mechanical testing of coupons with flaws based on these physical characterization data was performed to understand effects of these defects. Representative blade materials and manufacturing methods were utilized and both material properties and damage progression were measured. It was observed that flaw parameters directly affected the mechanical response. While the data gathered in this first step are widely useful, it was also intended for use as a foundation for the rest of the study, to perform probabilistic analysis and comparative analysis of progressive damage models.

Nelson, Jared W. (ORCID:0000000207736091)↗
DOE OSTI2015

Sensitivity studies to Support TEX critical experiments design

In the frame of the ongoing Thermal/Epithermal experiments program, supported by the DOE-NCSP, we are characterizing expected data with analysis of sensitivity coefficients to nuclear data. The computations were performed for detailed and simplified models of the experimental configurations in order to demonstrate their invariance with respect to small geometry variations. The sensitivity coefficients were computed with recently developed precise methodologies using Monte Carlo tools (MCNP-6.1, SCALE 6.1 and MORET 5.C.1) with the following nuclear data libraries: ENDF/B-VII.0, ENDF/B-VII.1, and JEFF3.1. Since the considered experiments are devoted to tantalum data validation, their neutronic characteristics are compared with the relevant integral experiment data collected in the OECD/NEA ICSBEP Handbook. Although analysis of sensitivity coefficients taken alone is insufficient for an entire assessment, we can conclude that TEX experimental results can fill gaps in the available benchmarks to facilitate quantification of uncertainty for plutonium containing systems with epithermal neutron spectra (e.g. wet plutonium-based powders). However, analysis of sensitivity profiles demonstrates that an advanced statistical methodology will be needed to fit tantalum nuclear data or to evaluate the associated uncertainties. (authors)

42 ENGINEERING↗
DOE OSTI2024

Generation and validation of comprehensive synthetic weather histories using auto-regressive moving-average models

As energy system design moves to more complex methods of optimization including machine learning there is a significant need for more weather data than is available. One method to solve this is using synthetic data models such as the auto-regressive moving-average (ARMA) model which has been frequently utilized to create such data. This paper looks at extending the ARMA algorithm to generate solar components through the use of clearsky detrending, maintaining vector relationships and by leveraging physical relationships. The method for the creation of entirely synthetic weather data files including key weather variables for energy system analysis is presented. Furthermore, a detailed comparison of energy system simulations utilizing both real and synthetic data is made using NREL’s System Advisor Model. Whilst good agreement is made for the solar variables, and other weather variables, ARMA methods often fail to capture the standard deviation and skew of annual weather distributions. Vector-ARMA is shown to maintain correlations between variables and thus generate data sets that perform similarly in energy system design. Here, it is finally shown that the ARMA method fails to preserve day-today correlations in weather variables and thus over-predicts optimal energy storage by 21% for a residential solar application.

42 ENGINEERING↗
DOE OSTI2017

Bayesian Estimation of Thermonuclear Reaction Rates for Deuterium+Deuterium Reactions

The study of d+d reactions is of major interest since their reaction rates affect the predicted abundances of D, 3 He, and 7 Li. In particular, recent measurements of primordial D/H ratios call for reduced uncertainties in the theoretical abundances predicted by Big Bang nucleosynthesis (BBN). Different authors have studied reactions involved in BBN by incorporating new experimental data and a careful treatment of systematic and probabilistic uncertainties. To analyze the experimental data, Coc et al. used results of ab initio models for the theoretical calculation of the energy dependence of S -factors in conjunction with traditional statistical methods based on χ 2 minimization. Bayesian methods have now spread to many scientific fields and provide numerous advantages in data analysis. Astrophysical S -factors and reaction rates using Bayesian statistics were calculated by Iliadis et al. In this paper we present a similar analysis for two d+d reactions, d(d, n) 3 He and d(d, p) 3 H, that has been translated into a total decrease of the predicted D/H value by 0.16%.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2015

When will low-contrast features be visible in a STEM X-ray spectrum image?

When will a small or low-contrast feature, such as an embedded second-phase particle, be visible in a scanning transmission electron microscopy (STEM) X-ray map? This work illustrates a computationally inexpensive method to simulate X-ray maps and spectrum images (SIs), based upon the equations of X-ray generation and detection. To particularize the general procedure, an example of nanostructured ferritic alloy (NFA) containing nm-sized Y 2 Ti 2 O 7 embedded precipitates in ferritic stainless steel matrix is chosen. The proposed model produces physically appearing simulated SI data sets, which can either be reduced to X-ray dot maps or analyzed via multivariate statistical analysis. Comparison to NFA X-ray maps acquired using three different STEM instruments match the generated simulations quite well, despite the large number of simplifying assumptions used. A figure of merit of electron dose multiplied by X-ray collection solid angle is proposed to compare feature detectability from one data set (simulated or experimental) to another. The proposed method can scope experiments that are feasible under specific analysis conditions on a given microscope. As a result, future applications, such as spallation proton–neutron irradiations, core-shell nanoparticles, or dopants in polycrystalline photovoltaic solar cells, are proposed.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗