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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

A Sparse Tableau Formulation for Node-Breaker Representations in Security-Constrained Optimal Power Flow

Realistic representations of contingencies in AC optimal power flow (ACOPF) often challenge traditional bus-branch network models. Derived from nodal analysis, such approaches represent network constraints in terms of the familiar bus admittance matrix, Ybus. A fixed Ybus is unable to represent common circuit breaker actions such as bus splitting. Work-arounds for Ybus-based analysis typically rely on topology processing, switching between different Ybus matrices depending on breaker settings. In this paper, we propose a very general node-breaker approach, employing multi-port element models and using a sparse tableau formulation (STF) for network constraints. Instead of treating breaker action as altering network topology, and hence changing the structure of Kirchhoff’s voltage law (KVL) and Kirchhoff’s current law (KCL) equations, this approach represents a breaker’s position as impacting only constraints associated with a single component, thereby maintaining fixed structure in the KVL and KCL constraints. While larger numbers of variables are required, STF proves sparser than Ybus formulations. Numerical case studies herein demonstrate that STF provides computational efficiency comparable to a Ybus-based ACOPF at the scale of several hundred buses, and lower computational cost in an example of over one thousand buses.

Park, Byungkwon (ORCID:000000033189816X)↗
DOE OSTI2018

Process-Based Model Evaluation Using Surface Energy Budget Observations in Central Greenland

Energy exchange at the Greenland ice sheet surface governs surface temperature variability, a factor critical for representing surface melt. Physical processes link driving forces to subsequent surface energy budget responses, including radiative, turbulent, and ground heat fluxes, and ultimately control surface temperature evolution. A reanalysis product (ERA-Interim, ERA-I), operational model (Climate Forecast System version 2, CFSv2), and climate model (Community Earth System Model, CESM) are evaluated using a comprehensive set of surface energy budget observations and process-based relationships obtained at Summit, Greenland. Simulated downwelling longwave radiation is underestimated, which is linked to a deficiency of liquid-bearing clouds. Lower than observed surface albedo, especially in ERA-I, compensates for summer deficiencies in downwelling longwave radiation. In winter, such deficiencies are compensated by an overestimation of the sensible heat flux. Process-based relationships convey that all three models underestimate the response of surface temperature to changes in radiative forcing, primarily due to an overactive ground heat flux response in ERA-I, turbulent heat fluxes in CFSv2, and sensible heat flux in CESM. Cross comparison of three distinct models indicates that the ground heat flux response for ERA-I, CFSv2, and CESM is too high, too low, and comparatively accurate, respectively, signifying the benefit of using an advanced representation of snow properties. Relatively small biases in CESM surface albedo suggest that advances in the representation of cloud microphysics result in more realistic radiative forcing. These results provide insight into model strengths and deficiencies, indicating the importance of representing physical processes when portraying cloud impacts on surface temperature variability.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Hybrid PSO-ASVR-based method for data fitting in the calibration of infrared radiometer

The present paper describes a hybrid particle swarm optimization-adaptive support vector regression (PSO-ASVR)-based method for data fitting in the calibration of infrared radiometer. The proposed hybrid PSO-ASVR-based method is based on PSO in combination with Adaptive Processing and Support Vector Regression (SVR). The optimization technique involves setting parameters in the ASVR fitting procedure, which significantly improves the fitting accuracy. However, its use in the calibration of infrared radiometer has not yet been widely explored. Bearing this in mind, the PSO-ASVR-based method, which is based on the statistical learning theory, is successfully used here to get the relationship between the radiation of a standard source and the response of an infrared radiometer. Main advantages of this method are the flexible adjustment mechanism in data processing and the optimization mechanism in a kernel parameter setting of SVR. Numerical examples and applications to the calibration of infrared radiometer are performed to verify the performance of PSO-ASVR-based method compared to conventional data fitting methods.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Development of Automated Material Handling System with Alternate Gripper Designs for the Purpose of Increased Performance & Worker Safety

Savannah River National Laboratory’s (SRNL) Surplus Plutonium Disposition (SPD) Program leads the development and transition of automated unit operations for the processing of Plutonium oxide. A mixing can is opened, filled with material, mixed, set inside of a die can, and finally punched into compressed material. Replication of the process is constructed in A-area, where the mixing can weighs 1.6 kg (3.5 lbs.) and the compressed material weighs 4 kg (8.8 lbs.). Due to the constant process of Plutonium disposition, the fatigue on workers and worker dose accumulates quickly over time. SPD aims to automate this process by using a robotic arm to replace the hands-on worker. Automation will: Reduce worker radiation dose; Increase process throughout; Reduce costs for the disposition of Plutonium oxide.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Field Validation of MVA Technology for Offshore CCS: Novel Ultra-High-Resolution 3D Marine Seismic Technology (P-Cable) (Final Report)

The objectives of the proposed study were to deploy and validate a specific monitoring technology, high-resolution 3D marine seismic (HR3D), appropriate for large-demonstration and commercial-scale offshore CCS sites. The project accomplished successful acquisition two HR3D seismic surveys. The first HR3D dataset was over the offshore injection site of the Tomakomai, Japan integrated pilot CCS project, which at the time of survey acquisition was actively injecting CO 2 . The first survey also represented a successful international collaboration between the DOE NETL program and Japan’s national CCS program and was the first successful acquisition and use of HR3D over an active CO 2 injection site (Meckel, Feng et al. 2019). The Tomakomai HR3D survey successfully tested a novel 4-streamer HR3D system array in which, for the first time, no cross-cable (aka “P-Cable”) was utilized and only four GeoEel streamers were used instead of the standard 12-streamer configuration. Consequently, this was not, strictly speaking, a deployment of the “P-Cable” system of (Planke and Berndt 2004) but rather a modified version, thereof, and it is the first known demonstration of the modified system configuration. One very positive outcome from the Japanese collaboration earlier in the project was the ability to learn from the Japanese how they used tail buoys with GPS to determine the position of the seismic source and receivers in time and space. Based on that experience, GCCC designed and built six GPS receivers that could be used to position the streamer receivers and the seismic source via tail buoys. A fundamental advance that was made on the original design, was the ability to directly power the tail buoy GPS units and transfer data through the streamers (i.e., vs. the batteries used at Tomakomai). The bulkiness of the GPS batteries caused drag and episodic surging of the buoys, which affected data quality by lifting up the tail end of the streamers so the receivers were not at the same depth. The units were tested onshore for accuracy and functionality, and the design was subsequently and successfully tested in marine acquisition mode during the SLP survey acquisition. The marine acquisition test and survey satisfied Subtasks 2.2.2, Novel Positioning Technology Selection and Subtask 2.2.3, Novel Positioning Technology Deployment. Results of the novel positioning technology selection (Subtask 2.2.2) were considered successful and will be incorporated in future HR3D seismic acquisition projects to reduce costs, improve deployment safety at sea, and integrate both seismic and data recording via a single data transfer through the streamers to the recording system. The project also established a permitting process through NETL NEPA compliance, which included an Environmental Assessment in a marine setting and is required for conducting these types of surveys using Federal funding. The permitting process charted a “boilerplate,” which can allow future surveys related to other funded projects to move forward more expeditiously. Future improvements that could be considered are more robust seals on the GPS module and stronger materials (especially joints) on tail buoy fabrication. These would increase fixed costs, but would be advisable and probably more economic long-term if multiple HR3D surveys are planned. Project Accomplishments include: • Pre-survey Sensitivity Study • Marine geochemistry methods and data analysis • Successful HR3D seismic dataset acquired @ Tomakomai active CO 2 injection marine site • Developed advanced seismic processing techniques • No NRMS anomalies detected in overburden; Demonstration of containment • Repeatability study • Second survey collected @ San Luis Pass, TX • 4D application using positioning techniques developed in the project for monitoring were successful

3D seismic GPS positioning↗
DOE OSTI2018

Medical diagnoses using three-way fuzzy concept lattice and their Euclidean distance

Searching the closest symptoms of a particular disease in the given patient is a major concern for medical diagnoses expert. In most cases, this problem arises due to large number of incomplete, uncertain, or inconsistent information generated in medical diagnoses data set. Recently, some of the researchers tried to pay attention towards precise measurement of uncertainty and vagueness in medical data set using the properties of applied abstract algebra. In this process, researchers noticed that calculus of three-way decision space is more useful to characterize the uncertainty and vagueness in medical data set based on truth, indeterminacy, and falsity membership-values. However, searching some relevant query based on user requirement to diagnoses the disease is a major issue in three-way decision space. To encounter this problem, current paper tried to analyze the medical data set using the properties of single-valued neutrosophic graph-based concept lattice. In addition, another method is proposed to select some of the interesting three-way fuzzy concepts at user-defined granulation for their computed Euclidean distance with an illustrative example.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Physiological Characterization of Language Comprehension

In this project, our goal was to develop methods that would allow us to make accurate predictions about individual differences in human cognition. Understanding such differences is important for maximizing human and human-system performance. There is a large body of research on individual differences in the academic literature. Unfortunately, it is often difficult to connect this literature to applied problems, where we must predict how specific people will perform or process information. In an effort to bridge this gap, we set out to answer the question: can we train a model to make predictions about which people understand which languages? We chose language processing as our domain of interest because of the well- characterized differences in neural processing that occur when people are presented with linguistic stimuli that they do or do not understand. Although our original plan to conduct several electroencephalography (EEG) studies was disrupted by the COVID-19 pandemic, we were able to collect data from one EEG study and a series of behavioral experiments in which data were collected online. The results of this project indicate that machine learning tools can make reasonably accurate predictions about an individual?s proficiency in different languages, using EEG data or behavioral data alone.

42 ENGINEERING↗
DOE OSTI2024

Materials Characterization, Prediction, and Control Project: Summary Report on Material Characterization, Part 1

The Pacific Northwest National Laboratory (PNNL) undertook the Materials Characterization, Prediction, and Control (MCPC) Laboratory Directed Research and Development Project to advance understanding of nuclear material processing and enable multifold acceleration in the development and qualification of new material systems in national security and advanced energy applications (Smith 2021). The MCPC Project executed research across three scientific vertices—material characterization, predictive modeling, and data analytics—with extensive support by a data curation and management team. The central technical objective in the MCPC Project was to improve the prediction and characterization of the process-structure-property relationships within the microstructurally refined region of stainless-steel samples prepared utilizing friction stir processing (FSP). Application of the FSP technique is well established at PNNL within the Solid Phase Processing capability through many years of investment across a range of materials and applications (PNNL 2024). Three distinct rounds of FSP experiments were performed by the experimental team, producing replicate samples utilizing across different nominal processing conditions (Condition IDs) listed in Table 1. The starting material on which FSP was applied was commercially available unprocessed stainless-steel type 316L material. Chosen processing conditions were very diverse, and some were intentionally chosen to produce defects. Several samples experienced tool breakage during experimentation, so a full set of three replicates was not produced for every nominal processing condition.

36 MATERIALS SCIENCE↗
DOE OSTI2016

iVirus: facilitating new insights in viral ecology with software and community data sets imbedded in a cyberinfrastructure

Microbes affect nutrient and energy transformations throughout the world’s ecosystems, yet they do so under viral constraints. In complex communities, viral metagenome (virome) sequencing is transforming our ability to quantify viral diversity and impacts. Although some bottlenecks, for example, few reference genomes and nonquantitative viromics, have been overcome, the void of centralized data sets and specialized tools now prevents viromics from being broadly applied to answer fundamental ecological questions. Here we present iVirus, a community resource that leverages the CyVerse cyberinfrastructure to provide access to viromic tools and data sets. The iVirus Data Commons contains both raw and processed data from 1866 samples and 73 projects derived from global ocean expeditions, as well as existing and legacy public repositories. Through the CyVerse Discovery Environment, users can interrogate these data sets using existing analytical tools (software applications known as ‘Apps’) for assembly, open reading frame prediction and annotation, as well as several new Apps specifically developed for analyzing viromes. Because Apps are web based and powered by CyVerse supercomputing resources, they enable scalable analyses for a broad user base. Finally, a use-case scenario documents how to apply these advances toward new data. This growing iVirus resource should help researchers utilize viromics as yet another tool to elucidate viral roles in nature.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

MapRE GIS Tools & Data (MapRE)

The MapRE (Multi-criteria Analysis for Planning Renewable Energy) GIS (Geographic Information Systems) Tools are a set of ArcGIS tools to a) conduct site suitability analysis for wind and solar resources using inclusion and exclusion criteria, and create resource maps, b) create project opportunity areas and compute various attributes such as cost, distances to existing and planned infrastructure. and environmental impact factors; and c) calculate and update various attributes for already processed renewable energy zones. In addition, MapRE data sets are geospatial data of renewable energy project opportunity areas and zones with pre-calculated attributes for several countries. These tools and data are available at mapre.lbl.gov.

Deshmukh, Ranjit↗
DOE OSTI2018

Barotropic growth of monsoon depressions

While monsoon depressions are a principal synoptic-scale element of the South Asian monsoon, producing extreme rainfall over India and surrounding regions, there exists no widely accepted mechanism explaining their occurrence. This study presents a hierarchy of numerical experiments aimed at finding such an explanation. Using a perturbation-basic state decomposition, we derive an anelastic system of equations that can represent disturbances growing in the complex, three-dimensional monsoon basic state. We find that modal solutions to these equations linearized about this basic state can explain many features of observed monsoon depressions, including their warm-over-cold core structure, westward propagation, and lower-tropospheric wind maximum. For the zonally symmetric case, these modes are barotropically unstable, drawing energy from the meridional shear of the monsoon trough. For the zonally varying basic state, modal solutions still derive energy from barotropic conversion, but fail to achieve positive net growth rates when dissipative processes are included. For the nonlinear equation set, these modes can be excited by a heating impulse, and their energy then remains roughly constant over several days as barotropic energy transfers oppose dissipative losses. Our conclusions support the idea that the general concept of barotropic instability can explain the structure, propagation, and geographic distribution of monsoon depressions, but not their rapid growth rates. We suggest that condensational heating coupled to these waves is needed to obtain a positive growth rate.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

One-loop analysis of β decays in SMEFT

We perform a loop-level analysis of charged-current (CC) processes involving light leptons and quarks within the Standard Model Effective Field Theory (SMEFT). This work is motivated by the high precision reached in experiment and Standard Model calculations for CC decays of mesons, neutron, and nuclei, and by a lingering tension in the Cabibbo universality test. We identify the SMEFT operators that induce the largest loop-level contributions to CC processes. These include four-quark and four-fermion semileptonic operators involving two third-generation quarks. We discuss the available constraints on the relevant effective couplings and along the way we derive new loop-level bounds from K → πν$\overline{v}$ on four-quark operators involving two top quarks. We find that low-energy CC processes are quite competitive with other probes, set constraints that do not depend on flavor-symmetry assumptions, and probe operators involving third-generation quarks up to effective scales of Λ ≃ 8 TeV. Finally, we briefly discuss single-field ultraviolet completions that could induce the relevant operators.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2018

Multi-approach assessment of the spatial distribution of the specific yield: application to the Crau plain aquifer, France

Spatially distributed values of the specific yield, a fundamental parameter for transient groundwater mass balance calculations, were obtained by means of three independent methods for the Crau plain, France. In contrast to its traditional use to assess recharge based on a given specific yield, the water-table fluctuation (WTF) method, applied using major recharging events, gave a first set of reference values. Then, large infiltration processes recorded by monitored boreholes and caused by major precipitation events were interpreted in terms of specific yield by means of a one-dimensional vertical numerical model solving Richards’ equations within the unsaturated zone. Finally, two gravity field campaigns, at low and high piezometric levels, were carried out to assess the groundwater mass variation and thus alternative specific yield values. The range obtained by the WTF method for this aquifer made of alluvial detrital material was 2.9– 26%, in line with the scarce data available so far. The average spatial value of specific yield by the WTF method (9.1%) is consistent with the aquifer scale value from the hydro-gravimetric approach. In this investigation, an estimate of the hitherto unknown spatial distribution of the specific yield over the Crau plain was obtained using the most reliable method (the WTF method). A groundwater mass balance calculation over the domain using this distribution yielded similar results to an independent quantification based on a stable isotope-mixing model. This agreement reinforces the relevance of such estimates, which can be used to build a more accurate transient hydrogeological model.

58 GEOSCIENCES↗
DOE OSTI2016

Coping with uncertainty in environmental impact assessments: Open techniques

Uncertainty is virtually unavoidable in environmental impact assessments (EIAs). From the literature related to treating and managing uncertainty, we have identified specific techniques for coping with uncertainty in EIAs. Here, we have focused on basic steps in the decision-making process that take place within an EIA setting. More specifically, we have identified uncertainties involved in each decision-making step and discussed the extent to which these can be treated and managed in the context of an activity or project that may have environmental impacts. To further demonstrate the relevance of the techniques identified, we have examined the extent to which the EIA guidelines currently used in Colombia consider and provide guidance on managing the uncertainty involved in these assessments. Some points that should be considered in order to provide greater robustness in impact assessments in Colombia have been identified. These include the management of stakeholder values, the systematic generation of project options, and their associated impacts as well as the associated management actions, and the evaluation of uncertainties and assumptions. We believe that the relevant and specific techniques reported here can be a reference for future evaluations of other EIA guidelines in different countries. - Highlights: • uncertainty is unavoidable in environmental impact assessments, EIAs; • we have identified some open techniques to EIAs for treating and managing uncertainty in these assessments; • points for improvement that should be considered in order to provide greater robustness in EIAs in Colombia have been identified; • the paper provides substantiated a reference for possible examinations of EIAs guidelines in other countries.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Evolution of LIBS technology to mobile instrumentation for expediting firearm-related investigations at the laboratory and the crime scene

Gunshot residue (GSR) is one of the few forensic disciplines that lack accurate screening techniques. This study proposes using a mobile LIBS instrument to detect inorganic GSR and compares performance to a previously validated laboratory instrument. The mobile LIBS is designed with advanced configurations specifically for on-site GSR analysis, including a CMOS detector and a sampling chamber that holds up to six typical GSR collection devices with separate gas flow ports to prevent cross-contamination. A significant novelty of the portable instrument is its image magnification, which allows quick searching and visualization of GSR particle morphology. The single-particle imaging and elemental composition capability is one of a kind and offers superior confirmatory features for GSR. The mobile LIBS performance was evaluated for residues collected from the hands of shooters (100 samples) and non-shooters (200 background samples), analyzed sequentially by the mobile instrument and then the laboratory instrument. Accuracies better than 98.8% were obtained by both instruments, demonstrating their suitability for trace IGSR detection from skin specimens. Implementation of this methodology is anticipated to drastically speed up response times (i.e., from several hours per sample by standard SEM-EDS practice to a few minutes by LIBS). The screening methods can be easily incorporated into workflows to improve decision-making processes at the crime scene and laboratory settings, reduce backlogs, and improve case management.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Imprecise global sensitivity analysis using bayesian multimodel inference and importance sampling

Global Sensitivity Analysis (GSA) aims to understand the relative importance of uncertain input variables to model response. Conventional GSA involves calculating sensitivity (Sobol’) indices for a model with known model parameter distributions. However, model parameters are affected by aleatory and epistemic uncertainty, with the latter often caused by lack of data. In this paper, we propose a new framework to quantify uncertainty in probability model-form and model parameters resulting from small datasets and integrate these uncertainties into Sobol’ index estimates. First, the process establishes, through Bayesian multimodel inference, a set of candidate probability models and their associated probabilities. Imprecise Sobol’ indices are calculated from these probability models using an importance sampling reweighting approach. This results in probabilistic Sobol’ indices, whose distribution characterizes uncertainty in the sensitivity resulting from small dataset size. The imprecise Sobol’ indices thus provide a measure of confidence in the sensitivity estimate and, moreover, can be used to inform data collection efforts targeted to minimize the impact of uncertainties. Through an example studying the parameters of a Timoshenko beam, we show that these probabilistic Sobol’ indices converge to the true/deterministic Sobol’ indices as the dataset size increases and hence, distribution-form uncertainty reduces. The approach is then applied to assess the sensitivity of the out-of-plane properties of an E-glass fiber composite material to its constituent properties. This second example illustrates the approach for an important class of materials with wide-ranging applications when data may be lacking for some input parameters.

42 ENGINEERING↗
DOE OSTI2019

“Teamwork Makes the Dream Work”: Tribal Competition Evolutionary Search as a Surrogate for Free-Energy-Based Structural Predictions

Crystal structure prediction has been a grand challenge in material science owing to the large configurational space that one must explore. Evolutionary (genetic) algorithms coupled with first principles calculations are commonly used in crystal structure prediction to sample the ground and metastable states of materials based on configurational energies. However, crystal structure predictions at finite temperature (T), pressure (P), and composition (X) require a free-energy-based search that is often computationally expensive and tedious. Here in this paper, we introduce a new machine-learning workflow for structure prediction that is based on a concept inspired by the evolution of human tribes in primitive society. Our tribal genetic algorithm (GA) combines configurational sampling with evolutionary optimization to accurately predict entropically stabilized phases at finite (T, P, X), at a computational cost that is an order of magnitude smaller than that required for a free-energy-based search. In a departure from standard GA techniques, the populations of individuals are divided into multiple tribes based on a bond-order fingerprint, and genetic operations are modified to ensure that cluster configurations are sampled adequately to capture entropic contributions. Team competition introduced into the evolutionary process allows winning teams (representing a better set of individuals) to expand their sizes; this translates into a more expanded search of the phase space allowing us to explore solutions near possible global minimum. Each team explores a specific section of the structural phase space and avoids bias on solutions arising from the use of individual populations in a purely energy-based search. We demonstrate the efficacy of our approach by performing the structural prediction of a representative two-dimensional two-body system as well as Lennard-Jones clusters over a range of temperatures up to its melting point. Our approach outperforms the standard GA approaches and enables structural search under “real nonambient conditions” on both bulk systems and finite-sized clusters.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Morphology and CO Oxidation Activity of Pd Nanoparticles on SrTiO 3 Nanopolyhedra

Single crystal SrTiO 3 nanocuboids having primarily TiO 2 -(001) surfaces and nanododecahedra having primarily (110) surfaces were created by two separate hydrothermal synthesis processes. Pd nanoparticles grown on the two sets of STO nanopolyhedra by atomic layer deposition show different morphologies and CO oxidation performance. Transmission electron microscopy and small-angle X-ray scattering show that 2-3 nm Pd nanoparticles with 3-5 nm interparticle distances decorate the STO surfaces. When the number of ALD cycles increases, the growth of the Pd nanoparticles is more significant in size on TiO 2 -(001)-STO surfaces, while that on (110)-STO surfaces is more predominant in number. High resolution electron microscopy images show that single crystal and multiply twinned Pd nanoparticles coexist on both types of the STO nanopolyhedra and exhibit different degrees of adhesion. The CO oxidation reaction, which was employed to determine the dependence of catalytic activity, demonstrated that the Pd catalytic performance was dominated by the coverage of CO, which is more directly related to Pd nanoparticle size than to shape. CO turnover frequency analysis and diffuse reflectance infrared Fourier transform spectroscopy show that regardless of the shape or degrees of wetting, larger Pd nanoparticles (~ 3 nm) have lower catalytic activity due to high CO coverage on nanoparticle facets. Smaller nanoparticles (~ 2 nm) have more edge and corner sites and present 2-3 times higher TOF at 80 and 100 degrees C.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗