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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 1,063 records · Page 59
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Analytic image reconstruction from partial data for a single-scan cone-beam CT with scatter correction

Purpose: A beam-blocker composed of multiple strips is a useful gadget for scatter correction and/or for dose reduction in cone-beam CT (CBCT). However, the use of such a beam-blocker would yield cone-beam data that can be challenging for accurate image reconstruction from a single scan in the filtered-backprojection framework. The focus of the work was to develop an analytic image reconstruction method for CBCT that can be directly applied to partially blocked cone-beam data in conjunction with the scatter correction. Methods: The authors developed a rebinned backprojection-filteration (BPF) algorithm for reconstructing images from the partially blocked cone-beam data in a circular scan. The authors also proposed a beam-blocking geometry considering data redundancy such that an efficient scatter estimate can be acquired and sufficient data for BPF image reconstruction can be secured at the same time from a single scan without using any blocker motion. Additionally, scatter correction method and noise reduction scheme have been developed. The authors have performed both simulation and experimental studies to validate the rebinned BPF algorithm for image reconstruction from partially blocked cone-beam data. Quantitative evaluations of the reconstructed image quality were performed in the experimental studies. Results: The simulation study revealed that the developed reconstruction algorithm successfully reconstructs the images from the partial cone-beam data. In the experimental study, the proposed method effectively corrected for the scatter in each projection and reconstructed scatter-corrected images from a single scan. Reduction of cupping artifacts and an enhancement of the image contrast have been demonstrated. The image contrast has increased by a factor of about 2, and the image accuracy in terms of root-mean-square-error with respect to the fan-beam CT image has increased by more than 30%. Conclusions: The authors have successfully demonstrated that the proposed scanning method and image reconstruction algorithm can effectively estimate the scatter in cone-beam projections and produce tomographic images of nearly scatter-free quality. The authors believe that the proposed method would provide a fast and efficient CBCT scanning option to various applications particularly including head-and-neck scan.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2012

Cooking Up Creative Solutions

There comes a time in every scientist’s career when one's mind seems to hit a wall. You can’t think of a new experiment that hasn’t been done before or figure out how to crack a problem that is blocking your progress. The easy questions have been answered. You go back to the wellspring of your creativity and find it dry. What to do? Collaborating with investigators who are investigating problems from a different data or analytical perspective is the best way I know to kick-start research creativity. They not only can provide new data, but they can also bring an expertise on how to get the most “flavor” out of the ingredient that they bring to your problem. As the complexity of the important biological problems continues to grow, too many cooks will never spoil the broth, but become a hallmark of the most creative research.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2019

Backsheets: Correlation of Long-Term Field Reliability with Accelerated Laboratory Testing

Our objective is to develop for backsheets a predictive tests and a model based on point-in-time data from analytical techniques and datastreams that are applicable to both outdoor and indoor PV module backsheet studies and are supplemented with meteorology data, climatic and brand/model, and other accessible information. The predictive tests and models will specify indoor and outdoor exposure and evaluation data acquisition criteria, variable selection, and temporal duration and variation so as to be able to predict backsheet performance in various climatic zones. This backsheet performance prediction is based on defined backsheet failures in the field, and is quantified by tracking backsheet degradation in the field so as to determine degradation rates.

14 SOLAR ENERGY↗
DOE OSTI2020

Assessing Current and Future Infrastructure Hazards

Project Objective Execute intelligent analytics via an advanced analytical framework, to assess the current state of offshore infrastructure, evaluate infrastructure life, and identify technologies to reduce infrastructure hazards, costs, and extend infrastructure life. Approach &amp; Results thus Far• Build comprehensive dataset• Perform data-driven analytics to evaluate infrastructure integrity<p> 1. Remaining lifespan</p><p> 2. Likelihood of future risk</p><p>• Apply data-driven advanced spatial, statistical, and Machine Learning (ML) models to quantify existing infrastructure integrity</p><p>• Release data and models through a smart, online platform hosted by Energy Data eXchange (EDX)</p>

Romeo, Lucy F.↗
DOE OSTI2018

PIPER: Performance Insights for Programmers and Exascale Runtimes

During the lifetime of the project, the PIPER at the University of Utah worked in collaboration with the team from the partner institutions to establish a set of software tools for analyzing and improving the performance parallel computing tools. These activities complement and complete the work performed by the other X-Stack 2 projects with the definition of a common data models and computing infrastructures, which have been a central element in the targeted performance analysis pipeline and new programming models. The University of Utah team have focused mainly on developing data analysis and visualization systems to facilitate exploration, comparison and evaluation of the behavior and performance of complex algorithms in modern HPC infrastructures. This is involved several demonstrations of the performance achieved and presentation of the results in a way that facilitates the users understand bottlenecks and ways to overcome them. One major focus of the University of Utah activities has been the analysis of the performance characteristics of Fat-Tree and Dragonfly topology networks. The work involved the development of practical visualization systems especially in collaboration with the team at LLNL, and published several papers and gave invited talks at prestigious venues such as the Salishan Conference on High-Speed Computing or the International Conference on High Performance Computing, Data, and Analytics. In addition, the university of Utah team has advanced the core activities on analyzing the performance characteristics of I/O and other data movement systems and their practical use for scaling Uintah and other simulation codes poised for use in the exascale computing environments of the future.

42 ENGINEERING↗
DOE OSTI2023

Robust Vector BOTDA Signal Processing with Probabilistic Machine Learning

This paper presents a novel probabilistic machine learning (PML) framework to estimate the Brillouin frequency shift (BFS) from both Brillouin gain and phase spectra of a vector Brillouin optical time-domain analysis (VBOTDA). The PML framework is used to predict the Brillouin frequency shift (BFS) along the fiber and to assess its predictive uncertainty. We compare the predictions obtained from the proposed PML model with a conventional curve fitting method and evaluate the BFS uncertainty and data processing time for both methods. The proposed method is demonstrated using two BOTDA systems: (i) a BOTDA system with a 10 km sensing fiber and (ii) a vector BOTDA with a 25 km sensing fiber. The PML framework provides a pathway to enhance the VBOTDA system performance.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Deep learning interfacial momentum closures in coarse-mesh CFD two-phase flow simulation using validation data

Multiphase flow phenomena have been widely observed in the industrial applications while it remains a challenging yet unsolved problems. Three-dimensional computational fluid dynamics (CFD) approaches resolve the flow fields on a finer special and temporal scales which can complement the dedicated experimental study. However, closures have to be introduced to reflect the underlying physics in multiphase flow. Among them, the interfacial forces, including drag, lift, turbulent dispersion and wall lubrication forces, play in important role on the bubble’s distribution and migration in liquid-vapor two-phase flow. Development of those closures traditionally rely on the experimental data and analytical derivation with simplified assumptions which usually cannot deliver a universal solution across wide range of flow conditions. In this paper, a data-driven approach, named as Feature Similarity Measurement (FSM), is developed and applied to improve the simulation capability of two-phase flow with coarse-mesh CFD approach. Interfacial momentum transfer in adiabatic bubbly flow serves as the focus of the present study. Both a mature and a simplified set of interfacial closures are taken as the low fidelity data. Experimental data and fine mesh CFD simulations results are adopted as high-fidelity data. Qualitative and quantitative analysis are performed in this paper which reveals that FSM can substantially improve the prediction of coarse mesh CFD model regardless of the choice of interfacial closures and it provides scalability and consistency across discontinuous flow regimes. Furthermore, it demonstrates that data-driven method can aid the multiphase flow modeling by exploring the connections between local physical features and simulation errors.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2010

Effect of the thickness of electron beams on the gyrotron efficiency

In this paper the effect of the spread in the radii of electron guiding centers on the gyrotron efficiency is studied. First, the analytical theory is developed for describing this effect in gyrotrons operating in regimes of soft and hard self-excitations. Then, study of this effect in a 670 GHz gyrotron is carried out both analytically and numerically with the use of the available nonstationary self-consistent code. Comparison of results demonstrates very reasonable agreement between numerical data and analytical predictions. It was found that in the case of beam injection at the inner peak of the function describing the beam coupling to the wave the spread in electron guiding center radii can be significantly larger than is usually allowed. This fact greatly alleviates the design of electron guns for terahertz-range gyrotrons.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2012

Design Principles for Effective Knowledge Discovery from Big Data

Big data phenomenon refers to the practice of collection and processing of very large data sets and associated systems and algorithms used to analyze these massive datasets. Architectures for big data usually range across multiple machines and clusters, and they commonly consist of multiple special purpose sub-systems. Coupled with the knowledge discovery process, big data movement offers many unique opportunities for organizations to benefit (with respect to new insights, business optimizations, etc.). However, due to the difficulty of analyzing such large datasets, big data presents unique systems engineering and architectural challenges. In this paper, we present three sys- tem design principles that can inform organizations on effective analytic and data collection processes, system organization, and data dissemination practices. The principles presented derive from our own research and development experiences with big data problems from various federal agencies, and we illustrate each principle with our own experiences and recommendations.

Architecture↗
DOE OSTI2021

Structural characterization of HIV-1 matrix mutants implicated in envelope incorporation

During the late phase of HIV-1 infection, viral Gag polyproteins are targeted to the plasma membrane (PM) for assembly. Gag localization at the PM is a prerequisite for the incorporation of the envelope protein (Env) into budding particles. Gag assembly and Env incorporation are mediated by the N-terminal myristoylated matrix (MA) domain of Gag. Nonconservative mutations in the trimer interface of MA (A45E, T70R, and L75G) were found to impair Env incorporation and infectivity, leading to the hypothesis that MA trimerization is an obligatory step for Env incorporation. Conversely, Env incorporation can be rescued by a compensatory mutation in the MA trimer interface (Q63R). The impact of these MA mutations on the structure and trimerization properties of MA is not known. In this study, we employed NMR spectroscopy, X-ray crystallography, and sedimentation techniques to characterize the structure and trimerization properties of HIV-1 MA A45E, Q63R, T70R, and L75G mutant proteins. NMR data revealed that these point mutations did not alter the overall structure and folding of MA but caused minor structural perturbations in the trimer interface. Analytical ultracentrifugation data indicated that mutations had a minimal effect on the MA monomer–trimer equilibrium. The high-resolution X-ray structure of the unmyristoylated MA Q63R protein revealed hydrogen bonding between the side chains of adjacent Arg-63 and Ser-67 on neighboring MA molecules, providing the first structural evidence for an additional intermolecular interaction in the trimer interface. These findings advance our knowledge of the interplay of MA trimerization and Env incorporation into HIV-1 particles.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Simple analytical model for fitting QENS data from liquids

The advent of new generation of neutron spectrometers for quasielastic scattering measurements has demonstrated the need for multi-component (at least two-component) fitting of data collected from liquids. The narrowest component is associated with long-range translational diffusion, whereas the broader component originates from localized center-of-mass motions in the transient cage of the nearest neighbors. Intra-particle dynamics (e.g., of molecular side groups) may give rise to additional components besides the center-of-mass motions. We present a simple analytical model for two-component fits of quasielastic neutron scattering data collected from liquids. Here, the use of such models is optional (albeit helpful) in the traditional approach, where fits are performed sequentially and independently for the data collected at separate Q values, but imperative in the global fitting, where the data are fitted simultaneously at all Q values, which may be necessary to rationalize the data from increasingly complex systems.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Data Assimilation for Robust UQ Within Agent-Based Simulation on HPC Systems

Agent-based simulation provides a powerful tool for in silico system modeling. However, these simulations do not provide built-in methods for uncertainty quantification (UQ). Within these types of models a typical approach to UQ is to run multiple realizations of the model then compute aggregate statistics. This approach is limited due to the compute time required for a solution. When faced with an emerging biothreat, public health decisions need to be made quickly and solutions for integrating near real-time data with analytic tools are needed. We propose an integrated Bayesian UQ framework for agent-based models based on sequential Monte Carlo sampling. Given streaming or static data about the evolution of an emerging pathogen this Bayesian framework provides a distribution over the parameters governing the spread of a disease through a population. These estimates of the spread of a disease may be provided to public health agencies seeking to abate the spread. By coupling agent-based simulations with Bayesian modeling in a data assimilation, our proposed framework provides a powerful tool for modeling dynamical systems in silico. We propose a method which reduces model error and provides a range of realistic possible outcomes. Moreover, our method addresses two primary limitations of ABMs: the lack of UQ and an inability to assimilate data. Our proposed framework combines the flexibility of an agent-based model with UQ provided by the Bayesian paradigm in a workflow which scales well to HPC systems. We provide algorithmic details and results on a simulated outbreak with both static and streaming data.

Spannaus, Adam [ORNL] (ORCID:0000000225213657)↗
DOE OSTI2019

Spectral and Microclimate Measurements in Relation to Gold-Standard Methods Field Campaign Report

Arable is an agricultural data and analytics company offering an Internet of things (IOT)-enabled irrigation management tool, weather station, and crop monitor: the Arable Mark. The device synthesizes both climate and plant data to produce actionable insights on natural resource management, mainly commercial agriculture at any scale. Arable collected 11 months of microclimate and radiometric data at the U.S. Department of Energy’s Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) observatory to compare measurements of the Arable Mark to the ARM-SGP gold-standard sensors, and for demonstrating the ease of installation and system value to stakeholders. A member from Arable labs installed the device on January 10, 2018, at the ARM facilities and the site managers were in charge of maintaining the sensors in a clean state until the unit’s removal on January 15, 2019. The sampling was positively uneventful, except for a period during the winter when the device stopped posting data for about one week. The verdict was that the equipment required an external solar panel to stay powered through the shorter days of winter. A solar panel was shipped to the SGP, and the unit came back to full charge to continue sending data for the rest of the sampling period. The main goal of the project is to use the data collected by the Arable Mark and build a model that can establish a close relationship with the current methodologies applied to measure ecosystem response to environmental changes. During the sampling period, our team discovered that there was a drift in some of the meteorological data and also in the radiometry, so all efforts are focused into the development of models that would reduce the errors in the reported values.

Southern Great Plains, evapotranspiration, photosy↗
DOE OSTI2021

Tailored Fiber Placement for Complex Preforms

Tailored Fiber Placement (TFP) offers a novel approach to optimize fiber architecture for the fabrication of complex, structural parts not traditionally suitable for advanced composites. This technology not only offers new routes for weight reduction via metal substitution, it also offers cost reduction through minimization of material scrap and reduced labor. This reduction in component weight leads to increased fuel efficiency, and reduced production energy consumption, thereby, helping to achieve the stated IACMI technical goals. This technology leverages centuries of manufacturing development in support of the textile and embroidery industry. One major drawback to this technology is the lack of commercial or non- proprietary structural performance data and robust analytical tools used to optimize fiber architecture and predict performance. This project was structured to utilize common sub-element features to validate analytical performance tools, generate performance data, and gather cost and performance data on components of interest. This project was designed to give industry sponsors the confidence and ability to take full advantage of TFP to fabricate primary, highly loaded structure and integrate features such as metallic fasteners. The project focused principally on the use of high strength carbon fiber, such as T700, and the use of aerospace epoxy resin matrix to primarily support development of new composite applications in vehicle, aerospace, and industrial markets. This project applied previously developed analytical tools to predict the performance of TFP produced parts. This work focused on developing the pipeline to characterize material in order to accurately predict component performance when modifying the TFP print paths and stitch density. This focused on experimental characterization via standardized ASTM testing, alongside experimental testing of more representative service components by testing curved beam strength, beam shear performance, a large scale TFP lug, and ultimately designing a fully TFP clip bracket that reduced weight and cost compared to a traditional metallic component. The new knowledge gained from this program included: 1) development and demonstration of novel analytical tools applied to analysis of TFP preforms; 2) development and demonstration of a building block approach using coupons and sub-elements to optimize the design of a more complex component; 3) demonstration that optimized fiber orientation using TFP can exceed performance of conventional textile composite materials and can open new applications currently limited to metallic components; 4) Demonstration of performance and cost benefits of the TFP process as compared to metallic and conventional textile composites. Recommendations for follow-on work include development of design allowables to assess the impact of high temperature/moisture exposure or saturation during loading, tracking the impact of stitching needle wear on the performance of parts and ability to stitch thicker preforms, using TFP preforms as local reinforcement at areas of bearing or complex loading, and topology optimization of components by tow steering. The expertise developed during the course of this project can be leveraged to provide commercial engineering design and fabrication services using TFP. UDRI is in the process of formalizing their partnership with Spintech, who will serve as the commercialization partner for this technology and provide molding services and deliver finished components to the end user. UDRI will continue to produce the preforms until the economics allow Spintech to procure its own TFP equipment or lease UDRI equipment, at which point UDRI will step away from manufacture and serve as the engineering and design lead on product development.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Storage and Read-Optimized Data Placement Structures for High-Performance Analysis [Book Chapter]

Here, we present state-of-art structures and methods for efficient data preparation and representation for analysis. Our intent is to introduce the data science and analytics communities to open source data placements, structures, and methods. These practices can make the foundational processes of data preparation and access dramatically more efficient than typical raw file or database representations and use more conservative storage. To illustrate this, we introduce two highly efficient data placement structures. We then present a tutorial, supported by step-by-step examples, of how to create, use, and access data, structured by Parquet or ORC (Optimized Row Columnar), using Apache Spark. Finally, we illustrate the benefits of using these structures with computational and storage volume benchmarks.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2012

Measures of soil, sediment, and groundwater background used by Los Alamos National Laboratory, 2012

This document summarizes approaches used by Los Alamos National Laboratory (LANL) to estimate background concentrations of constituents in soils, sediment, and groundwater. For the sake of presentation and interpretation, LANL frequently reports a “background value” that statistically represents an upper bound for a data set of background concentrations. However, actual background concentrations vary by soil and bedrock type, disturbance regimes, precipitation levels, vegetative cover, and a wide variety of other factors. The LANL reported background values are estimates for comparison, not absolute limits of possible background concentrations. In evaluating whether a sample result represents a background concentration, LANL staff evaluate the results statistically (if the sample size is large enough) or graphically against the complete distribution of the relevant background data set. For analytes with no established background data set, LANL site results are sometimes compared to upgradient or geographically distant results on a study-specific basis.

Environmental Protection↗
DOE OSTI2020

Current–Induced Ion Concentration Polarization at a Perfect Ion–Exchange Patch in an Infinite Insulating Wall

This research examines theoretically the ion concentration polarization, ion fluxes, and electrostatic fields near an ion exchange patch in the wall of an electrified fluidic channel. These phenomena are important in related microfluidic ion-preconcentration systems. Under an electric field, counterions enter the ion-exchange patch at one side and leave at the other, with salt depletion occurring near the entrance and accumulation near the exit. Furthermore, the high patch conductivity and the concentration profiles lead to local electric field perturbations that may facilitate preconcentration. This study includes analytical expressions of ion concentrations and electrochemical potentials at small to moderate electric fields, as well as numerical simulations. Additionally, a simple matrix of polynomial coefficients (obtained via fitting of numerical data) enables analytical calculation of the 2-dimensional concentration profiles at all electric fields within the range investigated in the numerical simulations. This is possible because a single dimensionless parameter controls this problem.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗