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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 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
DOE OSTI2013

Energy levels, radiative rates, and electron impact excitation rates for transitions in Li-like ions with 12≤Z≤20

We report calculations of energy levels, radiative rates, and electron impact excitation rates for transitions in Li-like ions with 12≤Z≤20. The GRASP (general-purpose relativistic atomic structure package) is adopted for calculating energy levels and radiative rates, while for determining the collision strengths and subsequently the excitation rates, the Dirac atomic R-matrix code is used. Oscillator strengths, radiative rates, and line strengths are reported for all E1, E2, M1, and M2 transitions among the lowest 24 levels of the Li-like ions considered. Collision strengths have been averaged over a Maxwellian velocity distribution, and the effective collision strengths obtained are reported over a wide temperature range up to 10{sup 7.4} K. Additionally, lifetimes are also listed for all calculated levels of the ions. Finally, extensive comparisons are made with results available in the literature, as well as with our parallel calculations for all parameters with the Flexible Atomic Code, in order to assess the accuracy of the reported results.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2023

Automated Extraction of Energy Systems Information from Remotely Sensed Data: A Review and Analysis

We report high quality energy systems information is a crucial input to energy systems research, modeling, and decision-making. Unfortunately, actionable information about energy systems is often of limited availability, incomplete, or only accessible for a substantial fee or through a non-disclosure agreement. Recently, remotely sensed data (e.g., satellite imagery, aerial photography) have emerged as a potentially rich source of energy systems information. However, the use of these data is frequently challenged by its sheer volume and complexity, precluding manual analysis. Recent breakthroughs in machine learning have enabled automated and rapid extraction of useful information from remotely sensed data, facilitating large-scale acquisition of critical energy system variables. Here we present a systematic review of the literature on this emerging topic, providing an in-depth survey and review of papers published within the past two decades. We first taxonomize the existing literature into ten major areas, spanning the energy value chain. Within each research area, we distill and critically discuss major features that are relevant to energy researchers, including, for example, key challenges regarding the accessibility and reliability of the methods. We then synthesize our findings to identify limitations and trends in the literature as a whole, and discuss opportunities for innovation. These include the opportunity to extend the methods beyond electricity to broader energy systems and wider geographic areas; and the ability to expand the use of these methods in research and decision making as satellite data become cheaper and easier to access. We also find that there are persistent challenges: limited standardization and rigor of performance assessments; limited sharing of code, which would improve replicability; and a limited consideration of the ethics and privacy of data.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Modeling and Analysis of UN TRISO Fuel for LWR Application Using the PARFUME Code

The Idaho National Laboraroty (INL) PARFUME (particle fuel model) code was used to assess the overall fuel performance of uranium nitride (UN) tristructural isotropic (TRISO) ceramic fuel under irradiation conditions typical of a Light Water Reactor (LWR). The dimensional changes of the fuel particle layers and kernel were calculated, including the formation of an internal gap. The survivability of the UN TRISO particle was estimated depending on the strain behavior of the constituent materials at high fast fluence and burn up. For nominal cases, internal gas pressure and representative thermal profiles across the kernel and layers were determined along with stress levels in the inner and outer pyrolytic carbon (IPyC/OPyC) and silicon carbide (SiC) layers. These parameters were then used to evaluate fuel particle failure probabilities. Results of the study show that the survivability of UN TRISO fuel under LWR irradiation conditions might only be guaranteed if the kernel and PyC swelling rates are limited at high fast fluence and burn up. These material properties have large uncertainties at the irradiation levels expected to be reached by UN TRISO fuel in LWRs. Therefore, a large experimental effort would be needed to establish material properties, including kernel and PyC swelling rates, under these conditions before definitive conclusions can be drawn on the behavior of UN TRISO fuel in LWRs.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2019

A data-driven framework for error estimation and mesh-model optimization in system-level thermal-hydraulic simulation

We report over the past decades, several computer codes have been developed for simulation and analysis of thermal-hydraulics and system response in nuclear reactors under operating, abnormal transient, and accident conditions. However, simulation errors and uncertainties still inevitably exist even while these codes have been extensively assessed and used. In this work, a data-driven framework (Optimal Mesh/Model Information System, OMIS) is formulated and demonstrated to estimate simulation error and suggest optimal selection of computational mesh size (i.e., nodalization) and constitutive correlations (e.g., wall functions and turbulence models) for low-fidelity, coarse-mesh thermal-hydraulic simulation, in order to achieve accuracy comparable to that of high-fidelity simulation. Using results from high-fidelity simulations and experimental data with many fast-running low-fidelity simulations, an error database is built and used to train a machine learning model that can determine the relationship between local simulation error and local physical features. This machine learning model is then used to generate insight and help correct low-fidelity simulations for similar physical conditions. The OMIS framework is designed as a modularized six-step procedure and accomplished with state-of-the-art methods and algorithms. A mixed-convection case study was performed to illustrate the entire framework.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Mechanisms behind impurity spreading in a channeled, long-leg divertor configuration

One suggested benefit of long-leg, tightly baffled divertor configurations, a common feature included in the designs of many next-generation fusion devices, is access to a delocalized “spread” of impurity radiation along the leg, allowing for a substantial radiation region while maintaining both sufficient distance from the core to prevent pollution of the plasma fuel and avoiding local overheating of the plasma-facing materials. However, it is unclear whether this increased connection length and divertor volume afforded by the long-leg configuration is compatible with impurity transport, and whether it will enable this desired impurity radiation spread at all. Here, the SOLPS 4.3 code is used to assess the distribution of nitrogen and neon impurity radiation in a long-leg, tightly baffled divertor geometry. Further, there is a strong correspondence between the distribution of impurity radiation in the long leg and impurity recycling on the divertor side walls with both the nitrogen simulation set and the neon simulation set, suggesting that impurity spreading along these long legs is due to the interplay between the cross-field transport and associated neutralization of the impurity on the material surfaces.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

$\mathrm{T}$ransient $\mathrm{CHI}$ System Design Studies for $\mathrm{P}$ EGASUS -$\mathrm{III}$

We report transient coaxial helicity injection (transient CHI), first developed on the Helicity Injected Torus-II (HIT-II) and later on the National Spherical Torus Experiment (NSTX) for implementing solenoid-free plasma current startup capability in a spherical tokamak (ST), is now planned to be tested on the Pegasus-III ST using a novel double-biased configuration. Such a configuration is likely needed for transient CHI deployment in a reactor. The transient CHI system optimization will be studied on Pegasus-III to enable startup toroidal persisting currents at the limits permitted by the external poloidal field coils. A transient CHI discharge is generated by driving injector current along magnetic field lines that connect the inner and outer divertor plates on one end of the ST. Simulations using the Tokamak Simulation Code are used to assess the transient CHI toroidal current generation potential and electrode gap location on the Pegasus-III. While past transient CHI systems have used high-voltage, oil-filled capacitors for driving the injector current, for improved safety, Pegasus-III will use a high-current capacitor bank based on low-voltage electrolytic capacitors. The designed and fabricated system is capable of over 32 kA. The modular design features permit the system to be upgraded to higher currents, as needed, to meet the future needs of the Pegasus-III facility.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2015

SYNTHESIZED SPECTRA OF OPTICALLY THIN EMISSION LINES PRODUCED BY THE BIFROST STELLAR ATMOSPHERE CODE, INCLUDING NONEQUILIBRIUM IONIZATION EFFECTS: A STUDY OF THE INTENSITY, NONTHERMAL LINE WIDTHS, AND DOPPLER SHIFTS

In recent years realistic 3D numerical models of the solar atmosphere have become available. The models attempt to recreate the solar atmosphere and mimic observations in the best way, in order to make it possible to couple complicated observations with physical properties such as the temperatures, densities, velocities, and magnetic fields. We here present a study of synthetic spectra created using the Bifrost code in order to assess how well they fit with previously taken solar data. A study of the synthetic intensity, nonthermal line widths, Doppler shifts, and correlations between any two of these three components of the spectra first assuming statistical equilibrium is made, followed by a report on some of the effects nonequilibrium ionization will have on the synthesized spectra. We find that the synthetic intensities compare well with the observations. The synthetic observations depend on the assumed resolution and point-spread function (PSF) of the instrument, and we find a large effect on the results, especially for intensity and nonthermal line width. The Doppler shifts produce the reported persistent redshifts for the transition region (TR) lines and blueshifts for the upper TR and corona lines. The nonthermal line widths reproduce the well-known turnoff point around (2–3) × 10{sup 5} K, but with much lower values than those observed. The nonthermal line widths tend to increase with decreasing assumed instrumental resolution, also when nonequilibrium ionization is included. Correlations between the nonthermal line width of any two TR line studies as reported by Chae et al. are reproduced, while the correlations of intensity to line width are reproduced only after applying a PSF to the data. Doppler shift correlations reported by Doschek for the TR lines and correlations of Doppler shift to nonthermal line width of the Fe xii{sub 19.5} line reported by Doschek et al. are reproduced.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

MO-F-CAMPUS-I-03: Tissue Equivalent Material Phantom to Test and Optimize Coherent Scatter Imaging for Tumor Classification

Purpose: To accurately model different breast geometries using a tissue equivalent phantom, and to classify these tissues in a coherent x-ray scatter imaging system. Methods: A breast phantom has been designed to assess the capability of coded aperture coherent x-ray scatter imaging system to classify different types of breast tissue (adipose, fibroglandular, tumor). The tissue-equivalent phantom was modeled as a hollow plastic cylinder containing multiple cylindrical and spherical inserts that can be positioned, rearranged, or removed to model different breast geometries. Each enclosure can be filled with a tissue-equivalent material and excised human tumors. In this study, beef and lard, placed inside 2-mm diameter plastic Nalgene containers, were used as surrogates for fibroglandular and adipose tissue, respectively. The phantom was imaged at 125 kVp, 40 mA for 10 seconds each with a 1-mm pencil beam. The raw data were reconstructed using a model-based reconstruction algorithm and yielded the location and form factor, or momentum transfer (q) spectrum of the materials that were imaged. The measured material form factors were then compared to the ground truth measurements acquired by x-ray diffraction (XRD) imaging. Results: The tissue equivalent phantom was found to accurately model different types of breast tissue by qualitatively comparing our measured form factors to those of adipose and fibroglandular tissue from literature. Our imaging system has been able to define the location and composition of the various materials in the phantom. Conclusion: This work introduces a new tissue equivalent phantom for testing and optimization of our coherent scatter imaging system for material classification. In future studies, the phantom will enable the use of a variety of materials including excised human tissue specimens in evaluating and optimizing our imaging system using pencil- and fan-beam geometries. United States Department of Homeland Security Duke University Medical Center - Department of Radiology Carl E Ravin Advanced Imaging Laboratories Duke University Medical Physics Graduate Program.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

TH-AB-209-12: Tissue Equivalent Phantom with Excised Human Tissue for Assessing Clinical Capabilities of Coherent Scatter Imaging Applications

Purpose: Previously we reported the development of anthropomorphic tissue-equivalent scatter phantoms of the human breast. Here we present the first results from the scatter imaging of the tissue equivalent breast phantoms for breast cancer diagnosis. Methods: A breast phantom was designed to assess the capability of coded aperture coherent x-ray scatter imaging to classify different types of breast tissue (adipose, fibroglandular, tumor). The phantom geometry was obtained from a prone breast geometry scanned on a dedicated breast CT system. The phantom was 3D printed using the segmented DICOM breast CT data. The 3D breast phantom was filled with lard (as a surrogate for adipose tissue) and scanned in different geometries alongside excised human breast tissues (obtained from lumpectomy and mastectomy procedures). The raw data were reconstructed using a model-based reconstruction algorithm and yielded the location and form factor (i.e., momentum transfer (q) spectrum) of the materials that were imaged. The measured material form factors were then compared to the ground truth measurements acquired by x-ray diffraction (XRD) imaging. Results: Our scatter imaging system was able to define the location and composition of the various materials and tissues within the phantom. Cancerous breast tissue was detected and classified through automated spectral matching and an 86% correlation threshold. The total scan time for the sample was approximately 10 minutes and approaches workflow times for clinical use in intra-operative or other diagnostic tasks. Conclusion: This work demonstrates the first results from an anthropomorphic tissue equivalent scatter phantom to characterize a coherent scatter imaging system. The functionality of the system shows promise in applications such as intra-operative margin detection or virtual biopsy in the diagnosis of breast cancer. Future work includes using additional patient-derived tissues (e.g., human fat), and modeling additional organs (e.g., lung).

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Advantages and Limits of Metagenomic Assembly and Binning of a Giant Virus

ABSTRACT Giant viruses have large genomes, often within the size range of cellular organisms. This distinguishes them from most other viruses and demands additional effort for the successful recovery of their genomes from environmental sequence data. Here, we tested the performance of genome-resolved metagenomics on a recently isolated giant virus, Fadolivirus, by spiking it into an environmental sample from which two other giant viruses were isolated. At high spike-in levels, metagenome assembly and binning led to the successful genomic recovery of Fadolivirus from the sample. A complementary survey of the major capsid protein indicated the presence of other giant viruses in the sample matrix but did not detect the two isolated from this sample. Our results indicate that genome-resolved metagenomics is a valid approach for the recovery of near-complete giant virus genomes given that sufficient clonal particles are present. However, our data also underline that a vast majority of giant viruses remain currently undetected, even in an era of terabase-scale metagenomics. IMPORTANCE The discovery of large and giant nucleocytoplasmic large DNA viruses (NCLDV) with genomes in the megabase range and equipped with a wide variety of features typically associated with cellular organisms was one of the most unexpected, intriguing, and spectacular breakthroughs in virology. Recent studies suggest that these viruses are highly abundant in the oceans, freshwater, and soil, impact the biology and ecology of their eukaryotic hosts, and ultimately affect global nutrient cycles. Genome-resolved metagenomics is becoming an increasingly popular tool to assess the diversity and coding potential of giant viruses, but this approach is currently lacking validation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

HIPSTER (Harmonized Impacts across Products, Scenarios, and Technologies for Environmental and Resource metrics) [SWR-24-17]

Development of a prototype, code-based life cycle assessment framework, the Harmonized Impacts across Products, Scenarios, and Technologies for Environmental and Resource metrics (HIPSTER), to coherently assess outputs of prospective NREL models across environmental and resource use metrics. Eventually, HIPSTER is aimed to also cover socioeconomic and justice metrics. At present, NREL model scenario impact assessments are performed incoherently, as they as based on varying assumptions and inputs, specifically life cycle inventories, and cover different system boundaries. HIPSTER was created to align the assumptions and boundaries with those of cradle-to-grave life cycle assessment. In FY22, HIPSTER was successfully applied using scenarios from the ReEDS™ model, NREL's flagship capacity expansion model resulting in cradle-to-grace time-series life cycle impacts across LCA midpoints and resource use metrics.

Ghosh, Tapajyoti↗
DOE OSTI2019

PTBP1 mRNA isoforms and regulation of their translation

Polypyrimidine tract-binding proteins (PTBPs) are RNA binding proteins that regulate a number of posttranscriptional events. Human PTBP1 transits between the nucleus and cytoplasm and is thought to regulate RNA processes in both. However, information about PTBP1 mRNA isoforms and regulation of PTPB1 expression remains incomplete. Here we mapped the major PTBP1 mRNA isoforms in HEK293T cells and identified alternative 5' and 3' untranslated regions (5'-UTRs, 3'-UTRs), as well as alternative splicing patterns in the protein coding region. We also assessed how the observed PTBP1 mRNA isoforms contribute to PTBP1 expression in different phases of the cell cycle. Previously, PTBP1 mRNAs were shown to crosslink to eukaryotic translation initiation factor 3 (eIF3). We find that eIF3 binds differently to each PTBP1 mRNA isoform in a cell cycle dependent manner. We also observe a strong correlation between eIF3 binding to PTBP1 mRNAs and repression of PTBP1 levels during the S phase of the cell cycle. Our results provide evidence of translational regulation of PTBP1 protein levels during the cell cycle, which may affect downstream regulation of alternative splicing and translation mediated by PTBP1 protein isoforms.

3′-UTR↗
DOE OSTI2020

Neutronics Analysis of Cold Critical KRUSTY Experiments using MCNP and Serpent

Kilowatt Reactor Using Stirling Technology (KRUSTY) is a prototype designed as a proof of concept for NASA’s Kilo power program, which was funded in order to create a small reactor for various space applications such as providing power for a colony on Mars or the moon and eventually as a possible option for powering rockets on deep space missions. KRUSTY was tested at the National Criticality Experiments Research Center (NCERC) located at the Nevada National Security Site (NNSS) from November 2017, through March 2018. The experimental campaign was conducted in four phases: com ponent critical experiments, cold critical experiments, warm critical runs, and high temperature demonstration. The component critical and cold critical experiments were used to determine the worth of the beryllium oxide (BeO) reflector rings and the boron carbide (B4C) control rod disks under different conditions. These conditions were altered by the addition and subtraction of other components in the assembly. The component critical phase was performed at atmospheric pressure and had four solid support rods spanning the center core; whereas the cold critical phase had the center core placed in a vacuum chamber and eight sodium-filled heat pipes spanning the center core region. This summary discusses the static neutronic analysis completed on the cold critical phase of the campaign using MCNP ® and Serpent. These two codes were used to assess any potential differences or biases in the simulation results. Understanding these potential biases is a key step toward the final goal of being able to fully analyze the transient experiments performed during phases 3 and 4 of the campaign.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2012

Assessing the Predictive Capability of the LIFEIV Nuclear Fuel Performance Code Using Sequential Calibration

This report considers the problem of calibrating a numerical model to data from an experimental campaign (or series of experimental tests). The issue is that when an experimental campaign is proposed, only the input parameters associated with each experiment are known (i.e. outputs are not known because the experiments have yet to be conducted). Faced with such a situation, it would be beneficial from the standpoint of resource management to carefully consider the sequence in which the experiments are conducted. In this way, the resources available for experimental tests may be allocated in a way that best 'informs' the calibration of the numerical model. To address this concern, the authors propose decomposing the input design space of the experimental campaign into its principal components. Subsequently, the utility (to be explained) of each experimental test to the principal components of the input design space is used to formulate the sequence in which the experimental tests will be used for model calibration purposes. The results reported herein build on those presented and discussed in [1,2] wherein Verification & Validation and Uncertainty Quantification (VU) capabilities were applied to the nuclear fuel performance code LIFEIV. In addition to the raw results from the sequential calibration studies derived from the above, a description of the data within the context of the Predictive Maturity Index (PMI) will also be provided. The PMI [3,4] is a metric initiated and developed at Los Alamos National Laboratory to quantitatively describe the ability of a numerical model to make predictions in the absence of experimental data, where it is noted that 'predictions in the absence of experimental data' is not synonymous with extrapolation. This simply reflects the fact that resources do not exist such that each and every execution of the numerical model can be compared against experimental data. If such resources existed, the justification for numerical models would be reduced considerably. The authors note that the PMI is primarily intended to provide a high-level, quantitative description of year-to-year (or version-to-version) improvements in numerical models, where these descriptions can be used as a means of justifying funding requests to support further model development research. It is in this context that the present report should be considered: the availability of data from experimental tests should be viewed as a time-dependent variable, where experiments are added to the calibration suite as resources become available. For the present report, the experimental data is of course already available (permitting demonstration of the proposed methodology). Furthermore, the authors are not proposing this methodology as the answer to the question of how to allocate resources for experimental tests, and readers are directed to [5] and the references contained in Section 1 of [5] for additional information on the subject. However, the strength of this methodology is that it offers a means by which to select the sequence of experiments in a pre-arranged experimental campaign (a situation for which the methods discussed in [5] are less appropriate). The report is organized as follows. Section 2 describes the methodology employed to formulate the sequences of experiments for the calibrations performed for this study. Section 3 then presents the results associated with two sequences; supplementary results are provided in the Appendix. The report then concludes in Section 4 with a brief summary.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2016

RAVEN Beta Release

This documents the release of the Risk Analysis Virtual Environment (RAVEN) code. A description of the RAVEN code is provided, and discussion of the release process for the M2LW-16IN0704045 milestone. The RAVEN code is a generic software framework to perform parametric and probabilistic analysis based on the response of complex system codes. RAVEN is capable of investigating the system response as well as the input space using Monte Carlo, Grid, or Latin Hyper Cube sampling schemes, but its strength is focused toward system feature discovery, such as limit surfaces, separating regions of the input space leading to system failure, using dynamic supervised learning techniques. RAVEN has now increased in maturity enough for the Beta 1.0 release.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2015

PORFLOW Simulations Supporting Saltstone Disposal Unit Design Optimization

SRNL was requested by SRR to perform PORFLOW simulations to support potential cost-saving design modifications to future Saltstone Disposal Units in Z-Area (SRR-CWDA-2015-00120). The design sensitivity cases are defined in a modeling input specification document SRR-CWDA-2015-00133 Rev. 1. A high-level description of PORFLOW modeling and interpretation of results are provided in SRR-CWDA-2015-00169. The present report focuses on underlying technical issues and details of PORFLOW modeling not addressed by the input specification and results interpretation documents. Design checking of PORFLOW modeling is documented in SRNL-L3200-2015-00146.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2018

IER 489: Critical Unresolved Region Integral Experiment (CURIE) CEDT Phase-2 Final Design

The final design for the CURIE integral benchmark experiment is presented in this report. Measurements will be performed on the Comet vertical assembly machine and include various critical configurations consisting of High Enriched Uranium (HEU) metal plates and Teflon moderator plates surrounded by a thick copper reflector. The various configurations with different Teflon plate thickness planned allow for complimentary measurements with differing nuclear data sensitivity in the Unresolved Resonance Region (URR). Similar to previously performed Zeus experiments, the proposed work will serve to validate vital nuclear data quantities and uncertainties and identify deficiencies in current radiation transport codes. Additionally, it will assess the applicability of optimization approaches to nuclear critical experiment design. The final experiment design is detailed in this report and includes design, optimization, uncertainty and continuous-energy nuclear data sensitivity analysis for the final experimental configurations that will provide the basis for a future benchmark evaluation intended for submission to the International Criticality Safety Benchmark Evaluation Project (ICSBEP) Handbook [1]. This document discusses the method, approach, considerations and final design chosen with conclusions. It also includes cost and schedule. The basis and principles of this document come from the preliminary design report [2]. Section 2 discusses the content and potential impact; section 3 gives an overview of the nuclear data and unresolved resonance region; section 4 gives a summary of the work done during the preliminary design; section 5 discusses the machine learning method and principles used for final design; section 6 summaries the results from final design; section 7 provides conclusions and the range of configurations chosen to carry forward to experiment execution; and section 8 includes a summary of costs.

42 ENGINEERING↗