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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 OSTI2021

A resource of lipidomics and metabolomics data from individuals with undiagnosed diseases

Every year individuals experience symptoms that remain undiagnosed by healthcare providers. In the United States, these rare diseases are defined as a condition that affects fewer than 200,000 individuals. However, there are an estimated 7000 rare diseases, and there are an estimated 25–30 million Americans in total (7.6–9.2% of the population as of 2018) affected by such disorders. The NIH Common Fund Undiagnosed Diseases Network (UDN) seeks to provide diagnoses for individuals with undiagnosed disease. Mass spectrometry-based metabolomics and lipidomics analyses could advance the collective understanding of individual symptoms and advance diagnoses for individuals with heretofore undiagnosed disease. Here, we report the mass spectrometry-based metabolomics and lipidomics analyses of blood plasma, urine, and cerebrospinal fluid from 148 patients within the UDN and their families, as well as from a reference population of over 100 individuals with no known metabolic diseases. The raw and processed data are available to the research community so that they might be useful in the diagnoses of current or future patients suffering from undiagnosed disorders.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

The Chemical and Products Database, a resource for exposure-relevant data on chemicals in consumer products

Quantitative data on product chemical composition is a necessary parameter for characterizing near-field exposure. This data set comprises reported and predicted information on more than 75,000 chemicals and more than 15,000 consumer products. The data’s primary intended use is for exposure, risk, and safety assessments. The data set includes specific products with quantitative or qualitative ingredient information, which has been publicly disclosed through material safety data sheets (MSDS) and ingredient lists. A single product category from a refined and harmonized set of categories has been assigned to each product. The data set also contains information on the functional role of chemicals in products, which can inform predictions of the concentrations in which they occur. These data will be useful to exposure and risk assessors evaluating chemical and product safety.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

A new Gaussian MCTDH program: Implementation and validation on the levels of the water and glycine molecules

We report the main features of a new general implementation of the Gaussian Multi-Configuration Time-Dependent Hartree model. The code allows effective computations of time-dependent phenomena, including calculation of vibronic spectra (in one or more electronic states), relative state populations, etc. Moreover, by expressing the Dirac-Frenkel variational principle in terms of an effective Hamiltonian, we are able to provide a new reliable estimate of the representation error. After validating the code on simple one-dimensional systems, we analyze the harmonic and anharmonic vibrational spectra of water and glycine showing that reliable and converged energy levels can be obtained with reasonable computing resources. The data obtained on water and glycine are compared with results of previous calculations using the vibrational second-order perturbation theory method. Additional features and perspectives are also shortly discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

COBRA-SFS thermal-hydraulic analysis code for spent fuel storage and transportation casks: Models and methods

COBRA-SFS, a thermal-hydraulics code developed for steady-state and transient analysis of multi-assembly spent-fuel storage and transportation systems, has been incorporated into the Used Nuclear Fuel-Storage, Transportation and Disposal Analysis Resource and Data System tool as a module devoted to spent fuel package thermal analysis. This paper summarizes the basic formulation of the equations and models used in the COBRA-SFS code, showing that COBRA-SFS fully captures the important physical behavior governing the thermal performance of spent fuel storage systems, with internal and external natural convection flow patterns, and heat transfer by convection, conduction, and thermal radiation. Of particular significance is the capability for detailed thermal radiation modeling within the fuel rod array.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2017

Shielding Analysis Capability of UNF-ST&DARDS

The Used Nuclear Fuel Storage, Transportation and Disposal Analysis Resource and Data System (UNF-ST&DARDS) is used to perform dose rate calculations for spent nuclear fuel (SNF) transportation packages based on the actual physical and nuclear characteristics (i.e., assembly design, burnup, initial enrichment, and cooling time) of the as-loaded SNF. Nuclear fuel data, transportation package model templates, and SNF canister loading map information residing within the tool facilitate automated generation of SCALE input files for radiation source term and dose rate calculations. Transportation package specific models developed for UNF-ST&DARDS dose rate analyses are described in detail. UNF-ST&DARDS dose rate analyses were performed in this paper for over 400 SNF canisters from 16 sites in their designated transportation casks. For simplicity, representative dose rate calculation results are presented as a function of time (i.e., selected calendar years between 2020 and 2100) for 73 SNF canisters in dry storage at four sites. For these canisters, the projected maximum dose rate values at 2 m from the lateral surfaces of the vehicle under normal conditions of transport (NCT) would vary between 1.9 and 11.5 mrem/h in 2020. Five SNF canisters will exceed the regulatory dose rate limit of 10 mrem/h at 2 m in 2020, and the analyzed SNF canisters will comply with regulatory dose rate limits by 2030. An analysis of the impact on the dose rate of fuel failure and reconfiguration during transportation indicated that the maximum dose rate for hypothetical accident conditions will be unaffected, and the NCT maximum dose rate at 2 m would have a maximum increase by a factor of 1.7 for a representative pressurized water reactor package and by a factor of 2.6 for a representative boiling water reactor package relative to intact fuel. Finally, analysis of the actual heat loading and the dose rate at 2 m from the lateral surface of the vehicle for the five SNF canisters exceeding the NCT regulatory dose rate limit of 10 mrem/h in 2020 showed that the dose rate could be more limiting with respect to regulatory requirements than the heat loading; i.e., the canister transportability date may be evaluated based on the transportation package’s external dose rate.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2017

UNF-ST&DARDS Unified Database and the Automatic Document Generator

The U.S. Department of Energy, Office of Nuclear Energy is sponsoring development of a database to store information related to spent nuclear fuel (SNF) in support of its Spent Fuel and Waste Disposition efforts. This database, referred to as the Unified Database (UDB), is part of a larger engineering analysis tool, the Used Nuclear Fuel Storage, Transportation & Disposal Analysis Resource and Data System (UNF-ST&DARDS). The UDB provides a comprehensive, controlled source of SNF information, including dry cask attributes, assembly data, economic attributes, transportation infrastructure attributes, potential future facility attributes, and federal government radioactive waste attributes. There are a number of existing and envisioned data reports that can be expected to use data stored within the UDB; however, previously, there was not a streamlined method to couple the database to such data reports. Therefore, to streamline the creation of these reports, two methods were developed to generate documents from information in the database automatically. The first method used Java and LaTeX for automatically generating the report, and the second method used the Python programming language along with Sphinx, a Python documentation generator. There are some advantages and disadvantages to both approaches, but both methods produced equally high-quality, automatically generated reports that were directly coupled to the database. Finally, this study describes data currently available in the UDB; explains the two different methods for automatically generating reports from these data; and shows examples of inline text, figures, and tables automatically generated using both approaches.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2017

Thermal Analysis Capability of UNF-ST&DARDS

In the United States, approximately 2,500 casks are loaded with commercial spent nuclear fuel (SNF) that has transitioned from wet storage (spent fuel pools) to dry storage. The number of loaded dry storage casks is increasing by approximately 200 each year. Over time, cask designs have evolved to enhance safety and to accommodate more fuel and higher heat loads. Also, higher burnup fuel is being transitioned into dry storage. The SNF is being stored in dry casks for longer times than specified in the original certification period. Several degradation mechanisms related to fuel assemblies and canisters are affected by temperature. For the cladding, temperature-dependent phenomena include creep and annealing, hydride reorientation and embrittlement, and the ductile-to-brittle transition. Temperature can also influence phenomena that affect the long-term integrity of the storage system, including deliquescence, corrosion, and stress-corrosion cracking. Therefore, accurate determination of the temperatures of various components is needed to evaluate potential safety-related issues during transportation after extended storage and to ensure SNF retrievability. The Used Nuclear Fuel-Storage, Transportation & Disposal Analysis Resource and Data System (UNF ST&DARDS) is being developed for the US Department of Energy Office of Nuclear Energy to streamline analyses for the waste management system [1]. Lastly, the thermal analysis capability within UNF-ST&DARDS and example results are discussed herein.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2017

Containment Analysis Capability of UNF-ST&DARDS

The Used Nuclear Fuel-Storage, Transportation & Disposal Analysis Resource and Data System (UNF-ST&DARDS) methodology to perform automated containment analyses for potential transportation packages based on canister loading map information is described in this paper, and its capability is illustrated with example results. The allowable leakage rate is calculated with the procedures provided in ANSI N14.5-2014 and NUREG/CR-6487, which were adapted for containment analysis of a transportation package containing fuel assemblies with different nuclear characteristics (e.g., initial enrichment, burnup, and cooling time) and clad integrity (intact or damaged). UNF-ST&DARDS applies different source term calculation methodologies for low-burnup fuel (LBF) (i.e., <45 GWd/tonne U) assemblies and high-burnup fuel (HBF) (i.e., ≥45 GWd/tonne U) assemblies. The LBF radionuclide activities are based on actual fuel assembly burnup, initial enrichment, and cooling time. Bounding radionuclide activities based on a fuel pellet burnup value of 65 GWd/tonne U and actual fuel assembly cooling time are used for HBF assemblies. The fraction of failed fuel rods and the release fractions for the contributors to releasable source terms recommended in NUREG-1617 are used in the containment analysis regardless of fuel assembly burnup. However, UNF-ST&DARDS supports different parameter values for LBF and HBF assemblies. Finally, the containment analysis methodology for as-loaded transportation packages is presented in detail, and the UNF-ST&DARDS containment analysis capability is illustrated with results for simulated transportation packages containing spent nuclear fuel canisters in dry storage at selected sites.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2017

Additional Capability Being Developed from UNF-ST&DARDS Unified Database: System Analysis and Fuel Cycle Option Analysis

The Used Nuclear Fuel Storage, Transportation & Disposal Analysis Resource and Data System (UNF-ST&DARDS) is being developed for the U.S. Department of Energy’s Office of Nuclear Energy by the national laboratories. An important part of UNF-ST&DARDS is the Unified Database (UDB), which contains information that can support a variety of activities including fuel storage, fuel transportation, and disposal-related system analysis. Currently, the main application of the UDB is to support evaluation of the characteristics of discharged spent nuclear fuel (SNF) from the U.S. commercial reactors. However, because of the extensive amount of data that has been collected and analyzed for UNF-ST&DARDS, there are many more applications that can utilize the UDB including system analysis with the Next-Generation System Analysis Model (NGSAM) and fuel cycle analysis with fuel cycle simulation codes such as ORION. Going forward, NGSAM and fuel cycle transition analysis with ORION integrate UDB data wherever possible in the UDB’s development plan. Finally, these advances in NGSAM and fuel cycle analysis can be used in conjunction with the UDB to help answer more complex questions about the optimization, utilization, storage, and eventual disposal of SNF.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2017

As-Loaded Criticality Margin Assessment of Dual-Purpose Canisters Using UNF-ST&DARDS

A novel assessment has been completed in this paper to determine the previously unquantified and uncredited criticality margin available in as-loaded commercial spent nuclear fuel (SNF) canisters. This assessment was performed as part of a broader effort to assess issues and uncertainties with storage, subsequent transportation, and final disposal of SNF canister systems. Detailed analyses crediting the burnup, initial enrichment, and postirradiation cooling time of actual SNF inventory were performed for 554 SNF canisters stored at 23 commercial reactor sites to determine realistic criticality safety margins. These detailed analyses were automated by the Used Nuclear Fuel-Storage, Transportation & Disposal Analysis Resource and Data System (UNF-ST&DARDS), a comprehensive, integrated data and analysis tool. Calculated, uncredited criticality margins (Δk eff ) with respect to the safety analysis results range from 0 to almost 0.30 Δk eff for normal storage and transportation cases. Calculated eigenvalues (k eff ) range from 0.72 to 1.11 assuming a degraded neutron absorber disposal condition, and they range from 0.94 to 1.20 assuming a degraded basket disposal condition. Calculations with NaCl present in the moderator (which is possible for certain disposal geologies) were used to demonstrate the possibility for subcriticality for degraded cases with a k eff above 0.98 with freshwater. The methods used to calculate k eff for the canisters analyzed in this work are discussed in detail. The results demonstrate that, for the majority of canisters analyzed here, significant uncredited safety margin is available that could be used to compensate for uncertainties in the SNF assembly and canister internal components. These uncertainties are associated with long-term storage and subsequent transportation and disposal. Results also suggest that the inherent margins associated with how canisters are loaded could support future changes in licensing SNF storage and transportation systems to directly or indirectly credit the margins associated with actual SNF characteristics. Finally, ongoing research continues to gather additional data to quantify uncredited safety margins for SNF canisters loaded at other nuclear reactor sites and to explore potential methods for applying this uncredited margin.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2016

WarpIV: In situ visualization and analysis of ion accelerator simulations

The generation of short pulses of ion beams through the interaction of an intense laser with a plasma sheath offers the possibility of compact and cheaper ion sources for many applications--from fast ignition and radiography of dense targets to hadron therapy and injection into conventional accelerators. To enable the efficient analysis of large-scale, high-fidelity particle accelerator simulations using the Warp simulation suite, the authors introduce the Warp In situ Visualization Toolkit (WarpIV). WarpIV integrates state-of-the-art in situ visualization and analysis using VisIt with Warp, supports management and control of complex in situ visualization and analysis workflows, and implements integrated analytics to facilitate query- and feature-based data analytics and efficient large-scale data analysis. WarpIV enables for the first time distributed parallel, in situ visualization of the full simulation data using high-performance compute resources as the data is being generated by Warp. The authors describe the application of WarpIV to study and compare large 2D and 3D ion accelerator simulations, demonstrating significant differences in the acceleration process in 2D and 3D simulations. WarpIV is available to the public via https://bitbucket.org/berkeleylab/warpiv. The Warp In situ Visualization Toolkit (WarpIV) supports large-scale, parallel, in situ visualization and analysis and facilitates query- and feature-based analytics, enabling for the first time high-performance analysis of large-scale, high-fidelity particle accelerator simulations while the data is being generated by the Warp simulation suite. Furthermore, this supplemental material https://extras.computer.org/extra/mcg2016030022s1.pdf provides more details regarding the memory profiling and optimization and the Yee grid recentering optimization results discussed in the main article.

43 PARTICLE ACCELERATORS↗
DOE OSTI2016

MOLNs: A Cloud Platform for Interactive, Reproducible, and Scalable Spatial Stochastic Computational Experiments in Systems Biology Using PyURDME

Computational experiments using spatial stochastic simulations have led to important new biological insights, but they require specialized tools and a complex software stack, as well as large and scalable compute and data analysis resources due to the large computational cost associated with Monte Carlo computational workflows. The complexity of setting up and managing a large-scale distributed computation environment to support productive and reproducible modeling can be prohibitive for practitioners in systems biology. This results in a barrier to the adoption of spatial stochastic simulation tools, effectively limiting the type of biological questions addressed by quantitative modeling. In this paper, we present PyURDME, a new, user-friendly spatial modeling and simulation package, and MOLNs, a cloud computing appliance for distributed simulation of stochastic reaction-diffusion models. In conclusion, MOLNs is based on IPython and provides an interactive programming platform for development of sharable and reproducible distributed parallel computational experiments.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Data for "Land-based Resources for Engineered Carbon Dioxide Removal in the United States Exceed the Expected Needs"

Gigatonne-scale atmospheric carbon dioxide removal (CDR), alongside deep emission cuts, is critical to stabilizing the climate. However, some of the most scalable CDR technologies are also the most land intensive. Here, we examine whether adequate land resources exist in the contiguous United States to meet CDR targets when prioritizing grid emissions reduction, food production, and the protection of sensitive ecosystems. We focus on biomass carbon removal and storage (BiCRS) and direct air capture and storage (DACS) and show that suitable lands exceed the expected needs: 37.6 million hectares of land are available for BiCRS, resulting in 0.26 GtCO2 of CDR/year, and 34 million hectares are suitable for wind- and solar-powered DACS, resulting in 4.8 GtCO2 of CDR/year if facilities are co-located with geologic CO2 storage. We identify biomass and energy supply hotspots to meet CDR targets while ensuring land protection and minimizing land competition.

carbon↗
DOE OSTI2017

Tularosa Basin Play Fairway Analysis: Raw MT Data for the McGregor Range, Fort Bliss, New Mexico

This is a zipped file containing raw magnetotelluric (MT) data collected as part of the Phase 2 Tularosa Basin geothermal play fairway analysis project in New Mexico. The data for each MT station are in standard .edi text files which are accompanied by graphic files illustrating details. These data cover part of McGregor Range, Fort Bliss, New Mexico. The MT survey was done by Quantec Geoscience.

15 GEOTHERMAL ENERGY↗
DOE OSTI2018

Utah FORGE: Earth Model Mesh Data for Selected Surfaces

This submission contains a number of data files with vertices of meshed/interpolated surfaces used in the Phase 2B earth model. Examples include land surface (based on 10-meter DEM), the granitoid-basin fill contact, several faults, and also interpolated temperature isosurfaces for 175 and 225 degrees C. All data are georeferenced to UTM, zone 12N, NAD 83, NAVD 88.

15 GEOTHERMAL ENERGY↗
DOE OSTI2019

Utah FORGE: Wells Wow2 and Wow3 Groundwater Monitoring Data

This dataset includes ground water level data for Utah FORGE Phase 2c ground water monitoring wells Wow2 and Wow3. The readme file explains the fields contained in the included Excel spreadsheet and contains the coordinates for the wells. The Excel spreadsheet contains raw data taken directly from downhole transducers and includes fields labeled Date, Time, LEVEL, and TEMPERATURE.

15 GEOTHERMAL ENERGY↗
DOE OSTI2016

Accuracy of genomic prediction in switchgrass ( Panicum virgatum L.) improved by accounting for linkage disequilibrium

Switchgrass is a relatively high-yielding and environmentally sustainable biomass crop, but further genetic gains in biomass yield must be achieved to make it an economically viable bioenergy feedstock. Genomic selection (GS) is an attractive technology to generate rapid genetic gains in switchgrass, and meet the goals of a substantial displacement of petroleum use with biofuels in the near future. In this study, we empirically assessed prediction procedures for genomic selection in two different populations, consisting of 137 and 110 half-sib families of switchgrass, tested in two locations in the United States for three agronomic traits: dry matter yield, plant height, and heading date. Marker data were produced for the families’ parents by exome capture sequencing, generating up to 141,030 polymorphic markers with available genomic-location and annotation information. We evaluated prediction procedures that varied not only by learning schemes and prediction models, but also by the way the data were preprocessed to account for redundancy in marker information. More complex genomic prediction procedures were generally not significantly more accurate than the simplest procedure, likely due to limited population sizes. Nevertheless, a highly significant gain in prediction accuracy was achieved by transforming the marker data through a marker correlation matrix. Our results suggest that marker-data transformations and, more generally, the account of linkage disequilibrium among markers, offer valuable opportunities for improving prediction procedures in GS. Furthermore, some of the achieved prediction accuracies should motivate implementation of GS in switchgrass breeding programs.

59 BASIC BIOLOGICAL SCIENCES↗