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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 1,117 records · Page 62
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Dose Rate Evaluation for the ES-3100 Package with HEU Content Using MCNP, ADVANTG, Monaco, and MAVRIC

This paper presents a comparative study of dose rate calculations for the ES-3100 package with highly enriched uranium (HEU) content for different source configurations using computer codes: (1) MCNP; (2) Automated Variance Reduction Generator (ADVANTG)/MCNP; (3) Monaco; and (4) Monaco with Automated Variance Reduction using Importance Calculations (MAVRIC). The Model ES-3100 package was developed at the Y-12 National Security Complex for domestic and international transportation of Type B fissile radioactive material. In this study, six different source configurations (i.e., solid cylinder, cylindrical hemi-shell, cylindrical shell, rectangular plate, cylindrical rod, or cylindrical segment form) having 36 kg of HEU metal inside the package containment vessel (based on configurations in the ES-3100/HEU safety analysis report for packaging) are evaluated. Dose rates at the package surfaces and 1 m from the package surfaces are calculated for these different source configurations. MCNP and Monaco cases are run without any biasing options to accelerate the convergence. Consistent Adjoint Driven Importance Sampling (CADIS) and Forward-Weighted CADIS (FW-CADIS) methods developed at the Oak Ridge National Laboratory are implemented in ADVANTG/MCNP and MAVRIC codes to accelerate the convergence. ADVANTG generates variance reduction parameters using Denovo code, and MCNP is used with the variance reduction parameters to accelerate the convergence. MAVRIC uses Denovo code to construct an importance map and a biased source distribution that are supplied to Monaco to accelerate the Monte Carlo simulation. The FW-CADIS option in ADVANTG and MAVRIC is used to accelerate the convergence in this study. The accelerated convergence cases (ADVANTG/MCNP and MAVRIC) are about 100 times faster with 100 times less particle simulation than those cases run without biasing options (analog MCNP and analog Monaco). The MCNP, ADVANTG/MCNP, Monaco, and MAVRIC calculated dose rates at the package surfaces and at 1 m from the package surfaces for the different source configurations are compared and are found to be in general agreement.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2018

Effects of Exhaust Gas Recirculation (EGR) on Turbulent Combustion and Emissions in Advanced Gas Turbine Combustors with High-Hydrogen-Content (HHC) Fuels (Final Report)

This Final Report documents the entire four years of the Cooperative Agreement DE-FE0011822, from October 1, 2013 through September 30, 2017, that was competitively awarded under Funding Opportunity Announcement DE-FOA-0000795 in support of the U.S. Department of Energy’s (DOE) National Energy Technology Laboratory (NETL) University Turbine Systems Research (UTSR) Program. Under the UTSR Program, DOE typically issues Funding Opportunity Announcement (FOA) solicitations every 1-2 years so that U.S. colleges/universities may propose research & development (R&D) projects in specific technical topic areas (e.g., combustion, aerodynamics/heat transfer, advanced materials) that have been identified as both scientifically and industrially relevant to the gas turbine industry. The primary objectives of this Purdue University project (in collaboration with Princeton University through a sub-award) was to develop experimental methods, kinetic models, and numerical tools to help quantify and predict the impact of exhaust gas recirculation (EGR) on NOx and CO emissions, combustion kinetics, radiation heat transfer, turbulent combustion, and combustion instabilities for natural gas and high hydrogen content (HHC) fuels by using laminar and turbulent flow reactors and gas turbine combustors operating at high temperatures and pressures. This project has obtained detailed data for improving chemical kinetic models to study EGR effects and provide insight into the effects of EGR on flame speeds and turbulent flame structure, as well as assessing the impact of EGR on emissions in a high-pressure combustion test rig. The project was divided into six primary tasks: 1) Project Management and Program Planning; 2) Flow Reactor Investigation of EGR Chemical Kinetics; 3) Combustion Bomb Investigation of EGR Effects on Flame Speed; 4) Investigation of EGR Effects on Turbulent Flame Structure in Reactor-Assisted Turbulent Slot (RATS) Burner; 5) Investigation of EGR Effects in Purdue Staged Combustion Test Rig; and 6) Development and Validation of a Large Eddy Simulation (LES) Tool for Gas Turbine Combustion and Emission Modeling using HHC Fuels. Details on the execution and results of each of these tasks are provided in the main report. To assist the reader, each task is described in a chapter-like format with its own separate listing of tables, figures, and references so that the results of each task/subtask (i.e., technical sections covering various experiments and modeling work focused on a specific area) can be quickly obtained while also getting an overall feel of the project execution. This chapter-like format also allows for acknowledgement of support from other programs relative to specific tasks. In this manner, the reader can more conveniently digest the R&D results in the various task/subtask sections that may be of most interest to the reader. In addition to this Final Report, the Purdue/Princeton team was able to publish 7 journal articles and provide 7 presentations at national scientific meetings/conferences to disseminate results. A listing of these journal articles and presentations is provided at the end of this report

03 NATURAL GAS↗
DOE OSTI2020

COVID-19 biomarkers based on respiratory microbiome content

COVID-19 patient care management would greatly benefit from new tools that enable accurate assessment of disease severity and stage, potentially enabling a personalized medicine approach. Detection of the SARS-CoV-2 virus itself, or even quantitation of viral loads, is not sufficient for accurate assessment of disease state beyond diagnosis of infection [eg, doi:10.1093/cid/ciaa344]. Levels of usual suspect protein biomarkers associated with host response to infection [eg, C-reactive protein (CRP); cytokines like IL-6, TNF-alpha, and IL-10; complement proteins like C3a and C5a], and of individual blood cell types (eg, leukocytes, lymphocytes, and subsets thereof), show limited correlation with disease severity and stage, with high patient-to-patient and study-to-study variability [eg, doi:10.1093/cid/ciaa248]. High-dimensional panels of biomarkers should have greater predictive power and resilience to unavoidable sources of variability; however, their assembly from proteins and cell types is extremely difficult, due to technical limitations in analyte measurement, especially with regard to starting material requirements and detection sensitivity. Host response profiling through Next Generation Sequencing (NGS) of gene expression patterns (ie, RNA-Seq) is a promising approach, but at the time of this project there were only two publicly available datasets of relevance [doi:10.1093/cid/ciaa203, doi:10.1080/22221751.2020.1747363], and close inspection of them revealed that each had at least one major flaw that severely undermined its value in supporting robust analysis of host response to SARS-CoV- 2 infection. However, the first of these studies [doi:10.1093/cid/ciaa203] fortuitously collected NGS data not only from host cells, but also from bacteria present in bronchoalveolar lavage fluid (BALF) recovered from COVID-19 patients; and because the respiratory microbiome (in terms of bacterial species content) is far less complex than the human transcriptome, the NGS data collected were sufficient to provide coverage depth supporting robust analysis. Surprisingly, the authors of the study did not carry out a detailed analysis of these data and their potential for revealing important new information about COVID-19. Therefore, we carried out a meta-analysis of the dataset as a first step in evaluating the potential for profiling of respiratory microbiome dynamics as a means of accurately assessing COVID-19 disease state.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Update to Waste Form Performance Constraints and OWL Status and Inventory Content. Draft

This report provides (1) an updated set of inputs (Sections 1 through 4) on various additional waste forms (WF) for the generic Defense Waste Repository (DWR) inventory represented in the generic disposal system analyses (GDSA); (2) summaries of evaluations initiated to refine particular characteristics of particular WF for future use (Section 5); and (3) status updates (Section 6) for the Online Waste Library (OWL) inventory content, data entry checking process, and external OWL BETA testing initiated in fiscal year 2017. As such, this report represents completion of both deliverables M3SF-17SNO10501022 (SFWD-SFWST-2017-000047 — this actual report) and M4SF-17SN010501012 (SFWD-SFWST-2017- 000112 — to be completed by reference to the first milestone report in the PICSNE system).

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2018

Glass Compositions and Properties of Enhanced Waste Glass with High Alumina Content for High-Level Waste

This report documents the work performed to collect critical property data on high-level waste (HLW) glasses with high alumina content. This report covers the experimental results of thermal, physical, chemical, and electrical properties of 46 high alumina (15 to 30 wt%) borosilicate waste-glass compositions with one duplicate for a total of 47 glasses. These experimental results are essential for developing property-composition models for the future operation of the Waste Treatment and Immobilization Plant (WTP) currently under construction at the Hanford Site in Richland, Washington. Pacific Northwest National Laboratory (PNNL) was requested by the U.S. Department of Energy’s Office of River Protection to provide expert evaluation and experimental work in support of the vitrification technology development program.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Uranium-Titanium Alloys: The Effect of Ti Content on Phase Transformations, Microstructures, and Mechanical Properties

This report documents the findings of collaborative research done at Sandia National Laboratory and the Y-12 Development Division during the 1980s. Ongoing progress reports were presented at various U. S. Department of Energy (DOE) meetings throughout the 1980s, but the findings were never integrated into an inclusive final report. This report provides a summary of the key findings and implications of this research. This work was supported by the DOE National Nuclear Security Administration. The effect of titanium content on phase transformations, microstructures, and mechanical properties of uranium-titanium alloys has been investigated in alloys containing 0.3 wt.% to 2.0 wt.% Ti.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Analysis of wave mode content in fully turbulent, moderately collisional plasma laboratory experiment and kinetic simulation. Final Report

A final report of the activities of Bryn Mawr College for award DE-SC0018258. The major goal for the project is to make magnetic and Langmuir-probe-based density fluctuations measurements using identical diagnostic and acquisition setups on two different laboratory-based turbulent plasma devices: SSX at Swarthmore College and a new plasma source in development at Bryn Mawr College (BMX). We propose to generate single-point correlation and k-filtering metrics using these experimental measurements. These metrics will be compared directly to kinetic simulations of the experimental environments in order to determine wave mode content of the laboratory turbulence.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Collaborative Research: Analysis of wave mode content in fully turbulent, moderately collisional plasma laboratory experiment and kinetic simulation

Our major goal for the project is to make magnetic and Langmuir-probe-based density fluctuations measurements using identical diagnostic and acquisition setups on two different laboratory-based turbulent plasma devices: SSX at Swarthmore College and a new plasma source in development at Bryn Mawr College (BMX). We propose to generate single-point correlation and k-filtering metrics using these experimental measurements. These metrics will be compared directly to kinetic simulations of the experimental environments in order to determine wave mode content of the laboratory turbulence.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Analysis of wave mode content in fully turbulent, moderately collisional plasma laboratory experiment and kinetic simulation

Our major goal for the project was to make magnetic field and plasma density fluctuation measurements using identical diagnostic and acquisition setups on two different laboratory-based turbulent plasma devices: SSX at Swarthmore College and a new plasma source in development at Bryn Mawr College (BMX). We used single-point correlation and k-filtering metrics using these experimental measurements. These metrics were compared to kinetic simulations of the experimental environments in order to determine wave mode content of the laboratory turbulence.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Determination of the uranium content of storage containers filled with waste from Fukushima using cosmic ray data

This report presents the results of an experimental study of cosmic ray tomography aimed at determining the uranium contents of waste containers filled with waste from Fukushima. Data, taken using the Giant Muon Tracker, were obtained on a set of scenes constructed from blocks of polyethylene, concrete, iron, and lead. The data have been provided to Toshiba and have been used to evaluate the composition of scenes using multivariate linear regression.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Real-Time, Simultaneous Soil Water Content and Meteorological Data Measurement to Support TRACER over Harris County, Texas (Field Campaign Report: Part I)

The main purpose of this project was to provide ground-truth and satellite-based soil water content data in the Houston, Texas, area to support the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility’s 2022 field campaign, the Tracking Aerosol Convection Interactions ExpeRiment (TRACER). This involved installing four soil monitoring stations at different locations in the Houston area, two of which were part of the ARM facility and two were ancillary. The two stations associated directly with ARM were installed alongside other facilities managed and maintained by the TRACER research team during the intensive operational period (IOP), one located at the La Porte, Texas airport and the other near Guy, Texas. Data from these stations were assimilated with similar data collected by the Harris County Flood Control District (HCFCD) to improve the spatial coverage of the real-time monitoring network. The ground-truth data were compared to the satellite-based (National Aeronautics and Space Administration [NASA]’s Soil Moisture Active Passive [SMAP] mission) data in the TRACER area of interest, and analyzed further to nowcast gridded data over the Houston area. The nowcasted, gridded data product was made available to TRACER researchers for use in climate and land-atmosphere interaction modeling that can help understand formation and persistence of convective storms in dense urban areas, and predict possible environmental events such as floods.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Determination of Biogenic Content by 14 C in fuels using Liquid Scintillation Analysis Laboratory Analytical Procedure (Laboratory Analytical Procedure)

This procedure covers the determination of the percent 14 C in biogenic gasoline, jet fuel, and diesel range hydrocarbons prepared from distillation of hydrotreated pyrolysis oils and blended with fossil derived hydrocarbons (e.g. fossil diesel, gasoline, jet, or toluene). Either an internal 14C standard or a color quench curve is used to correct for potential signal quenching effects. Recent publications provide some background of direct LSC methods used for determination of biogenic fuel content.

02 PETROLEUM↗
DOE OSTI2023

Discerning Deception: An Empirically-Driven Agent-Based Model of Expert Evaluation of Scientific Content

Both human subject experiments and computational, modeling and simulations have been used to study detection of deception. This work aims to combine these two methods by integrating empirically-derived information (from human subject experiments) into agent-based models to generate novel insights into the complex problems of detection of disinformation content. Computational experiments are used to simulate across multiple scenarios for evaluation and decision-making regarding the validity of potentially deceptive scientific documents. Factors influencing the human agent behaviors in the model were identified through a human subject experiment that was conducted to evaluate and characterize decision making related to disinformation discernment. Correlation and regression analyses were used to translate insights from the human subjects experiment to inform the parameterization of agent features and scenario development. Three scenarios were evaluated with the agent-based models to help evaluate the replicability of the simulations (validation analysis) and assess the influence of human agent and document features (sensitivity analyses). A replication of the human participant experiment demonstrated that the agent-based simulations compare favorably to empirical findings. The agent-based modeling was then used to conduct sensitivity analysis on the accuracy of deception detection as a function of document proportions and human agent features. Results indicate that precision values are adversely impacted when the proportion of deceptive documents is lower in the overall sample, whereas recall values are more sensitive to changes in human agent features. These findings indicate important nuances in accuracy evaluations that should be further considered (including consideration of potential alternate metrics) in future agent-based models of disinformation. Additional areas for future exploration include extension of simulations to consider other ways to align the agent-based model design with psychological theory and inclusion of agent-agent interactions, especially as it pertains to sharing of scientific information within an organizational context.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

Methodology for Determination of Cellulosic Glucans and Hemicellulose Content in a Fuel Ethanol Production Facility (CRADA Final Report)

Develop a single methodology for determination of the total cellulosic glucan, including both cellulose and beta-glucans, along with hemicellulose content in corn kernel fiber which could be utilized by the dry grind corn ethanol production industry to determine the cellulosic converted fraction of the corn kernel fiber. The work will build upon a methodology already described in literature but will specifically focus on a more complete determination of the structural polysaccharides in corn kernel fiber to make it more applicable to the corn ethanol industry.

09 BIOMASS FUELS↗
DOE OSTI2025

Using Separation-Enhanced Isotope Ratio Mass Spectrometry to Enable Increased Renewable Carbon Content in Transportation Fuels (CRADA 525)

Stable isotope ratio measurements of carbon atoms using isotope ratio mass spectrometry (IRMS) can be an effective tool for quantifying biogenic carbon in co-processed fuels, with results approaching the precision and accuracy of accelerator mass spectrometry (AMS). The lower cost of an IRMS may enable deployment to refineries, improving access and analysis turnaround times (≤2 hours), and, by extension, provide data that can allow process optimization to maximize renewable carbon in desired refinery products. This project explored the integration of chemical separation with IRMS analyses to enable highly detailed tracking of biogenic carbon into fuel product streams separated by boiling point range, chemical class, or specific compound. Forty-nine fuels and fuel components of fossil and biogenic origin, spanning gasoline and diesel boiling point ranges, were received from three refiners and were analyzed for their δ 13 C values via IRMS. Results spanned a 13 C range from ca. 10‰ to 44‰ and reflect materials derived from sustainable sources (e.g., C4 or C3 plants, animal-based pathways, syngas) or from fossil-derived fuels. Common ranges are approximately 18‰ to 9‰ and approximately 30‰ to 20‰ for C4 and C3 plants, respectively, and approximately 34‰ to 24‰ and approximately 70‰ to 33‰ for petroleum-derived fuels and methane, respectively. Fuel-like standards were developed and tested using direct-injection elemental analyzer (EA) IRMS for liquid fuels. This method was compared with the published methods, yielding statistically similar results. Four blend curve sets were produced ranging from 0% to 100% of a fuel containing biogenic carbon, focusing on 0% to 10% biogenic carbon. Linear fits were the most applicable for two of the four blend curve sets; however, two sets were found to exhibit slightly quadratic behavior, which was more pronounced in low biogenic blend samples, necessitating second-order fits. The origin of the slight quadratic behavior remains unclear; however, the discussion points to possible interpretations. CanmetENERGY thoroughly characterized a majority of the samples using one- and two-dimensional gas chromatography (GC and GC×GC, respectively) and other analyses. Selected samples were subjected to solid phase extraction (SPE) for saturate, olefin, aromatic, and polar (SOAP) analysis, and the resulting solvent-diluted fractions containing saturates and aromatics were returned to Pacific Northwest National Laboratory (PNNL), where the solvent was removed via evaporation or physical separation using GC techniques. Characterization and separations provided an understanding of saturate and aromatic content, as well as boiling point ranges for each sample and sample fraction. Samples resulting from SPE were examined using EA-IRMS and gas chromatography combustion IRMS (GC-C-IRMS) analyses. Both approaches suggest that the range in values between end-members can be increased by selecting the paraffinic or aromatic fraction of the end-member or by selecting among individual compounds resulting from GC separation of the paraffinic fractions. Considerable work remains to put these approaches into practice and statistically validate the benefit for using a fraction or individual compound over bulk analysis of a sample. However, initial results suggest that separations provide advantages for samples having blend ratios of less than 10% biogenic blendstocks. 13 C results showed statistically similar biofuel blend results to those obtained at PNNL, although additional work is needed to obtain better reproducibility. Select samples were sent to Los Alamos National Laboratory (LANL) for IRMS measurements and Beta Analytics for AMS measurements. This work suggests that IRMS and AMS yield closely comparable results and in some circumstances, IRMS could serve as a surrogate for AMS. While additional work is needed to better resolve statistical advantages for separations and better show the comparable nature of IRMS and AMS in both the biogenic carbon analysis of bulk chemical classes, initial results from this study suggest that these should be pursued in order to proliferate this approach for quantifying biogenic carbon in transportation fuels to the refinery level, thereby potentially enabling process optimization in co-processing scenarios.

09 BIOMASS FUELS↗