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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Collaboration 51 Correlation Function Analysis Suite (c51_corr_analysis) v0.1.0

This is a data analysis package designed for analyzing correlation functions generated with lattice QCD calculations. The purpose is to make a centralized software suite for use by all members of my collaboration, so that various members can spend less time developing their own analysis codes, and more time extracting the interesting physics from our calculations. There are also 3 independent collaborations that have expressed interest in using this code, so there is some expectation it will be used in the broader international lattice QCD community.

Walker-Loud, Andre↗
DOE OSTI2022

Uncertainty quantification in elastic constants of SiC f /SiC m tubular composites using global sensitivity analysis

Silicon carbide fiber and silicon carbide matrix (SiC f /SiC m ) tubes produced through the chemical vapor infiltration process have become a candidate cladding material in nuclear applications. The performance of this composite is influenced by many variables such as braiding angle, porosity, material properties, etc., which vary over a range of values due to the inherent fluctuations in the manufacturing process. In this study, the variability in elastic constants of SiC f /SiC m composite has been quantified through multiscale finite element (FE) simulations, variable screening, and high-fidelity surrogate modeling. The key variables dominantly affecting the elastic constants of SiC f /SiC m tubes were identified using global sensitivity analysis. A surrogate to the high-fidelity FE-based model was used in Monte Carlo simulations to generate a hundred thousand samples from which the uncertainty in elastic constants was assessed. It turned out that the coefficient of variation was less than 10%.

Materials Science↗
DOE OSTI2020

A terminology for in situ visualization and analysis systems

The term "in situ processing" has evolved over the last decade to mean both a specific strategy for visualizing and analyzing data and an umbrella term for a processing paradigm. The resulting confusion makes it difficult for visualization and analysis scientists to communicate with each other and with their stakeholders. To address this problem, a group of over 50 experts convened with the goal of standardizing terminology. This paper summarizes their findings and proposes a new terminology for describing in situ systems. An important finding from this group was that in situ systems are best described via multiple, distinct axes: integration type, proximity, access, division of execution, operation controls, and output type. This paper discusses these axes, evaluates existing systems within the axes, and explores how currently used terms relate to the axes.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Round Robin Analysis of Uranium Isotopics on Cotton Swipes Measured Using Microextraction-Based Sampling Versus Conventional Bulk Analysis

A comparison of microextraction sampling methods to directly analyze uranium isotopics on cotton swipes was performed concurrently with traditional bulk-processing methods. For the microextraction sampling approach, two different detection platforms were evaluated, a quadrupole-based inductively coupled plasma mass spectrometer (ICP-MS) and the liquid sampling-atmospheric pressure glow discharge (LS-APGD) coupled to an Orbitrap mass spectrometer. Results presented from this innovative sampling approach (i.e., microextraction) are compared with a more traditional approach employed for analysis of cotton-based environmental swipes, namely bulk ashing/digestion, separation, and subsequent analysis by high-precision multi-collector ICP-MS. Overall, the microextraction approach proved to be a reliable and accurate means to determine isotopic ratios of uranium collected on cotton swipes. The ICP-MS-based detection had relative standard deviations of <0.65% for the major isotopic determinations, whereas the LS-APGD-Orbitrap method had relative standard deviations of <3%. The percent relative difference for the 235 U/ 238 U ratios, in comparison to the expected values, was <1% for ICP-MS and <4% for the microplasma-Orbitrap method. Additionally, the microextraction ICP-MS accurately (<2%) and precisely (<5%) determined the minor isotopic compositions (i.e., 234 U/ 238 U and 236 U/ 238 U).

ICP-MS↗
DOE OSTI2026

Data for A Fluorescence-Based Transient Expression Assay for the Analysis of Upstream Open Reading Frames in Plants

Scripts for the manuscript "A fluorescence-based transient expression assay for the analysis of upstream open reading frames in plant" by Haas et al. Upstream open reading frames (uORFs) are regulatory elements present in the 5′ leaders of mRNA that can significantly impact downstream gene expression in eukaryotes. In crop engineering, editing of uORFs can provide an avenue to upregulate expression of native genes without the need to add persistent transgenic copies. Even with genome- wide methods to identify translated uORFs such as ribosome profiling, their functional characterization depends on validation through reporter gene assays and mutagenesis studies. Current screening methods for plants use luciferases or protoplasts to measure differential gene expression between wild- type and mutated transcript leaders, which requires tissue processing and/or substrate addition. Here, we present a time- and cost- efficient alternative to investigate transcript leaders by co- expression of two fluorescent proteins in Nicotiana benthamiana leaf tissue and test our assay on genes involved in photoprotection, editing of which could provide a pathway to increase CO2 assimilation during sun–shade transitions.

Gene Editing↗
DOE OSTI2026

Data for Spatial Analysis of Cell Patterning to Aid Genetic and Phenotypic Understanding of Grass Stomatal Density: A Case Study in Maize

Biological processes involve complex hierarchies where composite traits result from multiple component traits. However, holistically understanding of how sets of component traits interact to underpin genotype-to-phenotype relationships is generally lacking. Stomatal density (SD) is a tractable model system for exploring how high-throughput phenotyping (HTP) data could be exploited by a new spatial analysis approach to better understand a developmentally and functionally important trait. SD is a composite trait, resulting from various components related to cell identity and size, which are themselves governed by a series of spatio-developmental processes. Data from 192 recombinant inbred lines of maize [Zea mays (L.)] were analyzed by a new stomatal patterning phenotype (SPP) to (1) describe the average spatial probability distribution of the nearest neighboring stomata; (2) derive a core set of component traits related to cell size, cell packing, and positional probabilities; (3) build a structural equation model of component traits underlying SD; and (4) identify stomatal patterning quantitative trait loci (QTL). The core set of SPP-derived traits explained 74% of the variation in SD. Analyzing SPP component traits allowed some loci previously identified as generic SD QTL to be recognized as specific to lateral versus longitudinal elements of stomatal patterning. Therefore, this study highlights how novel insights can be gained by decomposing a composite trait (e.g., SD) into a set of component traits that were present in HTP data but not previously exploited.

AI/ML↗
DOE OSTI2026

Data for Rewiring Yeast Metabolism for Producing 2,3-Butanediol and Two Downstream Applications: Techno-Economic Analysis and Life Cycle Assessment of Methyl Ethyl Ketone (MEK) and Agricultural Biostimulant Production

Rising concerns for sustainability and global climate change have driven the development of sustainable production pathways for biofuels and chemicals from lignocellulosic biomass via integrated biological and chemical processes. We constructed an engineered Saccharomyces cerevisiae capable of producing 2,3-butanediol (2,3-BDO) from glucose without accumulating ethanol and glycerol, which hinder downstream processing of 2,3-BDO, through extensive metabolic reprogramming. Specifically, we introduced heterologous 2,3-BDO biosynthetic enzymes and deleted the major isozymes of ethanol and glycerol biosynthetic enzymes. In addition, we introduced an NAD+ regenerating Pyruvate-Malate (PM) cycle and enhanced the NAD+ regenerating capability of the PM cycle to resolve the redox imbalance from the deletion of ethanol and glycerol production pathways. The resulting engineered yeast produced 109.9 g/L of 2,3-BDO with a productivity of 1.0 g/L/h and a yield of 0.36 g/g glucose in a fed-batch fermentation. We also conducted techno-economic analysis (TEA) and life cycle assessment (LCA) of the production of methyl ethyl ketone (MEK) through catalytic dehydration of 2,3-BDO. A TEA based on the experimental results indicated that the minimum product selling price (MPSP) was estimated to be $1.90/kg. Regarding cradle-to-grave LCA, 100-year global warming potential (GWP100) and fossil energy consumption (FEC) were found to be 0.37 kg CO2 eq/kg and 3.1 MJ/kg, respectively. These results demonstrated the feasibility of cost-competitive and sustainable bio-based MEK production via yeast fermentation. In addition, we explored the possibility of using the fermentation broth containing 2,3-BDO as a biostimulant inducing drought tolerance in plants. As a result, the yeast 2,3-BDO fermentation broth can induce drought tolerance in Arabidopsis thaliana without a complicated purification process.

Economics↗
DOE OSTI2026

Performing Numerical Analysis of Cybersecurity Options Using Dynamic Risk Analysis Tool EMRALD

Cyberattacks can have many different attack paths, durations, and goals. There are also many different mitigation options involving hardware, software, and/or humans. Considering a cyber threat should involve defense-in-depth methods and a quantitative or numerical evaluation of overall effectiveness against dynamic, time-dependent attacks to make cost and risk-informed decisions. Typical cyberattack modeling methods only provide a qualitative evaluation. The main areas of cybersecurity are confidentiality, integrity, and availability. For companies with cyber-physical systems such as advanced nuclear reactors, cyber-related safety is a requirement set by North American Electric Reliability and the U.S. Nuclear Regulatory Commission. They are also concerned about availability or reliability as a business case. As cyber threats are evolving to a business-for-hire structure, more attacks may focus on disrupting business success and reliability, causing financial and economic stability risk. Companies want to know business reliability and recovery from those threats, and that requires modeling physical behavior of the targets. Dynamic-state-based and Markov-based modeling provides a method for better cyber scenario modeling with different tools having issues such as state-base explosion. Dynamic modeling enables time and conditional features not found in other numerical evaluation methods. EMRALD (Event Modeling Risk Assessment using Lined Diagrams) is a dynamic risk analysis modeling and simulation tool and has features that reduce modeling issues. It has been used to model different time-dependent events including plant behavior and operator procedures. As a general modeling tool, EMRALD can also be used to model cyberattack scenarios with varying mitigation options and quantify effectiveness, producing numerical data for risk-informed decisions. This paper uses EMRALD to demonstrate that dynamic numerical risk analysis can be used for cyber threat modeling to provide insights for design decision-making and optimize defense strategies. Keywords: cyber modeling; cyber-physical systems; numerical cyber modeling

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2020

CO₂ Storage prospeCtive Resource Estimation Excel aNalysis (CO₂-SCREEN) User’s Manual

This user’s manual guides the use of the National Energy Technology Laboratory’s (NETL) CO₂ Storage prospeCtive Resource Estimation Excel aNalysis (CO₂-SCREEN) tool, which was developed to aid users screening geologic formations for prospective CO₂ storage resources. This manual is specific to the CO₂-SCREEN 4.0 version which is based in Python. CO₂-SCREEN applies U.S. Department of Energy (DOE) methods and equations for estimating prospective CO₂ storage resources for saline formations, shale formations, and residual oil zones (ROZ). CO₂-SCREEN was developed to be substantive and user-friendly and provide a consistent method for calculating prospective CO₂ storage resources. CO₂-SCREEN uses a Java based graphical user interface for data inputs and uses Python to calculate prospective CO₂ storage resources.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Experimental and Simulation Analysis of Binary Mixtures of Biomass and Inert Material

A literature review was conducted to identify experiments on various scales of biomass combustion specific to circulating fluidized bed (CFB) combustors. Typical feedstock and inert bed material characteristics for biomass combustion in a CFB were gathered. This information was used to design laboratory-scale, non-reacting experiments on biomass-inert bed material mixtures in a 1-in. cylindrical test rig in the Multiphase Flow Analysis Laboratory (MFAL) in Morgantown, WV. The biomass chosen was a hardwood. Pellets from the hardwood were milled and sieved to obtain three size ranges—small, medium, and large. Three mass loadings of each of the biomass samples were fluidized with glass beads as the inert bed material to study the mixing characteristics under varying fluidizing gas velocities. Hydrodynamic data including pressure drop measurements at select vertical locations and video recordings of the mixture behavior were generated in this effort.

09 BIOMASS FUELS↗
DOE OSTI2021

Jaynesian Analysis of Environmental Chemistry: Systems Model Component Integration via the Arctic Aquatic Carbon Cycle

Focal Areas: All three are touched upon from the OBER call. We will consider formal logical inference and entropic information analysis for sparse but intensive chemical measurements, as optimal drivers for managing process complexity. As a centerpiece for the discussion we take soil-to-sea organic structural evolution within the Arctic hydro-geochemosphere, assessing detrital negentropy then algorithmic greed to generate ranked, reduced mechanisms for system integration.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Hanford Site Composite Analysis Special Analysis: P2R Model Predictive Contaminant Transport Simulations - Sensitivity Case

This environmental calculation file (ECF) documents the methodologies, assumptions, and results of predictive fate and transport simulations using the Plateau-to-River (P2R) model. This ECF supports the reevaluation of the representativeness of solid-waste radionuclide inventory and release rate from three solid waste sites included in the recently completed Hanford Site Composite Analysis (CA) (DOE-RL-2019-52, Composite Analysis for Low-Level Waste Disposal in the Hanford Site Central Plateau (FY 2020)). Specifically, this ECF supports the reevaluation of the representativeness of the base case inventory and radionuclide waste release rates from three solid waste sites (i.e., 218-E-12B, 218-W-3A and 218-W-3AE) and two radionuclides (carbon-14 [C-14] and technetium [Tc-99]). These three waste sites and two radionuclides were identified as being the most significant contributors to groundwater contamination and dose in the CA at time periods after the compliance period. The release rates and footprints of the releases from the vadose zone are implemented in the fate and transport modeling utilizing the HSS package.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Metallic Fuel Performance Analysis for the European Sodium Fast Reactor (ESFR-SIMPLE): Analysis of metallic fuel performance using SAS4A/SASSYS-1 $-$ MFUEL

The European Sodium Fast Reactor - Safety by Innovative Monitoring, Power Level flexibility and Experimental research (ESFR-SIMPLE) project was initiated in 2022 and includes assessment of a metallic-fueled version of the ESFR concept. Argonne National Laboratory (ANL) has been partnering with the ESFR-SIMPLE project to share its expertise on metallic fueled SFR designs and support some of its analysis. This report focuses on metallic fuel behavior analysis for ESFR-SIMPLE design conditions under base irradiation and transients (ULOF and UTOP).

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2023

Workflow for High-throughput Screening of Enzyme Mutant Libraries Using Matrix-assisted Laser Desorption/Ionization Mass Spectrometry Analysis of Escherichia coli Colonies

High-throughput molecular screening of microbial colonies and DNA libraries are critical procedures that enable applications such as directed evolution, functional genomics, microbial identification, and creation of engineered microbial strains to produce high-value molecules. A promising chemical screening approach is the measurement of products directly from microbial colonies via optically guided matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS). Measuring the compounds from microbial colonies bypasses liquid culture with a screen that takes approximately 5 s per sample. We describe a protocol combining a dedicated informatics pipeline and sample preparation method that can prepare up to 3,000 colonies in under 3 h. The screening protocol starts from colonies grown on Petri dishes and then transferred onto MALDI plates via imprinting. The target plate with the colonies is imaged by a flatbed scanner and the colonies are located via custom software. The target plate is coated with MALDI matrix, MALDI-MS analyzes the colony locations, and data analysis enables the determination of colonies with the desired biochemical properties. This workflow screens thousands of colonies per day without requiring additional automation. The wide chemical coverage and the high sensitivity of MALDI-MS enable diverse screening projects such as modifying enzymes and functional genomics surveys of gene activation/inhibition libraries.

Choe, Kisurb↗
DOE OSTI2021

Multi-Omics Driven Metabolic Network Reconstruction and Analysis of Lignocellulosic Carbon Utilization in Rhodosporidium toruloides

An oleaginous yeast Rhodosporidium toruloides is a promising host for converting lignocellulosic biomass to bioproducts and biofuels. In this work, we performed multi-omics analysis of lignocellulosic carbon utilization in R. toruloides and reconstructed the genome-scale metabolic network of R. toruloides . High-quality metabolic network models for model organisms and orthologous protein mapping were used to build a draft metabolic network reconstruction. The reconstruction was manually curated to build a metabolic model using functional annotation and multi-omics data including transcriptomics, proteomics, metabolomics, and RB-TDNA sequencing. The multi-omics data and metabolic model were used to investigate R. toruloides metabolism including lipid accumulation and lignocellulosic carbon utilization. The developed metabolic model was validated against high-throughput growth phenotyping and gene fitness data, and further refined to resolve the inconsistencies between prediction and data. We believe that this is the most complete and accurate metabolic network model available for R. toruloides to date.

09 BIOMASS FUELS↗
DOE OSTI2022

Concentration-response gene expression analysis in zebrafish reveals phenotypically-anchored transcriptional responses to retene

Polycyclic aromatic hydrocarbons (PAHs) are ubiquitous environmental contaminants and are associated with human disease. Canonically, many PAHs induce toxicity via activation of the aryl hydrocarbon receptor (AHR) pathway. While the interaction between PAHs and the AHR is well-established, understanding which AHR-regulated transcriptional effects directly result in observable phenotypes and which are adaptive or benign is important to better understand PAH toxicity. Retene is a frequently detected PAH in environmental sampling and has been associated with AHR2-dependent developmental toxicity in zebrafish, though its mechanism of toxicity has not been fully elucidated. To interrogate transcriptional changes causally associated with retene toxicity, we conducted whole-animal RNA sequencing at 48 hours post-fertilization after exposure to eight retene concentrations. The concentrations were selected to produce effects ranging from no phenotype to mortality and malformations in 100% of animals at 5 days post-fertilization. We identified a concentration-response relationship between retene teratogenicity and differential gene expression in both number of DEGs and magnitude of expression change. Elevated expression of cyp1a at retene concentrations below the threshold for teratogenicity suggested that while cyp1a expression is a sensitive biomarker of AHR activation, it may be too sensitive to serve as a biomarker of AHR-dependent teratogenicity. Genes differentially expressed at only non-teratogenic concentrations were enriched for transforming growth factor-ß (TGF-ß) signaling pathway disruption while DEGs identified at only teratogenic concentrations were significantly enriched for response to xenobiotic stimulus and reduction-oxidation reaction activity. DEGs which spanned both non-teratogenic and teratogenic concentrations showed similar disrupted biological processes to those unique to teratogenic concentrations, indicating these processes were disrupted at low exposure concentrations. Gene co-expression network analysis identified several gene modules, including those associated with PAHs and AHR2 activation. One, Module 7, was strongly enriched for AHR2-associated genes and contained the strongest responses to retene. Benchmark concentration (BMC) of Module 7 genes identified a median BMC of 7.5 µM, nearly the highest retene concentration with no associated teratogenicity, supporting the hypothesis that Module 7 genes are largely responsible for retene toxicity.

Toxin, Zebrafish, Retene, Transcriptomics, network↗
DOE OSTI2021

Metadata Schemas and Ontologies for Building Energy Applications: A Critical Review and Use Case Analysis

With the increasing digitalization of processes throughout the lifecycle of buildings, data exchanged between stakeholders and between building systems has grown significantly. However, a lack of semantic interoperability between data in different systems is still prevalent, hindering the development of applications that can be reused across buildings and limiting the scalability of innovative solutions. Semantics refers to the description of the meaning of the data in a way that can be consistently understood by applications. Recently, several competing initiatives have been developing metadata schemas and ontologies to express this semantic information for different applications in the building domain. This paper systematically reviews these schemas and conducts an analysis of five of them to evaluate their applicability to three high-value use cases for building operations: energy audits, automated fault detection and diagnostics and optimal control. The survey finds 40 schemas published in the last 10 years but but their actual use in industry is difficult to estimate. Among the five selected ontologies, several gaps are highlighted in relation to the three use cases. Recommendations for the future include better harmonization of these initiatives, more centralized repositories and search engines for these schemas as well as better industry engagement to facilitate their adoption.

Smart Building, Sematic, Metadata, Ontology, Data ↗