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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 559 records · Page 31
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Site 200 - Building 225 Construction Project: Steel Pipe Abandonment Work Plan (October 2020)

In December 2019, a capped, 4-inch diameter pipe located inside a square concrete collar was discovered on the north side of a driveway leading into a construction project located at the northeast corner of First Street and Avenue and petroleum like odors were reported to Lawrence Livermore National Laboratory's (LLNL) Environment, Safety and Health (ES&H) staff. The pipe was also found to contain liquid, which was sampled. Analysis of the liquid showed the presence of refined petroleum hydrocarbons - primarily benzene, toluene, ethylbenzene and total xylenes, and lead. Based on various historical documents and maps, the pipe is assumed to be associated with one, or more of four 25,000-gallon, single-wall, concrete-construction, underground storage tanks (USTs) installed by the U.S. Department of Navy in approximately 1943. The USTs were reported to have been closed - abandoned in place and filled with sand in 1950.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Rapid Construction of Validated Chemistry Models for Advanced Biofuels (Co-Optima Final Report)

Computer methods were developed and demonstrated that make it possible to predict the combustion and pyrolysis chemistry of proposed biofuels, even before the biofuels are ever manufactured or experimentally tested. The methods are based on first-principles calculations of reaction rates and equilibria. A large number of complicated calculations are required, so we developed a computer workflow that automates many of the steps. With the chemical structure of the biofuel and the system conditions (temperature, pressure, compositions, etc.) as the input, the computer methods can construct a detailed kinetic model with refined parameters without intense human intervention. The automation of model construction makes it practical for a single engineer to make the predictions in a reasonable time period. The accuracy of the computer predictions was tested by measuring the time-profiles of various reaction intermediates (carbon monoxide, carbon dioxide, water, formaldehyde, methane, and ethylene) formed as the biofuels pyrolyze or ignite using sophisticated laser shock tube methods. Several biofuels, including methyl propyl ether, cyclopentanone, butyl acetate isomers, etc., were carefully studied to demonstrate the validity of the proposed computational and experimental methodology. This research project opens up the possibility for assessing some proposed biofuels on the computer without expensive experimental campaigns. The new computer methods are open source and well-documented, allowing a knowledgeable modeler to easily access the developed methods and implement them in their work routine. Moreover, they are also convenient and powerful, promising for developing the fuel chemistry models needed for use in engine simulators, facilitating co-optimization of new engine designs with new fuels.

09 BIOMASS FUELS↗
DOE OSTI2021

MARSAME Radiological Release Report TA-50, TRU Liquid Waste Construction Soil

Environmental Protection and Compliance, Environmental Stewardship (EPC-ES) has determined that the soil associated with Technical Area 50 (TA-50), Transuranic (TRU) Liquid Waste construction project (TLW) meets the criteria for unrestricted release to the public under Department of Energy (DOE) Order 458.1, Radiation Protection for the Public and the Environment (DOE 2020, NNSA 2021). This conclusion is based on the known history of the area combined with soil sample data collected in 2021; the findings are consistent with DOE Order 458.1 and Los Alamos National Laboratory (LANL) Functional Series Document EPC ES-FSD-004, Environmental Radiation Protection (LANL 2020a). Sampling and data analysis, as described in this report, were sufficient to meet measurement quality objectives under the Multi-Agency Radiation Survey and Assessment of Materials and Equipment (MARSAME) manual (MARSAME 2000) and LANL procedures (LANL 2020b). Final approvals for waste disposition will come from LANL’s Waste Management Program. The scope of this final release report includes the TLW construction site soil located south of TA-50, Building 001.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

LLNS Request for Permanent Variance from 10 CFR 851 for the Construction of Commercial Type Structures and Systems

Lawrence Livermore National Security, LLC (LLNS) requests variance from10 CFR 851 (the Rule) for the construction of commercial type structures and systems. The request is based upon successful application of similar variances granted to LLNS in continued support of the National Nuclear Security Administration (NNSA) initiative to streamline the delivery of commercial type line-item construction projects under $50 million. This request is aligned with the approved NA-50 safety approach.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2023

A Technology Roadmap for Advanced Geothermal Well Construction

Recent analysis has shown that by 2050, geothermal energy can supply up to 90 GW of power to the U.S. electrical grid. Reducing the lifecycle cost of geothermal wells is critical to achieving this level of adoption. While time-related costs of drilling remain an important issue, there is also a need to focus on the costs associated with casing and cementing of geothermal wells. This report provides a roadmap of R&D activities needed to reduce the life cycle cost of casing and cementing while improving life-of-well performance. The purpose of the roadmap is to develop priorities for R&D in the areas of (1) high-performance and cost-effective materials for target geothermal well conditions, (2) well construction methods and techniques to reduce construction costs, and (3) methods and techniques to decrease to decrease long-term operating costs. The roadmap sets targets for the next 10-year period and purposely excludes R&D efforts into improved rock reduction. The roadmap was developed by a joint working group of experts from Oak Ridge National Laboratory, Brookhaven National Laboratory, and Sandia National Laboratories as well as 35 experts from industry and academia. Input from a series of information gathering sessions was used to inform and guide the development of the roadmap.

15 GEOTHERMAL ENERGY↗
DOE OSTI2017

An Environmental Approach for Construction, Operation, and Maintenance of Floating Solar Array Renewable Energy Projects on Army Installations

The U.S. Army Office of Energy Initiatives (OEI) has primary responsibility over renewable projects to help achieve the Army’s renewable energy goals. The OEI serves as the central management office for partnering with U.S. Army installations to implement cost-effective, renewable energy projects, leveraging private sector financing. Siting, construction, and operation of solar power systems on U.S. Army installations help to achieve renewable energy goals. This report provides a general framework for environmental analysis for the siting, construction, and operation of floating solar renewable energy projects on U.S. Army installations, to include joint bases managed by the Department of the Army. This report includes specific information by resource area regarding the potential environmental impacts and probable best management practices or minimization approaches that afford environmental protection. This report provides analyses and suggestions that could support a programmatic analysis or site-specific action.

14 SOLAR ENERGY↗
DOE OSTI2025

Construction of approximate invariants for non-integrable Hamiltonian systems

We present a method to construct high-order polynomial approximate invariants (AI) for non integrable Hamiltonian dynamical systems, and apply it to a modern ring-based particle accelerator. Taking advantage of a special property of one-turn transformation maps in the form of a square matrix, AIs can be constructed order-by-order iteratively. Evaluating AI with simulation data, we observe that AI’s fluctuation is actually a measure of chaos. Through minimizing the fluctuations, the stable region of long-term motions, i.e., the dynamic aperture of the accelerator, could be enlarged.

43 PARTICLE ACCELERATORS↗
DOE OSTI2026

SENTRA: A Modular Computational Graph Framework for Critical Mineral and Materials Supply Chains: Part I: Network Construction Latent-Quantity Estimation, and Temporal Graph Forecasting

Global supply chains for critical minerals and materials are complex, evolving networks of countries, products, production stages, and trade relationships. Existing analytical approaches are limited by fragmented data and static network representations that do not capture the dynamic production dependencies linking raw materials, intermediate products, and final goods across multiple countries. Trade and production statistics provide only a partial view of domestic production, inventories, and material flows, making it difficult to identify indirect sourcing pathways, hidden dependencies, and embedded foreign exposures. This paper introduces the Supply Chain Exposure Network Tracking and Risk Assessment (SENTRA) framework, a modular graph-based computational framework for constructing, analyzing, and forecasting dynamic supply chain networks. As the first paper in a three-part methodological series, it establishes the computational foundation of SENTRA by constructing a temporal attributed multi-relational graph whose nodes represent product–country pairs and whose edges encode observed trade and within-country value-chain relationships. Statistical estimation and constrained optimization recover latent production, final demand, and product input dependency coefficients while enforcing economic accounting constraints. Graph-derived exposure measures quantify direct, transshipment, value-chain, and multi-hop supply chain dependencies independently of the forecasting model. A temporal graph forecasting architecture based on a relational graph neural network then forecasts the evolution of the graph under mass-balance constraints with distribution-free conformal uncertainty quantification. Validation on the global aluminum supply chain shows that the learned graph representations recover economically meaningful supply chain structure, accurately forecast out-of-sample trade relationships, and produce well-calibrated prediction intervals. Subsequent papers apply this computational foundation to exposure assessment, disruption analysis, and scenario-based policy analysis, and extend the framework to multimaterial supply chain modeling and decision support.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Constructing Networks of Organelle Functional Modules in Arabidopsis

With the rapid accumulation of gene expression data, gene functional module identification has become a widely used approach in functional analysis. However, tools to identify organelle functional modules and analyze their relationships are still missing. We present a soft thresholding approach to construct networks of functional modules using gene expression datasets, in which nodes are strongly co-expressed genes that encode proteins residing in the same subcellular localization, and links represent strong inter-module connections. Our algorithm has three steps. First, we identify functional modules by analyzing gene expression data. Next, we use a self-adaptive approach to construct a mixed network of functional modules and genes. Finally, we link functional modules that are tightly connected in the mixed network. Analysis of experimental data from Arabidopsis demonstrates that our approach is effective in improving the interpretability of high-throughput transcriptomic data and inferring function of unknown genes.

Arabidopsis thaliana↗
DOE OSTI2023

Design and construction of Cosmic Muon Veto for the mini-ICAL detector at IICHEP, Madurai

A 51-kiloton magnetised Iron Calorimeter (ICAL) detector, using Resistive Plate Chambers (RPCs) as active detector elements, aims to study atmospheric neutrinos. A prototype - 1/600 of the weight of ICAL, called mini-ICAL was installed in the INO transit campus at Madurai. A modest proof-of-principle cosmic muon veto detector of about 1 m×1 m×0.3 m dimensions was set up a few years ago, using scintillator paddles. The measured cosmic muon veto efficiency of 99.98% and simulation studies of muon-induced background events in the ICAL detector surrounded by an efficient veto detector were promising. This led to the idea of constructing a bigger cosmic muon veto around the mini-ICAL detector. Details of the design, fabrication, quality control, and construction of the detector including the electronics, trigger, and DAQ systems planned will be briefly presented.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

KBase Narrative - Formation of a constructed microbial community in a nutrient rich environment indicates bacterial interspecific competition

This Narrative is the parent for the three Narratives referenced in "Formation of a constructed microbial community in a nutrient rich environment indicates bacterial interspecific competition." Wang J, Appidi MR, Burdick LH, Abraham PE, Hettich RL, Pelletier DA, Doktycz MJ. 2024. Formation of a constructed microbial community in a nutrient-rich environment indicates bacterial interspecific competition. mSystems. American Society for Microbiology.

Wang, Jia↗
DOE OSTI2024

Prognostic analysis of high-flow nasal cannula therapy and non-invasive ventilation in mild to moderate hypoxemia patients and construction of a machine learning model for 48-h intubation prediction—a retrospective analysis of the MIMIC database

Background This study aims to investigate the clinical outcome between high-flow nasal cannula (HFNC) and non-invasive ventilation (NIV) therapy in mild to moderate hypoxemic patients on the first ICU day and to develop a predictive model of 48-h intubation. Methods The study included adult patients from the MIMIC III and IV databases who first initiated HFNC or NIV therapy due to mild to moderate hypoxemia (100 < PaO2/FiO2 ≤ 300). The 48-h and 30-day intubation rates were compared using cross-sectional and survival analysis. Nine machine learning and six ensemble algorithms were deployed to construct the 48-h intubation predictive models, of which the optimal model was determined by its prediction accuracy. The top 10 risk and protective factors were identified using the Shapley interpretation algorithm. Result A total of 123,042 patients were screened, of which, 673 were from the MIMIC IV database for ventilation therapy comparison (HFNC n = 363, NIV n = 310) and 48-h intubation predictive model construction (training dataset n = 471, internal validation set n = 202) and 408 were from the MIMIC III database for external validation. The NIV group had a lower intubation rate (23.1% vs. 16.1%, p = 0.001), ICU 28-day mortality (18.5% vs. 11.6%, p = 0.014), and in-hospital mortality (19.6% vs. 11.9%, p = 0.007) compared to the HFNC group. Survival analysis showed that the total and 48-h intubation rates were not significantly different. The ensemble AdaBoost decision tree model (internal and external validation set AUROC 0.878, 0.726) had the best predictive accuracy performance. The model Shapley algorithm showed Sequential Organ Failure Assessment (SOFA), acute physiology scores (APSIII), the minimum and maximum lactate value as risk factors for early failure and age, the maximum PaCO 2 and PH value, Glasgow Coma Scale (GCS), the minimum PaO 2 /FiO 2 ratio, and PaO 2 value as protective factors. Conclusion NIV was associated with lower intubation rate and ICU 28-day and in-hospital mortality. Further survival analysis reinforced that the effect of NIV on the intubation rate might partly be attributed to the other impact factors. The ensemble AdaBoost decision tree model may assist clinicians in making clinical decisions, and early organ function support to improve patients’ SOFA, APSIII, GCS, PaCO 2 , PaO 2 , PH, PaO 2 /FiO 2 ratio, and lactate values can reduce the early failure rate and improve patient prognosis.

Fu, Wei↗
DOE OSTI2017

Construction of Viable Soil Defined Media Using Quantitative Metabolomics Analysis of Soil Metabolites

Exometabolomics enables analysis of metabolite utilization of low molecular weight organic substances by soil bacteria. Thus, environmentally-based defined media are needed to examine ecologically relevant patterns of substrate utilization. Here, we describe an approach for the construction of defined media using untargeted characterization of water soluble soil microbial metabolites from a saprolite soil collected from the Oak Ridge Field Research Center (ORFRC). To broadly characterize metabolites, both liquid chromatography mass spectrometry (LC/MS) and gas chromatography mass spectrometry (GC/MS) were used. With this approach, 96 metabolites were identified, including amino acids, amino acid derivatives, sugars, sugar alcohols, mono- and di-carboxylic acids, nucleobases, and nucleosides. From this pool of metabolites, 25 were quantified. Molecular weight cut-off filtration determined the fraction of carbon accounted for by the quantified metabolites and revealed that these soil metabolites have an uneven quantitative distribution (e.g., trehalose accounted for 9.9% of the < 1 kDa fraction). This quantitative information was used to formulate two soil defined media (SDM), one containing 23 metabolites (SDM1) and one containing 46 (SDM2). To evaluate the viability of the SDM, we examined the growth of 30 phylogenetically diverse soil bacterial isolates from the ORFRC field site. The simpler SDM1 supported the growth of 13 isolates while the more complex SDM2 supported 15 isolates. To investigate SDM1 substrate preferences, one isolate, Pseudomonas corrugata strain FW300-N2E2 was selected for a time-series exometabolomics analysis. Interestingly, it was found that this organism preferred lower-abundance substrates such as guanine, glycine, proline and arginine and glucose and did not utilize the more abundant substrates maltose, mannitol, trehalose and uridine. These results demonstrate the viability and utility of using exometabolomics to construct a tractable environmentally relevant media. We anticipate that this approach can be expanded to other environments to enhance isolation and characterization of diverse microbial communities.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

The Extended Northern ROSAT Galaxy Cluster Survey (NORAS II). I. Survey Construction and First Results

As the largest, clearly defined building blocks of our universe, galaxy clusters are interesting astrophysical laboratories and important probes for cosmology. X-ray surveys for galaxy clusters provide one of the best ways to characterize the population of galaxy clusters. We provide a description of the construction of the NORAS II galaxy cluster survey based on X-ray data from the northern part of the ROSAT All-Sky Survey. NORAS II extends the NORAS survey down to a flux limit of 1.8 × 10{sup −12} erg s{sup −1} cm{sup −2} (0.1–2.4 keV), increasing the sample size by about a factor of two. The NORAS II cluster survey now reaches the same quality and depth as its counterpart, the southern REFLEX II survey, allowing us to combine the two complementary surveys. The paper provides information on the determination of the cluster X-ray parameters, the identification process of the X-ray sources, the statistics of the survey, and the construction of the survey selection function, which we provide in numerical format. Currently NORAS II contains 860 clusters with a median redshift of z = 0.102. We provide a number of statistical functions, including the log N –log S and the X-ray luminosity function and compare these to the results from the complementary REFLEX II survey. Using the NORAS II sample to constrain the cosmological parameters, σ {sub 8} and Ω{sub m}, yields results perfectly consistent with those of REFLEX II. Overall, the results show that the two hemisphere samples, NORAS II and REFLEX II, can be combined without problems into an all-sky sample, just excluding the zone of avoidance.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Lifting MGARD: Construction of (pre)wavelets on the interval using polynomial predictors of arbitrary order

MGARD (MultiGrid Adaptive Reduction of Data) is an algorithm for compressing and refactoring scientific data, based on the theory of multigrid methods. The core algorithm is built around stable multilevel decompositions of conforming piecewise linear $C^0$ finite element spaces, enabling accurate error control in various norms and derived quantities of interest. In this work, we extend this construction to arbitrary order Lagrange finite elements $\mathbb{Q}_p$, $p \geq 0$, and propose a reformulation of the algorithm as a lifting scheme with polynomial predictors of arbitrary order. Additionally, a new formulation using a compactly supported wavelet basis is discussed, and an explicit construction of the proposed wavelet transform for uniform dyadic grids is described.

Reshniak, Viktor [Oak Ridge National Laboratory (O↗
DOE OSTI2025

Weak Form Scientific Machine Learning: Test Function Construction for System Identification

Weak form Scientific Machine Learning (WSciML) is a recently developed framework for data-driven modeling and scientific discovery. It leverages the weak form of equation error residuals to provide enhanced noise robustness in system identification via convolving model equations with test functions, reformulating the problem to avoid direct differentiation of data. The performance, however, relies on wisely choosing a set of compactly supported test functions. In this work, we mathematically motivate a novel data-driven method for constructing Single-scale-Local reference functions for creating the set of test functions. Our approach numerically approximates the integration error introduced by the quadrature and identifies the support size for which the error is minimal, without requiring access to the model parameter values. Through numerical experiments across various models, noise levels, and temporal resolutions, we demonstrate that the selected supports consistently align with regions of minimal parameter estimation error. We also compare the proposed method against the strategy for constructing Multi-scale-Global (and orthogonal) test functions introduced in our prior work, demonstrating the improved computational efficiency.

FOS: Computer and information sciences↗
DOE OSTI2019

Carbon dioxide (CO 2 ) concentrations and emission in the newly constructed Belo Monte hydropower complex in the Xingu River, Amazonia

The Belo Monte hydropower complex located in the Xingu River is the largest run-of-the-river (ROR) hydroelectric system in the world and has one of the highest energy production capacities among dams. Its construction received significant media attention due to its potential social and environmental impacts. It is composed of two ROR reservoirs: the Xingu Reservoir (XR) in the Xingu's main branch and the Intermediate Reservoir (IR), an artificial reservoir fed by waters diverted from the Xingu River with longer water residence time compared to XR. We aimed to evaluate spatiotemporal variations in CO 2 partial pressure ( p CO 2 ) and CO 2 fluxes ( F CO 2 ) during the first 2 years after the Xingu River impoundment under the hypothesis that each reservoir has contrasting F CO 2 and p CO 2 as vegetation clearing reduces flooded area emissions. Time of the year had a significant influence on p CO 2 with the highest average values observed during the high-water season. Spatial heterogeneity throughout the entire study area was observed for pCO2 during both low- and high-water seasons. F CO 2 , on the other hand, only showed significant spatial heterogeneity during the high-water period. F CO 2 (0.90±0.47 and 1.08±0.62 µmol m 2 d –1 for XR and IR, respectively) and p CO 2 (1647±698 and 1676±323 µatm for XR and IR, respectively) measured during the high-water season were on the same order of magnitude as previous observations in other Amazonian clearwater rivers unaffected by impoundment during the same season. In contrast, during the low-water season F CO 2 (0.69±0.28 and 7.32±4.07 µmol m 2 d –1 for XR and IR, respectively) and p CO 2 (839±646 and 1797±354 µatm for XR and IR, respectively) in IR were an order of magnitude higher than literature F CO 2 observations in clearwater rivers with naturally flowing waters. When CO 2 emissions are compared between reservoirs, IR emissions were 90 % higher than values from the XR during low-water season, reinforcing the clear influence of reservoir characteristics on CO 2 emissions. Based on our observations in the Belo Monte hydropower complex, CO 2 emissions from ROR reservoirs to the atmosphere are in the range of natural Amazonian rivers. However, the associated reservoir (IR) may exceed natural river emission rates due to the preimpounding vegetation influence. Since many reservoirs are still planned to be constructed in the Amazon and throughout the world, it is critical to evaluate the implications of reservoir traits on F CO 2 over their entire life cycle in order to improve estimates of CO 2 emissions per kilowatt for hydropower projects planned for tropical rivers.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

PlasmidMaker: a Versatile, Automated, and High Throughput End-to-End Platform for Plasmid Construction

Plasmids are used extensively in basic and applied biology. However, design and construction of plasmids, specifically the ones carrying complex genetic information, remains one of the most time-consuming, labor-intensive, and rate-limiting steps in performing sophisticated biological experiments. Here, we report the development of a versatile, robust, automated end-to-end platform named PlasmidMaker that allows error-free construction of plasmids with virtually any sequences in a high-throughput manner. This platform consists of a most versatile DNA assembly method using Pyrococcus furiosus Argonaute ( Pf Ago)-based artificial restriction enzymes, a user-friendly frontend for plasmid design, and a backend that streamlines the workflow and integration with a robotic system. As a proof of concept, we used this platform to generate ~100 plasmids from six different species ranging from 5 to 18 kb in size from up to 11 DNA fragments within 3 days. PlasmidMaker should greatly expand the potential of synthetic biology.

Enghiad, Behnam↗