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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 865 records · Page 48
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

RolyPoly (rp) v0.1.0

The Rolypoly pipeline is designed to process raw RNA-seq data and identify potential RNA viral sequences. It is split into several self contained steps: 1. input data filtering and QC, 2. Genome assembly and refinement, 3. Assembly filtering, 4. Mapping to known RNA viral genomes, 5. Searching for RNA viral marker genes. 6. Genome functional and structural annotation. 6. Report preparation and potential downstream analysis The last module, may include taxonomic assignment, host range estimation, and phenotypic prediction. There are many similar software, but they focus on human related viruses, and lack the downstream applications or differ in their sensitivity. The initial user base are non-computational microbial ecologists who wish to better understand the potential RNA viruses in their own generated samples.

Neri, Uri↗
DOE OSTI2025

ggtaxplot v 0.0.1

ggtaxplot is an R package designed to process and visualize taxonomic data through a taxonomic river plot. This package is ideal for researchers and data scientists who need to visualize taxonomic data. ggtaxplot function processes data and generates a taxonomic river plot, allowing users to visualize the distribution of taxa across different samples.

Coclet, Clement [Lawrence Berkeley National Labora↗
DOE OSTI2021

Laser-based three-dimensional manufacturing technologies for rechargeable batteries

Laser three-dimensional (3D) manufacturing technologies have gained substantial attention to fabricate 3D structured electrochemical rechargeable batteries. Laser 3D manufacturing techniques offer excellent 3D microstructure controllability, good design flexibility, process simplicity, and high energy and cost efficiencies, which are beneficial for rechargeable battery cell manufacturing. In this review, notable progress in development of the rechargeable battery cells via laser 3D manufacturing techniques is introduced and discussed. The basic concepts and remarkable achievements of four representative laser 3D manufacturing techniques such as selective laser sintering (or melting) techniques, direct laser writing for graphene-based electrodes, laser-induced forward transfer technique and laser ablation subtractive manufacturing are highlighted. Finally, major challenges and prospects of the laser 3D manufacturing technologies for battery cell manufacturing will be provided.

25 ENERGY STORAGE↗
DOE OSTI2021

GeoThermalCloud framework for fusion of big data and multi-physics models in Nevada and Southwest New Mexico

Our GeoThermalCloud framework is designed to process geothermal datasets using a novel toolbox for unsupervised and physics-informed machine learning called SmartTensors. More information about GeoThermalCloud can be found at the GeoThermalCloud GitHub Repository. More information about SmartTensors can be found at the SmartTensors Github Repository and the SmartTensors page at LANL.gov. Links to these pages are included in this submission. GeoThermalCloud.jl is a repository containing all the data and codes required to demonstrate applications of machine learning methods for geothermal exploration. GeoThermalCloud.jl includes: - site data - simulation scripts - jupyter notebooks - intermediate results - code outputs - summary figures - readme markdown files GeoThermalCloud.jl showcases the machine learning analyses performed for the following geothermal sites: - Brady: geothermal exploration of the Brady geothermal site, Nevada - SWNM: geothermal exploration of the Southwest New Mexico (SWNM) region - GreatBasin: geothermal exploration of the Great Basin region, Nevada Reports, research papers, and presentations summarizing these machine learning analyses are also available and will be posted soon.

15 GEOTHERMAL ENERGY↗
DOE OSTI2020

In situ/operando synchrotron x-ray studies of metal additive manufacturing

Additive manufacturing (AM) comprises a group of transformative technologies that are likely to revolutionize manufacturing. In particular, laser-based metal AM techniques can not only fabricate parts with extreme complexity, but also provide innovative means for designing and processing new metallic systems. However, there are still several technical barriers that constrain metal AM. Overcoming these barriers requires a better understanding of the physics underlying the complex and dynamic laser–metal interaction at the heart of many AM processes. Furthermore, this article briefly describes the state of the art of in situ/operando synchrotron x-ray imaging and diffraction for studying metal AM, mostly the laser powder-bed fusion process. It highlights the immediate impact of operando synchrotron studies on the advancement of AM technologies, and presents future research challenges and opportunities.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Revealing atomic-to-nanoscale oxidation mechanisms of metallic materials

Oxidation and corrosion are the leading causes of degradation and failure of metallic materials. Future alloy development requires the incorporation of corrosion resistance into alloy design and processing, and this begins with attaining a fundamental insight into dynamic reaction mechanisms and kinetics between a metal and aggressive environments. With recent advances in environmental transmission electron microscopy, there have been increased efforts to apply this approach to atomically probe the microscopic mechanisms that govern the oxidation and corrosion behavior of metallic materials. Consequently, fundamental insights have been obtained in understanding the underlying processes of oxidation and passivation, including active sites, surface restructuring, oxide/metal interface dynamics, and microstructure and phase evolution. Additionally, we discuss on-going and future developments that are expected to significantly advance the field of high-temperature oxidation and corrosion.

25 ENERGY STORAGE↗
DOE OSTI2020

Interpretation of Hydraulic Fractures Based on Microseismic Response in the Marcellus Shale, Monongalia County, West Virginia, USA: Implications for Shale Gas Production

Summary Hydraulic fracturing is critical for extracting shale gas in the subsurface. The treatment technique of multistage hydraulic fracturing is widely used to maximize production. In multistage hydraulic fracturing, not all pumping stages make the same contribution for production, although the designed stimulation process is almost same in every pumping stage. In this study, we characterize the microseismic responses of hydraulic fracturing. Significant variations of microseismic characteristics are observed among the different pumping stages. Pre-existing natural fractures are examined along the horizontal well in selected stages. Combined with the Mohr’s circle analysis, results of the fracture study show that induced hydraulic fractures can be captured by pre-existing natural fractures. Induced hydraulic fractures are simulated by the unconventional fracture model (UFM), and the result reveals that the stress-shadow effect diverts the direction of hydraulic fractures. The diverted hydraulic fracture affects the development of the hydraulic fracture network, which has influence on production. The treatment of two-step pumping is investigated by application of hydraulic diffusivity. Hydraulic fracturing performance and production could be optimized by the treatment of two-step pumping in a single stage. The second pumping creates new fractures and fills the fractures with additional proppants to maintain production for a long duration.

Energy & Fuels↗
DOE OSTI2020

Strain Improvements that Keep Algae Ponds Growing Strong

A challenge for algal biofuel development is finding strains of algae best suited for producing copious amounts of oil quickly and under industrial-scale conditions. Furthermore, maintaining pond health is also challenging—deteriorating health in a small fraction of algal cells within a pond can quickly lead to the death of the entire pond’s population. To overcome these challenges, Los Alamos National Laboratory (LANL) scientist Christina Steadman and team designed a process to optimize algal physiology and metabolism in cultures by interrogating specific characteristics of the algae cells. This process uses flow cytometry methods and solves two problems: the LANL team can quickly detect potential pond problems, and use this process to streamline the screening of potential algae candidates for biofuel production.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Conversion of CO 2 into Synthetic Graphite

Carbon Dioxide (CO 2 ) can be utilized as a source for producing synthetic graphite. Our method converts CO 2 into solid carbon. These CO 2 -sourced solid carbon have an anisotropic property that allow them to be graphitized into synthetic graphite. Our patented thermal catalytic process uses carbon dioxide and hydrogen as the feedstocks for the reaction, producing solid carbon material, with distilled water as the sole byproduct. The process is designed as a closed loop, where all feedstock gases entering the reactor are converted into durable bulk carbons and water, with no emissions. These carbons materials can be sintered into a solid structure and then thermally annealed, taking the carbon atoms from a disordered state to a highly ordered state of graphitic material – producing synthetic graphite structures. Phase 1 will prove that these bulk carbons can be sintered into a machinable solid carbon structure, which will then be annealed into a fully graphitic solid structure. Standard analytics will be done to verify the extent of graphitization (Raman, XRD). Proving this CO 2 -sourced carbon pathway to synthetic graphite structures will give the US a domestic supply route for this critical material and remove reliance on foreign sources. In addition, since the synthetic graphite structure is made from CO 2 -sourced carbon, this is also a method to mitigate CO 2 . Graphite structures are used in high temperature and high friction applications, for example, as anodes for steel refining, for brake pad linings, as neutron reflectors in nuclear reactors.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Research in Neutrinoless Double-Beta Decay (Final Report)

The research objective of the supported work was to search for neutrinoless double-beta decay in 76 Ge and investigate and identify backgrounds to a double-beta decay search. Understanding the neutrino mass generation mechanism, the absolute neutrino mass scale, the neutrino mass spectrum, and the possible Majorana nature of neutrinos are some of the future discoveries of the next generation neutrino experiments. The Majorana collaboration operated the Demonstrator experiment comprising 44 kg (30 kg enriched in 76 Ge) of Ge detectors in total split between two modules contained in a low background shield at the Sanford Underground Research Facility in Lead, South Dakota. Observation of 0νββ would have profound implications for the Standard Model of particle physics by demonstrating that neutrinos are Majorana particles, that lepton number is not conserved, and it would provide a measure of the effective Majorana neutrino mass. The decay rate of 0νββ is incredibly small and may only produce a few signature events in a detector per year. Therefore, observation of this rare process demands a careful study and implementation of signal processing, detector design, and new levels of background suppression.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Extremely Lightweight Optical Structures for Rapid Deployment

The structures that surround and support optical components play a key role in the performance of the overall optical system. For aerospace applications, creating an opto-mechanical structure that is athermal, lightweight, robust, and can be quickly developed from concept through to hardware is challenging. This project demonstrates a design and fabrication method for optical structures using origami-style folded, photo-etched sheetmetal pieces that are micro-welded to each other or to 3d printed metal components. Thin flexures, critical for athermal mounting of optics, can be thinner with sheetmetal than from standard machining, which leads to more compact designs and the ability to mount smaller optics. Building a structure by starting with the thinnest features, then folding that thin material to make the ''thicker'' sections is the opposite of standard machining (cutting thin features from thicker blocks). A design method is shown with mass savings of >90%, and stiffness to weight ratio improvements of 5x to 10x compared to standard methods for space systems hardware. Designs and processes for small, flexured, actively aligned systems are demonstrated as are methods for producing lightweight, structural, Miura-core sandwich panels in both flat and curved configurations. Concepts for deployable panels and component hinges are explored, as is a lens subcell with tunable piston movement with temperature change and an ultralight sunshade.

42 ENGINEERING↗
DOE OSTI2021

Energy Systems Process Modeling, Analysis, and Experiment Design [Slides]

This presentation is to be used in Feynman Center outreach discussions. It describes public information about some Los Alamos interests and activities in modeling and analysis in energy systems including carbon capture and direct air capture. In particular this addresses the CCSI2 project’s open-source toolkit and ongoing partnerships, as well as summarizing the published Feynman Center capability snapshot on direct air capture.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Use of Operating Agreements and Energy Storage to Reduce Photovoltaic Interconnection Costs: Conceptual Framework

This report explores one integrated technical and process concept designed to manage interconnection costs and streamline interconnection timelines to support near-term renewable energy deployment. We describe a new agreement between renewable energy developers and utilities, informed by the technical analysis. The agreement defines the operational parameters for a renewable energy system, with the goal of reducing risk and cost to all parties. This work provides a foundation upon which other states and utilities may build proof of concept. This report is supported by a technical analysis that is detailed in a companion report, "Use of Operating Agreements and Energy Storage to Reduce Photovoltaic Interconnection Costs: Technical and Economic Analysis" (McLaren et al. 2022).

14 SOLAR ENERGY↗
DOE OSTI2022

A High-Throughput Computing Infrastructure to Generate Custom, Open Community Geothermal Datasets

The most significant challenge facing geothermal research, development, and deployment is a lack of comprehensive datasets describing the geological and economical properties of North America. Automated knowledge base construction, the process of designing algorithms to analyze text and images to programmatically build new datasets, is one possible solution to this problem. The xDD library of full-text scientific articles (https://xdd.wisc.edu) is one of the largest collections of open and controlled-access scientific documents available for knowledge base construction in the world, but it has been underutilized by experts in geothermal research. The xDD development team attributed the lack of engagement by software developers and geothermal researchers to two perceived shortcomings of the system. First, the workflow for obtaining data from xDD for local development and testing of data mining applications was unnecessarily abstruse and required significant manual intervention by xDD systems administrators. Second, although xDD already held articles from a broad cross-section of scientific literature with an emphasis on the geosciences, it did not have an explicit set of geothermal research documents that could serve as the nucleus of a geothermal data mining application. To address these issues, the Automated Data Extraction PlaTform (ADEPT) was proposed to extend the data distribution capabilities of the xDD system. The ADEPT extension added the following four key features to xDD: 1) integration of National Geothermal Data System (NGDS) documents into the xDD library to provide an explicitly geothermally-themed collection; 2) improved RESTful (i.e., https-protocol driven) web services for external partners to access xDD data for machine learning application development; 3) a web platform for end-users and xDD administrators to coordinate the development of data mining applications from the initial step of browsing available documents to the final stage of deploying a production-quality machine learning application on high-throughput computing infrastructure; and 4) the development of demonstration data mining applications to illustrate the new workflow to potential collaborators. A total of 21,674 geothermal documents from NGDS were fully ingested into the xDD library and the associated metadata is publicly available through the xDD web services; furthermore, the ADEPT web platform is now publicly accessible and fully live at https://xdd.wisc.edu/adept/.

15 GEOTHERMAL ENERGY↗
DOE OSTI2021

Surplus Plutonium Disposition Sphincter Seal Development & Testing

The Surplus Plutonium Disposition Project (SPD, Project Y744) requested the Savannah River National Laboratory (SRNL) to perform a series of leak and durability tests on sphincter seals that were designed to process blend cans and shield cans into an SPD glovebox. Each sphincter seal assembly consisted of a stainless-steel outer sleeve weldment that was bolted onto the test enclosure and an aluminum inner sleeve that housed seven to nine Neoprene seals. All tests were executed to determine long term effects from processing approximately a year’s worth of blend and shield cans through the sphincter seals.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

AI-Enabled Robots for Automated Nondestructive Evaluation and Repair of Power Plant Boilers. Final Report

Boiler failure could cause loss of life and safety issues, cost hundreds of thousands of dollars in equipment repairs, property damage and production losses, and drive up the cost of electric power. Boiler maintenance is challenging and risky for inspectors working on scaffolding in confined hazardous spaces inside of a boiler and sometimes the space is hard to access. The operation is also time-consuming due to the large area of vertical structures for inspection and the tremendous effort needed for scaffolding. Recently, the use of robotics (e.g., drones and crawlers) in power plants for maintenance is growing rapidly. However, the existing robotics solutions show two notable technological gaps: no live repair capability, and no Artificial Intelligence (AI) for smart autonomy. The objective of this project is to develop an integrated autonomous robotic platform that is equipped with compact non-destructive evaluation (NDE) sensors to perform live inspection, operates onboard repair devices to perform live repair, and uses AI for intelligent data fusion and predictive analysis for automated and smart spatiotemporal inspection, analysis and repair of the furnace walls in coal-fired boilers. The approach to achieve the objective includes developing NDE sensors with signal processing techniques, designing and evaluating repair devices for robots based on fusion and solid-state technologies, and an autonomous robotic platform that can attach to and navigate on boiler furnace walls using magnetic drive tracks. The robot is also powered by AI to automate data gathering (e.g., 3D mapping and damage localization) and predictive analysis. This project has advanced the state-of-the-art by providing technological breakthroughs including compact NDE and repair tools for robots, AI capabilities for smart autonomy, and a robotic platform for automated boiler maintenance. This project has great potential to result in significant benefits including limiting or eliminating the need to send operators to assess difficult-to-access or hazardous areas, enabling automated live inspection and repair, avoiding time consuming scaffolding (especially for partial maintenance during unplanned outage), collecting comprehensive and well-organized data smartly, and avoiding or limiting the need for onsite or remote piloting technicians. The impacts can be tremendous in terms of the time and cost savings, reducing the risk for human operators, and increasing boiler reliability, usability, and efficiency. In addition, by developing the new technologies on the autonomous inspection and repair robot, by involving multiple undergraduate and graduate students working together with the faculty members on this project, and by generating knowledge and building up collaborations with industrial partners, this effort will significantly update the education capabilities, support long-term fundamental research, and maintain the leadership of Colorado School of Mines and Michigan State University in energy fields.

20 FOSSIL-FUELED POWER PLANTS↗