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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Interim Report on FY22 ORNL A709 Welding Research and Testing of Production Welds in Support of Developing ASME A709 Code Case Data Package

As part of the Alloy 709 ASME Code Case development effort under the Advanced Reactor Technologies (ART) Program, this work covers the development of the technical basis for weld fabrication and weld qualification of Alloy 709. This report summarizes the Alloy 709 welding research conducted at Oak Ridge National Laboratory (ORNL) in FY 2022. Two new production welds were fabricated on two commercial heats of Alloy 709 of different phosphorus (P) levels using Alloy 709 filler metal with P content less than 20 wppm with gas tungsten arc welding (GTAW). Both production welds successfully passed ASME Section IX weld qualification tests, and this concludes the Alloy 709 welding procedure development to scale up to 2-in thick plates. In FY 2022, we also demonstrated the success in welding of high P commercial Alloy 709 plates with weld wires having higher P content at 30 wppm. A test weld fabricated with the 30 wppm weld wire on the first commercial heat (140 wppm P) passed all weld qualification tests without issues. Additionally, experiment setup and testing procedure of the circular patch weldability test has been developed, for evaluating the P effect in weld wire on solidification cracking susceptibility of Alloy 709 weld, with the preliminary results summarized in this report. Research on further relaxing the P level restriction beyond 30 wppm are planned in FY 2023. The preliminary cross-weld creep tests results continue to show little or no creep strength reduction relative to the base metal.

36 MATERIALS SCIENCE↗
DOE OSTI2025

A dataset for understanding self-reported patterns influencing residential energy decisions

Household occupant behavior and decision-making dynamics substantially impact technology uptake and residential building energy performance. Although significant research underscores the importance of social science in energy studies, few public data with representative samples on household energy decision-making patterns are available. The dataset (UPGRADE-E: Understanding Patterns Guiding Residential Adoption and Decisions about Energy Efficiency) presents 9,919 responses from U.S. residents of single-family and small multifamily homes. Derived from a national-scale internet survey, the dataset contains 391 variables: demographics, building characteristics, home modifications, willingness to adopt new technologies, motivations for making changes, barriers, program participation, trusted information sources, and energy scenarios. Responses were validated via internal consistency checks and comparison with other U.S. national scale datasets. UPGRADE-E advances knowledge of household energy related decision-making, tying demographics, home modifications, and self-reported cognitive drivers together at a scale and breadth that has not been previously achieved. Policymakers and researchers at local, regional, and national levels may leverage this dataset to understand drivers influencing the adoption of key technologies in U.S. homes.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Smart Methane Emission Detection System Development Final Report

Working with the Department of Energy's National Energy Technology Laboratory, Southwest Research Institute® (SwRI®) developed a system to identify methane leaks reliably, accurately, and autonomously at critical midstream sections of the natural gas distribution network in real- time for the purpose of mitigating methane emissions using Optical Gas Imaging (OGI) cameras. SwRI's Smart Leak Detection – Methane (SLED/M) adds a high degree of automation to the process of methane leak detection to minimize sources of human error, minimize response time to a leak event, and maximize midstream visibility. Furthermore, SwRI has been working towards integrating Quantitative OGI (QOGI) capabilities into this existing technology. By leveraging Deep Learning, SwRI now has the capability to estimate fugitive emission leak rates quickly and reliably, which allows operators to detect emissions, quantify leak rate, prioritize repairs, and validate the repairs in a single instrument. The next generation QOGI technology leverages the same cameras used in Leak Detection and Repair (LDAR) programs, with improvements in safety and speed for traditional quantification-based repairs, ultimately leading to less overhead cost for the operators.

03 NATURAL GAS↗
DOE OSTI2021

Smart Methane Emission Detection System Development (Final Report)

Working with the Department of Energy's National Energy Technology Laboratory, Southwest Research Institute® (SwRI®) developed a system to identify methane leaks reliably, accurately, and autonomously at critical midstream sections of the natural gas distribution network in real-time for the purpose of mitigating methane emissions using Optical Gas Imaging (OGI) cameras. SwRI's Smart Leak Detection – Methane (SLED/M) adds a high degree of automation to the process of methane leak detection to minimize sources of human error, minimize response time to a leak event, and maximize midstream visibility. Furthermore, SwRI has been working towards integrating Quantitative OGI (QOGI) capabilities into this existing technology. By leveraging Deep Learning, SwRI now has the capability to estimate fugitive emission leak rates quickly and reliably, which allows operators to detect emissions, quantify leak rate, prioritize repairs, and validate the repairs in a single instrument. The next generation QOGI technology leverages the same cameras used in Leak Detection and Repair (LDAR) programs, with improvements in safety and speed for traditional quantification-based repairs, ultimately leading to less overhead cost for the operators. The goals for this research were to develop two types of models with the following goals: Run in real-time on the edge (≥ 12 Hz), Classification: Achieve less than 5% false positive detection, Classification: Achieve ≥ 95% methane plume detection rate, Regression: achieve ≤ 10 standard cubic feet per hour (scfh) prediction > 70% of the time. In order to achieve these results, multiple infrared (IR) and other sensors were investigated in tandem with the midwave IR (MWIR) OGI to provide additional information to train the underlying models. Information on atmospheric conditions including humidity, temperature, pressure, and solar radiation was provided by a weather station. Several machine learning and deep learning architectures and methods, including looking at quantized classification networks and regressions networks, were explored. As further data was collected, curated, and labeled, it allowed for more refined regressive networks to be adequately trained, leading to better insight into the true flow rates being observed. An important valuable deliverable of this research effort was the development of an advanced network which underwent multiple iterations capable of giving a continuous output. The current network has a predicted mean average percentage error (MAPE) of 12.3% just outside our target goal of 10.00%, but an accuracy of 97.78% at ±50 scfh, well within the overall goal for the Department of Energy (DOE) program. Upon closer inspection, it was observed that more than 10% of datapoints contributing to the MAPE predictions were the result of low flow rate predictions and are beyond the sensitivity of instrument measurement as a result of normal operational variation and noise.

03 NATURAL GAS↗
DOE OSTI2023

TCF High Efficiency Anaerobic Electroporation (CRADA Final Report)

The Joint BioEnergy Institute (JBEI) researchers were co-inventors of the technology that will be used on this project and have developed a more current version of the chip and controller. JBEI will also assist with the design of the pathways and implementation of pathways on the chip. LanzaTech has developed novel gas fermentation technology that captures and utilizes greenhouse gases for production of fuels and chemicals. In contrast to traditional fermentation that uses sugars as substrate (and releases CO2 as a byproduct), gas fermentation utilizes C1 substrates carbon monoxide (CO) or CO2. This enables a diverse range of feedstock options including waste gases from industrial sources (e.g., steel mills and processing plants) or syngas generated from any biomass resource (e.g., agricultural waste, municipal solid waste, or organic industrial waste). Biomass is then gasified, allowing for maximum yields and complete carbon utilization including the recalcitrant lignocellulosic fraction that cannot be utilized in traditional sugar fermentation. To maximize the value that can be added to the array of gas resources that the LanzaTech process can use as an input, LanzaTech has pioneered genetic modification of acetogens and developed a comprehensive set of genetic tools to perform routine strain modification, including genome editing tools as CRISPR/Cas9 and libraries of validated genetic parts as promoters and terminators. Using this platform, production of over 50 new molecules have been demonstrated directly from gas. For a few selected molecules production rates and yields have been optimized and surpass production of native producers and engineered E. coli or yeast strains, but a higher throughput approach for combinatorial optimization of pathways is required to further advance synthesis of additional products in parallel.

09 BIOMASS FUELS↗
DOE OSTI2025

Direct solar self-catalyzing pyrolysis of natural gas to hydrogen and high-quality graphite (Final Technical Report)

This project, led by researchers at UCLA in partnership with Southwest Solar Technology (SST) and SolGrapH, successfully demonstrated a new method for producing clean hydrogen fuel and high-quality graphite using concentrated solar energy. The primary goal was to develop a technology that converts natural gas (primarily methane) into two valuable products—hydrogen gas and solid carbon—without releasing carbon dioxide (CO2) into the atmosphere. This process, known as solar thermal pyrolysis, uses heat from the sun to split the methane molecules directly.

03 NATURAL GAS↗
DOE OSTI2021

Smart Methane Emission Detection System Development (Final Report)

Working with the Department of Energy’s National Energy Technology Laboratory, Southwest Research Institute® (SwRI®) developed a system to identify methane leaks reliably, accurately, and autonomously at critical midstream sections of the natural gas distribution network in real- time for the purpose of mitigating methane emissions using Optical Gas Imaging (OGI) cameras. SwRI’s Smart Leak Detection – Methane (SLED/M) adds a high degree of automation to the process of methane leak detection to minimize sources of human error, minimize response time to a leak event, and maximize midstream visibility. Furthermore, SwRI has been working towards integrating Quantitative OGI (QOGI) capabilities into this existing technology. By leveraging Deep Learning, SwRI now has the capability to estimate fugitive emission leak rates quickly and reliably, which allows operators to detect emissions, quantify leak rate, prioritize repairs, and validate the repairs in a single instrument. The next generation QOGI technology leverages the same cameras used in Leak Detection and Repair (LDAR) programs, with improvements in safety and speed for traditional quantification-based repairs, ultimately leading to less overhead cost for the operators. The goals for this research were to develop two types of models with the following goals: 1. Run in real-time on the edge (≥ 12 Hz) 2. Classification: Achieve less than 5% false positive detection 3. Classification: Achieve ≥ 95% methane plume detection rate 4. Regression: achieve ≤ 10 standard cubic feet per hour (scfh) prediction > 70% of the time In order to achieve these results, multiple infrared (IR) and other sensors were investigated in tandem with the midwave IR (MWIR) OGI to provide additional information to train the underlying models. Information on atmospheric conditions including humidity, temperature, pressure, and solar radiation was provided by a weather station. Several machine learning and deep learning architectures and methods, including looking at quantized classification networks and regressions networks, were explored. As further data was collected, curated, and labeled, it allowed for more refined regressive networks to be adequately trained, leading to better insight into the true flow rates being observed. An important valuable deliverable of this research effort was the development of an advanced network which underwent multiple iterations capable of giving a continuous output. The current network has a predicted mean average percentage error (MAPE) of 12.3% just outside our target goal of 10.00%, but an accuracy of 97.78% at ±50 scfh, well within the overall goal for the Department of Energy (DOE) program. Upon closer inspection, it was observed that more than 10% of datapoints contributing to the MAPE predictions were the result of low flow rate predictions and are beyond the sensitivity of instrument measurement as a result of normal operational variation and noise.

03 NATURAL GAS↗
DOE OSTI2026

Energy I-Corps Annual Report 2025

Energy I-Corps is an initiative of the Department of Energy's Office of Technology Commercialization. The focus of this 2-month program is to train National Laboratory researchers in evaluating industry needs and potential market applications for their DOE technologies. This year's annual report details the accomplishments, activities, and finances of Energy I-Corps' 2025 fiscal year programming.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

GEN3D Experimental and Numerical Development of GEN3 Durability Models

Understanding of the high temperature durability of particles and the materials that contain them is critical to next generation of concentrating solar power (CSP) technology. Here we studied the durability of particles and their containment materials under extreme UV cycling, thermal cycling, and in low-speed high temperature mechanical wear situations. The optical stability of seven candidate particles has been determined following exposure to the high temperature conditions present in a generation 3 particle-based CSP technology. Particle solar weighted absorptance and emittance measured periodically during 10,000 high solar irradiance exposure cycles and up to 400 hours of isothermal aging has been documented. The particle aging due to repeated exposure to concentrated solar flux represented the 30-year lifetime of a power plant. Models were fit to the absorptivity and emissivity data following the isothermal aging provides the projected optical degradation of the particles as a function of temperature. Mechanical wear was studied through the use of custom developed wear testing facilities for measuring high temperature impact wear, abrasion wear, and particle attrition. Additionally, a novel technique for measuring the high temperature mechanical properties of single particles was developed. Through these tests it was observed that high nickel alloys generally showed lower wear than comparable iron based steels, particularly at elevated temperatures of 800°C. Mechanical wear at these temperatures is a highly complex phenomenon combining both mechanical wear and oxidation. Additionally, the containment materials wear rates are influenced by the particles (both hardness and roundness), making the wear mechanisms complex. The initial wear test conducted in the abrasion test rig revealed a substantial amount of oxide materials in the particle bed after testing (in relative to later tests), and substantially more wear, likely indicating a need for concern in startup operation of particle facilities to not incur high wear from the presence of oxides. Particle attrition experiments have only been conducted for a single material but increase size distribution, reduction in circularity, and particle diameter is observed. Efforts to develop predictive models was limited due to a testing campaign that prioritized testing materials for particle pathway developers over building a comprehensive design of experiments. The results discussed in this report inform future CSP developers and researchers further de risking the technology and assisting in its future development. ParticleBased CSP development provides a path to dispatchable solar power generation with storage at a price competitive in the current energy market. Lowering the cost of CSP technology provides a carbon free power generation solution that can assist in the transition from fossil fuels to renewable sources of electricity.

14 SOLAR ENERGY↗
DOE OSTI2022

Cost and Performance Baseline for Fossil Energy Plants Volume 1: Bituminous Coal and Natural Gas to Electricity

This revised report presents an independent assessment of the cost and performance of select fossil energy power systems—integrated gasification combined cycle (IGCC), pulverized coal (PC), and natural gas combined cycle (NGCC) plants—using a systematic, transparent technical and economic approach. The cost and performance of fossil fuel-based generation technologies represented in this report (and the series at large) are important inputs to assessments and determinations of technology combinations to be utilized to meet the projected demands of future power markets. In addition to informing technology comparisons, the reference plant configurations found in this report provide perspective for regulators and policy makers. From a research and development perspective, this report is used to assess goals and metrics and to provide a consistent basis for comparing developing technologies.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2023

Cost and Performance Baseline for Fossil Energy Plants Volume 3: Low Rank Coal and Natural Gas to Electricity

This report presents an independent assessment of the cost and performance of select fossil energy power systems—pulverized coal (PC), circulating fluidized bed (CFB), and natural gas combined cycle (NGCC) plants—using a systematic, transparent technical and economic approach. This is Volume 3 of a five-volume series, which comprise the following reports: Volume 1: Bituminous Coal and Natural Gas to Electricity; Volume 2: Coal to Synthetic Natural Gas and Ammonia (Various Coal Ranks); Volume 3: Low Rank Coal and Natural Gas to Electricity; Volume 4: Bituminous Coal to Liquid Fuels; and Volume 5: Natural Gas Electricity Generating Units for Flexible Operation. The cost and performance of fossil fuel-based generation technologies represented in this report (and the series at large) are important inputs to assessments and determinations of technology combinations to be utilized to meet the projected demands of future power markets. In addition to informing technology comparisons, the reference plant configurations found in this report provide perspective for regulators and policy makers. From a research and development perspective, this report is used to assess goals and metrics and to provide a consistent basis for comparing developing technologies.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2025

Roadmap for Assessing Fuel Reprocessing in Fluoride-Based Salts

This joint report assesses the pyroprocessing of used nuclear fuel from molten fluoride salts being conducted between Idaho National Laboratory and Argonne National Laboratory. The goal of this report is to identify the research and development gaps needed to reduce the technical risks of extending pyroprocessing technologies and unit operations to molten fluoride salts used in molten salt reactors (MSRs). Assessing and performing the tasks outlined in this report will help mitigate the technical risks and design appropriate flowsheets for reprocessing fuel and coolant salts. These suggested tasks will provide necessary data to implement the development of unit operations. Sections are highlighted to identify processes that need to be assessed and unit operations that may be used in fluoride-based chemistries. Research and development needs are listed and discussed including re-fluorination methods, electrowinning for separations, reference electrode development, materials compatibility, salt purification/re-fluorination, and waste disposition. This report will examine the technical challenges associated with pyroprocessing in molten fluoride-based salt and outline approaches to increase the technical readiness level of pyroprocessing in molten fluoride salts.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Commercialization of Pumped Storage Hydropower Technologies

Argonne National Laboratory and the National Laboratory of the Rockies were tasked by the U.S. Department of Energy’s Water Power Technology Office (WPTO) to conduct the Commercialization of Pumped Storage Hydropower Technologies study to investigate commercialization challenges faced by developers of pumped storage hydropower (PSH) projects and technologies by going beyond literature review to gather direct industry insights, lessons learned and best practices from interviews and webinars with industry specialists to create this report for PSH stakeholders and the general public. Researchers explored key challenges faced by PSH developers and innovators seeking to commercialize new technologies to improve PSH design, siting, construction, and operations. Along with highlighting challenges, the study sought to identify the best practices in developing and deploying new PSH projects and innovations. This report is designed to present insights, lessons learned, and best practices relevant to those with an interest in highlighting, informing, or advancing these PSH commercialization efforts. Along with highlighting challenges and best practices, the study sought to identify avenues by which DOE and national laboratories can help support and streamline PSH commercialization and project development processes.

13 HYDRO ENERGY↗
DOE OSTI2023

Machine-learning-assisted material discovery of oxygen-rich highly porous carbon active materials for aqueous supercapacitors

Abstract Porous carbons are the active materials of choice for supercapacitor applications because of their power capability, long-term cycle stability, and wide operating temperatures. However, the development of carbon active materials with improved physicochemical and electrochemical properties is generally carried out via time-consuming and cost-ineffective experimental processes. In this regard, machine-learning technology provides a data-driven approach to examine previously reported research works to find the critical features for developing ideal carbon materials for supercapacitors. Here, we report the design of a machine-learning-derived activation strategy that uses sodium amide and cross-linked polymer precursors to synthesize highly porous carbons (i.e., with specific surface areas > 4000 m 2 /g). Tuning the pore size and oxygen content of the carbonaceous materials, we report a highly porous carbon-base electrode with 0.7 mg/cm 2 of electrode mass loading that exhibits a high specific capacitance of 610 F/g in 1 M H 2 SO 4 . This result approaches the specific capacitance of a porous carbon electrode predicted by the machine learning approach. We also investigate the charge storage mechanism and electrolyte transport properties via step potential electrochemical spectroscopy and quasielastic neutron scattering measurements.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Solar +: Clean Energy Strategies for the Sunshine State (Final Technical Report (FTR) of the Florida Alliance for Accelerating Solar and Storage Technology Readiness (FAASSTeR))

This reports on a four-year effort to provide foundational research, analysis, strategies and assistance to help Florida, and other states that might learn from this work, to grow solar energy in conjunction with other distributed energy resources by addressing and overcoming existing barriers, and in way that delivers increased value. The start of this effort coincided with an inflection point of sorts into a new dawn for solar energy in Florida, where the Sunshine state’s national ranking in total installed solar, according to the Solar Energy Industries Association (SEIA), has rose from 13th to 4th. Florida has now become the national leader in annual utility-scale solar growth as dozens of large plants have come online. Also, during this time, Florida utilities have expressed a strong and growing interest in understanding the role of energy storage and how to best plan for and deploy this unique resource as part of strategies to grow solar. The utility-scale solar growth experienced has been fueled by the economics of solar cost-parity with natural gas combined cycle plants and Florida Public Service Commission’s (PSC) approval of cost-recovery for the Investor-Owned Utilities (IOU’s), primarily through the Solar Base Rate Adjustment (SoBRA) mechanism. This has led to gigawatts (GW’s) of rate-based solar capacity additions over several years, along with fairly significant amounts of energy storage. Meanwhile, municipal electric utilities, which, collectively, are the third largest source of power in the state, have been increasing solar considerably through power purchase agreements (PPA’s) and are on track to have close to 1 GW of grid-connected solar by 2024. Florida’s municipal utilities and the Florida Municipal Electric Association (FMEA) have been key partners in the Florida Alliance for Accelerating Solar and Storage Technology Readiness (FAASSTeR), formed to carry out this effort. The six largest of these have been Core Team utilities, engaging throughout the project in weekly calls, discussions, and project direction, participating in and hosting workshops and benefiting from technical assistance in several areas.

14 SOLAR ENERGY↗
DOE OSTI2023

Renewable Thermal Energy Systems: Systemic Challenges and Transformational Policies (Report 2)

Two important challenges for RTES are the need for significant further innovation and deployment, particularly in the United States. In the face of continued success of other renewable energy technologies, such as solar photovoltaics (PV) and land-based wind energy for electricity, it is worthwhile to evaluate the current state of select RTES technologies in the context of technology innovation systems and energy transitions. This report marks a departure from the existing body of research we are aware of and have contributed to relating to RTES applications for industrial process heat in the United States. Our objectives for this report are fourfold: 1) Begin considering the challenges of RTES deployment in the United States through application of socio-technical and transitions frameworks; 2) Begin applying the theory of RTES as configurational technology innovation systems in the United States and for industrial process heat specifically; 3) Review RTES innovation, policies, and market formation activities in the contexts of Objectives 1 and 2; 4) Identify future paths for RTES research. Ultimately, the challenges associated with scaling the deployment of RTES in the United States are related to the need to develop a well-functioning innovation system that can overcome resistance from a highly stable socio-technical regime within a shrinking window of time to address the climate crisis, U.S. industrial competitiveness, and volatile energy commodity price shocks. Current efforts toward scaling for RTES applications in industry and buildings emphasize the need for further cost reductions, but not for interventions that support actors and their interactions and that increase the legitimacy of the technologies. As a result, there are significant opportunities to analyze the social contexts of RTES that can then be used to inform the design of effective, transformational policy portfolios.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗