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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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NASA NTRS2017

Young People's Burden: Requirement of Negative CO2 Emissions

Global temperature is a fundamental climate metric highly correlated with sea level, which implies that keeping shorelines near their present location requires keeping global temperature within or close to its preindustrial Holocene range. However, global temperature excluding short-term variability now exceeds +1 C relative to the 1880 - 1920 mean and annual 2016 global temperature was almost +1.3 C. We show that global temperature has risen well out of the Holocene range and Earth is now as warm as it was during the prior (Eemian) interglacial period, when sea level reached 6 - 9 m higher than today. Further, Earth is out of energy balance with present atmospheric composition, implying that more warming is in the pipeline, and we show that the growth rate of greenhouse gas climate forcing has accelerated markedly in the past decade. The rapidity of ice sheet and sea level response to global temperature is difficult to predict, but is dependent on the magnitude of warming. Targets for limiting global warming thus, at minimum, should aim to avoid leaving global temperature at Eemian or higher levels for centuries. Such targets now require "negative emissions", i.e., extraction of CO2 from the air. If phasedown of fossil fuel emissions begins soon, improved agricultural and forestry practices, including reforestation and steps to improve soil fertility and increase its carbon content, may provide much of the necessary CO2 extraction. In that case, the magnitude and duration of global temperature excursion above the natural range of the current interglacial (Holocene) could be limited and irreversible climate impacts could be minimized. In contrast, continued high fossil fuel emissions today place a burden on young people to undertake massive technological CO2 extraction if they are to limit climate change and its consequences. Proposed methods of extraction such as bioenergy with carbon capture and storage (BECCS) or air capture of CO2 have minimal estimated costs of USD 89 - 535 trillion this century and also have large risks and uncertain feasibility. Continued high fossil fuel emissions unarguably sentences young people to either a massive, implausible cleanup or growing deleterious climate impacts or both.

Hansen, James↗

DOE OSTI2025

Finite domain solution of a hydraulic fracture in a permeable rock

In this work, we present a domain-based algorithm to simulate the propagation of a plane-strain hydraulic fracture in a zero-toughness permeable elastic medium. The algorithm utilizes a domain-based method to solve the elasticity equation and integrates a multi-scale tip asymptote, which is particular to hydraulic fractures, into this framework. This integration is key to accurately model the energy dissipation and the fluid leak-off in the fracture tip region. The algorithm combines a 2D finite volume method (FVM) for solving the elasticity equation with a 1D FVM for solving the nonlinear lubrication equation. Incorporating the far-field asymptotics and using a moving-mesh scheme reduces the computational burden while improving the accuracy of the scheme. The paper concludes with an analysis of the numerical results. This study demonstrates the potential of this domain-based approach for modeling hydraulic fractures in poroelastic media.

Domain-based method↗

NASA NTRS2003

Fuel cell environmental life cycle assessment : a progress report

Energy generation using fuel cells offers the possibility of high conversion efficiency and reduced pollution. Thus, in the futue, conventional methods of energy generation using coalfired power plants, natural gas turbines and internal combustion engines can potentially be replaced by fuel cells. The United States, Japan and several countries in Europe are currently developing fuel cells for transportation, distributed energy generation and portable electronics applications. On a system basis, the efficiency of chemical to electrical energy conversion in fuel cells can be as high as 45%. Also, because of the lower operating temperatures compared to turbines and internal combustion engines, emissions such as carbon monoxide and nitrogen oxides are extremely small. An assessment of the environmental impact of fuel cells over the entire lifecycle is needed to determine the specific benefits in various application scenarios. Such a comparative pollutants assessment must include a "cradle to grave" approach encompassing fuel production, fuel transportation, materials/manufacturing processes, waste management, and recycling. A comparative pollutant model would be a useful tool for industry and government in estimating energy savings and environmental credits, and providing a holistic understanding on regulatory needs. Another important benefit would be the ability to make appropriate comparisons with competitive energy generation technologies such as hybrids, turbines, and internal combustion engines, and to set up realistic targets. Also, exercising the model will assist in the initial screening for potential hot spots and showstoppers and focus on the right component technologies design for manufacturing, designs for input substitution and waste minimization, and prevent any unforeseen burdens.

Narayanan, S. R.↗

DOE OSTI2024

Fostering Geothermal Machine Learning Success: Elevating Big Data Accessibility and Automated Data Standardization in the Geothermal Data Repository: Preprint

The Department of Energy's (DOE) Geothermal Data Repository (GDR) has implemented improvements to both its data lakes and its data standards and automated data pipelines. The GDR data lakes have reduced storage and compute-related barriers to using large geothermal datasets, enabling these large datasets to be accessed by anyone with a modern computer and internet access. More recently, the GDR has been working to further reduce barriers through streamlining the data intake process, educating users on the process and requirements, and aiding users in accessing data from the data lakes. These improvements have augmented the quantity of datasets the GDR is able to accept into its data lakes and have enabled users who are new to cloud tools to access these datasets more easily, overall increasing the accessibility of big geothermal data for use in machine learning and other projects. In addition, the GDR now has built-in data standards and pipelines for drilling data, geospatial data, and distributed acoustic sensing (DAS) data. These standardization efforts aim to enhance the real-world applicability of geothermal machine learning outcomes by improving the quality of training data. Specifically, through standardizing high-value datasets, the GDR is reducing project-specific data curation requirements, thus allowing more time for actual research. By automating this process, the burden of standardization is lifted from the user, ultimately increasing the availability of standardized data.

accessibility↗

DOE OSTI2023

An Update on the Geothermal Data Repository's Data Standards and Pipelines: Geospatial Data and Distributed Acoustic Sensing Data

The Department of Energy's (DOE) Geothermal Data Repository (GDR) team has implemented data standards and automated data pipelines for the following data types: 1) drilling data, 2) geospatial datasets, and 3) DAS data. An additional data pipeline is proposed for stimulation data. These data standards and pipelines are intended to improve the real-world applicability of geothermal machine learning outputs through improving the quality of data. More specifically, through standardizing high-value datasets, the GDR is reducing project-specific data curation requirements, allowing more time to be spent on actual research. By automating this process, the burden of standardization is taken off of the user, overall increasing the availability of standardized data. This paper provides an update on the GDR's transition toward data standardization through automated data pipelines and calls for feedback from the community on how we can improve this process.

cloud-optimized↗

DOE OSTI2021

A miniaturized long-life acoustic transmitter for animal tracking in marine environments

Marine and hydrokinetic (MHK) energy devices are early-stage technologies and their impacts to ocean life and environment are largely unknown, which consequently limits the progress of deploying these devices at commercial scale. Optical and acoustic imaging have been the primary technologies for monitoring marine animals’ behavior at existing or potential MHK sites. However, these technologies lack the ability to identify individual animals, which makes them less useful in identifying protected species as well as studying the animals’ long-term behavior. Implantable acoustic transmitters with unique identification codes could be used as a complementary technology. To minimize the tag burden on the tagged animal (and hence the resulting bias) and to satisfy the long-term monitoring needs, it is desired that the implanted transmitter be as small and light as possible and can last for as long as possible. To date, the smallest acoustic transmitters suitable for marine animal tracking have relatively short service life and detection range (up to 200 m). In this report, we introduce a new miniaturized acoustic transmitter which operates at 208.3 kHz. It offers a smaller dry weight (0.45 g), a significantly longer service life (140 days at a 5-second ping rate) as well as a greater detection range than the existing commercial counterparts, which will help obtain more comprehensive movement and behavioral information of animals around MHK energy devices.

Li, Huidong↗

DOE OSTI2023

An Update on the Geothermal Data Repository's Data Standards and Pipelines: Geospatial Data and Distributed Acoustic Sensing Data: Preprint

cloud-optimized↗

DOE OSTI2024

Techno-economic and life-cycle analysis of strategies for improving operability and biomass quality in catalytic fast pyrolysis of forest residues

Many of the challenges faced by the first commercial biorefineries were associated with feedstock handling, quality, and cost. Strategies are needed to enable further expansion of biorefineries and meet the growing demand for bio-based fuels and products. Here, we examine 2 key feedstock challenges and mitigation strategies in the context of a catalytic fast pyrolysis (CFP) biorefinery: (1) the operability of the feed system, which may be improved by modifying the minimum particle size fed to the reactor, and (2) the quality of the biomass, which may be improved by employing air classification to remove undesirable material and increase fuel yields. We conduct techno-economic analysis (TEA) and life-cycle analysis for these strategies, employing a discrete event simulation model for biomass preprocessing combined with a series of correlations developed from literature data and a rigorous CFP conversion model. Our results highlight the importance of balancing increased cost and material losses from preprocessing against improved operability and fuel yields. Economics and sustainability were optimized when operating at the lowest minimum particle size, emphasizing the importance of minimizing material losses while maintaining the operability of the process. Economically, additional costs and material losses from air classification could be acceptable due to improved biomass conversion, and an optimum air classification speed was identified; however, the fuel GHG emissions were minimized when air classification was not used. Valorizing material removed during preprocessing as a coproduct could improve economics and sustainability, decreasing the burden of material losses.

09 - BIOMASS FUELS↗

DOE OSTI2020

Dynamic Restoration Strategy for Distribution System Resilience Enhancement

In electric power distribution systems, distributed energy resources (DERs) can act as controllable power sources and support utility operators to minimize power outages after extreme weather events (e.g., hurricane, earthquake, wildfire) and thus help enhance the grid's resilience. Meanwhile, the influences of extreme events and the capabilities of DERs are dynamic and difficult to predict. Hence, the desired distribution system restoration strategy should be able to evolve according to real-time fault/dis-turbance information and the availability of DERs. In this paper, we propose a new dynamic restoration strategy for distribution systems to enhance system resilience against potential hazards. An efficient reconfiguration algorithm is developed to eliminate the use of integer variables to relieve the computational burden. Model predictive control is implemented to adjust the system topology and DER operation set points based on the updated fault information and DER forecasts. The effectiveness of the proposed restoration model in enhancing distribution system resilience is validated through an IEEE 123-bus test system. Simulation results also validate that the proposed restoration model can mitigate the occurrence of unexpected events and the fluctuations of DERs.

distributed energy resources (DERs)↗

DOE OSTI2023

An Update on the Geothermal Data Repository's Data Standards and Pipelines: Geospatial Data and Distributed Acoustic Sensing Data

The Department of Energy's (DOE) Geothermal Data Repository (GDR) team has implemented or is currently implementing data standards and automated data pipelines for the following geothermal data types: 1) drilling data, 2) geospatial datasets, and 3) Distributed Acoustic Sensing (DAS) data. These data standards and pipelines are intended to improve the real-world applicability of geothermal machine learning outputs through improving the quality of data. More specifically, through standardizing high-value datasets, the GDR is reducing project-specific data curation requirements, allowing more time to be spent on actual research. By automating this process, the burden of standardization is taken off of the user, overall increasing the availability of standardized data. This paper provides an update on the GDR's transition toward data standardization through automated data pipelines and calls for feedback from the community on how the GDR team can improve this process.

cloud-optimized↗

DOE OSTI2025

Size-resolved process understanding of stratospheric sulfate aerosol following the Pinatubo eruption

Stratospheric sulfate aerosol produced by volcanic eruptions plays important roles in atmospheric chemistry and the global radiative balance of the atmosphere. The simulation of stratospheric sulfate concentrations and optical properties is highly dependent on the chemistry scheme and microphysical treatment. In this work, we implemented a sophisticated gas-phase chemistry scheme (full chemistry, FC) and a 5-mode version of the Modal Aerosol Module with Prognostic Stratospheric Aerosol (MAM5-PSA) for the interactive treatment of stratospheric sulfate aerosol in the Department of Energy's Energy Exascale Earth System Model version 2 (E3SMv2) model to better simulate the chemistry-aerosol feedback following the Pinatubo eruption, and to compare it against a simulation using simplified chemistry (SC) and the default 4-mode version of the Modal Aerosol Module (MAM4). MAM5-PSA experiments were found to better capture the stratospheric sulfate burden from the eruption of the volcano to the end of 1992 as compared to the High-resolution Infrared Sounder (HIRS) observations, and the formation of sulfate in MAM5-PSA with FC (with an additional OH replenishment reaction) was significantly faster than in MAM4 with FC. Analyses of microphysical processes indicate that more sulfate aerosol mass was generated in total in FC experiments than in SC experiments. MAM5-PSA performs better than MAM4 in simulation of aerosol optical depth (AOD); AOD anomalies from the MAM5-PSA experiment have better agreement with observations. The simulated largest changes in global mean net radiative flux at the top of the atmosphere following the eruption were about −3 W m −2 in MAM5-PSA experiments and roughly −1.5 W m −2 in MAM4 experiments.

AEROSOL↗

DOE OSTI2020

Commercial building loads providing ancillary services In PJM

The adoption of low carbon energy technologies such as variable renewable energy and electric vehicles, coupled with the efficacy of energy efficiency to reduce traditional base load has increased the uncertainty inherent in the net load shape. Handling this variability with slower, traditional resources leads to inefficient system dispatch, and in some cases may compromise reliability. Grid operators are looking to future energy technologies, such as automated demand response (DR), to provide capacity-based reliability services as the need for these services increase. While DR resources are expected to have the flexibility characteristics operators are looking for, demonstrations are necessary to build confidence in their capabilities. Additionally, building owners are uncertain of the monetary value and operational burden of providing these services. To address this, the present study demonstrates the ability of demand response resources providing two ancillary services in the PJM territory, synchronous reserve and regulation, using an OpenADR 2.0b signaling architecture. The loads under control include HVAC and lighting at a big box retail store and variable frequency fan loads. The study examines performance characteristics of the resource: the speed of response, communications latencies in the architecture, and accuracy of response. It also examines the frequency and duration of events and the value in the marketplace which can be used to examine if the opportunity is sufficient to entice building owners to participate.

MacDonald, Jason↗

DOE OSTI2023

Evaluating U.S. Natural Gas Environmental Performance

This work summarizes the U.S. Department of Energy National Energy Technology Laboratory's (NETL) modeling and analysis of natural gas environmental performance. Over the past year, NETL updated its U.S. natural gas supply chain life cycle baseline model to incorporate 2020 data, regionalize the transmission and distribution network into six regions, incorporate improved gathering and boosting stage and distribution stage emissions factors, and assign environmental burdens among the various co-products (i.e., crude oil, natural gas liquids, natural gas) of the natural gas supply chain. The updated natural gas model helps generate more comprehensive and regionalized natural gas profiles, mapping production basins to the relevant transmission and distribution regions downstream. The work incorporates data from multiple peer reviewed measurement-based studies to achieve the objective of providing a comprehensive understanding of emissions from the U.S. natural gas supply chain. This presentation also explores future work by NETL to develop a platform that enables stakeholders to customize key parameters within the natural gas LCA model and observe the corresponding effects on the carbon intensity of the overall supply chain. The platform aims to offer a convenient method for stakeholders to obtain relevant insights from the updated model, without diving deep into the intricacies of the NETL natural gas model with hundreds of parameters and linkages.

Khutal, Harshvardhan↗

DOE OSTI2024

Data-driven Quasi-static Surrogate Models for Nuclear-powered Integrated Energy Systems

The integration of nuclear power into energy systems presents a promising avenue to address the growing global energy demands while minimizing greenhouse gas emissions. In this paper, we introduce a data-driven quasi-static surrogate model for nuclear-powered Integrated Energy Systems (IES) that comprises various components, including a small modular reactor (SMR), steam manifold, balance of plant (BOP), high-temperature steam electrolysis (HTSE), and district heating (DH) system. Traditional physics-based models for these components often entail significant computational resource and time consumption, necessitating the development of efficient surrogate models. The development of a complete surrogate model for the IES involves the creation of individual surrogate models for each component, leveraging machine learning techniques and simulated data. These isolated surrogate models are subsequently integrated, enabling a holistic view of the IES and reducing the computational burden associated with detailed physics-based simulations. This paper outlines the development process, validation, and the performance evaluation of the surrogate models. The exceptional performance, with low root-mean-squared errors and R-squared scores of at least 99.8% across all individual surrogate models, underscores their accuracy and practical applicability. These results demonstrate the potential of these models to expedite the analysis of nuclear-powered IES, offering insights that can shape future research and development efforts.

08 HYDROGEN↗

DOE OSTI2020

Dynamic Restoration Strategy for Distribution System Resilience Enhancement

In electric power distribution systems, distributed energy resources (DERs) can act as controllable power sources and support utility operators to minimize power outages after extreme weather events (e.g., hurricane, earthquake, wildfire) and thus help enhance the grid's resilience. Meanwhile, the influences of extreme events and the capabilities of DERs are dynamic and difficult to predict. Hence, the desired distribution system restoration strategy should be able to evolve according to real-time fault/disturbance information and the availability of DERs. In this paper, we propose a new dynamic restoration strategy for distribution systems to enhance system resilience against potential hazards. An efficient reconfiguration algorithm is developed to eliminate the use of integer variables to relieve the computational burden. Model predictive control is implemented to adjust the system topology and DER operation set points based on the updated fault information and DER forecasts. The effectiveness of the proposed restoration model in enhancing distribution system resilience is validated through an IEEE 123-bus test system. Simulation results also validate that the proposed restoration model can mitigate the occurrence of unexpected events and the fluctuations of DERs.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2025

Accumulation of trace elements in soil and fauna within a site historically contaminated with coal combustion residues

Legacy contaminants tied to energy production are a worldwide concern. Coal combustion residues (CCRs) contain high concentrations of potentially toxic trace elements such as arsenic (As), mercury (Hg), and selenium (Se), which can persist for decades after initial contamination. Coal combustion residue disposal methods, including aquatic settling basins and landfills, can facilitate environmental exposure through intentional and accidental releases. Wildlife exposed to CCRs can experience numerous deleterious effects, such as on development, reproduction, and survival. In the current study, we quantified and compared concentrations of As, Hg, Se, and strontium (Sr) within soils and target fauna (three vertebrate and three invertebrate taxa) from a CCR-contaminated site and a reference site within the U.S. Department of Energy’s Savannah River Site, South Carolina, United States. Our objectives were to (1) compare current concentrations of tested elements in soil and resident fauna to levels from our reference site, (2) assess natural attenuation of elements in soils by comparing current concentrations to historic levels, and (3) evaluate the biomagnification potential of the elements measured via body burden and trophic position correlations among fauna. Here, element concentrations were higher in contaminated soils than reference soils; however, concentrations in 2022 were unchanged from concentrations measured in 2003, suggesting no natural attenuation of tested elements. Additionally, target fauna had elevated As, Se, and Sr levels in comparison to reference samples. A positive correlation was observed in southern toads between Sr concentrations and trophic position, as assessed by nitrogen stable isotope ratios, suggesting potential for biomagnification of Sr within our study system. Collectively, our results demonstrate that legacy contaminants are still present and bioaccumulate in a diversity of taxa in a CCR-contaminated site that has not received effluents in more than 50 years, suggesting monitoring programs in CCR-contaminated sites should be maintained long term in the absence of remediation.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗

DOE OSTI2023

Impacts of Lanthanide Ion Complexation on the Radiation Robustness of Diglycolamide Extractants

Nuclear power reactors represent a clean and reliable source of baseload energy. However, nuclear reactors produce used nuclear fuel (UNF), which, if not recycled/reprocessed, must be disposed of as high-level radioactive waste, necessitating long-term storage options. UNF contains approximately a third of the periodic table, including the radioactive minor actinides (MA) americium and curium. Removal of these MA from UNF would greatly reduce the radiotoxic burden, volume, and cost of a storage facility or geological repository. Thus, a significant global effort has been devoted to the design of reprocessing strategies for the clean separation of the MA from UNF. As MA separations are difficult, due to the presence of lanthanide elements in UNF and their remarkably similar chemical properties, many extractants have been studied. The diglycolamide (DGA) class of extractants are promising for this separation as they exhibit high distribution coefficients for the MAs, high metal loading capacities, and are robust in highly acidic radiation environments.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

DOE OSTI2024

Portable HCAL reconstruction in the CMS detector using the Alpaka library

CMS has deployed a number of different GPU algorithms at the High-Level Trigger (HLT) in Run 3. As the code base for GPU algorithms continues to grow, the burden for developing and maintaining separate implementations for GPU and CPU becomes increasingly challenging. To mitigate this, CMS has adopted the Alpaka (Abstraction Library for Parallel Kernel Acceleration) library as the performance portability solution to provide a single-code base for parallel execution on both GPUs and CPUs in CMS software (CMSSW). A direct CUDA version of HCAL energy reconstruction, called Minimization At Hcal, Iteratively (MAHI), has been deployed at the HLT in the 2022-2023 data taking period. This contribution will describe how the CUDA version is converted into a portable implementation using the Alpaka library. We will discuss the porting experience from CUDA to Alpaka, the validation process and the performance of the Alpaka version in CPU and GPU.

Kwok, Martin↗