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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 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

HPC for Fission Modeling in Support of Nuclear Data [Slides]

The presentation discusses the background of the High-Performance Computing (HPC) division at the Los Alamos National Laboratory (LANL), with emphasis on its computational needs and computational techniques. It also discusses the highlights of the HPC and the results of calculations, including energy sharing parameterized from DFT calculations, parameterization used in CGMF calculations, angular momentum from microscopic calculations, and correlations between FF angular momenta. The presentation concludes with an outlook including what remains to be done in the HPC division and how it will benefit nuclear data, specifically how it will provide a better understanding of the fission process.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

The importance of Aitken mode aerosol particles for cloud sustenance in the summertime high Arctic – a simulation study supported by observational data

The potential importance of Aitken mode particles (diameters ~ 25–80 nm) for stratiform mixed-phase clouds in the summertime high Arctic (>80° N) has been investigated using two large-eddy simulation models. We find that, in both models, Aitken mode particles significantly affect the simulated microphysical and radiative properties of the cloud and can help sustain the cloud when accumulation mode concentrations are low (< 10–20 cm –3 ), even when the particles have low hygroscopicity (hygroscopicity parameter – κ=0.1). However, the influence of the Aitken mode decreases if the overall liquid water content of the cloud is low, either due to a higher ice fraction or due to low radiative cooling rates. An analysis of the simulated supersaturation (ss) statistics shows that the ss frequently reaches 0.5 % and sometimes even exceeds 1 %, which confirms that Aitken mode particles can be activated. The modelling results are in qualitative agreement with observations of the Hoppel minimum obtained from four different expeditions in the high Arctic. Our findings highlight the importance of better understanding Aitken mode particle formation, chemical properties and emissions, particularly in clean environments such as the high Arctic.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Energy Justice Framework for Marine Energy: Considerations from PacWave

To accelerate the energy transition while addressing land use conflicts and community opposition, federal policies and incentives require that new energy infrastructure provide direct benefits to communities, and ensure that these benefits remain in the community. The objective of this study is to develop a framework for collecting demographic, socioeconomic, and environmental data and supporting communities in understanding how such data can support more just and equitable outcomes. Specifically, this study addresses two research questions: (1) How can energy justice be incorporated into ME project life cycle, and (2) what social and economic data are needed to assess how marine energy development supports energy justice? Based on our literature review and the data collection template, a case study of PacWave, a wave energy testing facility located on the central Oregon Coast, is employed to draw more specific implications for how energy justice can be integrated into marine energy. PacWave represents a flagship investment by Oregon State University, the State of Oregon, and the Department of Energy. The facility is situated in Lincoln County, which is home to the Confederated Tribes of Siletz Indians and family-scale fishing enterprises. PacWave has strong community support as a testing site and holds potential to provide valuable lessons for other communities.

16 TIDAL AND WAVE POWER↗
DOE OSTI2020

Evaporation Dataset from a Temperate Closed-basin Lake in Minnesota 2014-2016

This data set contains observed and modeled evaporation data, eddy covariance data, and supporting information measured at White Bear Lake in the Twin Cities Metropolitan Area near St. Paul, Minnesota, USA. The data package includes csv files containing half-hourly latent heat flux, sensible heat flux, and meteorological data from 2014 to 2016. It also includes csv files containing half-hourly observed evaporation measurements, along with supporting data for validation and retrospective modeling of evaporation. This data was collected to examine current, past, and future lake evaporation to better understand how climate will impact the water balance of lakes within this region.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Online Analytics for Remedy Support at DOE Environmental Management Sites

Environmental data is important for managing environmental restoration/waste site remediation, planning of monitoring efforts, addressing climate resilience, and engaging with stakeholders and regulators. A major challenge is how to manage the many different types and the large volume of environmental data in a way that allows practitioners and site managers to understand data implications and support decisions. The Suite Of Comprehensive Rapid Analysis Tools for Environmental Sites (SOCRATES, https://www.pnnl.gov/projects/socrates) is a web application that provides data access, visualization, and rapid analytics to help make sense of environmental data, support remedy decisions, and communicate information. Development of SOCRATES has been funded through the DOE Richland Operations Office (RL) to support communication and decision making for the Hanford Site, thus is only tied into Hanford environmental data. However, the capabilities of SOCRATES are more broadly applicable to DOE-EM sites engaged in environmental remediation and management. This report describes the work to develop mechanisms for bringing non-Hanford data into SOCRATES so that other DOE-EM sites could make use of the visualization and analysis capabilities to support communication and decision making related to managing environmental restoration/waste site remediation, optimization/exit strategies for pump-and-treat systems, planning monitoring efforts, addressing climate resilience, and/or engaging with stakeholders and regulators. The background, approach, data transfer formats, examples, and next steps for this new SOCRATES-EM software are described in this report.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

MHTLS Cross-flow Heat Exchanger Temperature Performance Data

The presentation and supporting information provide data on the performance of an engineering-scale cross-flow heat exchanger used in hydrothermal liquefaction (HTL). Temperature profiles are provide for the process of waste water treatment sludges and a food waste. The data can be used to model larger-scale heat exchangers used in HTL.

Bioenergy Technologies Tags Heat Exchanger HTL MHT↗
DOE OSTI2022

The Geothermal Data Repository: Ten Years of Supporting the Geothermal Industry with Open Access to Geothermal Data: Preprint

The Department of Energy's (DOE) Geothermal Data Repository (GDR) is celebrating its tenth anniversary! Over the last decade it has grown from the simple idea of storing public data in a centralized location to a valuable tool at the center of the US geothermal scientific community and an integral part of the DOE Geothermal Technologies Office (DOE GTO) project management strategy. Researchers funded by the DOE GTO have contributed over 1,300 data submissions to the GDR. These data have been used to further advancements in geothermal science, economic analysis, exploration, research, development, and operational efficiency. The adoption of open data methodologies and a data management strategy that prioritizes universal open access and standardized, interoperable data have further increased the value of GDR data, making them available across a distributed network of data sharing partners and improving their utility to other industries and related fields, including material science and space exploration. Incorporating feedback from users has been critical to the GDRs success, allowing it to grow over the years to meet the evolving needs of the geothermal community. This paper will explore some of many changes that occurred throughout the GDRs tenure and the lessons learned along the way, as well as highlight some of the new features and recent improvements that been implemented to support innovation, reduce duplication of effort, and advance the geothermal industry as a whole.

accessibility↗
DOE OSTI2022

The Geothermal Data Repository: Ten Years of Supporting the Geothermal Industry with Open Access to Geothermal Data

The Department of Energy's (DOE) Geothermal Data Repository (GDR) is celebrating its tenth anniversary! Over the last decade it has grown from the simple idea of storing public data in a centralized location to a valuable tool at the center of the US geothermal scientific community and an integral part of the DOE Geothermal Technologies Office (DOE GTO) project management strategy. Researchers funded by the DOE GTO have contributed over 1,300 data submissions to the GDR. These data have been used to further advancements in geothermal science, economic analysis, exploration, research, development, and operational efficiency. The adoption of open data methodologies and a data management strategy that prioritizes universal open access and standardized, interoperable data have further increased the value of GDR data, making them available across a distributed network of data sharing partners and improving their utility to other industries and related fields, including material science and space exploration. Incorporating feedback from users has been critical to the GDR's success, allowing it to grow over the years to meet the evolving needs of the geothermal community. This paper will explore some of many changes that occurred throughout the GDRs tenure and the lessons learned along the way, as well as highlight some of the new features and recent improvements that been implemented to support innovation, reduce duplication of effort, and advance the geothermal industry as a whole.

access↗
DOE OSTI2020

The National Microbiome Data Collaborative: Enabling Microbiome Science

To harness the potential of microbiome science across the broad range of relevant disciplines, new approaches to data infrastructure and transdisciplinary collaboration are necessary. The National Microbiome Data Collaborative (NMDC) is a new initiative to support microbiome data exploration and discovery through a collaborative integrative data science ecosystem.

Wood-Charlson, Elisha M.↗
DOE OSTI2022

Multi-Variable Parametric Analysis of Prototype Building Energy Performance Using Current and Future Weather Scenarios For Data-Driven Market Transformation Support

This project aimed to develop a public building simulation data set that may be used to inform building code development and guidelines for building innovation. The data set consists of several common building types and many representative locations across the United States. A parametric design of building properties was developed to create a range of building energy models that represent common building design decisions with a particular focus on fenestration options. The US Department of Energy prototype building energy models were altered according to a parametric building design and simulated using both current weather data and future weather estimates derived from global climate models. The resulting data set allows for pertinent exploration of building design parameters, including fenestration, within different environments across the United States in the broader context of climate change.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Integration of Condition-Based, Diagnostic, Prognostic, And Anomaly Detection Data into Reliability Models to Support a Predictive Maintenance Context

Reliability data employed in plant reliability models are an approximated integral representation of the past industrywide operational experience, and they neglect the present asset health status (available, for example, from online monitoring data and diagnostic assessments) and forecasted health projection (when available from prognostic models). Ideally, in a predictive maintenance context, system reliability models should support decision making by propagating actual health information from the asset to the system level in order to provide a quantitative snapshot of system health and identify the most critical assets. Asset health should be informed solely by that specific asset’s current and historical performance data and should not be an approximated integral representation of the past industrywide operational experience (as currently performed by system reliability models through Bayesian updating processes). This paper proposes a reliability modeling approach that relies on asset diagnostic and prognostic assessments, along with monitoring data to measure asset health. We show how state-of-the art condition-based, diagnostic, prognostic, and anomaly detection models can be linked to system reliability models not in probability terms, but in terms of margin where margin is defined as the “distance” between the present status and an undesired event (e.g., failure or unacceptable performance). Then, we show how the propagation of margin data from the asset to the system level is performed through classical reliability models such as fault trees or reliability block diagrams. The described method is in fact able to propagate heterogenous health data from the asset to the system level in order to analytically assess system health.

97 MATHEMATICS AND COMPUTING↗