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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

EVALUATION OF HRA METHODOLOGIES FOR APPLICATION IN SDP WORK

This study critically evaluates human reliability analysis (HRA) methodologies applicable to regulatory probabilistic safety assessment (PSA) model, with a particular focus on their role in supporting the significance determination process (SDP) in nuclear safety assessment. Firstly, three widely utilized HRA methods – IDHEAS-ECA, SPAR-H, and ASEP/THERP – were qualitatively and quantitatively assessed. Qualitative assessments were conducted using attributes from the NEA/CSNI/R(2015)1 report, while quantitative evaluations employed regression and correlation analyses to compare predicted human error probabilities (HEPs) against empirical data. Results reveal distinct strengths, for example, IDHEAS-ECA’s robust predictive accuracy and K-HRA’s alignment with operational practices. In addition, dependency analysis and recovery analysis were critically evaluated. For dependency analysis, the methods’ handling of inter-task dependencies and their impact on HEPs were examined, while recovery analysis highlighted strategies for mitigating failure events. Furthermore, strategies were proposed to evaluate performance-shaping factors under conditions of reduced human performance, such as stress, fatigue, or cognitive overload, addressing specific challenges faced in SDP evaluations. Human errors from KINS’s operational performance information system event reports were evaluated as a case study. This study identifies gaps and provides actionable insights to ensure their validity and applicability in SDP HRA applications. This paper is a part of research conducted by KINS, and it should be noted that this result does not represent the regulatory position of KINS.

99 - GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

AmeriFlux FLUXNET-1F CL-SDP Senda Darwin Peatland

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site CL-SDP Senda Darwin Peatland. This is the FLUXNET version of the carbon flux data for the site CL-SDP Senda Darwin Peatland produced by applying the standard ONEFlux (1F) software. Site Description - Located at the Senda Darwin Biological Station, in a old-growth rainforest. Locally named "pomponal" from the common name of Sphagnum, is an anthropogenic peatland, formed after the forest is cut or a forest fire. The station is 15 km east of Ancud, in the Chiloé Island, close to the Huicha river.

Perez-Quezada, Jorge [University of Chile]↗
DOE OSTI2022

AmeriFlux CL-SDP Senda Darwin Peatland

This is the AmeriFlux version of the carbon flux data for the site CL-SDP Senda Darwin Peatland. Site Description - Located at the Senda Darwin Biological Station, in a old-growth rainforest. Locally named "pomponal" from the common name of Sphagnum, is an anthropogenic peatland, formed after the forest is cut or a forest fire. The station is 15 km east of Ancud, in the Chiloé Island, close to the Huicha river.

Perez-Quezada, Jorge↗
DOE OSTI2021

Overview of the 2021 SDP 3C Citation Context Classification Shared Task

This paper provides an overview of the 2021 3C Citation Context Classification shared task. The second edition of the shared task was organised as part of the 2nd Workshop on Scholarly Document Processing (SDP 2021). The task is composed of two subtasks: classifying citations based on their (Subtask A) purpose and (Subtask B) influence. As in the previous year, both tasks were hosted on Kaggle and used a portion of the new ACT dataset. A total of 22 teams participated in Subtask A, and 19 teams competed in Subtask B. All the participated systems were ranked based on their achieved macro f-score. The highest scores of 0.26973 and 0.60025 were reported for sub-task A and B, respectively.

Kunnath, Suchetha N.↗
NASA NTRS1992

Solar concentrator technology development for space based applications, volume 1

Thermoelectric conversion using a radio-isotope heat source has been used where outer planetary space craft are too far away for absorbing significant solar energy. Solar dynamic power (SDP) conversion is one technology that offers advantages for applications within the inner planet region. Since SDP conversion efficiency can be 2 to 3 times higher than photovoltaic, the collecting surfaces are much reduced in area and therefore lighter. This becomes an advantage in allocating more weight to launched payloads. A second advantage results for low earth orbit applications. The reduced area results in lower drag forces on the spacecraft and requires less reboost propellant to maintain orbit. A third advantage occurs because of the sun-to-shade cycling while in earth orbit. Photovoltaic systems require batteries to store energy for use when in the shade, and battery life for periods of 10 to 15 years is not presently achievable. For these reasons the Solar Dynamics and Thermal Systems Branch at NASA LeRC has funded work in developing SDP systems. The generic SDP system uses a large parabolic solar concentrator to focus solar energy onto a power conversion device. The concentrators are large areas and must therefore be efficient and have low specific weights. Yet these surfaces must be precise and capable of being stowed in a launch vehicle and then deployed and sometimes unfurled in space. There are significant technical challenges in engineering such structures, and considerable investigation has been made to date. This is the first of two volumes reporting on the research done by the Advanced Manufacturing Center at Cleveland State University to assist NASA LeRC in evaluating this technology. The objective of the grant was to restore the solar concentrator development technology of the 1960s while improving it with advances that have occurred since then. This report summarizes the work done from January 1989 through December 1991.

Pintz, A.↗
NASA NTRS1992

Solar concentrator technology development for space based applications, volume 2

Thermoelectric conversion using a radio-isotope heat source has been used where outer planetary space craft are too far away for absorbing significant solar energy. Solar dynamic power (SDP) conversion is one technology that offers advantages for applications within the inner planet region. Since SDP conversion efficiency can be 2 to 3 times higher than photovoltaic, the collecting surfaces are much reduced in area and therefore lighter. This becomes an advantage in allocating more weight to launched payloads. A second advantage results for low earth orbit applications. The reduced area results in lower drag forces on the spacecraft and requires less reboost propellant to maintain orbit. A third advantage occurs because of the sun-to-shade cycling while in earth orbit. Photovoltaic systems require batteries to store energy for use when in the shade, and battery life for periods of 10 to 15 years is not presently achievable. For these reasons the Solar Dynamics and Thermal Systems Branch at NASA LeRC has funded work in developing SDP systems. The generic SDP system uses a large parabolic solar concentrator to focus solar energy onto a power conversion device. The concentrators are large areas and must therefore be efficient and have low specific weights. Yet these surfaces must be precise and capable of being stowed in a launch vehicle and then deployed and sometimes unfurled in space. There are significant technical challenges in engineering such structures, and considerable investigation has been made to date. This is the second of two volumes reporting on the research done by the Advanced Manufacturing Center at Cleveland State University to assist NASA LeRC in evaluating this technology. This volume includes the appendices of selected data sets, drawings, and procedures. The objective of the grant was to restore the solar concentrator development technology of the 1960s while improving it with advances that have occurred since then. This report summarizes the work done from January 1989 through December 1991.

Pintz, A.↗
NASA NTRS2001

The Landsat Data Purchase and ESAD

The Earth Science Applications Directorate (ESAD) purchases satellite imagery for The Scientific Data Purchase (SDP) Project. SDP allows a variety of customers in turn to purchase Landsat, IKONOS, and other data. The SDP customer base includes includes private companies, universities, and government agencies. SDP customers are required to register and receive clearance.

Policelli, Fritz↗
NASA NTRS2001

Scientific Data Purchase Project Overview Presentation

The Scientific Data Purchase (SDP) project acquires science data from commercial sources. It is a demonstration project to test a new way of doing business, tap new sources of data, support Earth science research, and support the commercial remote sensing industry. Phase I of the project reviews simulated/prototypical data sets from 10 companies. Phase II of the project is a 3 year purchase/distribution of select data from 5 companies. The status of several SDP projects is reviewed in this viewgraph presentation, as is the SDP process of tasking, verification, validation, and data archiving. The presentation also lists SDP results for turnaround time, metrics, customers, data use, science research, applications research, and user feedback.

Holekamp, Kara↗
DOE OSTI2023

Assessing the Optimality of LinDist3Flow for Optimal Tap Selection of Step Voltage Regulators in Unbalanced Distribution Networks

The adoption of distributed energy resources such as photovoltaics (PVs) has increased dramatically during the previous decade. The increased penetration of PVs into distribution networks (DNs) can cause voltage fluctuations that have to be mitigated. One of the key utility assets employed to this end are step-voltage regulators (SVRs). It is desirable to include tap selection of SVRs in optimal power flow (OPF) routines, a task that turns out to be challenging because the resultant OPF problem is nonconvex with added complexities stemming from accurate SVR modeling. While several convex relaxations based on semi-definite programming (SDP) have been presented in the literature for optimal tap selection, SDP based schemes do not scale well and are challenging to implement in large-scale planning or operational frameworks. This paper deals with the optimal tap selection (OPTS) problem for wye-connected SVRs using linear approximations of power flow equations. Specifically, the LinDist3Flow model is adopted and the effective SVR ratio is assumed to be continuous- enabling the formulation of a problem called LinDist3Flow-OPTS, which amounts to a linear program. The scalability and optimality gap of LinDist3Flow-OPTS are evaluated with respect to existing SDP-based and nonlinear programming techniques for optimal tap selection in three standard feeders, namely, the IEEE 13-bus, 123-bus, and 8500-node DNs. For all DNs considered, LinDist3Flow-OPTS achieves an optimality gap of approximately 1% or less while significantly lowering the computational burden.

linear approximations↗
NASA NTRS2002

NASA Scientific Data Purchase Project: From Collection to User

NASA's Scientific Data Purchase (SDP) project is currently a $70 million operation managed by the Earth Science Applications Directorate at Stennis Space Center. The SDP project was developed in 1997 to purchase scientific data from commercial sources for distribution to NASA Earth science researchers. Our current data holdings include 8TB of remote sensing imagery consisting of 18 products from 4 companies. Our anticipated data volume is 60 TB by 2004, and we will be receiving new data products from several additional companies. Our current system capacity is 24 TB, expandable to 89 TB. Operations include tasking of new data collections, archive ordering, shipment verification, data validation, distribution, metrics, finances, customer feedback, and technical support. The program has been included in the Stennis Space Center Commercial Remote Sensing ISO 9001 registration since its inception. Our operational system includes automatic quality control checks on data received (with MatLab analysis); internally developed, custom Web-based interfaces that tie into commercial-off-the-shelf software; and an integrated relational database that links and tracks all data through operations. We've distributed nearly 1500 datasets, and almost 18,000 data files have been downloaded from our public web site; on a 10-point scale, our customer satisfaction index is 8.32 at a 23% response level. More information about the SDP is available on our Web site.

Nicholson, Lamar↗