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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
NASA NTRS2007

Observations on Cost Modeling and Performance Measurement of Long Term Archives

This paper describes a prototype suite of Excel-based tools that could be used for estimating lifecycle costs for newly planned or modified long-term archival facilities. These tools may also prove valuable for monitoring the long-term performance of such facilities once operational. Cost estimation is by analogy, using statistical curve-fitting techniques across a database of comparable data activities. The database currently includes 29 operational data centers ranging from small (2 FTEs) to large (66 FTEs), and is readily expandable to include additional activities specifically involving data preservation and added value. Each comparable data center is described in terms of its staffing, throughput workload, archival and distribution requirements, levels of user service, overall complexity, degree of automation, and other data, comprising 94 distinct descriptors in all. The descriptors were developed by normalizing heterogeneous data from the various centers and mapping them into an Excel framework consistent with the OAIS reference model. A user-friendly tool is provided for generating input to and updating the comparables database. This tool can also be used to benchmark the performance (in terms of cost versus throughput) of an operational data center, and to update the staffing, cost and workload data on a periodic basis. The comparables database could thus provide a history of staffing and throughput over time, as a means of performance monitoring and providing feedback for continuous improvement. Ancillary tools are also provided for performing "what-if' cost exercises for planning purposes, and for graphical display of data and results. We provide a high-level description of the tools; present our experiences and observations on gathering the information and maintaining the database; and discuss how this tool set might be applied to long term archives.

Fontaine, Kathy↗
NASA NTRS1998

Assessment of Uncertainty in the Determination of Activation Energy for Polymeric Materials

An assessment of the experimental uncertainty in obtaining the kinetic activation energy from thermogravimetric analysis (TGA) data is presented. A neat phenolic resin, Borden SC1O08, was heated at three heating rates to obtain weight loss vs temperature data. Activation energy was calculated by two methods: the traditional Flynn and Wall method based on the slope of log(q) versus 1/T, and a modification of this method where the ordinate and abscissa are reversed in the linear regression. The modified method produced a more accurate curve fit of the data, was more sensitive to data nonlinearity, and gave a value of activation energy 75 percent greater than the original method. An uncertainty analysis using the modified method yielded a 60 percent uncertainty in the average activation energy. Based on this result, the activation energy for a carbon-phenolic material was doubled and used to calculate the ablation rate In a typical solid rocket environment. Doubling the activation energy increased surface recession by 3 percent. Current TGA data reduction techniques that use the traditional Flynn and Wall approach to calculate activation energy should be changed to the modified method.

Darby, Stephania P.↗
NASA NTRSDate not supplied

NASA’s Commercial Smallsat Data Acquisition (CSDA) Program Data System

The National Aeronautic and Space Administration (NASA) Commercial Smallsat Data Acquisition (CSDA) Program was established to identify, evaluate, and acquire data from commercial satellite companies that support and complement NASA’s Earth sciences missions and research goals. Since becoming a sustained program in 2020, CSDA has been developing a data system to provide scalable, efficient, continuous, and repeatable data management processes for all commercial data acquired by NASA. This includes providing access to commercial data to approved science investigators through NASA developed and vendor operated interfaces. As the commercial data user community and volume of data acquired by CSDA has grown, the team managing these data has adapted technologies and services to better address the data and information search, discovery, and access needs of the science user community. This presentation will provide an overview of CSDA Program data system activities including data availability, development of CSDA user interfaces, challenges in managing large-volume diverse datasets, and long-term data preservation activities to retain data for scientific reproducibility.

data management↗
DOE OSTI2015

Absorbed Doses and Risk Estimates of {sup 211}At-MX35 F(ab'){sub 2} in Intraperitoneal Therapy of Ovarian Cancer Patients

Purpose: Ovarian cancer is often diagnosed at an advanced stage with dissemination in the peritoneal cavity. Most patients achieve clinical remission after surgery and chemotherapy, but approximately 70% eventually experience recurrence, usually in the peritoneal cavity. To prevent recurrence, intraperitoneal (i.p.) targeted α therapy has been proposed as an adjuvant treatment for minimal residual disease after successful primary treatment. In the present study, we calculated absorbed and relative biological effect (RBE)-weighted (equivalent) doses in relevant normal tissues and estimated the effective dose associated with i.p. administration of {sup 211}At-MX35 F(ab'){sub 2}. Methods and Materials: Patients in clinical remission after salvage chemotherapy for peritoneal recurrence of ovarian cancer underwent i.p. infusion of {sup 211}At-MX35 F(ab'){sub 2}. Potassium perchlorate was given to block unwanted accumulation of {sup 211}At in thyroid and other NIS-containing tissues. Mean absorbed doses to normal tissues were calculated from clinical data, including blood and i.p. fluid samples, urine, γ-camera images, and single-photon emission computed tomography/computed tomography images. Extrapolation of preclinical biodistribution data combined with clinical blood activity data allowed us to estimate absorbed doses in additional tissues. The equivalent dose was calculated using an RBE of 5 and the effective dose using the recommended weight factor of 20. All doses were normalized to the initial activity concentration of the infused therapy solution. Results: The urinary bladder, thyroid, and kidneys (1.9, 1.8, and 1.7 mGy per MBq/L) received the 3 highest estimated absorbed doses. When the tissue-weighting factors were applied, the largest contributors to the effective dose were the lungs, stomach, and urinary bladder. Using 100 MBq/L, organ equivalent doses were less than 10% of the estimated tolerance dose. Conclusion: Intraperitoneal {sup 211}At-MX35 F(ab'){sub 2} treatment is potentially a well-tolerated therapy for locally confined microscopic ovarian cancer. Absorbed doses to normal organs are low, but because the effective dose potentially corresponds to a risk of treatment-induced carcinogenesis, optimization may still be valuable.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2021

Data-driven building energy modeling with feature selection and active learning for data predictive control

Three gaps impede the development of cost-effective and accurate data-driven building energy modeling/models (DBEM) for energy forecasting and predictive control strategies. Gap 1: data bias is common in building operation data, but this topic is hardly studied in DBEM; Gap 2: high data dimensionality is common in DBEM, but a systematic and scalable methodology is lacking to solve the problem; Gap 3: the interactions between data bias and high dimensionality have not been systematically studied for DBEM and predictive control in buildings. In this work, to address the three gaps mentioned above, we develop a framework that integrates active learning and feature selection for DBEM used for whole building data predictive control (or DPC, which is a branch of model predictive control). The framework provides a systematic methodology and automatic workflow that starts with raw data from building automation systems to the establishment of data-driven energy models for DPC controllers. The developed strategies and framework are evaluated in a virtual testbed based on EnergyPlus and BCVTB. Improved performance and reduced computational complexity are observed from the DBEM built with the developed framework, as well as the DPC controller based on that DBEM, indicating the effectiveness of the developed framework.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2017

Development of models for predicting Torsade de Pointes cardiac arrhythmias using perceptron neural networks

Background: Blockage of some ion channels and in particular, the hERG (human Ether-a’-go-go-Related Gene) cardiac potassium channel delays cardiac repolarization and can induce arrhythmia. In some cases it leads to a potentially life-threatening arrhythmia known as Torsade de Pointes (TdP). Therefore recognizing drugs with TdP risk is essential. Candidate drugs that are determined not to cause cardiac ion channel blockage are more likely to pass successfully through clinical phases II and III trials (and preclinical work) and not be withdrawn even later from the marketplace due to cardiotoxic effects. The objective of the present study is to develop an SAR (Structure-Activity Relationship) model that can be used as an early screen for torsadogenic (causing TdP arrhythmias) potential in drug candidates. The method is performed using descriptors comprised of atomic NMR chemical shifts (13C and 15N NMR) and corresponding interatomic distances which are combined into a 3D abstract space matrix. The method is called 3D-SDAR (3-dimensional spectral data-activity relationship) and can be interrogated to identify molecular features responsible for the activity, which can in turn yield simplified hERG toxicophores. A dataset of 55 hERG potassium channel inhibitors collected from Kramer et al. consisting of 32 drugs with TdP risk and 23 with no TdP risk was used for training the 3D-SDAR model. Results: An artificial neural network (ANN) with multilayer perceptron was used to define collinearities among the independent 3D-SDAR features. A composite model from 200 random iterations with 25% of the molecules in each case yielded the following figures of merit: training, 99.2%; internal test sets, 66.7%; external (blind validation) test set, 68. 4%. In the external test set, 70.3% of positive TdP drugs were correctly predicted. Moreover, toxicophores were generated from TdP drugs. Conclusion: A 3D-SDAR was successfully used to build a predictive model for drug-induced torsadogenic and non-torsadogenic drugs based on 55 compounds. The model was tested in 38 external drugs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Assessment of Methane Emissions – Impact of Using Natural Gas Engines in Unconventional Resource Development

Researchers at the Center for Alternative Fuels, Engines, and Emissions (CAFEE) completed a multi-year program under DE-FE0013689 entitled, “Assessing Fugitive Methane Emissions Impact Using Natural Gas Engines in Unconventional Resource Development.” When drilling activity was high and industry sought to lower operating costs and reduce emissions they began investing in dual fuel and dedicated natural gas engines to power unconventional well equipment. From a review of literature we determined that the prime-movers (or major fuel consumers) of unconventional well development were the service trucks (trucking), horizontal drilling rig (drilling) engines, and hydraulic stimulation pump (fracturing) engines. Based on early findings from on-road studies we assessed that conversion of prime movers to operate on natural gas could contribute to methane emissions associated with unconventional wells. As such, we collected significant in-use activity data from service trucks and in-use activity, fuel consumption, and gaseous emissions data from drilling and fracturing engines. Our findings confirmed that conversion of the prime movers to operate as dual fuel or dedicated natural gas – created an additional source of methane emissions. While some gaseous emissions were decreased from implementation of these technologies – methane and CO 2 equivalent emissions tended to increase, especially for non-road engines. The increases were highest for dual fuel engines due to methane slip from the exhaust and engine crankcase. Dedicated natural gas engines tended to have lower exhaust methane emissions but higher CO 2 emissions due to lower efficiency. Therefore, investing in currently available natural gas technologies for prime movers will increase the greenhouse gas footprint of the unconventional well development industry.

03 NATURAL GAS↗
DOE OSTI2022

United States Nuclear Data Program Annual Report for FY2021

The US Nuclear Data Program (USNDP) Annual Report for Fiscal Year 2021 (FY21) summarizes the work of USNDP for the period of October 1, 2020 through September 30, 2021, with respect to the Work Plan for FY21 that was prepared in 2019. The Work Plan and Final Report for USNDP are prepared for the DOE Office of Science, Office of Nuclear Physics. The support for the nuclear data activity from sources outside the nuclear data program is described in the staffing table and in Appendix A. This leverage amounts to about 3.24 FTE scientific, to be compared with 25.095 FTEs at USNDP units funded by the DOE Office of Science, Office of Nuclear Physics. Since it is often difficult to separate accomplishments funded by various sources, some of the work reported in the present report was accomplished with nuclear data program support leveraged by other funding.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

United States Nuclear Data Program Annual Report for FY 23

The US Nuclear Data Program (USNDP) Annual Report for Fiscal Year 2023 (FY23) summarizes the work of USNDP for the period of October 1, 2022 through September 30, 2023, with respect to the Work Plan for FY23 that was prepared in 2022. The Work Plan and Final Report for USNDP are prepared for the DOE Office of Science, Office of Nuclear Physics. The support for the nuclear data activity from sources outside the nuclear data program is described in the staffing table and in Appendix A. This leverage amounts to about 17.4 FTE scientific, to be compared with 23.8 FTEs at USNDP units funded by the DOE Office of Science, Office of Nuclear Physics. Since it is often difficult to separate accomplishments funded by various sources, some of the work reported in the present report was accomplished with nuclear data program support leveraged by other funding.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

United States Nuclear Data Program Annual Report for Fiscal Year 2024

The US Nuclear Data Program (USNDP) Annual Report for Fiscal Year 2024 (FY24) summarizes the work of USNDP for the period of October 1, 2023 through September 30, 2024, with respect to the Work Plan for FY24 that was prepared in 2022. The Work Plan and Final Report for USNDP are prepared for the DOE Office of Science, Office of Nuclear Physics. The support for the nuclear data activity from sources outside the nuclear data program is described in the staffing table and in Appendix A. This leverage amounts to about 14.8 FTE scientific, to be compared with 13.9 FTEs at USNDP units funded by the DOE Office of Science, Office of Nuclear Physics. Since it is often difficult to separate accomplishments funded by various sources, some of the work reported in the present report was accomplished with nuclear data program support leveraged by other funding.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1977

Metabolic cost of extravehicular activities

The Skylab zero-g extravehicular activity data is of particular interest when it is considered in combination with the Apollo and Gemini data. The energy cost of extravehicular activity from Gemini through Skylab is discussed.

Waligora, J. M.↗
NASA NTRS1989

On developing the local research environment of the 1990s - The Space Station era

A requirements analysis for the Space Station's polar platform data system has been performed. Based upon this analysis, a cluster, layered cluster, and layered-modular implementation of one specific module within the Eos Data and Information System (EosDIS), an active data base for satellite remote sensing research has been developed. It is found that a distributed system based on a layered-modular architecture and employing current generation work station technologies has the requisite attributes ascribed by the remote sensing research community. Although, based on benchmark testing, probabilistic analysis, failure analysis and user-survey technique analysis, it is found that this architecture presents some operational shortcomings that will not be alleviated with new hardware or software developments. Consequently, the potential of a fully-modular layered architectural design for meeting the needs of Eos researchers has also been evaluated, concluding that it would be well suited to the evolving requirements of this multidisciplinary research community.

Chase, Robert↗
DOE OSTI2017

Generation of an Activation Map for Decommissioning Planning of the Berlin Experimental Reactor-II

The BER-II is an experimental facility with 10 MW that was operated since 1974. Its operation will end in 2019. To support the decommissioning planning, a map with the overall distribution of relevant radionuclides has to be created according to the state of the art. The activation analysis comprises all load periods until the planned shutdown. A procedure for an activation calculation of the pool structure of the BER-II research reactor including the concrete shielding is presented. With the combination of the options offered by MCNP6 and PARTISN, an effective method to compute the neutron flux for a reactor geometry model with 2,790,000 cells could be achieved. The fact that for calculations with PARTISN some extra effort to generate the XS is needed is more than compensated by the fact that for all volumes of the model, neutron fluxes are produced that can be subsequently used for the activation calculation. With the power history provided together with the material compositions, an activation map was created for the whole structure, even for the most remote parts. The activity can be calculated for all nuclides of the FISPACT library. Depending on material and irradiation history, however, only a limited number of nuclides must be regarded to reduce the size of activation data base. The results for the activation at calibration points give an example that the use of detailed calculation methods allows reliable estimation of the activity of relevant nuclides. The mean and the maximum activity can be determined. For a more detailed analysis, it is desirable to provide some more calibration points and realistic material specifications including impurities where the results of the activation can be validated, especially for more remote regions of the concrete structures.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Feasibility of Operating a Heavy-Duty Battery Electric Truck Fleet for Drayage Applications

Vehicle fleet electrification is regarded as one major pathway toward achieving energy independence and reducing air pollution and greenhouse gas emissions. Compared to light-duty and medium-duty vehicles, electrification of heavy-duty vehicles, especially Class 8 trucks, is more challenging owing to the battery size required to attain the driving range necessary for their operating goals. As drayage trucks generally have a limited daily mileage, return to a home base every night, and spend a large amount of time creeping and idling, drayage operation has been the first targeted application for Class 8 electric trucks. The feasibility of operating battery electric drayage trucks at the individual vehicle level has recently been demonstrated. However, questions remain as to whether these trucks are capable of meeting the needs of typical drayage operation at the fleet level. Here we present a feasibility analysis of operating an electric truck fleet based on real-world operation data of a diesel drayage operator in Southern California. Second-by-second activity data collected from 20 trucks in the fleet were used to estimate the corresponding electric energy consumption and the state of charge of the battery using a microscopic electric energy consumption model. An algorithm for generating tours of drayage activity from the collected data was developed and implemented. Multiple scenarios with different battery charging and truck scheduling assumptions were analyzed. The results show that 85% of the tours could be served by electric trucks if there is opportunity for charging at the home base during the time gap between consecutive tours.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2015

Mixed Initiative Visual Analytics Using Task-Driven Recommendations

Visual data analysis is composed of a collection of cognitive actions and tasks to decompose, internalize, and recombine data to produce knowledge and insight. Visual analytic tools provide interactive visual interfaces to data to support tasks involved in discovery and sensemaking, including forming hypotheses, asking questions, and evaluating and organizing evidence. Myriad analytic models can be incorporated into visual analytic systems, at the cost of increasing complexity in the analytic discourse between user and system. Techniques exist to increase the usability of interacting with such analytic models, such as inferring data models from user interactions to steer the underlying models of the system via semantic interaction, shielding users from having to do so explicitly. Such approaches are often also referred to as mixed-initiative systems. Researchers studying the sensemaking process have called for development of tools that facilitate analytic sensemaking through a combination of human and automated activities. However, design guidelines do not exist for mixed-initiative visual analytic systems to support iterative sensemaking. In this paper, we present a candidate set of design guidelines and introduce the Active Data Environment (ADE) prototype, a spatial workspace supporting the analytic process via task recommendations invoked by inferences on user interactions within the workspace. ADE recommends data and relationships based on a task model, enabling users to co-reason with the system about their data in a single, spatial workspace. This paper provides an illustrative use case, a technical description of ADE, and a discussion of the strengths and limitations of the approach.

active data↗
DOE OSTI2026

United States Nuclear Data Program Annual Report for Fiscal Year 2025

The US Nuclear Data Program (USNDP) Annual Report for Fiscal Year 2025 summarizes the work of USNDP for the period of October 1, 2024 through September 30, 2025, with respect to the Work Plan for FY 2025 that was prepared in 2024. The Work Plan and Final Report for USNDP are prepared for the DOE Office of Science, Office of Nuclear Physics. The support for the nuclear data activity from sources outside the US Nuclear Data Program is summarized in the staffing table and Appendix A. This leverage amounts to about 22.8 FTE scientific, to be compared with 21.9 FTEs at USNDP units funded by the DOE Office of Science, Office of Nuclear Physics. Since it is often difficult to separate accomplishments funded by various sources, some of the work reported in the present report was accomplished with nuclear data program support leveraged by other funding. FY 2025 was the 25th year in which the USNDP has operated under a Work Plan developed by the program participants. The program continued to carry out important work in support of the DOE mission. The work balances the ongoing collecting, analyzing, and archiving of nuclear physics information critical to basic nuclear research and to the development and improvement of nuclear technologies with the electronic distribution of this information to users in a timely and easily accessible manner. The present section of the report consists of activity summaries for the major components of the USNDP. This is followed by an updated staff level assignment table that reflects the final distribution of effort among the tasks carried out during FY 2025. Then, we continue with the detailed status of work performed during FY 2025.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2019

Experimental Study on the Thermodynamics of the CaO-SiO{sub 2}-Ce{sub 2}O{sub 3} System at 1873 K

The phase relations in the CaO-SiO{sub 2}-Ce{sub 2}O{sub 3} system under the reducing atmosphere at 1873 K were determined by the conventional equilibrium and quenching method combined with scanning electron microscopy-electron probe microanalysis (SEM-EPMA) and X-ray diffraction (XRD) measurements on the quenched samples. Based on these analyses, a large part of the isothermal phase diagram was constructed. Furthermore, the thermodynamic activities of Ce{sub 2}O{sub 3} in the melts at 1873 K were measured by the chemical equilibrium method. Using the measured activity data, an empirical formula to estimate the activity coefficient of Ce{sub 2}O{sub 3} was proposed based on the regular solution model. It was found that, for the melts with the same Ce{sub 2}O{sub 3} contents, the thermodynamic activities of Ce{sub 2}O{sub 3} increase gradually with the rise of basicity (the ratio of CaO to SiO{sub 2}) of the melts. This implies that, from the thermodynamic point of view, the increase of basicity is favorable to the enrichment and precipitation of Ce-containing mineral phases.

36 MATERIALS SCIENCE↗
NASA NTRS2003

MODIS Validation, Data Merger and Other Activities Accomplished by the SIMBIOS Project: 2002-2003

The purpose of this technical report is to provide current documentation of the Sensor Intercomparison and Merger for Biological and Interdisciplinary Oceanic Studies (SIMBIOS) Project activities, satellite data processing, and data product validation. This documentation is necessary to ensure that critical information is related to the scientific community and NASA management. This critical information includes the technical difficulties and challenges of validating and combining ocean color data from an array of independent satellite systems to form consistent and accurate global bio-optical time series products. This technical report focuses on the SIMBIOS Project s efforts in support of the Moderate-Resolution Imaging Spectroradiometer (MODIS) on the Earth Observing System (EOS) Terra platform (similar evaluations of MODIS/Aqua are underway). This technical report is not meant as a substitute for scientific literature. Instead, it will provide a ready and responsive vehicle for the multitude of technical reports issued by an operational project.

Fargion, Giulietta S.↗