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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 1,315 records · Page 73
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

High-voltage insulator having multiple materials

High-voltage insulators are disclosed that are capable of handling diverse requirements, such as providing high standoff voltages, high temperature cycling, and the ability to withstand flexural stress. One high-voltage insulator includes a first piece formed from a first material, a second piece formed from a second material, and an interface section where the first piece contacts with and forms a seal with the second piece. The interface includes a first groove located that accommodates a first gasket, sets of matching threads on the first and second pieces. The interface section further accommodates a second gasket. In this multi-piece high-voltage insulator, the first material can have a first set of flexural, heat resistance, and electrical standoff characteristics suitable for a first environment, and the second material can have a second set of flexural, heat resistance and electrical standoff characteristics suitable for a second environment.

Podpaly, Yuri Anatoly↗
DOE OSTI2021

Algae: A Single Cell for Multiple Solutions

An overview of the BETO support of public and private partners that work to improve and increase the use of algae for production of biofuels and bioproducts.

algae, biofuels, bioproducts↗
DOE OSTI2021

Weather responsive smart ventilation system using multiple optimization parameters

A smart ventilation system which uses outdoor temperature and moisture to optimize control of the system. The main principle is to shift ventilation from time periods that have large indoor-outdoor temperature and moisture differences to periods when these differences are smaller, and their energy and comfort impacts are expected to be less. Fan flow rates are reduced when the outside temperature and moisture falls outside of optimum levels, yet overall air exchange is maintained to ensure chronic and acute exposure to pollutants remains relative to best practice. Online weather and smart thermostat data can be used as control inputs, so no specific measurement devices are needed to control ventilation fans.

Parker, Danny↗
DOE OSTI2021

Three dimensional nanoporous membrane having multiple independent, continuous pore systems

According to one embodiment, a composition of matter includes: a first system of continuous voids arranged in a three-dimensional matrix; a second system of continuous voids arranged in the three-dimensional matrix; and a nanoporous barrier separating the first system of continuous voids and the second system of continuous voids. The first system of continuous voids and the second system of continuous voids are interwoven but independent so as to form a plurality of channels through the three-dimensional matrix. Corresponding methods for forming the composition of matter are also disclosed.

Ye, Jianchao↗
DOE OSTI2022

Investigation of Multiple Data Streams for Gearbox Bearing Fault Prediction Through Machine-Learning Models

Operations and maintenance (O&M) cost of wind plant accounts up to 30% of total energy cost, which can be reduced through continuous monitoring and successfully detecting incipient wind turbine failures. To accomplish this, condition monitoring and predictive maintenance systems are being implemented in wind industry to support O&M decision making. A wide range of approaches for condition monitoring and fault prediction have been developed. These approaches generally use historical data of wind turbines collected by Supervisory Control and Data Acquisition (SCADA) system to identify patterns that lead to failure. These SCADA data show the overall condition of a wind turbine and can be leveraged to detect when the turbine's performance is degrading and to identify if a fault is developing. However, it becomes challenging to predict the failure of a specific wind turbine gearbox bearing, because the SCADA data are often not directly linked to the component. To bridge the gap, we have investigated features calculated from SCADA data using physics-based models and the gearbox design over the years. The damaged metric we used in the physics domain is frictional energy. Combining these physics domain variables with SCADA data as inputs to various machine learning models for gearbox bearing fault prediction, we have demonstrated the benefits of leveraging both physics and data domain models. It was an attempt to improve frictional-energy-based damage metric by adding data domain inputs, as we had learned that the frictional-energy-based damage metric alone is not sufficient to single out failed bearings from healthy. As condition monitoring data (either vibration or oil debris data) has become available at more and more wind plants, we would like to evaluate whether by adding the condition monitoring data can help further improve the performance of frictional-energy-based damage metric for gearbox bearing fault prediction. Both cases by modeling through various machine learning algorithms are discussed in this study along with some observations.

fault prediction↗
DOE OSTI2022

Renewable Thermal Energy Systems Designed for Industrial Process Solutions in Multiple Industries

Industrial decarbonization is a key area that must be accelerated, to foster the removal of fossil fuels from the provision of heat, especially at low temperatures less than 300 degrees C. This paper looks at the results of two case studies for understanding the economics and potential for renewable thermal energy systems (RTES), particularly in hybrid configurations to provide industrial process heat (IPH). The first case study looks at heat pumps for district heating, and the second, the use of linear Fresnel collectors (LFCs) coupled with phase change material (PCM) thermal energy storage (TES) for direct steam generation (DSG). Using district heat as an input for the heat pump, three cases were run harvesting energy from ambient water (5 degrees C), sewage water (20 degrees C), and a solar collector (35 degrees C). Accounting for elevated costs of infrastructure for each heat source, the levelized cost of heat (LCOH) of the first case study ranged from $4-$15 per million British Thermal Units (MMBTU). For the second case study modeling LFCs with PCM and TES, the results show that a LCOH of $9-$15 per MMBTU is possible, depending on the direct normal irradiance.

concentrated solar thermal↗
DOE OSTI2022

Renewable Thermal Energy Systems Designed for Industrial Process Solutions in Multiple Industries: Preprint

Industrial decarbonization is a key area that must be accelerated, to foster the removal of fossil fuels from the provision of heat, especially at low temperatures less than 300 degrees C. This paper looks at the results of two case studies for understanding the economics and potential for renewable thermal energy systems (RTES), particularly in hybrid configurations to provide industrial process heat (IPH). The first case study looks at heat pumps for district heating, and the second, the use of linear Fresnel collectors (LFCs) coupled with phase change material (PCM) thermal energy storage (TES) for direct steam generation (DSG). Using district heat as an input for the heat pump, three cases were run harvesting energy from ambient water (5 degrees C), sewage water (20 degrees C), and a solar collector (35 degrees C). Accounting for elevated costs of infrastructure for each heat source, the levelized cost of heat (LCOH) of the first case study ranged from $4-$10 per million British Thermal Units (MMBTU). For the second case study modeling LFCs with PCM and TES, the results show that a LCOH of $9-$15 per MMBTU is possible, depending on the direct normal irradiance.

concentrated solar thermal↗
DOE OSTI2022

Charge multiplication in thin scCVD diamond detectors

This presentation describes experimental measurements with thin scCVD diamond detectors and their DD and DT neutron sources. This presentation will be given at the NNSS Prompt Radiation Detection and Imaging Workshop April 25-28, 2022.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗