Brenner, Alex (2022) Data Analysis in Parabolic Trough Fields - Determination of Mirror Cleanliness with Machine Learning. Helmholtz Energy Young Scientists Workshop, 30.05.2022, Frankfurt.
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Item URL in elib: | https://elib.dlr.de/189493/ | ||||||
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Document Type: | Conference or Workshop Item (Speech) | ||||||
Title: | Data Analysis in Parabolic Trough Fields - Determination of Mirror Cleanliness with Machine Learning | ||||||
Authors: |
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Date: | 30 May 2022 | ||||||
Refereed publication: | No | ||||||
Open Access: | Yes | ||||||
Gold Open Access: | No | ||||||
In SCOPUS: | No | ||||||
In ISI Web of Science: | No | ||||||
Status: | Published | ||||||
Keywords: | parabolic trough; condition monitoring; soiling; machine learning | ||||||
Event Title: | Helmholtz Energy Young Scientists Workshop | ||||||
Event Location: | Frankfurt | ||||||
Event Type: | national Conference | ||||||
Event Dates: | 30.05.2022 | ||||||
HGF - Research field: | Energy | ||||||
HGF - Program: | Materials and Technologies for the Energy Transition | ||||||
HGF - Program Themes: | High-Temperature Thermal Technologies | ||||||
DLR - Research area: | Energy | ||||||
DLR - Program: | E SW - Solar and Wind Energy | ||||||
DLR - Research theme (Project): | E - Advanced Heat Transfer Media | ||||||
Location: | Stuttgart | ||||||
Institutes and Institutions: | Institute of Solar Research > Solar High Temperature Technologies | ||||||
Deposited By: | Lucarelli, Fabio | ||||||
Deposited On: | 28 Oct 2022 10:48 | ||||||
Last Modified: | 13 Jan 2023 07:51 |
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