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Deep Learing Inversion of a Raytracer for Heliostat Surface Prediction

Lewen, Jan and Pargmann, Max and Maldonado Quinto, Daniel and Pitz-Paal, Robert (2023) Deep Learing Inversion of a Raytracer for Heliostat Surface Prediction. SolarPaces 2023, 11.10-14.10.2023, Sydney, Australien.

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Abstract

We trained an inverse deep learining raytracing model, that is capable of predicting heliostat surfaces from flux densities. We have presented results that prove the capability of the model on simulative data.

Item URL in elib:https://elib.dlr.de/199103/
Document Type:Conference or Workshop Item (Speech)
Title:Deep Learing Inversion of a Raytracer for Heliostat Surface Prediction
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Lewen, JanUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Pargmann, MaxUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Maldonado Quinto, DanielUNSPECIFIEDhttps://orcid.org/0000-0003-2929-8667146767890
Pitz-Paal, RobertUNSPECIFIEDhttps://orcid.org/0000-0002-3542-3391UNSPECIFIED
Date:13 October 2023
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
Status:Published
Keywords:deep learning, heliostat surfaces, deflectometry
Event Title:SolarPaces 2023
Event Location:Sydney, Australien
Event Type:international Conference
Event Dates:11.10-14.10.2023
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 - Smart Operation
Location: Köln-Porz
Institutes and Institutions:Institute of Solar Research
Institute of Solar Research > Solar Power Plant Technology
Deposited By: Lewen, Jan
Deposited On:16 Nov 2023 10:37
Last Modified:16 Nov 2023 10:37

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