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These cycles are based on tests where the data of interest is acquired by point sensors, generating little data, especially at large scales such as a complete aircraft. Indeed, due to the complexity of shapes at these scales, field measurement methods (displacement or temperature), generating dense data, operate with difficulty.
Thus, the objective of PreDICT is to extract more data, from the same tests, by extending the application domain of field measurements to large structures. This serves a dual purpose: the feeding of increasingly complex models, as well as a better understanding of the phenomena. To this end, PreDICT will introduce tools from computer vision, graphic rendering and Artificial Intelligence into the field of mechanical field measurement, with a physics-based approach and the creation of a digital twin of the structure under test.<\/p>\n
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Rapha\u00ebl Fouque (ISAE-SUPAERO 2021) Projet PreDICT (Photometric stereo Digital Image Correlation Technique)To reduce greenhouse gas emissions from the aviation sector, breakthrough innovations in aircraft design cycles are needed. These cycles are based on tests where the data of interest is acquired by point sensors, generating little data, especially at large scales such as a complete […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"_et_pb_use_builder":"on","_et_pb_old_content":"","_et_gb_content_width":"1080","footnotes":""},"categories":[],"tags":[],"class_list":["post-920","post","type-post","status-publish","format-standard","hentry"],"acf":[],"yoast_head":"\n