Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Tarek Iraki"'
Publikováno v:
Frontiers in Materials, Vol 8 (2022)
In materials design, supervised learning plays an important role for optimization and inverse modeling of microstructure-property relations. To successfully apply supervised learning models, it is essential to train them on suitable data. Here, suita
Externí odkaz:
https://doaj.org/article/c76af82cabb44e9cbf567d3e08c18244
Publikováno v:
Journal of Intelligent Manufacturing
Optimization along the chain processing-structure-properties-performance is one of the core objectives in data-driven materials science. In this sense, processes are supposed to manufacture workpieces with targeted material microstructures. These mic
Generative models for capturing and exploiting the influence of process conditions on process curves
Autor:
Norbert Link, Tarek Iraki
Publikováno v:
Journal of Intelligent Manufacturing. 33:473-492
Variations of dedicated process conditions (such as workpiece and tool properties) yield different process state evolutions, which are reflected by different time series of the observable quantities (process curves). A novel method is presented, whic
Publikováno v:
Journal of Intelligent Manufacturing, 33 (1), 333–352
A major goal of materials design is to find material structures with desired properties and in a second step to find a processing path to reach one of these structures. In this paper, we propose and investigate a deep reinforcement learning approach
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c301dcabe52383580be6594fe028308c
http://arxiv.org/abs/2009.09706
http://arxiv.org/abs/2009.09706