Show simple item record

dc.contributor.authorSharma, Aayushman
dc.contributor.authorMao, Zirui
dc.contributor.authorYang, Haiying
dc.contributor.authorChakravorty, Suman
dc.contributor.authorDemkowicz, Michael J.
dc.contributor.authorKalathil, Dileep
dc.date.accessioned2024-12-24T18:49:38Z
dc.date.available2024-12-24T18:49:38Z
dc.date.copyright8/24/2024 12:00:00 AM
dc.date.issued2024
dc.identifier.issn0022-0434
dc.identifier.otherds_146_06_061109.pdf
dc.identifier.urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4302823
dc.description.abstractIn this paper, we consider the optimal control of material microstructures. Such material microstructures are modeled by the so-called phase-field model. We study the underlying physical structure of the model and propose a data-based approach for its optimal control, along with a comparison to the control using a state-of-the-art reinforcement learning (RL) algorithm. Simulation results show the feasibility of optimally controlling such microstructures to attain desired material properties and complex target microstructures.
dc.publisherThe American Society of Mechanical Engineers (ASME)
dc.titleOptimal Control of Material Microstructures1
dc.typeJournal Paper
dc.journal.volume146
dc.journal.issue6
dc.journal.titleJournal of Dynamic Systems, Measurement, and Control
dc.identifier.doi10.1115/1.4065801
dc.journal.fristpage61109-1
dc.journal.lastpage61109-15
dc.page15
dc.treeJournal of Dynamic Systems, Measurement, and Control:;2024:;volume( 146 ):;issue: 006
dc.contenttypeFulltext


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record