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dc.contributor.authorFaruqi, Faraz
dc.contributor.authorAbdel-Rahman, Amira
dc.contributor.authorTejedor, Leandra
dc.contributor.authorNisser, Martin
dc.contributor.authorLi, Jiaji
dc.contributor.authorPhadnis, Vrushank
dc.contributor.authorJampani, Varun
dc.contributor.authorGershenfeld, Neil
dc.contributor.authorHofmann, Megan
dc.contributor.authorMueller, Stefanie
dc.date.accessioned2025-12-12T21:40:54Z
dc.date.available2025-12-12T21:40:54Z
dc.date.issued2025-11-19
dc.identifier.isbn979-8-4007-2034-5
dc.identifier.urihttps://hdl.handle.net/1721.1/164312
dc.descriptionSCF ’25, Cambridge, MA, USAen_US
dc.description.abstractRecent developments in Generative AI enable creators to stylize 3D models based on text prompts. These methods change the 3D model geometry, which can compromise the model’s structural integrity once fabricated. We present MechStyle, a system that enables creators to stylize 3D printable models while preserving their structural integrity. MechStyle accomplishes this by augmenting the Generative AI-based stylization process with feedback from a Finite Element Analysis (FEA) simulation. As the stylization process modifies the geometry to approximate the desired style, feedback from the FEA simulation reduces modifications to regions with increased stress. We evaluate the effectiveness of FEA simulation feedback in the augmented stylization process by comparing three stylization control strategies. We also investigate the time efficiency of our approach by comparing three adaptive scheduling strategies. Finally, we demonstrate MechStyle’s user interface that allows users to generate stylized and structurally viable 3D models and provide five example applications.en_US
dc.publisherACM|ACM Symposium on Computational Fabricationen_US
dc.relation.isversionofhttps://doi.org/10.1145/3745778.3766655en_US
dc.rightsCreative Commons Attributionen_US
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_US
dc.sourceAssociation for Computing Machineryen_US
dc.titleMechStyle: Augmenting Generative AI with Mechanical Simulation to Create Stylized and Structurally Viable 3D Modelsen_US
dc.typeArticleen_US
dc.identifier.citationFaraz Faruqi, Amira Abdel-Rahman, Leandra Tejedor, Martin Nisser, Jiaji Li, Vrushank Phadnis, Varun Jampani, Neil Gershenfeld, Megan Hofmann, and Stefanie Mueller. 2025. MechStyle: Augmenting Generative AI with Mechanical Simulation to Create Stylized and Structurally Viable 3D Models. In Proceedings of the ACM Symposium on Computational Fabrication (SCF '25). Association for Computing Machinery, New York, NY, USA, Article 24, 1–15.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratoryen_US
dc.contributor.departmentMassachusetts Institute of Technology. Center for Bits and Atomsen_US
dc.identifier.mitlicensePUBLISHER_POLICY
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/ConferencePaperen_US
eprint.statushttp://purl.org/eprint/status/NonPeerRevieweden_US
dc.date.updated2025-12-01T09:10:15Z
dc.language.rfc3066en
dc.rights.holderThe author(s)
dspace.date.submission2025-12-01T09:10:16Z
mit.licensePUBLISHER_CC
mit.metadata.statusAuthority Work and Publication Information Neededen_US


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