{"paper":{"title":"Mask-Morph Graph U-Net: A Generalisable Mesh-Based Surrogate for Crashworthiness Field Prediction under Large Geometric Variation","license":"http://creativecommons.org/licenses/by/4.0/","headline":"Mask-Morph Graph U-Net uses coarse-graph morphing and masked pretraining to generalise hierarchical GNNs to new mesh geometries in crash simulations.","cross_cats":["cs.CV"],"primary_cat":"cs.LG","authors_text":"Haoran Li, Haosu Zhou, Nan Li, Philipp Stocker, Tobias Lehrer, Tobias Pfaff, Yingxue Zhao","submitted_at":"2026-05-13T18:04:58Z","abstract_excerpt":"Nonlinear finite element crash simulations are accurate but computationally expensive, limiting their use in iterative design optimisation. Machine-learning surrogate models based on graph neural networks (GNNs) offer a faster alternative. Message-passing GNNs are widely used for mesh simulation, and their shared node and edge update functions are relatively generalisable across varying graph structures. By contrast, non-shareable edge-specific aggregation layers can capture nonlinear relationships more accurately but usually require fixed graph connectivity, which limits generalisability. 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R. Wu, Convergence study on explicit finite element for crashwor- thiness analysis, Tech. Rep. 2006-01-0672, SAE International (2006). doi:10.4271/2006-01-0672","work_id":"13d20550-59ad-4067-a002-f687f3f10592","ref_index":1,"cited_arxiv_id":"","is_internal_anchor":false},{"doi":"10.4271/2007-01-0982","year":2007,"title":"J. Chang, T. Tyan, M. El-Bkaily, J. Cheng, A. Marpu, Q. Zeng, J. Santini, Implicit and explicit finite element methods for crash safety analysis, Tech. Rep. 2007-01-0982, SAE International (2007). doi","work_id":"906c7423-d219-47b9-8a2a-52b8fee88b53","ref_index":2,"cited_arxiv_id":"","is_internal_anchor":false},{"doi":"","year":2023,"title":"E. Albak, Optimization design for circular multi-cell thin-walled tubes with discrete and continuous design variables, Mechanics of Advanced Materials and Structures 30 (24) (2023) 5091–5105","work_id":"650860c8-5870-4a30-a825-84b73009c2c6","ref_index":3,"cited_arxiv_id":"","is_internal_anchor":false},{"doi":"","year":2018,"title":"F. Xiong, D. Wang, Z.-D. Ma, L. Yang, Z. Li, B. Song, Multi-objective lightweight and crashworthiness optimization for the side structure of an automobile body, Structural and Multidisciplinary Optimi","work_id":"f4a3d349-b850-4589-a786-aa6f0f8890ec","ref_index":4,"cited_arxiv_id":"","is_internal_anchor":false},{"doi":"","year":2019,"title":"A. Ahmadi Dastjerdi, M. Moshref-Javadi, H. Ahmadian, M. Gholam- pour, Crushing analysis and multi-objective optimization of different length bi-thin walled cylindrical structures under axial impact lo","work_id":"b03319da-4261-4250-ab1c-2b092080af3f","ref_index":5,"cited_arxiv_id":"","is_internal_anchor":false}],"resolved_work":55,"snapshot_sha256":"c5efb8b033b4c3cc5fe5b690cfb5f64d95b1fea270fb49cda63690182c8bf678","internal_anchors":2},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"}