{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:3AAMN4EBTROVWA7G7N7QMXO2KW","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"998616416eea8c9c11cc99cc60ad0be43175c7b7af89cf7b0c979e092e1efd89","cross_cats_sorted":["cs.LG","cs.SY"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.SY","submitted_at":"2025-03-16T23:55:40Z","title_canon_sha256":"48bca7e2a5a38a641027f3be2634bdd469bc9c0bb15aaf4e51156fe06834c360"},"schema_version":"1.0","source":{"id":"2503.17386","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2503.17386","created_at":"2026-06-19T16:12:45Z"},{"alias_kind":"arxiv_version","alias_value":"2503.17386v2","created_at":"2026-06-19T16:12:45Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2503.17386","created_at":"2026-06-19T16:12:45Z"},{"alias_kind":"pith_short_12","alias_value":"3AAMN4EBTROV","created_at":"2026-06-19T16:12:45Z"},{"alias_kind":"pith_short_16","alias_value":"3AAMN4EBTROVWA7G","created_at":"2026-06-19T16:12:45Z"},{"alias_kind":"pith_short_8","alias_value":"3AAMN4EB","created_at":"2026-06-19T16:12:45Z"}],"graph_snapshots":[{"event_id":"sha256:d105c1f799d290c678586461566aea5b49c504221fbb4b5d8b8672194d587f74","target":"graph","created_at":"2026-06-19T16:12:45Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2503.17386/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Crashworthiness is a key performance measure in the design of safety-critical vehicle panel components such as B-pillars. Finite element (FE) simulations are widely used to evaluate crash responses but remain computationally expensive for large-scale, nonlinear impact scenarios, particularly when integrated into iterative design and optimisation processes. Although machine learning-based surrogate models have been developed for rapid crashworthiness analysis, they exhibit limitations in detailed representation of complex 3-dimensional components. Graph Neural Networks (GNNs) have emerged as a ","authors_text":"Haoran Li, Haosu Zhou, Nan Li, Tobias Pfaff, Yingxue Zhao","cross_cats":["cs.LG","cs.SY"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.SY","submitted_at":"2025-03-16T23:55:40Z","title":"A graph neural network surrogate model for mesh-based crashworthiness prediction of vehicle panel components"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2503.17386","kind":"arxiv","version":2},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:1c54c05e7b75f29d145167596762aa3c31f90f0aa5f7716da4a5fe982b52b0ab","target":"record","created_at":"2026-06-19T16:12:45Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"998616416eea8c9c11cc99cc60ad0be43175c7b7af89cf7b0c979e092e1efd89","cross_cats_sorted":["cs.LG","cs.SY"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.SY","submitted_at":"2025-03-16T23:55:40Z","title_canon_sha256":"48bca7e2a5a38a641027f3be2634bdd469bc9c0bb15aaf4e51156fe06834c360"},"schema_version":"1.0","source":{"id":"2503.17386","kind":"arxiv","version":2}},"canonical_sha256":"d800c6f0819c5d5b03e6fb7f065dda55b1a622d24788ecfcada17aec2474a974","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d800c6f0819c5d5b03e6fb7f065dda55b1a622d24788ecfcada17aec2474a974","first_computed_at":"2026-06-19T16:12:45.408515Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-19T16:12:45.408515Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"o0II7C6n2MmrALNqUI607JWCBPtg4Bc06MQiTobPGDZRUzzzypj3UtAAEKsGJc/a6Yr9bvs2sD8K6qZz67EzCA==","signature_status":"signed_v1","signed_at":"2026-06-19T16:12:45.408977Z","signed_message":"canonical_sha256_bytes"},"source_id":"2503.17386","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:1c54c05e7b75f29d145167596762aa3c31f90f0aa5f7716da4a5fe982b52b0ab","sha256:d105c1f799d290c678586461566aea5b49c504221fbb4b5d8b8672194d587f74"],"state_sha256":"04c17eb0203fb3539b34062a5e5ad9ca77db29fa702d6e5f2bcca8fa8c41a5bb"}