{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:CADPEYOD5EE56NAHZOYF5Q64NG","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":"d7fc9e150ad6b3b0ee11b856831bb88c4dfc463bd628accc8f86cfa5a783bf75","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"physics.flu-dyn","submitted_at":"2026-07-16T12:53:06Z","title_canon_sha256":"5b407139a139666b3d1c8483e2556cef63508af7121d3a398efa3d93425760f9"},"schema_version":"1.0","source":{"id":"2607.14944","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2607.14944","created_at":"2026-07-17T01:22:00Z"},{"alias_kind":"arxiv_version","alias_value":"2607.14944v1","created_at":"2026-07-17T01:22:00Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.14944","created_at":"2026-07-17T01:22:00Z"},{"alias_kind":"pith_short_12","alias_value":"CADPEYOD5EE5","created_at":"2026-07-17T01:22:00Z"},{"alias_kind":"pith_short_16","alias_value":"CADPEYOD5EE56NAH","created_at":"2026-07-17T01:22:00Z"},{"alias_kind":"pith_short_8","alias_value":"CADPEYOD","created_at":"2026-07-17T01:22:00Z"}],"graph_snapshots":[{"event_id":"sha256:221ad3bf1c33b1494897d2a5545215f8aad337bdfc72bebf12c85cdf7732681a","target":"graph","created_at":"2026-07-17T01:22:00Z","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/2607.14944/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Recent advances in data-driven modelling have highlighted the potential of hybrid approaches which combine Tensor Basis Neural Networks (TBNN) with Universal Differential Equations (UDE) to discover frame-invariant, non-linear viscoelastic constitutive models. These hybrid models enable the creation of digital twins for complex viscoelastic fluids, offering direct transferability to computational fluid dynamics simulations. In this work, we introduce a reduced dimensional tensor basis formulation that enhances both the physical consistency of the learned representations with respect to the tra","authors_text":"C. Fernandes, F. Dong, J.L. Cummings, M.A. Alves, M.S.N. Oliveira","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"physics.flu-dyn","submitted_at":"2026-07-16T12:53:06Z","title":"Harnessing Machine Learning for Hybrid Constitutive Modelling of Viscoelastic Fluid Flows in Computational Rheology"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.14944","kind":"arxiv","version":1},"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":"sha256:8644a1f413beed8480974406ef8f889d0fa90b66befd1ff69635c11970d74970","target":"record","created_at":"2026-07-17T01:22:00Z","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":"d7fc9e150ad6b3b0ee11b856831bb88c4dfc463bd628accc8f86cfa5a783bf75","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"physics.flu-dyn","submitted_at":"2026-07-16T12:53:06Z","title_canon_sha256":"5b407139a139666b3d1c8483e2556cef63508af7121d3a398efa3d93425760f9"},"schema_version":"1.0","source":{"id":"2607.14944","kind":"arxiv","version":1}},"canonical_sha256":"1006f261c3e909df3407cbb05ec3dc69b4bdd01abe6811983347728439a75315","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"1006f261c3e909df3407cbb05ec3dc69b4bdd01abe6811983347728439a75315","first_computed_at":"2026-07-17T01:22:00.417533Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-17T01:22:00.417533Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ttO8fbMxVoSJcpcHaQj24BtCAM+D1cVb7o+sDl0W1++WE1Lf0Yx4nFECgExK+dTXRGN/yh7F5C18OPH9nDWRBA==","signature_status":"signed_v1","signed_at":"2026-07-17T01:22:00.418375Z","signed_message":"canonical_sha256_bytes"},"source_id":"2607.14944","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:8644a1f413beed8480974406ef8f889d0fa90b66befd1ff69635c11970d74970","sha256:221ad3bf1c33b1494897d2a5545215f8aad337bdfc72bebf12c85cdf7732681a"],"state_sha256":"1a823c240f0e044b9ec54e85e851d36decf755a98d60ad5abd827ecfa9be56a2"}