{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:UUUYHSGRANGWJGDPZH5EFCO44T","short_pith_number":"pith:UUUYHSGR","canonical_record":{"source":{"id":"2605.30659","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"physics.flu-dyn","submitted_at":"2026-05-28T23:38:38Z","cross_cats_sorted":[],"title_canon_sha256":"62b9d46f58d59e9b8cb6723e04f86305e88052c4cb79196a5dc2f50a24c9da03","abstract_canon_sha256":"6a006a257521db228e67ab0464dc4d6a795beef47107d7f31df481d68781660a"},"schema_version":"1.0"},"canonical_sha256":"a52983c8d1034d64986fc9fa4289dce4f7dddba367c759c54f6d8ca761e6bc44","source":{"kind":"arxiv","id":"2605.30659","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.30659","created_at":"2026-06-01T01:03:06Z"},{"alias_kind":"arxiv_version","alias_value":"2605.30659v1","created_at":"2026-06-01T01:03:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.30659","created_at":"2026-06-01T01:03:06Z"},{"alias_kind":"pith_short_12","alias_value":"UUUYHSGRANGW","created_at":"2026-06-01T01:03:06Z"},{"alias_kind":"pith_short_16","alias_value":"UUUYHSGRANGWJGDP","created_at":"2026-06-01T01:03:06Z"},{"alias_kind":"pith_short_8","alias_value":"UUUYHSGR","created_at":"2026-06-01T01:03:06Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:UUUYHSGRANGWJGDPZH5EFCO44T","target":"record","payload":{"canonical_record":{"source":{"id":"2605.30659","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"physics.flu-dyn","submitted_at":"2026-05-28T23:38:38Z","cross_cats_sorted":[],"title_canon_sha256":"62b9d46f58d59e9b8cb6723e04f86305e88052c4cb79196a5dc2f50a24c9da03","abstract_canon_sha256":"6a006a257521db228e67ab0464dc4d6a795beef47107d7f31df481d68781660a"},"schema_version":"1.0"},"canonical_sha256":"a52983c8d1034d64986fc9fa4289dce4f7dddba367c759c54f6d8ca761e6bc44","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-01T01:03:06.912293Z","signature_b64":"qln5ptV42Ol41vmVby5ZPaDwthRRk1gHC2B3UuomlFur/e2/LEQrrEa56cqjKgOOMNaFuEXxSQhi5xa11RzNCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a52983c8d1034d64986fc9fa4289dce4f7dddba367c759c54f6d8ca761e6bc44","last_reissued_at":"2026-06-01T01:03:06.911269Z","signature_status":"signed_v1","first_computed_at":"2026-06-01T01:03:06.911269Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2605.30659","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-06-01T01:03:06Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"mbcSCFeDBaX5MHjwsPOhZLltNKBXb+X9XrcWcCifJOfCIfLbjaVWBJ8ad+9X3mT7sCJ1Pkhlxt/396euC5ClCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-27T10:36:05.859567Z"},"content_sha256":"91b30c932e2cecc2c656acc5b636b003a82d6a849be4873fec18f2f9ae8845a6","schema_version":"1.0","event_id":"sha256:91b30c932e2cecc2c656acc5b636b003a82d6a849be4873fec18f2f9ae8845a6"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:UUUYHSGRANGWJGDPZH5EFCO44T","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Neural-Network-based Viscosity Closure for Non-Newtonian Multiphase Flows","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"physics.flu-dyn","authors_text":"Abraham Wiletsky, Adarsh Krishnamurthy, Andrew Rhode, Angela A. Pitenis, Austin Cunniff, Baskar Ganapathysubramanian, Cheng-Hau Yang, Christopher M. Bates, Claire L. Nelson, Dhruv Gamdha, Kaitlyn W. Dilley, Michael L. Chabinyc, Patrick Babb, Suresh Murugaiyan","submitted_at":"2026-05-28T23:38:38Z","abstract_excerpt":"Materials used in polymer-based additive manufacturing processes, such as Digital Light Processing (DLP) and direct ink writing (DIW), typically exhibit non-Newtonian rheology. Carreau--Yasuda and power-law models describe basic shear-thinning and shear-thickening behavior well, but applying them to a new material requires choosing a functional form, deriving it, and re-implementing it inside the flow solver. We present a deployment workflow in which a neural network trained on experimental rheometry data serves as the viscosity closure inside a Cahn--Hilliard--Navier--Stokes (CHNS) finite ele"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.30659","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2605.30659/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-06-01T01:03:06Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"kpVTCtS3zXxiyaxmLYzQw+TF+R/FrKQM+yfnqGRuamUwMEUtju8+aklpJT98LBnlMSuema5uSSrOuvDbTe22DA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-27T10:36:05.859935Z"},"content_sha256":"764d3b091722466cc0fdeae372471cd010fb8c8fb86a7de3cc40043441e8770a","schema_version":"1.0","event_id":"sha256:764d3b091722466cc0fdeae372471cd010fb8c8fb86a7de3cc40043441e8770a"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/UUUYHSGRANGWJGDPZH5EFCO44T/bundle.json","state_url":"https://pith.science/pith/UUUYHSGRANGWJGDPZH5EFCO44T/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/UUUYHSGRANGWJGDPZH5EFCO44T/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-06-27T10:36:05Z","links":{"resolver":"https://pith.science/pith/UUUYHSGRANGWJGDPZH5EFCO44T","bundle":"https://pith.science/pith/UUUYHSGRANGWJGDPZH5EFCO44T/bundle.json","state":"https://pith.science/pith/UUUYHSGRANGWJGDPZH5EFCO44T/state.json","well_known_bundle":"https://pith.science/.well-known/pith/UUUYHSGRANGWJGDPZH5EFCO44T/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:UUUYHSGRANGWJGDPZH5EFCO44T","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":"6a006a257521db228e67ab0464dc4d6a795beef47107d7f31df481d68781660a","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"physics.flu-dyn","submitted_at":"2026-05-28T23:38:38Z","title_canon_sha256":"62b9d46f58d59e9b8cb6723e04f86305e88052c4cb79196a5dc2f50a24c9da03"},"schema_version":"1.0","source":{"id":"2605.30659","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.30659","created_at":"2026-06-01T01:03:06Z"},{"alias_kind":"arxiv_version","alias_value":"2605.30659v1","created_at":"2026-06-01T01:03:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.30659","created_at":"2026-06-01T01:03:06Z"},{"alias_kind":"pith_short_12","alias_value":"UUUYHSGRANGW","created_at":"2026-06-01T01:03:06Z"},{"alias_kind":"pith_short_16","alias_value":"UUUYHSGRANGWJGDP","created_at":"2026-06-01T01:03:06Z"},{"alias_kind":"pith_short_8","alias_value":"UUUYHSGR","created_at":"2026-06-01T01:03:06Z"}],"graph_snapshots":[{"event_id":"sha256:764d3b091722466cc0fdeae372471cd010fb8c8fb86a7de3cc40043441e8770a","target":"graph","created_at":"2026-06-01T01:03:06Z","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/2605.30659/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Materials used in polymer-based additive manufacturing processes, such as Digital Light Processing (DLP) and direct ink writing (DIW), typically exhibit non-Newtonian rheology. Carreau--Yasuda and power-law models describe basic shear-thinning and shear-thickening behavior well, but applying them to a new material requires choosing a functional form, deriving it, and re-implementing it inside the flow solver. We present a deployment workflow in which a neural network trained on experimental rheometry data serves as the viscosity closure inside a Cahn--Hilliard--Navier--Stokes (CHNS) finite ele","authors_text":"Abraham Wiletsky, Adarsh Krishnamurthy, Andrew Rhode, Angela A. Pitenis, Austin Cunniff, Baskar Ganapathysubramanian, Cheng-Hau Yang, Christopher M. Bates, Claire L. Nelson, Dhruv Gamdha, Kaitlyn W. Dilley, Michael L. Chabinyc, Patrick Babb, Suresh Murugaiyan","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"physics.flu-dyn","submitted_at":"2026-05-28T23:38:38Z","title":"Neural-Network-based Viscosity Closure for Non-Newtonian Multiphase Flows"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.30659","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":"sha256:91b30c932e2cecc2c656acc5b636b003a82d6a849be4873fec18f2f9ae8845a6","target":"record","created_at":"2026-06-01T01:03:06Z","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":"6a006a257521db228e67ab0464dc4d6a795beef47107d7f31df481d68781660a","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"physics.flu-dyn","submitted_at":"2026-05-28T23:38:38Z","title_canon_sha256":"62b9d46f58d59e9b8cb6723e04f86305e88052c4cb79196a5dc2f50a24c9da03"},"schema_version":"1.0","source":{"id":"2605.30659","kind":"arxiv","version":1}},"canonical_sha256":"a52983c8d1034d64986fc9fa4289dce4f7dddba367c759c54f6d8ca761e6bc44","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a52983c8d1034d64986fc9fa4289dce4f7dddba367c759c54f6d8ca761e6bc44","first_computed_at":"2026-06-01T01:03:06.911269Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-01T01:03:06.911269Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"qln5ptV42Ol41vmVby5ZPaDwthRRk1gHC2B3UuomlFur/e2/LEQrrEa56cqjKgOOMNaFuEXxSQhi5xa11RzNCQ==","signature_status":"signed_v1","signed_at":"2026-06-01T01:03:06.912293Z","signed_message":"canonical_sha256_bytes"},"source_id":"2605.30659","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:91b30c932e2cecc2c656acc5b636b003a82d6a849be4873fec18f2f9ae8845a6","sha256:764d3b091722466cc0fdeae372471cd010fb8c8fb86a7de3cc40043441e8770a"],"state_sha256":"0efe6b6885b8f76aac66cd0e278b44b07db21a030c7cc48019abbe6f10392936"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"GyerMfH4B+r/KtFOXC53t0fQn1DopUCDlKoXbIrpTeGHhgGSOhBYDCSXdbqQb1xYl/S6d/K/2lavHA/2+CWJAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-27T10:36:05.861924Z","bundle_sha256":"1d879e8a066068ff764b01a607f1390e9d4e3c7054c80dbacd663f1f82a8705c"}}