{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2015:YAGG37J3YOQWSZNHPTBFEXOWSU","short_pith_number":"pith:YAGG37J3","schema_version":"1.0","canonical_sha256":"c00c6dfd3bc3a16965a77cc2525dd6952f448955cb9815969fbd907c9466a9f7","source":{"kind":"arxiv","id":"1509.04489","version":1},"attestation_state":"computed","paper":{"title":"A new LES model derived from generalized Navier-Stokes equations with nonlinear viscosity","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["physics.flu-dyn"],"primary_cat":"math.AP","authors_text":"Jos\\'e M. Rodr\\'iguez, Raquel Taboada-V\\'azquez","submitted_at":"2015-09-15T10:47:03Z","abstract_excerpt":"Large Eddy Simulation (LES) is a very useful tool when simulating turbulent flows if we are only interested in its \"larger\" scales. One of the possible ways to derive the LES equations is to apply a filter operator to the Navier-Stokes equations, obtaining a new equation governing the behavior of the filtered velocity. This approach introduces in the equations the so called subgrid-scale tensor, that must be expressed in terms of the filtered velocity to close the problem. One of the most popular models is that proposed by Smagorinsky, where the subgrid-scale tensor is modeled by introducing a"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"1509.04489","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.AP","submitted_at":"2015-09-15T10:47:03Z","cross_cats_sorted":["physics.flu-dyn"],"title_canon_sha256":"b4ab66049b8dda0f51fd133118a05f22ee24deec7ce2134dd251f5ab380770ef","abstract_canon_sha256":"f2cfeb862b094d8a9952ae5db16706d742b4eb2b843f0982193510049c2bc1a6"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:48:54.982279Z","signature_b64":"NfZPbWStIlzQAgk4F0nWSbs+aa8ZubZ8/GPAGTdtBknRHoHkGNNFuFULfbEowLzSrvX0mK+ItGhBnb0Y9AF3BQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c00c6dfd3bc3a16965a77cc2525dd6952f448955cb9815969fbd907c9466a9f7","last_reissued_at":"2026-05-18T00:48:54.981494Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:48:54.981494Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"A new LES model derived from generalized Navier-Stokes equations with nonlinear viscosity","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["physics.flu-dyn"],"primary_cat":"math.AP","authors_text":"Jos\\'e M. Rodr\\'iguez, Raquel Taboada-V\\'azquez","submitted_at":"2015-09-15T10:47:03Z","abstract_excerpt":"Large Eddy Simulation (LES) is a very useful tool when simulating turbulent flows if we are only interested in its \"larger\" scales. One of the possible ways to derive the LES equations is to apply a filter operator to the Navier-Stokes equations, obtaining a new equation governing the behavior of the filtered velocity. This approach introduces in the equations the so called subgrid-scale tensor, that must be expressed in terms of the filtered velocity to close the problem. One of the most popular models is that proposed by Smagorinsky, where the subgrid-scale tensor is modeled by introducing a"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1509.04489","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":""},"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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1509.04489","created_at":"2026-05-18T00:48:54.981601+00:00"},{"alias_kind":"arxiv_version","alias_value":"1509.04489v1","created_at":"2026-05-18T00:48:54.981601+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1509.04489","created_at":"2026-05-18T00:48:54.981601+00:00"},{"alias_kind":"pith_short_12","alias_value":"YAGG37J3YOQW","created_at":"2026-05-18T12:29:50.041715+00:00"},{"alias_kind":"pith_short_16","alias_value":"YAGG37J3YOQWSZNH","created_at":"2026-05-18T12:29:50.041715+00:00"},{"alias_kind":"pith_short_8","alias_value":"YAGG37J3","created_at":"2026-05-18T12:29:50.041715+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/YAGG37J3YOQWSZNHPTBFEXOWSU","json":"https://pith.science/pith/YAGG37J3YOQWSZNHPTBFEXOWSU.json","graph_json":"https://pith.science/api/pith-number/YAGG37J3YOQWSZNHPTBFEXOWSU/graph.json","events_json":"https://pith.science/api/pith-number/YAGG37J3YOQWSZNHPTBFEXOWSU/events.json","paper":"https://pith.science/paper/YAGG37J3"},"agent_actions":{"view_html":"https://pith.science/pith/YAGG37J3YOQWSZNHPTBFEXOWSU","download_json":"https://pith.science/pith/YAGG37J3YOQWSZNHPTBFEXOWSU.json","view_paper":"https://pith.science/paper/YAGG37J3","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1509.04489&json=true","fetch_graph":"https://pith.science/api/pith-number/YAGG37J3YOQWSZNHPTBFEXOWSU/graph.json","fetch_events":"https://pith.science/api/pith-number/YAGG37J3YOQWSZNHPTBFEXOWSU/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/YAGG37J3YOQWSZNHPTBFEXOWSU/action/timestamp_anchor","attest_storage":"https://pith.science/pith/YAGG37J3YOQWSZNHPTBFEXOWSU/action/storage_attestation","attest_author":"https://pith.science/pith/YAGG37J3YOQWSZNHPTBFEXOWSU/action/author_attestation","sign_citation":"https://pith.science/pith/YAGG37J3YOQWSZNHPTBFEXOWSU/action/citation_signature","submit_replication":"https://pith.science/pith/YAGG37J3YOQWSZNHPTBFEXOWSU/action/replication_record"}},"created_at":"2026-05-18T00:48:54.981601+00:00","updated_at":"2026-05-18T00:48:54.981601+00:00"}