{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:5KDVZVZASAQDR4VZDUYFQTQDRH","short_pith_number":"pith:5KDVZVZA","schema_version":"1.0","canonical_sha256":"ea875cd720902038f2b91d30584e0389ff39ac1dcc14972b44260f11b3ace5b5","source":{"kind":"arxiv","id":"2403.00571","version":1},"attestation_state":"computed","paper":{"title":"Computational homogenization for aerogel-like polydisperse open-porous materials using neural network--based surrogate models on the microscale","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.NA"],"primary_cat":"math.NA","authors_text":"Ameya Rege, Axel Klawonn, Lucas Mager, Martin Lanser","submitted_at":"2024-03-01T14:48:26Z","abstract_excerpt":"The morphology of nanostructured materials exhibiting a polydisperse porous space, such as aerogels, is very open porous and fine grained. Therefore, a simulation of the deformation of a large aerogel structure resolving the nanostructure would be extremely expensive. Thus, multi-scale or homogenization approaches have to be considered. Here, a computational scale bridging approach based on the FE$^2$ method is suggested, where the macroscopic scale is discretized using finite elements while the microstructure of the open-porous material is resolved as a network of Euler-Bernoulli beams. Here,"},"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":"2403.00571","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.NA","submitted_at":"2024-03-01T14:48:26Z","cross_cats_sorted":["cs.NA"],"title_canon_sha256":"e3f508d0f7596d4049416da5de144ac4fd779d7fb23d22140db3d1f9fe972726","abstract_canon_sha256":"788591c9ab319b658bafea0281019a01bb61d29260000d009f8a9d5d60dd759c"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:51:05.893592Z","signature_b64":"iWf1AlEQb444ETbRfVvPluwAtqNTiiFe7bKimGY5eLqeDPGzI1Gxuqu/rQIMZDDVL4Pje4sws8FpcxmrzUsTDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ea875cd720902038f2b91d30584e0389ff39ac1dcc14972b44260f11b3ace5b5","last_reissued_at":"2026-07-05T07:51:05.893242Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:51:05.893242Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Computational homogenization for aerogel-like polydisperse open-porous materials using neural network--based surrogate models on the microscale","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.NA"],"primary_cat":"math.NA","authors_text":"Ameya Rege, Axel Klawonn, Lucas Mager, Martin Lanser","submitted_at":"2024-03-01T14:48:26Z","abstract_excerpt":"The morphology of nanostructured materials exhibiting a polydisperse porous space, such as aerogels, is very open porous and fine grained. Therefore, a simulation of the deformation of a large aerogel structure resolving the nanostructure would be extremely expensive. Thus, multi-scale or homogenization approaches have to be considered. Here, a computational scale bridging approach based on the FE$^2$ method is suggested, where the macroscopic scale is discretized using finite elements while the microstructure of the open-porous material is resolved as a network of Euler-Bernoulli beams. Here,"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2403.00571","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/2403.00571/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2403.00571","created_at":"2026-07-05T07:51:05.893292+00:00"},{"alias_kind":"arxiv_version","alias_value":"2403.00571v1","created_at":"2026-07-05T07:51:05.893292+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2403.00571","created_at":"2026-07-05T07:51:05.893292+00:00"},{"alias_kind":"pith_short_12","alias_value":"5KDVZVZASAQD","created_at":"2026-07-05T07:51:05.893292+00:00"},{"alias_kind":"pith_short_16","alias_value":"5KDVZVZASAQDR4VZ","created_at":"2026-07-05T07:51:05.893292+00:00"},{"alias_kind":"pith_short_8","alias_value":"5KDVZVZA","created_at":"2026-07-05T07:51:05.893292+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/5KDVZVZASAQDR4VZDUYFQTQDRH","json":"https://pith.science/pith/5KDVZVZASAQDR4VZDUYFQTQDRH.json","graph_json":"https://pith.science/api/pith-number/5KDVZVZASAQDR4VZDUYFQTQDRH/graph.json","events_json":"https://pith.science/api/pith-number/5KDVZVZASAQDR4VZDUYFQTQDRH/events.json","paper":"https://pith.science/paper/5KDVZVZA"},"agent_actions":{"view_html":"https://pith.science/pith/5KDVZVZASAQDR4VZDUYFQTQDRH","download_json":"https://pith.science/pith/5KDVZVZASAQDR4VZDUYFQTQDRH.json","view_paper":"https://pith.science/paper/5KDVZVZA","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2403.00571&json=true","fetch_graph":"https://pith.science/api/pith-number/5KDVZVZASAQDR4VZDUYFQTQDRH/graph.json","fetch_events":"https://pith.science/api/pith-number/5KDVZVZASAQDR4VZDUYFQTQDRH/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/5KDVZVZASAQDR4VZDUYFQTQDRH/action/timestamp_anchor","attest_storage":"https://pith.science/pith/5KDVZVZASAQDR4VZDUYFQTQDRH/action/storage_attestation","attest_author":"https://pith.science/pith/5KDVZVZASAQDR4VZDUYFQTQDRH/action/author_attestation","sign_citation":"https://pith.science/pith/5KDVZVZASAQDR4VZDUYFQTQDRH/action/citation_signature","submit_replication":"https://pith.science/pith/5KDVZVZASAQDR4VZDUYFQTQDRH/action/replication_record"}},"created_at":"2026-07-05T07:51:05.893292+00:00","updated_at":"2026-07-05T07:51:05.893292+00:00"}