{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:HTROOT52JDURJZYJVMQKHNPIYH","short_pith_number":"pith:HTROOT52","schema_version":"1.0","canonical_sha256":"3ce2e74fba48e914e709ab20a3b5e8c1cff250b7ca89276aa2f74f2384edbd1a","source":{"kind":"arxiv","id":"2504.16385","version":1},"attestation_state":"computed","paper":{"title":"Distributed Space Resource Logistics Architecture Optimization under Economies of Scale","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.SY"],"primary_cat":"eess.SY","authors_text":"Evangelia Gkaravela, Hang Woon Lee, Hao Chen","submitted_at":"2025-04-23T03:26:43Z","abstract_excerpt":"This paper proposes an optimization framework for distributed resource logistics system design to support future multimission space exploration. The performance and impact of distributed In-Situ Resource Utilization (ISRU) systems in facilitating space transportation are analyzed. The proposed framework considers technology trade studies, deployment strategy, facility location evaluation, and resource logistics after production for distributed ISRU systems. We develop piecewise linear sizing and cost estimation models based on economies of scale that can be easily integrated into network-based"},"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":"2504.16385","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SY","submitted_at":"2025-04-23T03:26:43Z","cross_cats_sorted":["cs.SY"],"title_canon_sha256":"9cb38baf76f275ec0c6bd5785bd2dc21aacc249c836b0a41579422a8500fdd72","abstract_canon_sha256":"2b75baf9e4076cea556657ea8bf975904ca3b0673a721893626d805463f07521"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:39:53.163713Z","signature_b64":"VsVGf10KA2lJBFz8/927GgxkabkVT87+lsiEtOsBfcCvqX1XCUq5fBGewSP4ivsJOPT+ht1QUcyfcYIggCldCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3ce2e74fba48e914e709ab20a3b5e8c1cff250b7ca89276aa2f74f2384edbd1a","last_reissued_at":"2026-07-05T11:39:53.163152Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:39:53.163152Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Distributed Space Resource Logistics Architecture Optimization under Economies of Scale","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.SY"],"primary_cat":"eess.SY","authors_text":"Evangelia Gkaravela, Hang Woon Lee, Hao Chen","submitted_at":"2025-04-23T03:26:43Z","abstract_excerpt":"This paper proposes an optimization framework for distributed resource logistics system design to support future multimission space exploration. The performance and impact of distributed In-Situ Resource Utilization (ISRU) systems in facilitating space transportation are analyzed. The proposed framework considers technology trade studies, deployment strategy, facility location evaluation, and resource logistics after production for distributed ISRU systems. We develop piecewise linear sizing and cost estimation models based on economies of scale that can be easily integrated into network-based"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2504.16385","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/2504.16385/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":"2504.16385","created_at":"2026-07-05T11:39:53.163210+00:00"},{"alias_kind":"arxiv_version","alias_value":"2504.16385v1","created_at":"2026-07-05T11:39:53.163210+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2504.16385","created_at":"2026-07-05T11:39:53.163210+00:00"},{"alias_kind":"pith_short_12","alias_value":"HTROOT52JDUR","created_at":"2026-07-05T11:39:53.163210+00:00"},{"alias_kind":"pith_short_16","alias_value":"HTROOT52JDURJZYJ","created_at":"2026-07-05T11:39:53.163210+00:00"},{"alias_kind":"pith_short_8","alias_value":"HTROOT52","created_at":"2026-07-05T11:39:53.163210+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":0,"sample":[{"citing_arxiv_id":"2606.18114","citing_title":"Ternary Mamba: Grouped Quantization-Aware Training of W1.58A16 State Space Models","ref_index":8,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/HTROOT52JDURJZYJVMQKHNPIYH","json":"https://pith.science/pith/HTROOT52JDURJZYJVMQKHNPIYH.json","graph_json":"https://pith.science/api/pith-number/HTROOT52JDURJZYJVMQKHNPIYH/graph.json","events_json":"https://pith.science/api/pith-number/HTROOT52JDURJZYJVMQKHNPIYH/events.json","paper":"https://pith.science/paper/HTROOT52"},"agent_actions":{"view_html":"https://pith.science/pith/HTROOT52JDURJZYJVMQKHNPIYH","download_json":"https://pith.science/pith/HTROOT52JDURJZYJVMQKHNPIYH.json","view_paper":"https://pith.science/paper/HTROOT52","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2504.16385&json=true","fetch_graph":"https://pith.science/api/pith-number/HTROOT52JDURJZYJVMQKHNPIYH/graph.json","fetch_events":"https://pith.science/api/pith-number/HTROOT52JDURJZYJVMQKHNPIYH/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/HTROOT52JDURJZYJVMQKHNPIYH/action/timestamp_anchor","attest_storage":"https://pith.science/pith/HTROOT52JDURJZYJVMQKHNPIYH/action/storage_attestation","attest_author":"https://pith.science/pith/HTROOT52JDURJZYJVMQKHNPIYH/action/author_attestation","sign_citation":"https://pith.science/pith/HTROOT52JDURJZYJVMQKHNPIYH/action/citation_signature","submit_replication":"https://pith.science/pith/HTROOT52JDURJZYJVMQKHNPIYH/action/replication_record"}},"created_at":"2026-07-05T11:39:53.163210+00:00","updated_at":"2026-07-05T11:39:53.163210+00:00"}