{"paper":{"title":"A Threshold Model for Micrometeoroid Atmospheric Entry: Filippov Dynamics, Survival Estimates, and Survivor-Only Inverse Limits","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"A reduced threshold model for micrometeoroid entry recovers the classical survival scaling of critical radius as the inverse cube of entry velocity.","cross_cats":["astro-ph.EP","math.DS"],"primary_cat":"physics.ao-ph","authors_text":"Md Shahrier Islam Arham, Min Heo, Prasun Panthi","submitted_at":"2026-03-19T22:21:42Z","abstract_excerpt":"Micrometeoroids enter Earth's atmosphere at hypervelocity speeds and experience rapid coupling between drag, heating, radiation, melting, ablation, and deceleration. This paper develops a reduced threshold model for the thermal survival boundary of spherical micrometeoroids. The model uses free molecular drag, an exponential atmosphere, projected-area heating, full-sphere radiative cooling, and a surplus-heat ablation rule at the melting temperature. The switching surface $T=T_m$ is treated as a Filippov/complementarity surface. Sustained melting occurs when the local heating-to-radiation rati"},"claims":{"count":4,"items":[{"kind":"strongest_claim","text":"Under the additional Allen--Eggers assumptions of constant radius, constant entry angle, negligible gravity during the main heating interval, and constant transport coefficients, this threshold yields the classical approximate survival scaling r_0^{crit}∼v_0^{-3}.","source":"verdict.strongest_claim","status":"machine_extracted","claim_id":"C1","attestation":"unclaimed"},{"kind":"weakest_assumption","text":"The Allen--Eggers assumptions of constant radius, constant entry angle, negligible gravity during the main heating interval, and constant transport coefficients, which are invoked to obtain the classical scaling and exact radius-loss identity.","source":"verdict.weakest_assumption","status":"machine_extracted","claim_id":"C2","attestation":"unclaimed"},{"kind":"one_line_summary","text":"A Filippov dynamics threshold model for micrometeoroid entry recovers the classical survival scaling r_0^crit ~ v_0^{-3} and formulates an inverse problem highlighting information loss in survivor-only data.","source":"verdict.one_line_summary","status":"machine_extracted","claim_id":"C3","attestation":"unclaimed"},{"kind":"headline","text":"A reduced threshold model for micrometeoroid entry recovers the classical survival scaling of critical radius as the inverse cube of entry velocity.","source":"verdict.pith_extraction.headline","status":"machine_extracted","claim_id":"C4","attestation":"unclaimed"}],"snapshot_sha256":"a3d78917ffa7feb5b26960b1d932b71fa65e1d37f2cb57814716502afb92113c"},"source":{"id":"2603.28785","kind":"arxiv","version":2},"verdict":{"id":"eb7aca64-5249-4edd-9d40-122b65a19572","model_set":{"reader":"grok-4.3"},"created_at":"2026-05-15T07:54:02.831425Z","strongest_claim":"Under the additional Allen--Eggers assumptions of constant radius, constant entry angle, negligible gravity during the main heating interval, and constant transport coefficients, this threshold yields the classical approximate survival scaling r_0^{crit}∼v_0^{-3}.","one_line_summary":"A Filippov dynamics threshold model for micrometeoroid entry recovers the classical survival scaling r_0^crit ~ v_0^{-3} and formulates an inverse problem highlighting information loss in survivor-only data.","pipeline_version":"pith-pipeline@v0.9.0","weakest_assumption":"The Allen--Eggers assumptions of constant radius, constant entry angle, negligible gravity during the main heating interval, and constant transport coefficients, which are invoked to obtain the classical scaling and exact radius-loss identity.","pith_extraction_headline":"A reduced threshold model for micrometeoroid entry recovers the classical survival scaling of critical radius as the inverse cube of entry velocity."},"references":{"count":12,"sample":[{"doi":"","year":null,"title":"Absolute and relative tolerances are set to 10 −10 and 10 −8 respectively","work_id":"9e093c40-fe92-4406-ba40-394c5d449199","ref_index":1,"cited_arxiv_id":"","is_internal_anchor":false},{"doi":"","year":null,"title":"Each trajectory is clas- sified into one of four outcome classes based onTmax, time aboveT melt, and final mass fraction","work_id":"d0fddc41-4baf-42bd-8c20-a7408ed1602f","ref_index":2,"cited_arxiv_id":"","is_internal_anchor":false},{"doi":"","year":null,"title":"Base sample sizeN= 8192 givesN×(2n+ 2) = 114 688 model evaluations for n= 6 parameters","work_id":"b3cb87b2-9441-4158-bb5f-d27d48fccdfa","ref_index":3,"cited_arxiv_id":"","is_internal_anchor":false},{"doi":"","year":null,"title":"For each of theN e = 300 entry bins, NMC = 30 trajectories are launched with parameters jit- tered uniformly within the bin bounds","work_id":"0dc28bb6-c1b5-4ddc-ab6f-ea04e555fa8a","ref_index":4,"cited_arxiv_id":"","is_internal_anchor":false},{"doi":"","year":1991,"title":"S. G. Love and D. E. Brownlee, Icarus89, 26 (1991)","work_id":"c0e8c414-07b5-4cdb-b1a4-55657bd06e83","ref_index":5,"cited_arxiv_id":"","is_internal_anchor":false}],"resolved_work":12,"snapshot_sha256":"ad0c33b459e837f04bf07aee26ba541692a988dda8af5caa42ada6d6aad7c0aa","internal_anchors":0},"formal_canon":{"evidence_count":2,"snapshot_sha256":"1f33510e270233808849017996928f49dae936bef84e1bf316e306e0d0f4812c"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"}