{"paper":{"title":"Two-component inner--outer scaling model for the wall-pressure spectrum at high Reynolds number","license":"http://creativecommons.org/licenses/by-sa/4.0/","headline":"A two-component model decomposes the wall-pressure spectrum into inner- and outer-scaled contributions that explain its growth at high Reynolds numbers.","cross_cats":["physics.data-an"],"primary_cat":"physics.flu-dyn","authors_text":"Alexander J. Smits, Beverley J. McKeon, Jonathan M. O. Massey","submitted_at":"2025-07-30T20:59:29Z","abstract_excerpt":"Wall-pressure fluctuations beneath turbulent boundary layers drive noise and structural fatigue through interactions between fluid and structural modes. Conventional predictive models for the spectrum--such as the widely accepted Goody model (\\textit{AIAA Journal} 42 (9), 2004, 1788--1794)--fail to capture the energetic growth in the {low-frequency range} that occurs at high Reynolds number, while at the same time over-predicting the variance.\n  To address these shortcomings, two semi-empirical models are proposed for the wall-pressure spectrum in canonical turbulent boundary layers, pipes and"},"claims":{"count":4,"items":[{"kind":"strongest_claim","text":"Both models capture the full spectrum and recover the observed logarithmic growth of its variance, providing a compact, physics-informed empirical representation for more accurate engineering predictions of wall-pressure fluctuations.","source":"verdict.strongest_claim","status":"machine_extracted","claim_id":"C1","attestation":"unclaimed"},{"kind":"weakest_assumption","text":"The wall-pressure spectrum can be decomposed into two overlapping components (inner-scaled δ+-invariant and outer-scaled with amplitude broadening smoothly with δ+) whose shapes are either log-normal or prescribed by theoretical arguments.","source":"verdict.weakest_assumption","status":"machine_extracted","claim_id":"C2","attestation":"unclaimed"},{"kind":"one_line_summary","text":"Two new two-component inner-outer scaling models for wall-pressure spectra in turbulent boundary layers, pipes and channels that capture low-frequency growth and logarithmic variance increase at high Reynolds numbers.","source":"verdict.one_line_summary","status":"machine_extracted","claim_id":"C3","attestation":"unclaimed"},{"kind":"headline","text":"A two-component model decomposes the wall-pressure spectrum into inner- and outer-scaled contributions that explain its growth at high Reynolds numbers.","source":"verdict.pith_extraction.headline","status":"machine_extracted","claim_id":"C4","attestation":"unclaimed"}],"snapshot_sha256":"73b801cabe4e6b6fbc0fd7cc2efad60fc72ad44077ac8bf6a1a56211bc1fd6e4"},"source":{"id":"2507.23098","kind":"arxiv","version":3},"verdict":{"id":"0b80d6e3-1016-44e7-bd8b-67e603482d5e","model_set":{"reader":"grok-4.3"},"created_at":"2026-05-19T01:54:10.307048Z","strongest_claim":"Both models capture the full spectrum and recover the observed logarithmic growth of its variance, providing a compact, physics-informed empirical representation for more accurate engineering predictions of wall-pressure fluctuations.","one_line_summary":"Two new two-component inner-outer scaling models for wall-pressure spectra in turbulent boundary layers, pipes and channels that capture low-frequency growth and logarithmic variance increase at high Reynolds numbers.","pipeline_version":"pith-pipeline@v0.9.0","weakest_assumption":"The wall-pressure spectrum can be decomposed into two overlapping components (inner-scaled δ+-invariant and outer-scaled with amplitude broadening smoothly with δ+) whose shapes are either log-normal or prescribed by theoretical arguments.","pith_extraction_headline":"A two-component model decomposes the wall-pressure spectrum into inner- and outer-scaled contributions that explain its growth at high Reynolds numbers."},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2507.23098/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"}