{"id":"W4388039132","doi":"10.1016/j.compfluid.2023.106065","title":"High-Order Implicit Large Eddy Simulation using Entropically Damped Artificial Compressibility","year":2023,"lang":"en","type":"article","venue":"Computers & Fluids","topic":"Fluid Dynamics and Turbulent Flows","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada; Alliance de recherche numérique du Canada","keywords":"Compressibility; Turbulence; Large eddy simulation; Airfoil; Vortex; Computational fluid dynamics; Applied mathematics; Flow (mathematics); Incompressible flow; Computer science; Compressible flow; Statistical physics; Mathematics; Mechanics; Physics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005176207,0.0006195123,0.001127891,0.0004715417,0.0009838992,0.001166254,0.001530691,0.001735213,0.002524625],"category_scores_gemma":[0.002718211,0.0005152794,0.0005318887,0.00050874,0.001051408,0.001094085,0.001075459,0.001332241,0.0002556703],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007288998,"about_ca_system_score_gemma":0.001668584,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01302606,"about_ca_topic_score_gemma":0.01017387,"domain_scores_codex":[0.9998054,0.00007143358,0.00001103517,0.0000200292,0.00005876352,0.00003334618],"domain_scores_gemma":[0.9986113,0.0008066837,0.0001130024,0.0001408607,0.0001834786,0.0001446575],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001362045,0.0001137479,0.0009000747,0.00004223649,0.00002663954,0.00009031727,0.0000493699,0.9897189,0.002260893,0.00382512,0.0002309312,0.002605498],"study_design_scores_gemma":[0.00001662072,0.000007640373,0.00004897919,0.000001126269,0.000001271354,0.000002160445,0.000002300118,0.9995065,0.0002114615,0.0001484964,0.00005080093,0.00000250892],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7287329,0.0004411489,0.2484752,0.0005820232,0.0003144727,0.0002222443,0.0004264313,0.001309738,0.01949583],"genre_scores_gemma":[0.9562442,0.0000698222,0.04073378,0.00005786344,0.00003253996,0.0001138047,0.0001435038,0.0001438565,0.002460824],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01302606,"threshold_uncertainty_score":0.02590048,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01633978304179496,"score_gpt":0.2536468431350882,"score_spread":0.2373070600932933,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}