{"id":"W4317597166","doi":"10.2514/6.2023-1224","title":"On the Use of Nonlinearly Stable Flux Reconstruction for Implicitly Filtered Large Eddy Simulation","year":2023,"lang":"en","type":"article","venue":"AIAA SCITECH 2023 Forum","topic":"Computational Fluid Dynamics and Aerodynamics","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Dissipation; Turbulence; Solver; Flux (metallurgy); Vortex; Physics; Large eddy simulation; Grid; Shock (circulatory); Kinetic energy; Mechanics; Statistical physics; Computer science; Applied mathematics; Classical mechanics; Mathematics; Mathematical optimization; Geometry","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001790626,0.0001134745,0.0001235314,0.0001472868,0.0001215283,0.00005506398,0.0001080856,0.00006462046,0.00003102142],"category_scores_gemma":[0.0001133389,0.00009778402,0.00008504295,0.0005089516,0.00001620081,0.0001622702,0.00003860703,0.00009399014,0.0000372753],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000468413,"about_ca_system_score_gemma":0.00001655136,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001411724,"about_ca_topic_score_gemma":0.00007195888,"domain_scores_codex":[0.9991721,0.00001072301,0.0002431755,0.0001473146,0.0001527388,0.000273962],"domain_scores_gemma":[0.9989659,0.0006555234,0.00004252498,0.000201367,0.0001054906,0.00002921355],"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":[0.00001273303,0.00000997103,0.0001259449,0.00002190225,0.00002668935,3.115644e-7,0.0000218407,0.9776309,0.003033328,0.01000753,0.004081087,0.005027748],"study_design_scores_gemma":[0.0002132578,0.0000491862,0.0009562559,0.00003053939,0.000007106934,8.214144e-7,0.00003942675,0.9888855,0.0002419073,0.00640471,0.003067627,0.0001036897],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7551014,0.000008180065,0.2423121,0.0003380288,0.000580207,0.0004288383,0.0009355163,0.0002300593,0.00006562156],"genre_scores_gemma":[0.995538,0.000009378532,0.002999509,0.00007943832,0.00005835851,0.00004153674,0.0004350885,0.00004139138,0.0007972989],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2404366,"threshold_uncertainty_score":0.3987516,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03265499963109265,"score_gpt":0.2548887135479652,"score_spread":0.2222337139168726,"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."}}