{"id":"W4403405073","doi":"10.1016/j.camwa.2024.10.008","title":"Two-level dynamic load-balanced p-adaptive discontinuous Galerkin methods for compressible CFD simulations","year":2024,"lang":"en","type":"article","venue":"Computers & Mathematics with Applications","topic":"Computational Fluid Dynamics and Aerodynamics","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Horizon 2020; HORIZON EUROPE Framework Programme; Deutsches Zentrum für Luft- und Raumfahrt; Office National d'études et de Recherches Aérospatiales; European Commission","keywords":"Mathematics; Computational fluid dynamics; Compressibility; Galerkin method; Applied mathematics; Discontinuous Galerkin method; Mathematical optimization; Control theory (sociology); Finite element method; Mechanics; Computer science; Physics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003009705,0.0005866385,0.0004698237,0.0004252586,0.0004903154,0.0007435736,0.001156036,0.0008032738,0.001578761],"category_scores_gemma":[0.0007489035,0.0002967205,0.0004565511,0.000361729,0.0005936965,0.0006477396,0.001360703,0.0009870469,0.0004309581],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004227383,"about_ca_system_score_gemma":0.0006705492,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001959522,"about_ca_topic_score_gemma":0.001430264,"domain_scores_codex":[0.9998146,0.00004057778,0.000008429045,0.00002672499,0.00008813356,0.00002158953],"domain_scores_gemma":[0.9998206,0.00006291228,0.00002098169,0.00003257583,0.00004119857,0.00002170234],"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":[0.00006892435,0.0000939622,0.0008817404,0.0001137742,0.00002992494,0.0001490051,0.0001202182,0.8937714,0.02661279,0.02187881,0.0007921347,0.05548724],"study_design_scores_gemma":[0.000005549562,0.000008005068,0.00004447886,0.000002678313,0.000001795766,0.000008946111,0.000004412861,0.996106,0.001598098,0.001331462,0.0008842805,0.000004157107],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01966411,0.0001732533,0.9764115,0.0001085391,0.00004405247,0.00004716432,0.00003604955,0.0003868697,0.003128462],"genre_scores_gemma":[0.5389221,0.0003221024,0.4564901,0.0001291239,0.00005067853,0.0003413288,0.0001579608,0.0002331797,0.003353453],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001959522,"threshold_uncertainty_score":0.005281448,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01863150238740031,"score_gpt":0.3130707619508157,"score_spread":0.2944392595634154,"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."}}