{"id":"W3134602405","doi":"10.1063/5.0033491","title":"An improved higher-order moving particle semi-implicit method for simulations of two-dimensional hydroelastic slamming","year":2021,"lang":"en","type":"article","venue":"Physics of Fluids","topic":"Fluid Dynamics Simulations and Interactions","field":"Engineering","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Slamming; Wedge (geometry); Physics; Mechanics; Smoothed-particle hydrodynamics; Convergence (economics); Particle (ecology); Consistency (knowledge bases); Hydroelasticity; Momentum (technical analysis); Fluid–structure interaction; Particle method; Classical mechanics; Geometry; Mathematics; Boundary value problem; Finite element method; Thermodynamics; Geology; Optics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006906786,0.0001237461,0.0002170498,0.00003834259,0.00007666113,0.00001708161,0.00007898378,0.00003965267,0.00005656759],"category_scores_gemma":[0.0000460558,0.0001419256,0.0001022098,0.000298873,0.00002165922,0.0002885302,0.00002608367,0.00008280583,0.000001590963],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003713427,"about_ca_system_score_gemma":0.00003992441,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003191309,"about_ca_topic_score_gemma":0.00001420056,"domain_scores_codex":[0.9991769,0.00002333908,0.0003465166,0.0001645282,0.0001081858,0.0001805209],"domain_scores_gemma":[0.9987838,0.0004535368,0.00004547587,0.0002941103,0.0003690463,0.00005401091],"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":[0.000003002002,0.00005591564,0.00005500853,0.00002567176,0.00004010278,9.856289e-8,0.0000677118,0.5137823,0.4790977,0.006238729,0.000008403132,0.0006252899],"study_design_scores_gemma":[0.0004017442,0.00004085878,0.0001792011,0.00002290104,0.00005864671,6.909154e-7,0.00001795033,0.8621204,0.132361,0.004639245,0.00004061106,0.0001166798],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4039375,0.00004440756,0.5954812,0.00002083823,0.0001716906,0.00009184184,0.00009020181,0.00004927473,0.0001130561],"genre_scores_gemma":[0.8942184,0.000001057986,0.1054833,0.00001546972,0.00009990911,0.00001429252,0.00008185016,0.00003467894,0.00005104965],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.4902809,"threshold_uncertainty_score":0.5787557,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01339431380112562,"score_gpt":0.2928275424562649,"score_spread":0.2794332286551393,"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."}}