{"id":"W2616586047","doi":"10.1080/10618562.2017.1324149","title":"A coupled WC-TL SPH method for simulation of hydroelastic problems","year":2017,"lang":"en","type":"article","venue":"International journal of computational fluid dynamics","topic":"Fluid Dynamics Simulations and Interactions","field":"Engineering","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"China Scholarship Council; Natural Sciences and Engineering Research Council of Canada; Mitacs; Türkiye Bilimsel ve Teknolojik Araştırma Kurumu; Canada Research Chairs","keywords":"Smoothed-particle hydrodynamics; Slosh dynamics; Hydroelasticity; Cantilever; Mechanics; Oscillation (cell signaling); Benchmark (surveying); Compressibility; Physics; Fluid–structure interaction; Boundary value problem; Structural engineering; Vibration; Finite element method; Geology; Acoustics; Engineering; Chemistry","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":[0.0003359103,0.0001625743,0.000284074,0.0003538181,0.0001382171,0.0001496988,0.0005631289,0.00007945086,0.00004355858],"category_scores_gemma":[0.0003619118,0.0001673483,0.0002509361,0.00005336407,0.00005587096,0.0006294481,0.00004494021,0.0001640881,0.000005190338],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002826321,"about_ca_system_score_gemma":0.00009678402,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001452708,"about_ca_topic_score_gemma":0.00002771801,"domain_scores_codex":[0.9983177,0.00002085702,0.0008865556,0.0001168458,0.0005191711,0.0001388632],"domain_scores_gemma":[0.9963878,0.0008171485,0.0005661384,0.0001709391,0.00198732,0.00007068366],"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":[0.00007502616,0.00007578918,0.0003884776,0.00003024254,0.0003544959,0.000003040968,0.00008357409,0.9823175,0.0008540339,0.01268111,0.00008534145,0.003051378],"study_design_scores_gemma":[0.001104899,0.0001013279,0.003363841,0.0001029723,0.00005378173,0.00004943808,0.00001838647,0.9746109,0.00004254423,0.02009651,0.0003158954,0.0001394585],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08509139,0.00004704211,0.9117512,0.0002776772,0.002055589,0.000169988,0.0001524079,0.00002542222,0.0004293269],"genre_scores_gemma":[0.9157935,0.00001889849,0.08368073,0.00002287407,0.0002630457,0.000006580296,0.0001074202,0.00003296487,0.00007401818],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8307021,"threshold_uncertainty_score":0.6824265,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01445114186119179,"score_gpt":0.3143782095321164,"score_spread":0.2999270676709246,"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."}}