{"id":"W3207723003","doi":"10.1016/j.euromechflu.2022.03.007","title":"Stability and accuracy of the weakly compressible SPH with particle regularization techniques","year":2022,"lang":"en","type":"article","venue":"European Journal of Mechanics - B/Fluids","topic":"Fluid Dynamics Simulations and Interactions","field":"Engineering","cited_by":27,"is_retracted":false,"has_abstract":false,"ca_institutions":"Hydro One (Canada); Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; Polytechnique Montréal","keywords":"Regularization (linguistics); Smoothed-particle hydrodynamics; Compressibility; Stability (learning theory); Mechanics; Applied mathematics; Mathematical optimization; Algorithm; Computer science; Statistical physics; Physics; Classical mechanics; Mathematics; Artificial intelligence","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":[0.003126304,0.0009157015,0.0009999969,0.001358149,0.0009483732,0.001680533,0.001776163,0.00199755,0.001503492],"category_scores_gemma":[0.01566441,0.0004694011,0.000933896,0.0005656769,0.003070127,0.001754655,0.003209533,0.001988452,0.0002794],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001071277,"about_ca_system_score_gemma":0.001782332,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007139398,"about_ca_topic_score_gemma":0.002475434,"domain_scores_codex":[0.9988029,0.000540462,0.00005914201,0.0001475062,0.0003619144,0.00008797859],"domain_scores_gemma":[0.9919882,0.005116509,0.0006532333,0.0006904364,0.001142793,0.0004088625],"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":[0.002101172,0.000277748,0.009238227,0.0003515043,0.0001974105,0.0003868846,0.000457839,0.7230462,0.0418893,0.1843981,0.00325548,0.03440015],"study_design_scores_gemma":[0.00001239294,0.00002012614,0.0004303241,0.000004996399,0.000004554387,0.00001356473,0.000007343174,0.9938809,0.001457392,0.004041409,0.000116867,0.00001022473],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5009634,0.001443427,0.4717263,0.004247043,0.0005606541,0.0001743922,0.0004634994,0.000947137,0.01947418],"genre_scores_gemma":[0.9508253,0.000228211,0.04101971,0.0001600581,0.0002413355,0.00009531757,0.0002714809,0.0003298902,0.006828671],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007139398,"threshold_uncertainty_score":0.01653367,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01280266019470027,"score_gpt":0.2125924602750387,"score_spread":0.1997898000803384,"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."}}