{"id":"W4406032195","doi":"10.48550/arxiv.2501.00620","title":"A Novel Velocity Discretization for Lattice Boltzmann Method: Application to Compressible Flow","year":2024,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Lattice Boltzmann Simulation Studies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Alliance de recherche numérique du Canada","keywords":"Lattice Boltzmann methods; Discretization; Compressibility; HPP model; Bhatnagar–Gross–Krook operator; Flow (mathematics); Mechanics; Statistical physics; Physics; Mathematics; Computer science; Mathematical analysis; Reynolds number","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.0006102761,0.0004489429,0.0005888394,0.0004667339,0.0006025229,0.0008132859,0.0009212677,0.001099127,0.001357719],"category_scores_gemma":[0.002311128,0.0002386197,0.0003599612,0.0006706122,0.0006920864,0.0008695198,0.0009713521,0.001288149,0.0004327377],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000546823,"about_ca_system_score_gemma":0.001075848,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004055863,"about_ca_topic_score_gemma":0.002659032,"domain_scores_codex":[0.9996463,0.0001188756,0.00001799611,0.00003828213,0.0001515437,0.00002691422],"domain_scores_gemma":[0.9994907,0.000198628,0.00004916839,0.00006270371,0.0001399331,0.00005886796],"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":[0.0001587927,0.0002224817,0.002168152,0.0002821322,0.00005827314,0.0003537127,0.0002425944,0.5996364,0.0428895,0.1861922,0.004553743,0.163242],"study_design_scores_gemma":[0.00001589661,0.00001521669,0.00006334191,0.000009500712,0.000002526279,0.0000405789,0.000008236511,0.9879504,0.001552807,0.006948069,0.003383104,0.00001029771],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.009924359,0.0005222664,0.9864912,0.0002607203,0.0002662292,0.00005370881,0.00005227296,0.0002577698,0.002171358],"genre_scores_gemma":[0.200891,0.0008018055,0.7935877,0.0002176495,0.0002173967,0.0002478324,0.0001651828,0.0002372082,0.003634182],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004055863,"threshold_uncertainty_score":0.008064508,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06744222915416359,"score_gpt":0.2410438010197971,"score_spread":0.1736015718656335,"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."}}