{"id":"W4322630531","doi":"10.3390/fluids8030086","title":"A Highly Scalable Direction-Splitting Solver on Regular Cartesian Grid to Compute Flows in Complex Geometries Described by STL Files","year":2023,"lang":"en","type":"article","venue":"Fluids","topic":"Computational Geometry and Mesh Generation","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Grid; Computational science; Solver; Scalability; Triangulation; Computer science; Computation; Regular grid; Cartesian coordinate system; Supercomputer; Parallel computing; Flow (mathematics); Algorithm; Mesh generation; Computer graphics (images); Tracing; Ray tracing (physics); Geometry; Mathematics; Physics; Programming language","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":[0.0006306337,0.0007710308,0.000715852,0.0005770268,0.000497515,0.0008121287,0.002023091,0.0008162766,0.0089436],"category_scores_gemma":[0.002077587,0.0004162095,0.0008408778,0.0009575197,0.0004596508,0.0007954657,0.001261337,0.001284328,0.002842837],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004831414,"about_ca_system_score_gemma":0.001641167,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003878175,"about_ca_topic_score_gemma":0.004809442,"domain_scores_codex":[0.9996343,0.00005859583,0.00002820278,0.00004438583,0.0001830461,0.0000514461],"domain_scores_gemma":[0.9990394,0.0003366794,0.00006462688,0.0001933715,0.0002948788,0.00007107147],"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":[0.0002247033,0.0002550002,0.004126422,0.0003830741,0.0001019048,0.0005992076,0.0004286252,0.6742791,0.02814214,0.0537205,0.0516305,0.1861088],"study_design_scores_gemma":[0.0001114033,0.00002798111,0.000197698,0.0000137506,0.00000485316,0.00006920196,0.00003321483,0.9798669,0.004323936,0.007149696,0.00818737,0.0000140407],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02864491,0.00007311976,0.9484473,0.0001893692,0.0001245745,0.0001775295,0.001503935,0.01131682,0.009522378],"genre_scores_gemma":[0.1129953,0.00008424122,0.878423,0.0001103236,0.00003115906,0.0004468689,0.002852581,0.002130724,0.002925728],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0089436,"threshold_uncertainty_score":0.02991927,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02457150693270149,"score_gpt":0.2524355163766536,"score_spread":0.2278640094439521,"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."}}