{"id":"W4382405474","doi":"10.1016/j.powtec.2023.118761","title":"Analyzing mixing behavior in a double paddle blender containing two types of non-spherical particles through discrete element method (DEM) and response surface method (RSM)","year":2023,"lang":"en","type":"article","venue":"Powder Technology","topic":"Granular flow and fluidized beds","field":"Engineering","cited_by":29,"is_retracted":false,"has_abstract":false,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Paddle; Discrete element method; Impeller; Mixing (physics); Mechanics; Péclet number; Rotational speed; Materials science; Thermal diffusivity; Particle (ecology); Calibration; Flow (mathematics); Mathematics; Biological system; Geometry; Physics; Composite material; Engineering; Mechanical engineering; Thermodynamics; Geology; Statistics","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":[0.0003405959,0.0002377151,0.0003810236,0.0003457997,0.0002189534,0.0003203022,0.0002423419,0.0004183997,0.0005849748],"category_scores_gemma":[0.0004391261,0.0001751011,0.0002548876,0.000253459,0.0001889448,0.0003881623,0.0001822727,0.0003299127,0.0001429335],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001469774,"about_ca_system_score_gemma":0.0001226968,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003737826,"about_ca_topic_score_gemma":0.0004575278,"domain_scores_codex":[0.9998087,0.00002553119,0.00001817594,0.00005405746,0.00007750408,0.00001596106],"domain_scores_gemma":[0.9997966,0.0001110877,0.00003299774,0.00001384589,0.00003026349,0.00001525851],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005116376,0.00009234669,0.001505934,0.00007391661,0.000009106351,0.00004694873,0.00005116144,0.001833142,0.9872158,0.000154822,0.00002710639,0.008478147],"study_design_scores_gemma":[0.00002211728,0.000436354,0.005884496,0.000003486487,0.00002388781,0.00004841299,0.00004638114,0.05535721,0.9377635,0.00006297838,0.0003389061,0.00001236886],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9865914,0.0001459931,0.01271004,0.00002944534,0.00001315574,0.00001408466,0.00004154399,0.00007968626,0.0003745437],"genre_scores_gemma":[0.9902049,0.0000897747,0.008872195,0.00001028531,0.00000322325,0.00001178156,0.00005433983,0.00001550343,0.0007380012],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0005849748,"threshold_uncertainty_score":0.00195688,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02617262070668195,"score_gpt":0.3280017338079395,"score_spread":0.3018291131012575,"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."}}