{"id":"W1668508842","doi":"10.1002/fld.3670","title":"A computational method for geometric optimization of enhanced heat transfer devices based upon entropy generation minimization","year":2012,"lang":"en","type":"article","venue":"International Journal for Numerical Methods in Fluids","topic":"Heat Transfer and Optimization","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Nusselt number; Heat transfer; Computation; Minification; Mathematical optimization; Computational fluid dynamics; Entropy (arrow of time); Optimization problem; Computer science; Mathematics; Applied mathematics; Algorithm; Mechanics; Physics; Thermodynamics","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0005680516,0.0004743067,0.0005968002,0.0004140149,0.0002999299,0.0004223691,0.0006620668,0.0004857171,0.002966242],"category_scores_gemma":[0.0006288032,0.0003023455,0.0005616324,0.0002906113,0.0004804863,0.0003581531,0.0006213532,0.0006691499,0.0003882465],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004132927,"about_ca_system_score_gemma":0.0007853238,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006862761,"about_ca_topic_score_gemma":0.000848122,"domain_scores_codex":[0.9998341,0.00004761285,0.000006772544,0.00001774502,0.00008135595,0.00001241326],"domain_scores_gemma":[0.9998112,0.0001005143,0.00001790418,0.00002387531,0.00003882376,0.000007676362],"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":[0.00002215443,0.00002118576,0.0001292292,0.00008459768,0.00001527607,0.0000332545,0.00002425621,0.9308347,0.009917872,0.03328289,0.0006629786,0.02497163],"study_design_scores_gemma":[0.000003818084,0.000009241072,0.00003148811,0.000003049475,0.000001614306,0.000007095281,0.000001342538,0.9963784,0.000897355,0.001728739,0.0009349722,0.000002919171],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004363547,0.00005995825,0.9924685,0.00003850528,0.00002135354,0.00004550994,0.0000235722,0.0001042985,0.002874837],"genre_scores_gemma":[0.2681796,0.0001871812,0.7252385,0.00005735959,0.00003753839,0.0006655583,0.0001071684,0.0002047064,0.005322286],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002966242,"threshold_uncertainty_score":0.0099231,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03632431741271734,"score_gpt":0.3732457895142531,"score_spread":0.3369214721015358,"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."}}