{"id":"W4403851853","doi":"10.1115/1.4067033","title":"Loss Breakdown in Axial Turbines: A New Method for Vortex Loss and Wake Detection From 3D RANS Simulations","year":2024,"lang":"en","type":"article","venue":"Journal of Turbomachinery","topic":"Turbomachinery Performance and Optimization","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Safran Electronics (Canada)","funders":"Association Nationale de la Recherche et de la Technologie","keywords":"Reynolds-averaged Navier–Stokes equations; Wake; Vortex; Mechanics; Wake turbulence; Aerospace engineering; Computational fluid dynamics; Materials science; Physics; Marine engineering; Engineering","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":[0.001178549,0.000904405,0.0006519091,0.001508403,0.0003910131,0.001155771,0.001150359,0.001188935,0.002292004],"category_scores_gemma":[0.003248799,0.000617975,0.0006440673,0.0005339345,0.0006451218,0.0007857684,0.001375916,0.001090583,0.0006447309],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003920108,"about_ca_system_score_gemma":0.0007272901,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002799015,"about_ca_topic_score_gemma":0.002099404,"domain_scores_codex":[0.9995436,0.0001359296,0.00003538864,0.0000385416,0.0002081865,0.00003831442],"domain_scores_gemma":[0.9986766,0.0004702747,0.0002309098,0.0001620007,0.0003837207,0.00007644101],"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":[0.0003033521,0.0003219139,0.008360414,0.0003097815,0.0001152081,0.0005065991,0.0003709348,0.8242778,0.0343831,0.01240934,0.002218559,0.1164229],"study_design_scores_gemma":[0.000005143671,0.0000123488,0.0002419324,0.000006021503,0.000001867044,0.00001284015,0.000008886213,0.9982417,0.0009195999,0.0002820401,0.0002621055,0.000005484587],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0603701,0.0001174111,0.9341272,0.00009902848,0.00005649688,0.0002262922,0.0001680875,0.002031939,0.002803537],"genre_scores_gemma":[0.573205,0.0001326066,0.4226713,0.0001094972,0.00004690294,0.0003942207,0.0004374838,0.0008079858,0.002195064],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002799015,"threshold_uncertainty_score":0.007667542,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006695690897652074,"score_gpt":0.2600262376182917,"score_spread":0.2533305467206396,"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."}}