{"id":"W4401833493","doi":"10.1016/j.nucengdes.2024.113523","title":"Effects of different momentum ratios and Reynolds number in a T-junction with an upstream elbow","year":2024,"lang":"en","type":"article","venue":"Nuclear Engineering and Design","topic":"Nuclear Engineering Thermal-Hydraulics","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Engineering and Physical Sciences Research Council; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada; Singapore Eye Research Institute; National Research Foundation","keywords":"Reynolds number; Mechanics; Momentum (technical analysis); Upstream (networking); Elbow; Physics; Statistical physics; Mathematics; Engineering; Economics; Turbulence; Medicine; Telecommunications; Anatomy; Financial economics","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":[0.0009119296,0.0006267107,0.0009049109,0.0007937113,0.0009742118,0.002045714,0.0006697873,0.001047855,0.001788274],"category_scores_gemma":[0.002677095,0.0004041055,0.0006817479,0.000502724,0.001061751,0.001236758,0.0007609704,0.001016167,0.0004406401],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006040473,"about_ca_system_score_gemma":0.0004557899,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002269586,"about_ca_topic_score_gemma":0.002004945,"domain_scores_codex":[0.9994312,0.0000699134,0.00004879057,0.0001708131,0.0001245283,0.0001546661],"domain_scores_gemma":[0.9987385,0.0004602203,0.0003204065,0.00009825287,0.0001964736,0.0001862799],"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":[0.003573715,0.0008950461,0.03764791,0.0004502904,0.000132912,0.002791185,0.0007283175,0.3002319,0.6259524,0.003688722,0.0006748255,0.02323282],"study_design_scores_gemma":[0.0001113932,0.002596352,0.0413823,0.00009318739,0.0002418726,0.0005528849,0.001695739,0.3838443,0.5658396,0.0006122299,0.002815977,0.0002141752],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9929142,0.0003833159,0.004477879,0.00006412202,0.00005556903,0.00002000895,0.00006571291,0.0001720993,0.001847154],"genre_scores_gemma":[0.9977405,0.00009007911,0.001638563,0.00001530369,0.000004299766,0.00001033551,0.00003717621,0.00002909735,0.0004345504],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002269586,"threshold_uncertainty_score":0.005982399,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003599066956818137,"score_gpt":0.167507139730569,"score_spread":0.1639080727737509,"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."}}