{"id":"W4236244003","doi":"10.32920/ryerson.14662458","title":"A Finite Element Formulation Of Active Constrained-Layer Functionally Graded Beam","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Composite Structure Analysis and Optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Constrained-layer damping; Beam (structure); Viscoelasticity; Finite element method; Newmark-beta method; Timoshenko beam theory; Materials science; Equations of motion; Cantilever; Vibration; Functionally graded material; Structural engineering; Hamilton's principle; Layer (electronics); Vibration control; Mathematics; Mathematical analysis; Composite material; Physics; Classical mechanics; Engineering; Acoustics","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00004989177,0.000195165,0.0003088779,0.0001596969,0.00002534132,0.00004166393,0.00007906388,0.0001562771,0.001006827],"category_scores_gemma":[0.00001131861,0.0001916709,0.0002055506,0.0001551713,0.00001045408,0.00007176503,0.00009015208,0.0002100878,0.000001417438],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009189005,"about_ca_system_score_gemma":0.00004764789,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003142594,"about_ca_topic_score_gemma":0.00008667904,"domain_scores_codex":[0.9990613,0.00001332026,0.0003860847,0.0002093082,0.0002176679,0.0001123077],"domain_scores_gemma":[0.9993643,0.00004551208,0.0001065715,0.000232064,0.0002164214,0.00003520024],"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":[0.000007827782,0.00001430714,0.0001003616,0.00009522012,0.0004436593,7.561321e-7,0.0002027701,0.9917056,0.0038513,0.0004220776,0.00007741382,0.003078737],"study_design_scores_gemma":[0.0003302853,0.00002151039,0.004630009,0.00007864083,0.0002758339,0.000001623428,0.0001650789,0.9591339,0.03416727,0.0006554602,0.0002327664,0.0003075746],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1379149,0.0001945541,0.8494287,0.00004695715,0.0005222623,0.0003421234,0.00006407318,0.0001593533,0.01132709],"genre_scores_gemma":[0.9906152,0.00007738526,0.007641064,0.00002512394,0.0000829062,0.00001680165,0.001425493,0.00001978552,0.00009625641],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8527002,"threshold_uncertainty_score":0.9999064,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01136795046129008,"score_gpt":0.2194074790455578,"score_spread":0.2080395285842677,"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."}}