{"id":"W4205807183","doi":"10.2514/6.2022-0165","title":"Analysis and Design Optimization of a Magnetorheological Elastomer-based Vibration Absorber for Maximum Vibration Attenuation of a Main Structure","year":2022,"lang":"en","type":"article","venue":"AIAA SCITECH 2022 Forum","topic":"Vibration Control and Rheological Fluids","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Dynamic Vibration Absorber; Magnetorheological fluid; Vibration; Sequential quadratic programming; Magnetorheological elastomer; Optimal design; Finite element method; Attenuation; Beam (structure); Structural engineering; Materials science; Magnetic field; Acoustics; Engineering; Computer science; Quadratic programming; Physics; Optics; Damper","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":[0.0002702271,0.0004369977,0.0003636466,0.0003138109,0.0001615647,0.0004580244,0.0003277017,0.0005562633,0.001374835],"category_scores_gemma":[0.0002492057,0.0002805211,0.0005590924,0.0001869374,0.000200696,0.000225824,0.0001987309,0.0002529074,0.0003144751],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003242927,"about_ca_system_score_gemma":0.0004243639,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006678406,"about_ca_topic_score_gemma":0.001303089,"domain_scores_codex":[0.9998785,0.00001648457,0.000003558333,0.00002564787,0.0000595655,0.00001617803],"domain_scores_gemma":[0.9999002,0.00003358931,0.00003576873,0.000005135823,0.00001980876,0.000005478339],"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":[0.0001110069,0.00009138536,0.0007576919,0.0005485726,0.00005299233,0.0001667001,0.00005658272,0.6179919,0.3523895,0.002500371,0.0005039827,0.02482935],"study_design_scores_gemma":[0.00001176371,0.0004105202,0.0007484399,0.00001585144,0.00003658374,0.00005467602,0.0000300905,0.9616646,0.03482801,0.0002317703,0.001956022,0.00001170801],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.442474,0.001808848,0.5353677,0.0003726362,0.00005520892,0.0001794981,0.0001786129,0.000399264,0.0191642],"genre_scores_gemma":[0.9018381,0.0006218054,0.09109543,0.00002873376,0.000009353554,0.0001643912,0.00008425026,0.00005549411,0.006102586],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001374835,"threshold_uncertainty_score":0.004599273,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008302928955004634,"score_gpt":0.2055722891524608,"score_spread":0.1972693601974561,"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."}}