{"id":"W3026005976","doi":"10.3390/ma13102261","title":"Multidisciplinary Design Optimization of a Novel Sandwich Beam-Based Adaptive Tuned Vibration Absorber Featuring Magnetorheological Elastomer","year":2020,"lang":"en","type":"article","venue":"Materials","topic":"Vibration Control and Rheological Fluids","field":"Engineering","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Magnetorheological elastomer; Electromagnet; Magnetorheological fluid; Finite element method; Materials science; Dynamic Vibration Absorber; Deflection (physics); Optimal design; Vibration; Natural frequency; Beam (structure); Structural engineering; Magnetic field; Mechanical engineering; Composite material; Magnet; Acoustics; Engineering; Computer science; Physics; Optics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0002887829,0.0003825892,0.0004036064,0.0002851107,0.0001663327,0.0004576659,0.0004480988,0.0007073298,0.001036575],"category_scores_gemma":[0.0002133964,0.0002150103,0.0004979349,0.0001708221,0.0002129279,0.0002679982,0.000338134,0.0002488196,0.0002342899],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001911255,"about_ca_system_score_gemma":0.0002564085,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003119465,"about_ca_topic_score_gemma":0.0006492284,"domain_scores_codex":[0.9998828,0.00002106458,0.000004493252,0.00002932831,0.00004415016,0.00001816506],"domain_scores_gemma":[0.9999106,0.00003424804,0.00002640992,0.000008000202,0.00001364775,0.000007130132],"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":[0.0001319182,0.0001256128,0.0008262952,0.000374039,0.00006138809,0.0001978602,0.00005027634,0.5071017,0.4647158,0.00232649,0.0002249589,0.02386368],"study_design_scores_gemma":[0.00001743856,0.0004678836,0.0007231825,0.00001504655,0.00003372018,0.00008737762,0.00003266539,0.9535324,0.04333397,0.0003585145,0.001382256,0.00001554895],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5070828,0.001149162,0.481674,0.0001890291,0.00005175962,0.0000893649,0.00007151681,0.0001963877,0.009495858],"genre_scores_gemma":[0.9200482,0.0003063518,0.07680526,0.00002935234,0.000007283626,0.0001069508,0.00003479201,0.00002087611,0.00264107],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001036575,"threshold_uncertainty_score":0.003467739,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03379345686324659,"score_gpt":0.2182705261177813,"score_spread":0.1844770692545347,"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."}}