{"id":"W4225147074","doi":"10.3390/act11050121","title":"Multidisciplinary Optimization for Weight Saving in a Variable Tapered Span-Morphing Wing Using Composite Materials—Application to the UAS-S4","year":2022,"lang":"en","type":"article","venue":"Actuators","topic":"Topology Optimization in Engineering","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Morphing; Sizing; Multidisciplinary design optimization; Topology optimization; Wing; Aerodynamics; Finite element method; Minimum weight; Structural engineering; Aeroelasticity; MATLAB; Stiffness; Computer science; Engineering; Aerospace engineering; Multidisciplinary approach; Artificial intelligence","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":[0.0003262494,0.0003299381,0.0002363023,0.0003356769,0.0001935807,0.0003118505,0.0002291208,0.000311592,0.0008566341],"category_scores_gemma":[0.0003491397,0.0001547603,0.0004153,0.0001617082,0.000261947,0.0002372025,0.0003584618,0.000233445,0.0000872413],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002228823,"about_ca_system_score_gemma":0.0003588416,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007790446,"about_ca_topic_score_gemma":0.001267263,"domain_scores_codex":[0.9999281,0.00001784942,0.000003067527,0.00001155391,0.00002797333,0.00001130944],"domain_scores_gemma":[0.9998667,0.00006375024,0.00002273267,0.00001624429,0.00001997663,0.00001050326],"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":[0.00004892101,0.00004467953,0.001225501,0.00007638546,0.00002002756,0.000114515,0.00003181679,0.9453969,0.03383206,0.002170601,0.0001563451,0.01688212],"study_design_scores_gemma":[0.000006920909,0.0001137054,0.0007317258,0.00000573885,0.000009178855,0.00004310135,0.00002647048,0.9902961,0.007392519,0.0005648046,0.000804095,0.000005601121],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7305586,0.0002835506,0.2595591,0.0001459936,0.00003492195,0.00006242162,0.0000700083,0.000136608,0.009148845],"genre_scores_gemma":[0.9132228,0.0001043539,0.08478274,0.00001937795,0.000004057538,0.00005388522,0.00005586039,0.00003788083,0.001719015],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0008566341,"threshold_uncertainty_score":0.002865732,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007589362453183965,"score_gpt":0.2234302363263887,"score_spread":0.2158408738732047,"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."}}