{"id":"W2062378303","doi":"10.1007/s00158-011-0722-z","title":"Development of a structural optimization strategy for the design of next generation large thermoplastic wind turbine blades","year":2011,"lang":"en","type":"article","venue":"Structural and Multidisciplinary Optimization","topic":"Topology Optimization in Engineering","field":"Engineering","cited_by":50,"is_retracted":false,"has_abstract":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Turbine blade; Topology optimization; Structural engineering; Deflection (physics); Blade (archaeology); Engineering design process; Thermoplastic; Engineering; Turbine; Mechanical engineering; Materials science; Finite element method; Composite material","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":[0.0003495582,0.0005798371,0.0005437068,0.000374087,0.0003496397,0.0004317144,0.000689676,0.0007553959,0.002548036],"category_scores_gemma":[0.000595211,0.0004586964,0.0005170913,0.0002267721,0.0002997832,0.0005130754,0.0004887501,0.0006093769,0.000425333],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003719027,"about_ca_system_score_gemma":0.0008837348,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00168118,"about_ca_topic_score_gemma":0.002984083,"domain_scores_codex":[0.9999096,0.00002746242,0.000003855066,0.00001203666,0.0000363434,0.00001068044],"domain_scores_gemma":[0.9998636,0.00005104494,0.00001571103,0.00001193675,0.00004629659,0.00001141607],"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":[0.00001598128,0.00003404044,0.0001596284,0.00003259989,0.00001240947,0.00003424365,0.00002293109,0.9683794,0.00745229,0.005196816,0.0002852992,0.01837434],"study_design_scores_gemma":[0.000004898592,0.00002187174,0.00003938253,0.00000201897,0.00000238808,0.000005015514,0.000005168224,0.9984523,0.0004947382,0.0005912497,0.0003792953,0.000001623348],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03479009,0.0001117258,0.9578937,0.0001266101,0.00004128903,0.00009657608,0.00003741408,0.0001490693,0.006753505],"genre_scores_gemma":[0.5098741,0.0002051796,0.4841163,0.00009352314,0.00003579036,0.0003499238,0.0001164031,0.0001604482,0.005048357],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002548036,"threshold_uncertainty_score":0.00852406,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05295923002588927,"score_gpt":0.2517438640850409,"score_spread":0.1987846340591516,"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."}}