{"id":"W2766009344","doi":"10.2514/1.j056163","title":"Efficient Monolithic Solution Algorithm for High-Fidelity Aerostructural Analysis and Optimization","year":2017,"lang":"en","type":"article","venue":"AIAA Journal","topic":"Computational Fluid Dynamics and Aerodynamics","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Krylov subspace; Mathematical optimization; Robustness (evolution); Algorithm; Computer science; Context (archaeology); Iterative method; Mathematics","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":[0.0006444075,0.0006600511,0.0005935426,0.0003878801,0.0003699608,0.0006770526,0.001090701,0.001018413,0.004580202],"category_scores_gemma":[0.001209344,0.0004922396,0.0005364512,0.0004792188,0.0005546485,0.0008268168,0.001117942,0.001256017,0.001449453],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005124987,"about_ca_system_score_gemma":0.001539198,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002272521,"about_ca_topic_score_gemma":0.003172111,"domain_scores_codex":[0.999688,0.00005970354,0.00001497,0.00005310679,0.0001522101,0.00003196367],"domain_scores_gemma":[0.9994556,0.000198715,0.00005154273,0.00008144056,0.0001840332,0.00002849844],"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":[0.00006153656,0.00008099472,0.0003848519,0.0001375414,0.00004254524,0.0001018026,0.00008757468,0.8394008,0.0219149,0.03976579,0.003486857,0.09453478],"study_design_scores_gemma":[0.000005695317,0.00001086641,0.00003893498,0.000003637294,0.000002051642,0.00001403689,0.000004620397,0.9953954,0.00124675,0.002106389,0.001168408,0.000003188206],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001882778,0.00004472029,0.9965748,0.0000274086,0.00001113103,0.00001828954,0.00001763883,0.0002530747,0.00117034],"genre_scores_gemma":[0.1094197,0.0001252685,0.8854695,0.0000995277,0.00002823802,0.000225751,0.0001892458,0.0002561135,0.00418657],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004580202,"threshold_uncertainty_score":0.01532227,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006482683223171195,"score_gpt":0.2275439723892261,"score_spread":0.2210612891660549,"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."}}