{"id":"W3013826162","doi":"10.5194/wes-2020-24","title":"Surrogate models for unsteady aerodynamics using non-intrusive Polynomial Chaos Expansions","year":2020,"lang":"en","type":"article","venue":"","topic":"Probabilistic and Robust Engineering Design","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Polynomial chaos; Aerodynamics; Turbine; Computational fluid dynamics; Wind power; Uncertainty quantification; Turbulence; Computer science; Computation; Flow (mathematics); Wind speed; Mathematics; Engineering; Algorithm; Statistics; Meteorology; Aerospace engineering; Monte Carlo method; Physics","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":[0.001167896,0.0006473683,0.0006452469,0.0007416105,0.0002553607,0.0008714852,0.0008026093,0.0008071285,0.001071207],"category_scores_gemma":[0.004406731,0.0003849513,0.0007832297,0.0005300728,0.0007558427,0.001038797,0.0007704569,0.001057546,0.000323984],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005367289,"about_ca_system_score_gemma":0.0007421079,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001921607,"about_ca_topic_score_gemma":0.001606615,"domain_scores_codex":[0.9994006,0.0002281831,0.00002760479,0.00005701356,0.0002364774,0.00005007027],"domain_scores_gemma":[0.9983068,0.001012558,0.0002359822,0.0001236071,0.0002626428,0.00005843648],"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":[0.00001669315,0.00001267713,0.0003350646,0.00002007457,0.000009287622,0.00002783252,0.00002043648,0.9786667,0.0009522959,0.0164892,0.0001690481,0.003280767],"study_design_scores_gemma":[5.487991e-7,0.000003867123,0.00002666514,0.000001279376,5.639387e-7,0.000003428909,9.169574e-7,0.998795,0.00008964963,0.001000149,0.0000764164,0.000001411448],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01945219,0.0001084926,0.9786848,0.00008816006,0.00002458113,0.00002649876,0.00006538754,0.00009734421,0.001452578],"genre_scores_gemma":[0.8936713,0.0004375844,0.100092,0.00007316483,0.00005005588,0.0001817121,0.0003241358,0.00009523646,0.005074725],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001921607,"threshold_uncertainty_score":0.006176472,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.241747229572022,"score_gpt":0.3590344280787769,"score_spread":0.1172871985067549,"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."}}