{"id":"W2992772646","doi":"","title":"Evaluation of stress intensity factor for turbine blade using finite element method","year":2018,"lang":"en","type":"article","venue":"International journal of advance research, ideas and innovations in technology","topic":"Fatigue and fracture mechanics","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Impact","funders":"","keywords":"Fillet (mechanics); Structural engineering; Turbine blade; Stress intensity factor; von Mises yield criterion; Stress concentration; Finite element method; Centrifugal compressor; Stress (linguistics); Gas compressor; Materials science; Engineering; Turbine; Mechanical engineering","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":[0.000619242,0.00060538,0.0006301434,0.0009756795,0.0003266456,0.0005829892,0.00074211,0.001363773,0.003015569],"category_scores_gemma":[0.001415787,0.0004211784,0.0007504105,0.0005332233,0.0002993648,0.0005982564,0.0002708634,0.0004418713,0.0006707234],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003493845,"about_ca_system_score_gemma":0.0005692705,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002576509,"about_ca_topic_score_gemma":0.002040168,"domain_scores_codex":[0.9996921,0.00004301454,0.00002369504,0.00004191329,0.0001672635,0.00003195701],"domain_scores_gemma":[0.9993287,0.0002806369,0.00007192603,0.00004187817,0.0002515889,0.00002521985],"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":[0.0001377226,0.0001950966,0.009349818,0.0003269464,0.00005091967,0.0002501012,0.0004095387,0.8019282,0.07595128,0.003074453,0.001225144,0.1071009],"study_design_scores_gemma":[0.000004588335,0.00003464605,0.0009997528,0.00001236009,0.000005216733,0.00003058486,0.00003050272,0.9943027,0.003803949,0.0002084602,0.0005559137,0.00001136615],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2600898,0.0003864873,0.729978,0.000192687,0.00009370652,0.0001529923,0.0003065205,0.002097734,0.00670205],"genre_scores_gemma":[0.8495389,0.0002409917,0.1464813,0.00003613698,0.00001857014,0.0002032187,0.0004364632,0.0001548782,0.002889586],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003015569,"threshold_uncertainty_score":0.01008809,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09080198778564336,"score_gpt":0.441091550400612,"score_spread":0.3502895626149686,"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."}}