{"id":"W2963960351","doi":"10.1177/1464420719863458","title":"Numerical simulation of ductile fracture in polyethylene pipe with continuum damage mechanics and Gurson-Tvergaard-Needleman damage models","year":2019,"lang":"en","type":"article","venue":"Proceedings of the Institution of Mechanical Engineers Part L Journal of Materials Design and Applications","topic":"Metal Forming Simulation Techniques","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"National Natural Science Foundation of China","keywords":"Crosshead; Necking; Materials science; Constitutive equation; Finite element method; Structural engineering; Fracture (geology); Damage mechanics; Stress (linguistics); Mechanics; Viscoplasticity; Composite material; Engineering; Flexural strength; Physics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005914174,0.0001442515,0.0004175507,0.0001539102,0.00002534735,0.00001646133,0.0001821386,0.0001190084,0.00001339556],"category_scores_gemma":[0.00005317728,0.0001077238,0.00004365907,0.0002290534,0.00004219752,0.0003591886,0.00002927482,0.0001465236,2.094341e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002819455,"about_ca_system_score_gemma":0.00002340993,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004475603,"about_ca_topic_score_gemma":1.857684e-7,"domain_scores_codex":[0.9988626,0.00001466759,0.0006607349,0.0001095999,0.000242267,0.0001101561],"domain_scores_gemma":[0.9990916,0.00008120267,0.0004339172,0.0001003979,0.0002391892,0.00005370015],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00009577774,0.00004343171,0.00001025111,0.0002883767,0.00003437647,1.175493e-7,0.0001352443,0.3880586,0.564634,0.04658978,0.00001637653,0.00009363028],"study_design_scores_gemma":[0.0005554008,0.0001534301,0.00005166868,0.000324629,0.00005497512,0.00001097058,0.00009097819,0.186795,0.8021244,0.009561422,0.0001614244,0.0001157131],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6238288,0.00006800941,0.3753878,0.00004909869,0.0000695354,0.0005167583,0.0000103281,0.00002498996,0.00004462046],"genre_scores_gemma":[0.9907489,0.00008529131,0.009087964,0.000008773018,0.00003103365,0.00001432306,0.000001501812,0.00001715969,0.000005058457],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3669201,"threshold_uncertainty_score":0.439285,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01115506558376507,"score_gpt":0.2173200677776338,"score_spread":0.2061650021938687,"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."}}