{"id":"W4231563647","doi":"10.1115/gt2018-75880","title":"Thermomechanical Model Reduction for Efficient Simulations of Rotor-Stator Contact Interaction","year":2018,"lang":"en","type":"preprint","venue":"","topic":"Tribology and Lubrication Engineering","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Safran Electronics (Canada)","funders":"","keywords":"Stator; Reduction (mathematics); Rotor (electric); Krylov subspace; Turbomachinery; Computer science; Work (physics); Model order reduction; Thermal; Mechanical engineering; Engineering; Mathematics; Algorithm; Iterative method; Physics; Projection (relational algebra)","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":[0.0001059089,0.0001628224,0.0002224269,0.0001473089,0.00003094838,0.000009996263,0.000110995,0.0002718413,0.00006657775],"category_scores_gemma":[0.00003997468,0.0001676846,0.0001124965,0.00006123347,0.0000147444,0.0000404028,0.0000425089,0.0002314716,0.000006006223],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000116914,"about_ca_system_score_gemma":0.00002761808,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000562827,"about_ca_topic_score_gemma":0.000001994802,"domain_scores_codex":[0.9992381,0.00001170825,0.0003402666,0.0001977605,0.0000769908,0.0001351934],"domain_scores_gemma":[0.9994034,0.00007758311,0.00007722651,0.000269599,0.0001321765,0.0000399725],"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":[0.00002138593,0.00002748585,0.000002443606,0.0001330519,0.00006840131,2.979344e-8,0.0001231288,0.9763313,0.02033012,0.002278346,0.0003046939,0.0003795947],"study_design_scores_gemma":[0.0001864302,0.00002510985,0.00005692036,0.00004616888,0.00003937881,0.000001375093,0.00001930963,0.9818806,0.01667115,0.0007037942,0.0002201896,0.0001495673],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2326093,0.00003159786,0.7650809,0.0000213899,0.001061473,0.0005378906,0.00008300164,0.0002764461,0.0002979856],"genre_scores_gemma":[0.9915502,0.000007774249,0.007929037,0.000003529666,0.0001647476,0.0001426337,0.0001082197,0.00003769051,0.00005617438],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7589409,"threshold_uncertainty_score":0.683798,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02877441123012552,"score_gpt":0.2847141704066751,"score_spread":0.2559397591765495,"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."}}