{"id":"W4391325110","doi":"10.2514/6.2024-2871","title":"Automated Convergence Acceleration of Flow Solvers Using Dynamic Mode Decomposition","year":2024,"lang":"en","type":"article","venue":"","topic":"Model Reduction and Neural Networks","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Acceleration; Dynamic mode decomposition; Convergence (economics); Computer science; Decomposition; Flow (mathematics); Mode (computer interface); Computational science; Mechanics; Physics; Classical mechanics","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":[0.00002463468,0.00006287476,0.00006843558,0.00003975496,0.00004067628,0.00003205108,0.00003405354,0.00002039557,0.0008757145],"category_scores_gemma":[1.742875e-7,0.00005692837,0.00005149467,0.0001119534,0.000014488,0.0001854655,0.00001033952,0.0000521838,0.00001396617],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001813008,"about_ca_system_score_gemma":0.00002857005,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009972449,"about_ca_topic_score_gemma":0.000001910144,"domain_scores_codex":[0.9995919,0.00001301993,0.0001303289,0.0001189356,0.00006397661,0.00008179985],"domain_scores_gemma":[0.9998538,0.000009295632,0.00002311223,0.00006197353,0.00002553455,0.00002624007],"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":[0.00001413495,0.00004719483,0.0002496124,0.00003201567,0.00006910637,8.161158e-7,0.0001638842,0.7229481,0.2441627,0.01370598,0.001411291,0.01719508],"study_design_scores_gemma":[0.00005731113,0.000007570812,0.00003891085,0.00002474439,0.00001291598,8.389289e-7,0.00002797832,0.9796238,0.01954097,0.0005681471,0.00003795496,0.00005888885],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5861464,0.00001726694,0.4120706,0.00004087662,0.0003700778,0.00006197146,0.000008152975,0.0001377149,0.001146982],"genre_scores_gemma":[0.9961858,0.000003619282,0.003505795,0.00001040731,0.00005663505,0.000002681446,0.0000548881,0.000007330138,0.0001728056],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4100395,"threshold_uncertainty_score":0.9588459,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01880993031478748,"score_gpt":0.3486400617562644,"score_spread":0.3298301314414769,"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."}}