{"id":"W2023477124","doi":"10.1002/cjce.20194","title":"Enhanced model predictive control of a catalytic flow reversal reactor","year":2009,"lang":"en","type":"article","venue":"The Canadian Journal of Chemical Engineering","topic":"Advanced Control Systems Optimization","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta; Polytechnique Montréal","funders":"","keywords":"Methane; Model predictive control; Continuous stirred-tank reactor; Plug flow reactor model; Volumetric flow rate; Combustion; Inert; Catalysis; Inlet; Energy balance; Catalytic combustion; Chemistry; Control theory (sociology); Nuclear engineering; Mechanics; Thermodynamics; Engineering; Computer science; Physics; Physical chemistry; Control (management); Mechanical engineering; Organic chemistry","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.0005865822,0.0006379845,0.0008323986,0.0002412956,0.0003175485,0.0008717219,0.0007665013,0.0006942526,0.001198135],"category_scores_gemma":[0.0005035381,0.0002960522,0.0004399543,0.0001831662,0.0005831242,0.0002737948,0.0004246633,0.0007430816,0.0001600378],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006089409,"about_ca_system_score_gemma":0.0006606458,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01082079,"about_ca_topic_score_gemma":0.004851076,"domain_scores_codex":[0.999808,0.00005820781,0.000007681361,0.00003758903,0.00005750992,0.00003096179],"domain_scores_gemma":[0.9997301,0.0001286074,0.00004431162,0.00002208966,0.00006232329,0.00001256786],"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":[0.0001087457,0.00005712542,0.0001879073,0.00004463718,0.00001630502,0.00005958833,0.00001697331,0.9858696,0.006914393,0.001215391,0.0001480592,0.005361166],"study_design_scores_gemma":[0.00001005006,0.00003926818,0.00004660477,9.98012e-7,0.000003009333,0.000002003314,0.000001022808,0.9990836,0.0006771371,0.00006470901,0.0000699559,0.000001588478],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4869973,0.000657201,0.4912237,0.0004665329,0.0001727058,0.0001313021,0.000130942,0.0009462811,0.01927401],"genre_scores_gemma":[0.9939929,0.00004986673,0.004777849,0.00001682029,0.00000747445,0.00003105285,0.00002343478,0.000005764208,0.001094841],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01082079,"threshold_uncertainty_score":0.02151561,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003521578953037826,"score_gpt":0.1654072616376433,"score_spread":0.1618856826846055,"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."}}