Multilevel Monte Carlo applied to chemical engineering systems subject to uncertainty

The aim of this study is to evaluate the performance of Multilevel Monte Carlo (MLMC) sampling technique for uncertainty quantification in chemical engineering systems. Three systems (a mixing tank, a wastewater treatment plant, and a ternary distillation column, all subject to uncertainty) were con...

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Veröffentlicht in:AIChE journal Jg. 64; H. 5; S. 1651 - 1661
Hauptverfasser: Kimaev, Grigoriy, Ricardez‐Sandoval, Luis A.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York American Institute of Chemical Engineers 01.05.2018
Schlagworte:
Chemical engineering
Computer applications
Distillation
Monte Carlo simulation
multilevel Monte Carlo
Polynomial Chaos
Power Series
Sampling
Studies
Uncertainty
uncertainty quantification
Wastewater treatment
Wastewater treatment plants
ISSN:0001-1541, 1547-5905
Online-Zugang:Volltext
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Zusammenfassung:The aim of this study is to evaluate the performance of Multilevel Monte Carlo (MLMC) sampling technique for uncertainty quantification in chemical engineering systems. Three systems (a mixing tank, a wastewater treatment plant, and a ternary distillation column, all subject to uncertainty) were considered. The expected values of the systems' observables were estimated using MLMC, Power Series and Polynomial Chaos expansions, and standard Monte Carlo (MC) sampling. The MLMC technique achieved results of significantly greater accuracy than other methods at a lower computational cost than standard MC. This study highlights the nuances of adapting the MLMC technique to chemical engineering systems and the advantages of using MLMC for uncertainty quantification. © 2017 American Institute of Chemical Engineers AIChE J, 64: 1651–1661, 2018
Bibliographie:ObjectType-Article-1
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ISSN:0001-1541
1547-5905
DOI:10.1002/aic.16045