TY - JOUR
T1 - Uncertainty quantification and global sensitivity analysis of continuous distillation considering the interaction of parameter uncertainty with feed variability
AU - Gozálvez-Zafrilla, José M.
AU - García-Díaz, J. Carlos
AU - Santafé-Moros, Asunción
N1 - Publisher Copyright:
© 2021 Elsevier Ltd
PY - 2021/5/18
Y1 - 2021/5/18
N2 - In this work, uncertainty and sensitivity analyses were applied to study the joint effects of model parameter uncertainty and feed variability on the response of a computational code for methanol–water continuous distillation. First, model parameter uncertainty (liquid–vapour equilibrium (VLE), enthalpy and tray efficiency) was characterised using existing experimental data. Afterwards, three tower configurations working at two operational modes (fixed product composition and fixed operation conditions) were studied at three feed variability levels. Morris analysis revealed the high importance of the VLE and efficiency-related factors. Sobol sensitivity analysis determined with more precision the sensitivity of the response to the parameters and detected non-linear effects and interactions. The Monte Carlo propagation method allowed obtaining the uncertainty margins as a function of feed variability. The results showed high impact of the model parameter uncertainty and encourage the use of the methods shown to obtain robust designs and quantify simulation accuracy.
AB - In this work, uncertainty and sensitivity analyses were applied to study the joint effects of model parameter uncertainty and feed variability on the response of a computational code for methanol–water continuous distillation. First, model parameter uncertainty (liquid–vapour equilibrium (VLE), enthalpy and tray efficiency) was characterised using existing experimental data. Afterwards, three tower configurations working at two operational modes (fixed product composition and fixed operation conditions) were studied at three feed variability levels. Morris analysis revealed the high importance of the VLE and efficiency-related factors. Sobol sensitivity analysis determined with more precision the sensitivity of the response to the parameters and detected non-linear effects and interactions. The Monte Carlo propagation method allowed obtaining the uncertainty margins as a function of feed variability. The results showed high impact of the model parameter uncertainty and encourage the use of the methods shown to obtain robust designs and quantify simulation accuracy.
KW - Distillation
KW - Morris analysis
KW - Sensitivity
KW - Sobol method
KW - Uncertainty
UR - http://www.scopus.com/inward/record.url?scp=85101154169&partnerID=8YFLogxK
U2 - 10.1016/j.ces.2021.116509
DO - 10.1016/j.ces.2021.116509
M3 - Article
AN - SCOPUS:85101154169
SN - 0009-2509
VL - 235
JO - Chemical Engineering Science
JF - Chemical Engineering Science
M1 - 116509
ER -