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Dual response surface optimization with hard‐to‐control variables for sustainable gasifier performance
Author(s) -
Coetzer R. L. J.,
Rossouw R. F.,
Lin D. K. J.
Publication year - 2008
Publication title -
journal of the royal statistical society: series c (applied statistics)
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.205
H-Index - 72
eISSN - 1467-9876
pISSN - 0035-9254
DOI - 10.1111/j.1467-9876.2008.00631.x
Subject(s) - wood gas generator , robustness (evolution) , response surface methodology , control variable , coal , process engineering , particle size , mathematical optimization , computer science , environmental science , engineering , mathematics , statistics , waste management , chemistry , biochemistry , gene , chemical engineering
Summary. Dual response surface optimization of the Sasol–Lurgi fixed bed dry bottom gasification process was carried out by performing response surface modelling and robustness studies on the process variables of interest from a specially equipped full‐scale test gasifier. Coal particle size distribution and coal composition are considered as hard‐to‐control variables during normal operation. The paper discusses the application of statistical robustness studies as a method for determining the optimal settings of process variables that might be hard to control during normal operation. Several dual response surface strategies are evaluated for determining the optimal process variable conditions. It is shown that a narrower particle size distribution is optimal for maximizing gasification performance which is robust against the variability in coal composition.