Dual response surface optimization with hard-to-control variables for sustainable gasifier performance

R. L.J. Coetzer, R. F. Rossouw, D. K.J. Lin

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

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.

Original languageEnglish (US)
Pages (from-to)567-587
Number of pages21
JournalJournal of the Royal Statistical Society. Series C: Applied Statistics
Volume57
Issue number5
DOIs
StatePublished - Dec 1 2008

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

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