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


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


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. Copyright Journal compilation (c) 2008 Royal Statistical Society.

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  • R. L. J. Coetzer & R. F. Rossouw & D. K. J. Lin, 2008. "Dual response surface optimization with hard-to-control variables for sustainable gasifier performance," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 57(5), pages 567-587.
  • Handle: RePEc:bla:jorssc:v:57:y:2008:i:5:p:567-587

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    References listed on IDEAS

    1. Kim, Kwang-Jae & Lin, Dennis K.J., 2006. "Optimization of multiple responses considering both location and dispersion effects," European Journal of Operational Research, Elsevier, vol. 169(1), pages 133-145, February.
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