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

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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.

Keywords: Desirability functions; Dual response surface; Gasification; Robustness studies

Document Type: Research Article


Affiliations: 1: Sasol Technology Research and Development, Sasolburg, South Africa 2: Pennsylvania State University, University Park, USA

Publication date: December 1, 2008


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