KMITL

Permanent URI for this communityhttps://dspace.kmitl.ac.th/handle/kmitl/1

Browse

Settings

Author: search.filters.author.Phongpipatpong, M.Subject: search.filters.subject.MINLP

Search Results

Now showing 1 - 2 of 2
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Publication,
    Synthesis of rice processing plants. I. Development of simplified models
    (2003-10-01)
    Phongpipatpong, M.
    ;
    Douglas, P. L.
    This article, the first of three articles on the synthesis of rice processing plants, focuses on the development of simplified mathematical models necessary for use in optimizing rice processing plants. The second concentrates on the optimal synthesis of a rice plant and the third on the sensitivity of the optimization to uncertainty in model parameters. Existing models for rice processing unit operations are not suitable for flowsheet optimization and new models need to be developed to overcome numerical difficulties that occur in optimization applications, specifically in mixed integer nonlinear programming (MINLP) applications. Simplified models of the drying, cooling, and tempering units are developed. In addition head rice yield models, used as a quality indicator, energy consumption, and economic models were also developed. Naturally, the new models exhibit some mismatch with respect to the existing models from which they were developed. However, a sensitivity analysis, presented in Part III, has shown that the optimal flowsheet structure was not sensitive to a lack of fit between the simplified and complex models. The simplified models were found adequate to be appropriate for use at the synthesis stage.
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Publication,
    Synthesis of rice processing plants. III. Sensitivity analysis
    (2003-10-01)
    Phongpipatpong, M.
    ;
    Douglas, P. L.
    An optimal process flowsheet for a rice processing plant has been developed. The optimization problem was formulated as a Mixed-Integer Nonlinear Programme, MINLP, consisting of a vector of binary and continuous variables. The set of optimum decision variables including the number of drying, cooling, and tempering units, temperature and relative humidity of drying air, drying time, cooling time, and tempering time were determined as the solution of the MINLP problem. Six objective functions were investigated as performance criteria. A sensitivity analysis of each model parameter was conducted to determine its influence on the optimal flowsheet. The MINLP approach is an efficient tool for optimization and the simplified models were adequate for use at the synthesis stage. The solution is insensitive to uncertainty in the models. However, due to the nonconvex nature of MINLPs, the solution was found to depend on the initial starting values, especially for the maximum profit flowsheet.