Systematic Approach For Sharp Separation Network

Document Type : Full-length article

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Department of refining and petrochemical engineering, faculty of petroleum and mining engineering, Suez university, Egypt

Abstract

This work developed a multi-object approach for synthesis the sharp separation network which used to separate a large number of components in a mixture that was difficult to separate because it was difficult to select the appropriate separation sequence from the extensive number of potential splits. The use of three expert rules to qualify the estimated mass load, the difference in boiling point, and the relative volatility forms the basis of the synthesis algorithm.There are two fuzzy analogical gates in use (symmetric and asymmetric). The normalized predicted mass load and the normalized relative volatility are the inputs for the symmetric gate (AND gate). The output of the AND gate and the normalization of the boiling point difference are the inputs for the asymmetric gate (INVOKE gate). for separation issues with many components, the size is huge and the amount of decision variables is enormous.
So, the suggested method can be carried out manually and is easy to use for large number of components. Several illustrative examples using existing fuzzy analogical gate are provided as examples of the suggested method's success

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