Abstract
A computer program, capable of carrying out the mathematical modelling and optimization of multi effect evaporation (MEE) systems is developed in the scope of this study. C# programming language is used in the development of the computer program. A Particle Swarm Optimization (PSO) based algorithm is developed and hybridized with a Levenberg-Marquardt (LM) based algorithm. A computer program interface is developed in .NET platform for the user to give inputs such as feed and product streams flowrate and concetration. The optimization results is represented through this interface. Concentrating the sodium hydroxide content in the wastewater of the mercerization process is selected as the sample case.
Highlights
Evaporation is the process of concentrating an aqeuous solution by vaporizing the water content
A computer program, capable of carrying out the mathematical modelling and optimization of multi effect evaporation (MEE) systems is developed in the scope of this study
In a MEE system, the solution is evaporated using saturated steam in the first effect and the vapour which is the outlet of each effect (Vi) is used as heating medium in the following effects
Summary
Evaporation is the process of concentrating an aqeuous solution by vaporizing the water content. In a MEE system, the solution is evaporated using saturated steam in the first effect and the vapour which is the outlet of each effect (Vi) is used as heating medium in the following effects. This design provides a huge steam economy. Backward feed sequence and preheating has a positive effect on evaporation economy through an equationoriented simulation model [1]. Correlations can be used to calculate temperature dependent properties such as enthalpy and heat capacity for simplification [5] These simplifications do not effect the selection of optimal feed sequence. Developing models and simultaneous solution algorithm which comprises the complete complex structure of the multi effect evaporation systems is challenging and further research in this field will aim the energy saving weighted optimization [7]
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