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The Study On Approach Of Carbon 5 Separation System Synthesis Optimization

Posted on:2003-07-25Degree:MasterType:Thesis
Country:ChinaCandidate:Y M WangFull Text:PDF
GTID:2121360065956068Subject:Chemical Engineering
Abstract/Summary:PDF Full Text Request
Separation process synthesis is a manipulation to deal with mixture that can separate mixture to different output with the minimum capital cost and energy consumption. And it is always used in the pretreatment of material, the purge of product, the purification of product and the disposal of scrap.Carbon 5 separation unit is a difficult separation system because of the tiny difference between the boiling point of the components. In this paper, we investigate the characteristic of the system based on the alteration of the system in a factory. The main work of this paper can be summarized into four points as follows:1. Two different projects to simulate the Carbon 5 separation unit using the simulator ASPEN PLUS and Pro/II with the conventional distillation process were actualized. These projects can satisfy the requirements of separation. Comparing with the primary project, the two projects have better purification and recovery, but the heat load is some bigger.2. The operational performance and the energy saving effects of the thermally coupled distillation was simulated and analyzed with the Carbon 5 separation unit. Applying the thermally coupled distillation, the extent of energy saving is above 20% comparing with the conventional distillation process according to the separation requirements.3. Mathematical model was constructed with artificial neural network based on the simulation results with Pro/II. The model can simulate the thermally coupled distillation rigorously.4. Modified genetic algorithm was used to optimize the artificial neural network model. With the proposed model and optimization algorithm, mathematical model can be calculated, decision variables and target'value can be reached automatically and quickly.
Keywords/Search Tags:Separation sequence, Thermally coupled distillation, Neural network, Genetic algorithm, Simulation, Optimization, ASPEN, Pro/Ⅱ
PDF Full Text Request
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