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Life Cycle Environmental Assessment of Polyethylene Process/Multiobjective Optimization

Shayannezhad، Amir Shayannezhad | 2023

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 55977 (06)
  4. University: Sharif University of Technology
  5. Department: Chemical and Petroleum Engineering
  6. Advisor(s): Farhadi, Fatollah; Vafa, Ehsan
  7. Abstract:
  8. The environmental impacts of chemical processes significantly affect the design of these processes and emphasize issues such as changing the reaction path, separation methods, thermal integration, and finally multi-objective optimization. Therefore, it is necessary to investigate the influence of environmental indicators in the design of chemical processes. The background system in this assessment includes two process units, olefin and polyolefin. Environmental impacts assessment has been carried out using the ReCiPe endpoint method (an efficient method for life cycle impact assessment that will be described in chapter 2) and these impacts have been determined in the form of damage to human health, ecosystem quality and natural resources. After determining the economic and environmental performance of the process in the base case, multi-objective optimization with economic and environmental objective functions has been performed in order to find the optimal operating conditions. To solve the optimization problem, by performing sensitivity analysis, two variables of the molar flow rate of ethane and naphtha feed input to the olefin plant have been selected as decision variables. As a result of multi-objective optimization using genetic algorithm, 18 operating points were obtained as Pareto optimum. Finally, using the "technique for order of preference by similarity to ideal solution" method (a method for selecting the final optimal solution that will be described in chapter 4), the molar flow rates of ethane and naphtha feed were selected as 133.16 and 251.15 kmol/hr, respectively, as optimal operating conditions. In this condition, the profitability of the process increases by 6% and the environmental damage increases by 5% compared to the base case
  9. Keywords:
  10. Multiobjective Optimization ; Genetic Algorithm ; Environmental Impact ; Olefin ; Polyolefins ; Pareto Improving ; Environmental Assessment

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