Title page for ETD etd-10252004-163127


Type of Document Dissertation
Author Xu, Aimin
Author's Email Address axu1@lsu.edu
URN etd-10252004-163127
Title Chemical Production Complex Optimization, Pollution Reduction and Sustainable Development
Degree Doctor of Philosophy (Ph.D.)
Department Chemical Engineering
Advisory Committee
Advisor Name Title
Ralph W. Pike Committee Chair
Armando B. Corripio Committee Member
Arthur M. Sterling Committee Member
F. Carl Knopf Committee Member
Ralph J. Portier Dean's Representative
Keywords
  • pollution reduction
  • chemical complex analysis system
  • sustainable development
  • sensitivity analysis
  • chemical production complex optimization
Date of Defense 2004-09-07
Availability unrestricted
Abstract
The objective of this research is to propose, develop and demonstrate chemical production complex optimization to determine the optimal configuration of chemical plants in a superstructure of possible plants. The Chemical Complex Analysis System is a new methodology that has been developed to determine the best configuration of plants in a chemical production complex based on the AIChE Total Cost Assessment (TCA) for economic, energy, environmental and sustainable costs.

All new, energy-efficient, and environmentally acceptable plants using greenhouse gases that can produce potentially commercial products designed with HYSYS were integrated into the chemical complex using the System. The optimum configuration of plants was determined based on the triple bottom line that includes sales, economic, environmental and sustainable costs using the System. From eighteen new processes in the superstructure, the optimum structure had seven potentially new processes including acetic acid, graphite, formic acid, methylamines, propylene and synthesis gas production. With the additional plants in the optimal structure the triple bottom line increased from $343 to $506 million per year and energy increased from 2,150 to 5,791 TJ/year.

Multicriteria optimization has been used with Monte Carlo simulation to determine the sensitivity of the optimal structure of a chemical production complex to prices, costs, and sustainable credits/cost. In essence, for each Pareto optimal solution, there is a cumulative probability distribution function that is the probability as a function of the triple bottom line. This information provides a quantitative assessment of the optimum profit versus sustainable credits/cost, and the risk (probability) that the triple bottom line will meet expectations.

The capabilities of the System have been demonstrated, and this methodology could be applied to other chemical production complexes in the world for reduced emissions and energy savings. With this System, engineers will have a new capability to consider projects in depths significantly beyond current capabilities. They will be able to convert their company’s goals and capital into viable projects that meet economic, environmental and sustainable requirements.

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