Process design for the environment: A multiobjective optimization framework

Increasing environmental awareness and regulations coupled with soaring waste management costs have created the need to incorporate more environmental considerations into the design and operation of industrial chemical processes. However, including environmental-economic objectives at any stage in process or product design poses a bewildering problem of multiple and conflicting objectives. Furthermore, environmental research in the last decade has resulted in new environmental control technologies, models for which are currently unavailable. This dissertation focuses on the multiobjective nature of the problems for evaluating the existing as well as new control technologies.;The modeling environments, which are considered, include the non-equilibrium model for the BACT of NOx removal process that is a complete transparent self-built model, the ASPEN chemical process simulator that is a semi-black-box model and a complete black-box model for heat exchanger design from the Heat Transfer Research Institute (HTRI).;The main contributions of the work include: (a) Modeling a new best available control technology (BACT) for NOx removal; (b) Defining system effectiveness in terms of economic and potential environmental impacts as a multiobjective framework; (c) Improving the efficiency and accuracy of the generalized framework by developing a new and efficient multiobjective optimization algorithm; (d) Promoting the market of this BACT control technology to reduce high level of NOx and SOx emissions by providing designs that are cost-effective and minimal environmental emissions through applying this new and efficient multiobjective optimization framework; (e) Augmenting traditional chemical process simulators such as ASPEN, with the capacity to design for environmentally friendly and economically effective processes by inclusion of the generalized waste reduction (WAR) algorithm and an efficient multiobjective framework under uncertainty in the ASPEN simulator; (f) Performing the first successful application of genetic algorithms to optimal design of heat exchanger with black-box models.