ABSTRACT - Diwekar - 9613561 With the growing concern for the environment, it is necessary to enhance process simulation capabilities and to develop design tools that account for environmental factors in the design and synthesis of large-scale chemical processes. A major obstacle in the design and development of processes incorporating environmental control strategies involve uncertainties in some of the technical and economic parameters, which commonly lead to uncertainties in design, plant performance and cost estimates. Incorporating environmental concerns in the design is a multi-objective problem satisfying a number of measures and constraints such as controllability, safety, compliance with regulations, cost and risk. A conceptual design of any chemical process involves the identification of an optimal flowsheet structure, commonly called optimal design configuration, obtained typically form a large number of alternatives constituting the "superstructure". In fact, synthesis, design, and optimization of large-scale processes involving uncertainties often requires considerable computational effort. This work and validation of efficient algorithms for stochastic modeling, stochastic optimization and programming, multi-objective optimization, and synthesis under uncertainty. The overall objective is to advance the state-of-the-art in the4 area of process design for environmental considerations by (a) providing an integrated assessment framework tool which can be used to insure that environmental issues are fully addressed in all phases of process engineering activities from synthesis to design to operations; and (b) developing improved algorithms for stochastic modeling, stochastic optimization, multi-objective optimization which will enhance the applicability of the framework for large scale complex problems. Real world problems in conjunction with participating industries will be used as test beds for these techniques. The methodology developed will be applied to analyze compl ex process flowsheets and is expected to provide insights into process feasibility based on environmental considerations and optimal design, plant performance and uncertainty issues.
