Statler College of Engineering and Mineral Resources
West Virginia University
395 Evansdale Drive, PO Box 6102
Morgantown, WV 26506-6102
Uncertainties are inherent in energy and environmental systems. To design and control these systems, modeling framework such as chemical simulators are used. However, uncertainties in these systems can change the system design completely. This is specifically true, when modeling framework is extended to start with material design stage on one end and dynamics and control on the other end.
There are two kinds of uncertainties, namely, the static uncertainties and dynamic or time dependent uncertainties. In order to deal with static uncertainties, most of the time Monte Carlo sampling techniques are used. However, these techniques can be computationally expensive. In this talk, I present novel sampling techniques for dealing with static uncertainties or Monte Carlo Simulations. A case study of molecular simulations for predicting biological or toxicological properties of materials is presented to show the efficiency of these new techniques.
In computer aided molecular design (CAMD) methods group contribution methods are used. These methods have significant uncertainties in predicting properties. Therefore, for CAMD which is a reverse use of group contribution method, stochastic optimization methods are necessary. I will present some algorithms for stochastic optimization with applications to CAMD for environmentally friendly solvent selection and solvent recycling systems. At the process design stage of chemical and energy systems, water management and recycling depends on weather uncertainties and variability resulting in another type of stochastic optimization problem.
The concept of overall sustainability goes beyond process design and operation and brings in time dependent nature of the ecosystem and multi-disciplinary decision making. Optimal control methods and theories from financial literature can be useful in handling the time dependent uncertainties in this problem. Fourth case study which considers both static and dynamic uncertainties is related to sustainability with respect to mercury pollution. In order to circumvent the persistent, bioaccumulative effect of mercury, one has to take decisions at various levels of the cycle starting with greener power systems, industrial symbiosis through trading, and controlling the toxic methyl mercury formation in water bodies and accumulation in aquatic biota.