Process synthesis uncertainty

Classical process synthesis consists of the synthesis of the alternatives, their analysis and final evaluation. Hurme and Jarvelainen (1995) have presented a combined process synthesis and simulation system consisting of an interactive rule-based system which is used for generating process alternatives (Fig. 10). The process alternatives are simulated, costed and evaluated through profitability analysis. The developed system concept combines process synthesis, simulation and costing with uncertainty estimation. 

Acevedo, J. and Pistikopoulos, E.N. (1998) Stochastic optimization based algorithms for process synthesis under uncertainty. Computers e[ Chemical Engineering, 22, 647. 

Optimal process synthesis Two problems (a) chemical process optimization for maximization of net present value (NPV) while minimizing uncertainty in the future demand of two products, and (b) utility system optimization for minimization of both total annual cost and CO2 emission. Multi-Criteria Branch and Bound (MCBB) Algorithm The existing MCBB algorithm was modified to increase speed, reliability and suitahility for a wide range of applications. Mavrotas and Diakoulaki (2005)... 

In the optimisation search of the chemical processes, many of the key parameters are only partially known where there is significant uncertainty regarding their future values. Furthermore, there are inherently uncertainties associated with both the plant model as well as the environmental model. Designing chemical processes under uncertainty has been a common class of problems in synthesis and design and has received considerable attention in recent years. A natural extension in the formulation proposed in this thesis is the incorporation/addition of uncertainty in the formulation of the optimisation problem. This, however, would naturally increase the computational complexity as the presence of uncertainty would lead to semi-infinite optimisation problems. 

Within each of the three general approaches toward process synthesis, key decisions are made about the flowsheet design that have a bearing on the operability characteristics of the plant. For example, in a hierarchical procedure (Ref. 6) we will make decisions about whether the plant is batch or continuous, what types of reactors are used, how material is recycled, what methods and sequences of separation are employed, how much energy integration is involved, etc. In a thermodynamic pinch analysis, we typically start with some flowsheet information, but we must then decide what streams or units to include in the analysis, what level of utilities are involved, what thermodynamic targets are used, etc. In an optimization approach, we must decide the scope of the superstructure to use, what physical data to include, what constraints to apply, what disturbances or uncertainties to consider, what objective function to employ, etc (Ref. 7). 

The ITIES with an adsorbed monolayer of surfactant has been studied as a model system of the interface between microphases in a bicontinuous microemulsion [39]. This latter system has important applications in electrochemical synthesis and catalysis [88-92]. Quantitative measurements of the kinetics of electrochemical processes in microemulsions are difficult to perform directly, due to uncertainties in the area over which the organic and aqueous reactants contact. The SECM feedback mode allowed the rate of catalytic reduction of tra 5-l,2-dibromocyclohexane in benzonitrile by the Co(I) form of vitamin B12, generated electrochemically in an aqueous phase to be measured as a function of interfacial potential drop and adsorbed surfactants [39]. It was found that the reaction at the ITIES could not be interpreted as a simple second-order process. In the absence of surfactant at the ITIES the overall rate of the interfacial reaction was virtually independent of the potential drop across the interface and a similar rate constant was obtained when a cationic surfactant (didodecyldimethylammonium bromide) was adsorbed at the ITIES. In contrast a threefold decrease in the rate constant was observed when an anionic surfactant (dihexadecyl phosphate) was used. 

Since the student will build neither, and since the professor probably cannot answer certain questions because of secrecy agreements or lack of knowledge, the student must learn to live with uncertainty. He will also learn how to defend his own views, and how to present material so as to obtain a favorable response from others. These learning experiences, coupled with exposure to the process of design as distinct from that of analysis and synthesis, are the major purposes of an introductory design course. 

In recent decades we have not only been using the materials provided by the earth, but making new matter new elements (by nuclear fission) and new chemicals (by organic synthesis). This new matter takes part in the processes of the earth it enters our bodies, soils, the water and air, where it interacts with the natural chemicals it encounters, transforming them and itself. Its novelty means that the processes in which it takes part can be considered to be new natural processes (Arendt, 1968, p58). The complexity of the environments in which these take place means that there is great uncertainty as to their outcomes. 

Nishida, N., Liu, Y.A. and Ichikawa, A., "Studies in Chemical Process Design and Synthesis II. Optimal Synthesis of Dynamic Process Systems with Uncertainty," AiChE J. Vol. 22, No. 3, pp 539-550, May 1976. 

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