By David H. West and Gregory Yablonsky (Eds.)

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M. Kaganovich et al. this constraint solution to problem (76)–(80) shifts from x~ ext to xext (inter­ section of the straight line kx2 = c with the boundary of the unattainability zone near the vertex A3). It is seen by sight that xext is somewhat distant from the vertex A3 (the point of maximum concentration of x3 with the only constraint of the material balance) than ~x ext and hence the mole content of the target product in xext is lower than in ~x ext . Even very short interpretation of the problem allows a most important advantage of MEIS to be indicated, namely its capability to choose and determine the value of the subjective parameter of order (Klimontovich, 1997) of the modeled system.

Figure 9 gives an insight into the potential objects of studies by model (58)–(65). It shows a scheme of the main double-pipe water heat network of the heat supply system for a large urban district. The optimal synthesis problem for this network consists in the determination of flow distribution 1 2 3 4 5 Figure 9 The scheme of heat supply system in a “double-line” representation 1, 2—sections of supply and return pipelines, 3—heat source, 4—nodes of consumer connection; 5—pumping station. M. Kaganovich et al.

1993). Let us consider a process during which some initial composition a should be used to get the max­ imum quantity of products b. Let the point y in Figure 7 denote an initial state of the reactive system. The point m corresponds to the maximum thermodynamically admissible concentration of b. The points l and k represent states of a chemical system with the use of catalysts that provide Equilibrium Thermodynamic Modeling of Dissipative Macroscopic Systems 41 x cmat l y • x eq m x bmat k x dmat Figure 7 Catalyst impact on the attainable state.

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