Reactor network synthesis energy integration

While synthesis strategies are well developed for energy integration and separation systems, relatively little work has been done in synthesizing reactor networks. This is due to the complex and nonlinear behavior of the reacting system, coupled with the combinatorial aspects inherent in all synthesis problems. This paper provides a brief summary of work to date in this area, focusing on targeting approaches for reactor network synthesis. 

Balakrishna, S. and Biegler, L.T., 1992b. Targeting strategies for the synthesis and energy integration of non-isothermal reactor networks. Industrial and Engineering Chemistry Research, 31(9), 2152. 

Balakrishna, S. and L. T. Biegler. Targeting Strategies for the Synthesis and Energy Integration of Nonisothermal Reactor Networks. Ind Eng Chem Res 31 2152-2164 (1992). 

The solution of the nonlinear optimization problem (PIO) gives us a lower bound on the objective function for the flowsheet. However, the cross-flow model may not be sufficient for the network, and we need to check for reactor extensions that improve our objective function beyond those available from the cross-flow reactor. We have already considered nonisothermal systems in the previous section. However, for simultaneous reactor energy synthesis, the dimensionality of the problem increases with each iteration of the algorithm in Fig. 8 because the heat effects in the reactor affect the heat integration of the process streams. Here, we check for CSTR extensions from the convex hull of the cross-flow reactor model, in much the same spirit as the illustration in Fig. 5, except that all the flowsheet constraints are included in each iteration. A CSTR extension to the convex hull of the cross-flow reactor constitutes the addition of the following terms to (PIO) in order to maximize (2) instead of [Pg.279]

Hierarchical Approach is a simple but powerful methodology for the synthesis of process flowsheets. It consists of a top-down analysis organised as a clearly defined sequence of tasks grouped in levels. Each level solves a fundamental problem as, number of plants, input/output structure, reactor design and recycle structure, separation system, energy integration, environmental analysis, safety and hazard analysis, and plantwide control. At each level, systematic methods can be applied for the synthesis of subsystems, as chemical reaction, separations, or heat exchangers network. 

This paper describes an integrated MINLP synthesis of overall process schemes using a combined synthesis / analysis approach. The synthesis is carried out by a multilevel-hierarchical MINLP optimization of the flexible superstructure, whilst the analysis is performed in an economic attainable region (EAR). The role of the MINLP synthesis step is to obtain a feasible and optimal process structure, and the role of the subsequent EAR analysis step is to verify the MINLP solution and to propose in the feedback loop, any profitable superstructure modifications for the next MINLP. The main objective of the integrated synthesis is to exploit interactions between the reactor network, separator network and the remaining part of the heat/energy integrated process scheme. 

We now provide a small process example to illustrate the simultaneous synthesis of reactor and energy networks. Here, we consider a reaction mechanism in the van de Vusse form, though with kinetic expressions different from those used above. The integrated flowsheet corresponding to the synthesis problem is shown in Fig. 12. 

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