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Heat exchanger network synthesis with detailed exchanger designs—2. Hybrid optimization strategy for synthesis of heat exchanger networks

Kazi, Saif R., Short, Michael, Isafiade, Adeniyi J. and Biegler, Lorenz T. (2020) Heat exchanger network synthesis with detailed exchanger designs—2. Hybrid optimization strategy for synthesis of heat exchanger networks AIChE Journal.

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Abstract

We propose a new strategy to synthesize heat exchanger networks with detailed designs of individual heat exchangers. The proposed strategy uses a multistep approach by first obtaining a heat exchanger network topology through solving a modified version of the mixed integer nonlinear programming (MINLP) stage‐wise superstructure of Yee and Grossmann, which includes a smoothed LMTD approximation and pressure drops. In a second nonlinear programming (NLP) suboptimization step, we allow for nonisothermal mixing to solve problems with or without exchanger bypasses. The selected heat exchangers along with the mass and energy balances obtained are then used to design the network with detailed exchanger designs through solving a sequence of NLPs for individual heat exchanger designs. The NLPs are based on the detailed discretized optimization models of Kazi et al., which solve quickly and reliably to obtain heat exchangers based on rigorous, first‐principles derived coupled differential equations. These models solve a differential algebraic equation system and do not rely on usual assumptions associated with other heuristic‐based exchanger design methods, such as log mean temperature difference and FT correction factors. These detailed exchanger designs are then used to update the network optimization model through sets of correction factors on heat exchanger area, number of shells, heat transfer coefficients, and pressure drops of each exchanger design, in a method based on that of Short et al. The method solves reliably, guaranteeing feasible exchangers for every potential network generated by the shortcut models, through validation with rigorous heat exchanger models at every iteration. In addition, the method does not increase the nonlinearity of the MINLP model, nor does it require any manual intervention or initialization from the user. Three examples are solved and the results are compared to those obtained in the literature.

Item Type: Article
Divisions : Faculty of Engineering and Physical Sciences > Chemical and Process Engineering
Authors :
NameEmailORCID
Kazi, Saif R.
Short, Michaelm.short@surrey.ac.uk
Isafiade, Adeniyi J.
Biegler, Lorenz T.
Date : 25 September 2020
DOI : 10.1002/aic.17057
Copyright Disclaimer : © 2020 American Institute of Chemical Engineers
Uncontrolled Keywords : Heat transfer; Optimization; Process; Process synthesis; Simulation
Depositing User : Clive Harris
Date Deposited : 06 Oct 2020 11:15
Last Modified : 06 Oct 2020 11:15
URI: http://epubs.surrey.ac.uk/id/eprint/858669

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