A trust region framework for heat exchanger network synthesis with detailed individual heat exchanger designs

We develop a trust region filter strategy for simultaneous optimal design of heat exchanger networks that includes detailed shell-and-tube exchangers. The first solves mixed-integer nonlinear programming (MINLP) formulation with shortcut models to generate candidate network topologies, which are then used in non-isothermal mixing (NLP) suboptimization embedded using modified (TRF) algorithm. An integer cut based is bound the solutions from MINLP and NLP aids convergence solution overall problem. Under assumptions, TRF can guarantee near presented thus able find designs on optimization topology mass energy balances, together optimization, including number shell tube passes, pressure drops, tubes, lengths, etc. proposed tested three literature case studies their results compared previous showcase its performance.