Optimization of layer patterning on a plate fin heat exchanger considering abnormal operating conditions

Abstract

Cryogenic processes such as natural gas (NG) liquefaction or boil off gas (BOG) re-liquefaction systems require complex heat transfer networks to achieve high thermal efficiency. A plate fin heat exchanger (PFHE) is a kind of multi-stream heat exchanger that can make a system simpler while saving space and performing the complex network functions within a single piece of equipment. However, if the layer stacking pattern that determines the PFHE cross section temperature profile is inadequately composed, the equipment can be damaged by increased thermal stress between the layers. Layer stacking patterns have mainly been determined by inefficient trial and error methods, and only considered design operating conditions. The objective of this study is to obtain a highly efficient thermal layer stacking pattern in a design condition, while also lowering thermal stress in abnormal conditions, using a Genetic Algorithm (GA). The proposed GA in this study has a checking module that reduces iteration and saves calculation time. In addition, maximum metal temperature difference is used to evaluate fitness for considering abnormal conditions. According to the proposed algorithm, PFHE metal temperature profile improved about 30% compared to trial and error methods under design condition in a single mixed refrigerant LNG liquefaction process. The optimal layer stacking pattern is determined by a fitting function that applies temperature difference between plates under abnormal and design conditions.