Abstract
The performance of cascade dual-catalyst systems is highly related to the catalysts spatial arrangement within the bed layers. However, optimization tools for the cascade dual-catalyst layer arrangements are still in need of development. In this study, an optimization framework based on genetic algorithms (GA) and artificial neural networks (ANN) is developed for optimization while explore effects of side reaction on optimized arrangement. Further, a new descriptor as known as delta switch (DS) is introduced. Isolated analysis of the effects of the two types of side reactions shows that the solely side reaction on S0 results in a repeated S0-S1-S0 structure, while the introduce of side reactions on S1 disrupts this structural regularity and reduces the optimal length of the bed layer. Based on DS patterns, a simplified cascade dual-catalysts spatial optimization framework (≤3 layers) is employed, achieving ≥ 95 % performance of original GA.
Published Version
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call