文献类型：期刊文献

英文题名：Multiobjective Optimization of a Novel Hybrid Triply Periodic Minimal Surface Structural Catalyst and Reactors for On-Board Methanol Steam Reforming

作者：Li, Chuandong[1]; Yu, Xinhai[1]; Yu, Wei[2]; Li, Bo[3]; Tu, Shan-Tung[1]

机构：[1] Key Laboratory of Pressure Systems and Safety [MOE], School of Mechanical and Power Engineering, East China University of Science and Technology, Shanghai, 200237, China; [2] School of Mathematics, East China University of Science and Technology, Shanghai, 200237, China; [3] Additive Manufacturing and Intelligent Equipment Research Institute, School of Mechanical and Power Engineering, East China University of Science and Technology, Shanghai, 200237, China

年份：2024

外文期刊名：SSRN

收录：EI(收录号：20240270209)

语种：英文

外文关键词：Catalysts - Computational fluid dynamics - Drops - Gaussian distribution - Gaussian noise (electronic) - Genetic algorithms - Methanol - Multiobjective optimization - Pressure drop - Shape optimization - Steam reforming

摘要：Triply periodic minimal surface (TPMS)-structured catalysts and reactors (SCRs) for vehicular methanol steam reforming (MSR) have garnered widespread attention due to their large surface area-to-volume ratio, high porosity, and excellent mechanical properties. However, current TPMS SCR designs are limited to singular periodic structures, and selection of their specific target requirements is random. In this study, a controllable-structure hybrid triply periodic minimal surface (H-TPMS) SCR for vehicular MSR with various targeting requirements was developed using 3D printing. Multiobjective optimization was conducted on the hybrid parameters λG and λD, cell size Ta, and volume density Tc using multioutput Gaussian processes (MOGPs) combined with the fast nondominated sorting genetic algorithm (NSGA-II). The results indicated a positive correlation between methanol conversion and CO selectivity in H-TPMSs. With the same Ta and Tc parameters, the uniform H-TPMS showed greater methanol conversion and CO selectivity than the other structures. Although the Schwarz-P-dominated H-TPMS had a lower methanol conversion, it exhibited an excellent low pressure drop. According to the importance-based evaluation metrics α1=0.5, α2=0.2, the global optimum in the Pareto front had a conversion rate of 97.8%, a CO selectivity of 1.78%, and a pressure drop of 14.6 Pa, corresponding to geometric parameters of [0.43 0.4 3.2 40.1], which are characteristic of uniform H-TPMSs. CFD simulations demonstrated that the intricate helical flow paths in hybrid structures promote gas transport and diffusion. Experimental validation showed that the CFD simulations and the established MOGP model had an accuracy less than 3%. This CFD data-driven rapid modeling and optimization strategy provides a reliable design basis for the development of TPMS SCRs. ? 2024, The Authors. All rights reserved.