TY - JOUR
T1 - Multi-objective topology optimization and flow characteristics study of the microfluidic reactor
AU - Wang, Jiahao
AU - Wang, Yue
AU - Ma, Lie
AU - Liu, Xiaomin
N1 - Publisher Copyright:
© 2022, Akadémiai Kiadó, Budapest, Hungary.
PY - 2022/10
Y1 - 2022/10
N2 - An improved topology optimization method is proposed to optimize the performance and structure of the packed bed microfluidic reactor (PBMR). Dimensionless general scaling factor (GSF) is established to fully reflect the multi-physical properties of first-order isothermal catalytic reaction. Reaction performance and the flow loss are combined into a multi-objective function. Pareto algorithm is developed by introducing the weighted-sum method with weight factors ω, so Pareto frontier solution composed of optimal solutions under different ω is obtained to reveal the trade-off relationship between single-objective functions. Material density controlled by the improved polynomial function is adopted as the design variable to control the catalyst distribution. Gradient information of the design variable is updated by using the adjoint-based sensitivity analysis method, and Helmholtz filter method is adopted to solve the problems of grayscale, unclear interface, and channel fracture. The results demonstrate that the GSF can reflect the scaling behavior of the topology optimization reactor. Multi-objective functions under different ω are responded by changing the distribution of catalyst blocks and channel structure, which affects the diffusion and mixing of reactant. From the perspective of engineering application, this study provides a general and efficient new method for developing high-performance PBMRs.
AB - An improved topology optimization method is proposed to optimize the performance and structure of the packed bed microfluidic reactor (PBMR). Dimensionless general scaling factor (GSF) is established to fully reflect the multi-physical properties of first-order isothermal catalytic reaction. Reaction performance and the flow loss are combined into a multi-objective function. Pareto algorithm is developed by introducing the weighted-sum method with weight factors ω, so Pareto frontier solution composed of optimal solutions under different ω is obtained to reveal the trade-off relationship between single-objective functions. Material density controlled by the improved polynomial function is adopted as the design variable to control the catalyst distribution. Gradient information of the design variable is updated by using the adjoint-based sensitivity analysis method, and Helmholtz filter method is adopted to solve the problems of grayscale, unclear interface, and channel fracture. The results demonstrate that the GSF can reflect the scaling behavior of the topology optimization reactor. Multi-objective functions under different ω are responded by changing the distribution of catalyst blocks and channel structure, which affects the diffusion and mixing of reactant. From the perspective of engineering application, this study provides a general and efficient new method for developing high-performance PBMRs.
KW - Microfluidic
KW - Multi-objective optimization algorithm
KW - Packed bed microfluidic reactor
KW - Reaction kinetic
KW - Topology optimization
UR - https://www.scopus.com/pages/publications/85133620293
U2 - 10.1007/s11144-022-02259-x
DO - 10.1007/s11144-022-02259-x
M3 - 文章
AN - SCOPUS:85133620293
SN - 1878-5190
VL - 135
SP - 2475
EP - 2501
JO - Reaction Kinetics, Mechanisms and Catalysis
JF - Reaction Kinetics, Mechanisms and Catalysis
IS - 5
ER -