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基于颗粒堆积床模型的线性菲涅尔式太阳能甲醇重整制氢系统综合性能研究

Translated title of the contribution: Study on Comprehensive Performance of Linear Fresnel Solar Methanol Reforming Hydrogen Production System Based on Packed Bed Model
  • Xi'an Jiaotong University
  • Nanjing Institute of Future Energy System

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

In this paper, a three-dimensional numerical model of the linear Fresnel solar receiver/ reactor (LFSRR) photo-thermal-chemical reaction process is established. The miniature LFSRR packed bed model is studied to explore the effects of the typical external factor (e.g., the solar heat flux distribution) and internal factor (e.g., the catalyst particle radius) on the comprehensive performance of the fluid flow, heat transfer and thermochemical reaction of the LFSRR system. Firstly, the random packing bed model of catalyst particles was established based on the discrete element method. Secondly, the solar heat flux distribution was obtained based on the Monte Carlo ray tracing method and multi-objective optimization genetic algorithm. Then, the comprehensive performance of LFSRRs before optimization, after optimization and under the corresponding ideal condition was compared. Subsequently, the influence of the catalyst particle radius was further analyzed. It is found that the chemical reaction performance of the LFSRR system after optimization is close to ideal. Reducing the particle radius can also promote the chemical reaction, but it will increase the flow resistance. There could be a tradeoff between chemical reaction performance, flow resistance and sintering temperature limit for optimizing the particle size.

Translated title of the contributionStudy on Comprehensive Performance of Linear Fresnel Solar Methanol Reforming Hydrogen Production System Based on Packed Bed Model
Original languageChinese (Traditional)
Pages (from-to)497-504
Number of pages8
JournalKung Cheng Je Wu Li Hsueh Pao/Journal of Engineering Thermophysics
Volume44
Issue number2
StatePublished - 1 Feb 2023

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