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Simulation and optimization of rice husk gasification using intrinsic reaction rate based CFD model

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  • Gao, Xiaoyan
  • Xu, Fei
  • Bao, Fubing
  • Tu, Chengxu
  • Zhang, Yaning
  • Wang, Yingying
  • Yang, Yang
  • Li, Bingxi

Abstract

Entrained flow gasification processes of rice husk were simulated and optimized in this study using an intrinsic reaction rate based CFD model. A detailed sensitivity analysis was conducted to characterize the effects of operation parameters on the gas composition, gas production and cold gas efficiency. Gasification temperature, average particle diameter, ER (equivalence ratio) and CO2/biomass (mass ratio of carbon dioxide to biomass) are important operation parameters affecting the gasification process, and they were investigated in this study. Three-objective optimization of rice husk gasification was performed base on the response surface methodology (RSM) to maximize CO content, gas production, and cold gas efficiency, and the Pareto optimal solutions were obtained from NSGA-II (non-dominated sorting genetic algorithm) to instruct gasification operation. With standard TOPSIS (technique for order preference by similarity to ideal situation), the optimal solutions with CO concentration of 25.15%, gas production of 1.96 Nm3/kg and cold gas efficiency of 65.34% were obtained.

Suggested Citation

  • Gao, Xiaoyan & Xu, Fei & Bao, Fubing & Tu, Chengxu & Zhang, Yaning & Wang, Yingying & Yang, Yang & Li, Bingxi, 2019. "Simulation and optimization of rice husk gasification using intrinsic reaction rate based CFD model," Renewable Energy, Elsevier, vol. 139(C), pages 611-620.
    • Handle: RePEc:eee:renene:v:139:y:2019:i:c:p:611-620
    DOI: 10.1016/j.renene.2019.02.108
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    References listed on IDEAS

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    1. Couto, Nuno & Silva, Valter & Monteiro, Eliseu & Brito, Paulo & Rouboa, Abel, 2015. "Using an Eulerian-granular 2-D multiphase CFD model to simulate oxygen air enriched gasification of agroindustrial residues," Renewable Energy, Elsevier, vol. 77(C), pages 174-181.
    2. Jack P. C. Kleijnen, 2015. "Response Surface Methodology," International Series in Operations Research & Management Science, in: Michael C Fu (ed.), Handbook of Simulation Optimization, edition 127, chapter 0, pages 81-104, Springer.
    3. Couto, Nuno & Silva, Valter & Rouboa, Abel, 2016. "Municipal solid waste gasification in semi-industrial conditions using air-CO2 mixtures," Energy, Elsevier, vol. 104(C), pages 42-52.
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    1. Tavakoli, Navid & Khoshkenar, Payam & Pourfayaz, Fathollah, 2024. "A combined approach-based techno-economic-environmental multi-optimization of a hydrogen generation system through waste biomass air-steam gasification," Renewable Energy, Elsevier, vol. 225(C).
    2. Sivabalan Kaniapan & Jagadeesh Pasupuleti & Kartikeyan Patma Nesan & Haris Nalakath Abubackar & Hadiza Aminu Umar & Temidayo Lekan Oladosu & Segun R. Bello & Eldon R. Rene, 2022. "A Review of the Sustainable Utilization of Rice Residues for Bioenergy Conversion Using Different Valorization Techniques, Their Challenges, and Techno-Economic Assessment," IJERPH, MDPI, vol. 19(6), pages 1-30, March.
    3. Yepes Maya, Diego Mauricio & Silva Lora, Electo Eduardo & Andrade, Rubenildo Vieira & Ratner, Albert & Martínez Angel, Juan Daniel, 2021. "Biomass gasification using mixtures of air, saturated steam, and oxygen in a two-stage downdraft gasifier. Assessment using a CFD modeling approach," Renewable Energy, Elsevier, vol. 177(C), pages 1014-1030.

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