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    杨俊宇, 李超, 代正华, 于广锁, 王辅臣. 基于停留时间分布的气流床气化炉通用网络模型[J]. 华东理工大学学报(自然科学版), 2015, (3): 287-292.
    引用本文: 杨俊宇, 李超, 代正华, 于广锁, 王辅臣. 基于停留时间分布的气流床气化炉通用网络模型[J]. 华东理工大学学报(自然科学版), 2015, (3): 287-292.
    YANG Jun-yu, LI Chao, DAI Zheng-hua, YU Guang-suo, WANG Fu-chen. General Network Model Based on the Residence Time Distribution for Entrained Flow Gasifier[J]. Journal of East China University of Science and Technology, 2015, (3): 287-292.
    Citation: YANG Jun-yu, LI Chao, DAI Zheng-hua, YU Guang-suo, WANG Fu-chen. General Network Model Based on the Residence Time Distribution for Entrained Flow Gasifier[J]. Journal of East China University of Science and Technology, 2015, (3): 287-292.

    基于停留时间分布的气流床气化炉通用网络模型

    General Network Model Based on the Residence Time Distribution for Entrained Flow Gasifier

    • 摘要: 气流床气化炉的数学模型是气化装置设计和操作优化的基础,气固停留时间分布是影响气流床气化炉出口组成和碳转化率的关键因素。以气固停留时间分布为依据,结合反应动力学建立气流床气化炉的通用网络模型,模拟值与工业值吻合。对于神府煤,考察了氧煤比改变对气化结果的影响,结果表明:最佳氧煤比(氧气体积与煤(干基)质量之比)期望值约为0.655 Nm3/kg,生产中为保证液态排渣,氧煤比应控制在0.663 Nm3/kg左右。该通用网络模型计算速度快,适用于建立气化炉的动态模型。

       

      Abstract: Mathematical model of entrained flow gasifier is the foundation of the gasification plant design and the operation optimization. The residence time distributions (RTD) of gas and particles are the key factors of the gasifier, which have significant effects on the syngas composition and carbon conversion. In this study, a general network model (GNM) was established based on the RTD of gas and particles and the detailed reaction kinetics. The simulation results agree well with the industrial data. The effects of oxygen coal ratio (ratio of oxygen volume to coal (dry basis mass)) on gasification performance were investigated for Shenfu coal. The simulation results indicate that the best theoretical oxygen coal ratio is approximate 0.655 Nm3/kg. To ensure discharging slags in liquid, the optimal oxygen coal ratio in operation should be controlled in a value around 0.663 Nm3/kg. The GNM can get result in acceptable computing time, which is suitable for the dynamic modeling.

       

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