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Fuzzy logic and bed-to-wall heat transfer in a large-scale CFBC

机译:大型CFBC中的模糊逻辑和床到墙传热

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Purpose - The purpose of this paper is to first present the key features of the fuzzy logic (FL) approach as a cost-effective technique in simulations of complex systems and then demonstrate the formulation and application of the method. Design/methodology/approach - The FL approach is used as an alternative method of data handling, considering the complexity of analytical and numerical procedures and high costs of empirical experiments. The distance from gas distributor, the temperature and the voidage of the bed, flue gas velocity and the load of the boiler are the input parameters, whereas the overall heat transfer coefficient for the membrane walls constitutes the output. Five overlapping sigmoid and constant linguistic terms are used to describe the input and the output data, respectively. The Takagi-Sugeno inference engine and the weighted average defuzzification methods are applied to determine the fuzzy and crisp output value, respectively. Findings - The performed FL model allows predicting the bed-to-wall heat transfer coefficient in a large-scale 670 t/h circulating fluidized bed (CFB) boiler. The local heat transfer coefficients evaluated using the developed model are in very good agreement with the data obtained in complementary investigations. Originality/value - The performed model constitutes an easy-to-use and functional tool. The new approach can be helpful for further research on the bed-to-wall heat transfer coefficient in the CFB units.
机译:目的-本文的目的是首先介绍模糊逻辑(FL)方法的关键特征,作为一种在复杂系统的仿真中具有成本效益的技术,然后演示该方法的制定和应用。设计/方法/方法-考虑到分析和数值程序的复杂性以及经验实验的高成本,FL方法用作数据处理的替代方法。距气体分配器的距离,床的温度和空隙度,烟道气速度和锅炉的负荷是输入参数,而膜壁的总传热系数构成输出。五个重叠的S形和恒定语言术语分别用于描述输入和输出数据。 Takagi-Sugeno推理引擎和加权平均去模糊方法分别用于确定模糊和清晰输出值。结果-执行的FL模型可以预测大型670 t / h循环流化床(CFB)锅炉的床对壁传热系数。使用开发的模型评估的局部传热系数与补充研究中获得的数据非常吻合。原创性/价值-所执行的模型构成了易于使用且实用的工具。这种新方法可能有助于进一步研究CFB装置中床对壁的传热系数。

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