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Optimisation of interaction parameters for CFD modelling of multiphase flow using NR method

机译:使用NR方法优化多相流量CFD建模的交互参数

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摘要

Accurate modelling of fluid and particle flow is essential for reliable predictions of gas-solid reactions in the multiphase reactor. Due to the promising features such as short contact time, less back mixing of solids and low residence time, downer column has been used in industries than conventional riser configuration. However, the effective simulation and validation of the hydrodynamic characteristics have been scarce. A RANS model with an appropriate Eulerian-Eulerian approach poses a challenging task of choosing the hydrodynamic simulation parameters, such as i) particle-particle restitution coefficient, ii) particle-wall restitution coefficient and iii) specularity coefficient. The objective of the present study was to optimise these model parameters to obtain close validation with experimental data so that accurate downer hydrodynamics can be predicted. The error obtained from validating the experimental data with the CFD simulation output is our function which needs to be minimised. Newton Raphson multi-parameter root finding method was used for this purpose. The Jacobian evaluation required multiple CFD simulations at each iteration. A 61% reduction in error was achieved after 3 iterations. Thus, the optimised model parameters of hydrodynamics used for further modelling study in predicting hydrodynamic characteristics of a 200 mm diameter 8 m column.
机译:精确的液体和颗粒流模型对于多相反应器中的气体固体反应可靠预测是必不可少的。由于有希望的特征,例如短接触时间,较少的固体和低停留时间的反复混合,桌上柱子已被用于行业而不是传统的提升管配置。然而,流体动力学特征的有效仿真和验证已经稀缺。具有适当的欧拉 - 欧拉米列方法的RAN模型构成了选择粒子粒子恢复系数,II)粒子恢复系数和III)镜面系数的具有挑战性的任务。本研究的目的是优化这些模型参数,以获得与实验数据的密切验证,从而可以预测准确的俯卧流流体动力学。通过CFD仿真输出验证实验数据的误差是我们的功能,需要最小化。牛顿Raphson多参数根发现方法用于此目的。雅各比评估需要在每次迭代时多次CFD模拟。在3次迭代后,误差减少了61%。因此,用于进一步建模研究的流体动力学的优化模型参数在预测200mm直径8M柱的流体动力学特征中的进一步建模研究。

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