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. Highlights Validation of hydrodynamics of multiphase flow in downer employing Eulerian-Eulerian Approach Optimisation of hydrodynamic interactive model parameters viz., Restitution and Specularity coefficient coupled with Newton Raphson multi-parameter root finding and Jacobian Method. Agreement between experimental and simulation with optimised modelling parameters

中文翻译：

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使用 NR 方法优化多相流 CFD 建模的相互作用参数

流体和颗粒流动的准确建模对于多相反应器中气固反应的可靠预测至关重要。由于接触时间短、固体返混少和停留时间短等有前途的特性，与传统的提升管配置相比，下行塔已在工业中使用。然而，流体动力学特性的有效模拟和验证一直很少。具有适当 Eulerian-Eulerian 方法的 RANS 模型提出了选择流体动力学模拟参数的挑战性任务，例如 i) 粒子 - 粒子恢复系数，ii) 粒子壁恢复系数和 iii) 镜面反射系数。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下游流体动力学。通过使用 CFD 模拟输出验证实验数据而获得的误差是我们需要最小化的函数。为此使用了牛顿拉夫森多参数求根方法。Jacobian 评估需要在每次迭代中进行多次 CFD 模拟。3 次迭代后，误差减少了 61%。因此，优化的流体动力学模型参数可用于进一步建模研究，用于预测直径 200 mm 8 m 柱的流体动力学特性。亮点使用欧拉-欧拉方法验证下沉管中多相流的流体动力学优化流体动力学交互模型参数，即，恢复和镜面反射系数与 Newton Raphson 多参数求根和雅可比方法相结合。实验和模拟之间的一致性与优化的建模参数