The application of Buckingham p theorem to Lattice-Boltzmann modelling of sewage sludge digestion
The application of Buckingham p theorem to Lattice-Boltzmann modelling of sewage sludge digestion
复制标题
白金汉p定理在污水污泥消化格子-玻尔兹曼模型中的应用
DOI：
10.1016/j.compfluid.2020.104632
复制
发表时间：
2020
影响因子：
2.8
通讯作者：
Dapelo D
中科院分区：
文献类型：
--
作者：
Dapelo D
首次将格点-玻尔兹曼双向耦合点欧拉-拉格朗日模型应用于污泥厌氧消化的气体混合。该集合包括一个局部模型，一个“第一邻居”（即，粒子所在的体素发生反向耦合，加上它的第一个邻居）和一个“平滑核”（通过平滑核平均过程发生正向和反向耦合）。实验室规模的测试显示，由于气泡直径大于体素尺寸，网格无关性问题，从而打破了颗粒尺寸可忽略的逐点欧拉-拉格朗日假设。为了解决这一问题，从而获得网格独立的结果，提出了一种基于白金汉π定理的点向欧拉-拉格朗日网格独立评估的数据缩放方法。对实验室尺度流动模式的评估和与实验数据的比较表明，模型之间以及数值模拟和实验数据之间只有微小的差异。中试规模的模拟表明，如果恢复了欧拉-拉格朗日可忽略（或至少是小）粒度的假设，所有模型都能产生与网格无关的连贯数据。在这两种情况下，都实现了二阶收敛。随后讨论了应用所提出的数据缩放方法而不是平滑核模型的机会。
For the first time, a set of Lattice-Boltzmann two-way coupling pointwise Euler-Lagrange models is applied to gas mixing of sludge for anaerobic digestion. The set comprises a local model, a “first-neighbour” (viz., back-coupling occurs to the voxel where a particle sits, plus its first neighbours) and a “smoothing-kernel” (forward- and back-coupling occur through a smoothed-kernel averaging procedure).Laboratory-scale tests display grid-independence problems due to bubble diameter being larger than voxel size, thereby breaking the pointwise Euler-Lagrange assumption of negligible particle size. To tackle this problem and thereby have grid-independent results, a novel data-scaling approach to pointwise Euler-Lagrange grid independence evaluation, based on an application of the Buckinghamπtheorem, is proposed.Evaluation of laboratory-scale flow patterns and comparison to experimental data show only marginal differences in between the models, and between numerical modelling and experimental data. Pilot-scale simulations show that all the models produce grid-independent, coherent data if the Euler-Lagrange assumption of negligible (or at least, small) particle size is recovered. In both cases, a second-order convergence was achieved.A discussion follows on the opportunity of applying the proposed data-scaling approach rather than the smoothing-kernel model.