Department of Environmental Engineering, Technical University of Denmark, Miljøvej, Building 113, 2800 Kgs. Lyngby, Denmark.
Department of Applied Mathematics and Computer Science, Technical University of Denmark, Richard Petersens Plads, Building 321, 2800 Kgs. Lyngby, Denmark; Department of Business Administration, Technology and Social Sciences, Luleå University of Technology, SE-97187 Luleå, Sweden.
Water Res. 2015 Oct 15;83:396-411. doi: 10.1016/j.watres.2015.06.012. Epub 2015 Jun 18.
The present study aims at using statistically designed computational fluid dynamics (CFD) simulations as numerical experiments for the identification of one-dimensional (1-D) advection-dispersion models - computationally light tools, used e.g., as sub-models in systems analysis. The objective is to develop a new 1-D framework, referred to as interpreted CFD (iCFD) models, in which statistical meta-models are used to calculate the pseudo-dispersion coefficient (D) as a function of design and flow boundary conditions. The method - presented in a straightforward and transparent way - is illustrated using the example of a circular secondary settling tank (SST). First, the significant design and flow factors are screened out by applying the statistical method of two-level fractional factorial design of experiments. Second, based on the number of significant factors identified through the factor screening study and system understanding, 50 different sets of design and flow conditions are selected using Latin Hypercube Sampling (LHS). The boundary condition sets are imposed on a 2-D axi-symmetrical CFD simulation model of the SST. In the framework, to degenerate the 2-D model structure, CFD model outputs are approximated by the 1-D model through the calibration of three different model structures for D. Correlation equations for the D parameter then are identified as a function of the selected design and flow boundary conditions (meta-models), and their accuracy is evaluated against D values estimated in each numerical experiment. The evaluation and validation of the iCFD model structure is carried out using scenario simulation results obtained with parameters sampled from the corners of the LHS experimental region. For the studied SST, additional iCFD model development was carried out in terms of (i) assessing different density current sub-models; (ii) implementation of a combined flocculation, hindered, transient and compression settling velocity function; and (iii) assessment of modelling the onset of transient and compression settling. Furthermore, the optimal level of model discretization both in 2-D and 1-D was undertaken. Results suggest that the iCFD model developed for the SST through the proposed methodology is able to predict solid distribution with high accuracy - taking a reasonable computational effort - when compared to multi-dimensional numerical experiments, under a wide range of flow and design conditions. iCFD tools could play a crucial role in reliably predicting systems' performance under normal and shock events.
本研究旨在使用经过统计学设计的计算流体动力学(CFD)模拟作为数值实验,以识别一维(1-D)对流-弥散模型 - 这是一种计算量较轻的工具,例如,作为系统分析中的子模型使用。目的是开发一种新的 1-D 框架,称为解释性 CFD(iCFD)模型,其中统计元模型用于计算伪弥散系数(D)作为设计和流动边界条件的函数。该方法 - 以简单透明的方式呈现 - 以圆形二次沉淀池(SST)为例进行说明。首先,通过应用实验设计的两级分因子设计的统计方法,筛选出重要的设计和流动因素。其次,根据通过因子筛选研究和系统理解确定的显著因素数量,使用拉丁超立方采样(LHS)选择 50 组不同的设计和流动条件。边界条件组施加在 SST 的 2-D 轴对称 CFD 模拟模型上。在该框架中,为了退化 2-D 模型结构,通过校准三种不同的 D 模型结构,将 CFD 模型输出近似为 1-D 模型。然后,将 D 参数的相关方程确定为所选设计和流动边界条件(元模型)的函数,并根据每个数值实验中估计的 D 值评估其准确性。使用从 LHS 实验区域角落采样的参数获得的场景模拟结果,对 iCFD 模型结构进行评估和验证。对于所研究的 SST,还进行了额外的 iCFD 模型开发,包括(i)评估不同密度流子模型;(ii)实施絮凝、受阻、瞬态和压缩沉降速度函数的组合;以及(iii)评估瞬态和压缩沉降开始的建模。此外,还进行了 2-D 和 1-D 模型的最佳离散化水平。结果表明,通过所提出的方法为 SST 开发的 iCFD 模型能够在广泛的流动和设计条件下,以合理的计算工作量,高精度地预测固体分布 - 与多维数值实验相比。iCFD 工具在可靠预测系统在正常和冲击事件下的性能方面可以发挥关键作用。