Meta‐Model‐Based Calibration and Sensitivity Studies of Computational Fluid Dynamics Simulation of Jet Pumps

Abstract

Calibration and sensitivity studies in the computational fluid dynamics (CFD) simulation of process equipment such as the annular jet pump are suitable for design, analysis, and optimization. The application of CFD for such purposes is computationally intensive. Hence, an alternative approach with kriging-based meta-models was utilized. Calibration via the adjustment of two turbulent model parameters, C m and C 2e , and likewise two parameters in the simulation correlation for C m was considered, while sensitivity studies were based on C m as input. The meta-model-based calibration aids exploration of different parameter combinations. Computational time was also reduced with kriging-assisted sensitivity studies which investigated the effect of different C m values on pressure distribution.

Multi-Objective Optimization of Jet Pump Based on RBF Neural Network Model

“…The maximum error of efficiency and head ratio are 8.6% and 6.1%, respectively. For further verification of the RBF model's accuracy, a statistical measure of objective function, correlation coefficient R 2 , is introduced to estimate the approximate degree [39]. An R 2 statistic that close to 1 indicates that a large proportion of the variability in the response is due to the regression.…”

Quantification of the uncertainty within a SAS-SST simulation caused by the unknown high-wavenumber damping factor

“…GP and it variants has been successfully applied to many subjects, i.e. studying the performance of a structural health monitoring system (Ghiasi et al, 2018;Olalusi and Spyridis, 2020); calibrating the model constants (Cox et al, 2001;Duan et al, 2021;Kajero et al, 2017); scrutinising CFD models (Duan et al, 2019); optimising engineering designs (Bernardini et al, 2015;Ding and Kareem, 2018), and global sensitivity analysis (Chen et al, 2005), as well as material informatics (Hoang et al, 2016;Duan, 2021a, 2021b). Therefore, the GP method is chosen as the analysis approach in this study.…”

Short CFD Simulation Activities in the Context of Fluid-Mechanical Learning in a Multidisciplinary Student Body

“…Furthermore, specific CFD software can be difficult to handle and, sometimes, unintuitive for students without previous experience. Carrying out processing tasks using CFD can become a long, hard and intense work when it is performed for specific applications [1], for example, optimization [3,6], model calibration [7], sensitivity analysis and consequence analysis [8]).…”