Response surface strategies in constructing statistical bubble flow models for the development of a novel bubble column simulation approach

Bubble columns represent a substantial contribution to chemical industrial equipment and due to their complex hydrodynamics are difficult and computationally expensive to simulate. A model of the flow structure around a single bubble is required for the development of a computationally efficient alternative model. The flow structure data obtained from CFD is highly non-linear, which lends itself to a Design and Analysis of Computer Experiments (DACE) approach. The situation differs from conventional DACE applications since high resolution data is summarized, which allows different sampling criteria, correlation functions and optimization criteria to be evaluated in an assessable manner. A modified powered exponential correlation function is introduced, which in conjunction with a gradient based space-filling design resulted in an averaged 8 times smaller mean squared error compared to other correlation design combinations. Furthermore, sequentially fitting the data is shown to produce the best overall fits, when used in combination with space-filling designs.

► DACE model is evaluated to construct surrogate model of bubble micro-flow field for Re ≤ 270 for the development of bubble column simulation approach.
► Different correlation functions, sampling designs and parameter estimation strategies are evaluated.
► Combination of gradient based sampling strategy and modified powered exponential correlation function introduced here results in averaged 8 times lower MSE.