CFD-aided morphing and design optimisation of ultrasonic flow meters

TY - GEN

T1 - CFD-aided morphing and design optimisation of ultrasonic flow meters

AU - Rincón, Mario Javier

AU - Reclari, Martino

AU - Yang, X.

AU - Abkar, Mahdi

PY - 2023/9

Y1 - 2023/9

N2 - Ultrasonic flow meters with an intrusive two-stand configuration present a complex flow behaviour due to their unique geometry, which offers an interesting and challenging case to evaluate optimisation methods in wall-bounded flows. In this study, the design and analysis of computer models and shape optimisation by mesh morphing are utilised to predict the turbulent flow and perform a robust two-step geometry optimisation of the flow meter. Design optimisation is accomplished by surrogate modelling based on Kriging, Latin hypercube sampling, and Bayesian strategies. A novel function to quantify flow meter measurement robustness is evaluated together with pressure drop in order to define a multi-objective optimisation problem. The design optimisation Pareto front is shown and compared numerically and experimentally. Subsequently, one of the non-dominated designs is further improved by mesh morphing with the aid of the adjoint method, acquiring a novel topology with further optimisation gains. The final results display performance gains, and the final geometrical changes in the 3D space are shown. The applied methodology provides a robust and efficient framework to evaluate design changes and improve complex internal-flow geometries with similar features.

AB - Ultrasonic flow meters with an intrusive two-stand configuration present a complex flow behaviour due to their unique geometry, which offers an interesting and challenging case to evaluate optimisation methods in wall-bounded flows. In this study, the design and analysis of computer models and shape optimisation by mesh morphing are utilised to predict the turbulent flow and perform a robust two-step geometry optimisation of the flow meter. Design optimisation is accomplished by surrogate modelling based on Kriging, Latin hypercube sampling, and Bayesian strategies. A novel function to quantify flow meter measurement robustness is evaluated together with pressure drop in order to define a multi-objective optimisation problem. The design optimisation Pareto front is shown and compared numerically and experimentally. Subsequently, one of the non-dominated designs is further improved by mesh morphing with the aid of the adjoint method, acquiring a novel topology with further optimisation gains. The final results display performance gains, and the final geometrical changes in the 3D space are shown. The applied methodology provides a robust and efficient framework to evaluate design changes and improve complex internal-flow geometries with similar features.

M3 - Article in proceedings

SP - 109

EP - 114

BT - The 14th International ERCOFTAC Symposium on Engineering Turbulence Modelling and Measurements

T2 - The 14th International ERCOFTAC Symposium on Engineering Turbulence Modelling and Measurements

Y2 - 1 September 2023

ER -