Hydrodynamic Shape Optimization of Axisymmetric Bodies Using Multi-fidelity Modeling

Leifsson, Leifur; Koziel, Slawomir; Ogurtsov, Stanislav

doi:10.1007/978-3-642-34336-0_14

Cited by 3 publications

(1 citation statement)

References 24 publications

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“…Multi-fidelity modelling can improve the efficiency of SBGO, by using the usual expensive and precise data together with less expensive but less accurate data. Results as early as that of Leifsson et al [22] show that optimised hull designs can be obtained at over 94% lower computational cost when using multi-fidelity optimisation as compared to a direct high-fidelity optimisation algorithm. However, these results typically do not scale to more design variables.…”

Section: Motivationmentioning

confidence: 98%

Multi-fidelity Kriging extrapolation together with CFD for the design of the cross-section of a falling lifeboat

Wenink,

van der Eijk,

Yorke-Smith

et al. 2023

ISP

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Surrogate modelling techniques such as Kriging are a popular means for cheaply emulating the response of expensive Computational Fluid Dynamics (CFD) simulations. These surrogate models are often used for exploring a parameterised design space and identifying optimal designs. Multi-fidelity Kriging extends the methodology to incorporate data of variable accuracy and costs to create a more effective surrogate. This work recognises that the grid convergence property of CFD solvers is currently an unused source of information and presents a novel method that, by leveraging the data structure implied by grid convergence, could further improve the performance of the surrogate model and the corresponding optimisation process. Grid convergence states that the simulation solution converges to the true simulation solution as the numerical grid is refined. The proposed method is tested with realistic multi-fidelity data acquired with CFD simulations. The performance of the surrogate model is comparable to an existing method, and likely more robust. More research is needed to explore the full potential of the proposed method. Code has been made available online at https://github.com/robertwenink/MFK-Extrapolation.

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Section: Motivationmentioning

confidence: 98%

Multi-fidelity Kriging extrapolation together with CFD for the design of the cross-section of a falling lifeboat

Wenink,

van der Eijk,

Yorke-Smith

et al. 2023

ISP

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AUV hull shape design based on desired pressure distribution

2015

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Designing of the body shape of an autonomous underwater vehicle using the design of experiments method

Alijani

Zeinali

Nouri

2018

Proceedings of the Institution of Mechanical Engineers, Part C:

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The process of designing autonomous underwater vehicles comprises several steps, including the designing of the body shape. The hydrodynamic designing of the body shape is a major step in designing the body of an underwater vehicle. The effective parameters in the hydrodynamic design of body shape include the lengths of nose and tail, nose and tail profiles, and also the dimensions of the blunt sections in front of the nose and behind the tail. In the present study, the design of experiments method has been employed to investigate the effect of each of the above parameters on the drag coefficient of an autonomous underwater vehicle body. For this purpose, in addition to introducing the body classes of the Hydrolab family of underwater vehicles, the numerical simulation results of fluid flow over the body of a Hydrolab500 AUV have been used for the design of experiments. In the first step, an experiment has been performed in water tunnel on a test model in order to validate the pressure profile for the body of Hydrolab500. The comparison between the empirical and numerical results related to Hydrolab500 body confirms the validity of the numerical approach used in this paper. The results of the present work show that the drag coefficient of an autonomous submersible in the final design can be accurately estimated with the help of the presented method.

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Hydrodynamic Shape Optimization of Axisymmetric Bodies Using Multi-fidelity Modeling

Cited by 3 publications

References 24 publications

Multi-fidelity Kriging extrapolation together with CFD for the design of the cross-section of a falling lifeboat

Multi-fidelity Kriging extrapolation together with CFD for the design of the cross-section of a falling lifeboat

AUV hull shape design based on desired pressure distribution

Designing of the body shape of an autonomous underwater vehicle using the design of experiments method

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