An Efficient Surrogate-Based Optimization Method for BWBUG Based on Multifidelity Model and Geometric Constraint Gradients

Daiyu Zhang,Zhidong Wang,Bei Zhang,Xinyao Zhu,Mehmet Cunkas

doi:10.1155/2021/6939863

Abstract

Performing shape optimization of blended-wing-body underwater glider (BWBUG) can significantly improve its gliding performance. However, high-fidelity CFD analysis and geometric constraint calculation in traditional surrogate-based optimization methods are expensive. An efficient surrogate-based optimization method based on the multifidelity model and geometric constraint gradient information is proposed. By establishing a shape parameterized model, deriving analytical expression of geometric constraint gradient, constructing multifidelity surrogate model, the calculation times of high-fidelity CFD model and geometric constraints are reduced during the shape optimization process of BWBUG, which greatly improve the optimization efficiency. Finally, the effectiveness and efficiency of the proposed method are verified by performing the shape optimization of a BWBUG and comparing with traditional surrogate-based optimization methods.

Highlights

With the development of human society, the resources on land are exhausted
To further improve the optimization efficiency of the surrogate model and explore the high lift-drag ratio characteristics of blended-wing-body underwater glider (BWBUG), an efficient surrogate-based optimization method based on the multifidelity model and geometric constraint gradient information is proposed to reduce the calculation times of high-fidelity model and geometric constraints in the shape optimization process of BWBUG
An efficient surrogate-based optimization method based on the multifidelity model and geometric constraint gradient information is proposed, which can greatly reduce the calculation times of the high-fidelity model and geometric constraints in the shape optimization process of BWBUG

Summary

Introduction

With the development of human society, the resources on land are exhausted. Because the ocean has unique advantages in resources, environment, and space, countries in the world are gradually paying attention to the development and utilization of marine resources. Erefore, the gradient-free optimization method is very time-consuming when it is applied to the shape optimization of BWBUG with a large number of variables. For the shape optimization design of BWBUG, Wang et al [23] established the hydrodynamic surrogate model of flying wing underwater glider using Gaussian kernel function and optimized it by particle swarm optimization algorithm. Considering the high-fidelity CFD evaluation is time-consuming for BWBUG, the SBO method still needs to be improved to reduce the computational cost when it is applied to the shape optimization design of BWBUG. To further improve the optimization efficiency of the surrogate model and explore the high lift-drag ratio characteristics of BWBUG, an efficient surrogate-based optimization method based on the multifidelity model and geometric constraint gradient information is proposed to reduce the calculation times of high-fidelity model and geometric constraints in the shape optimization process of BWBUG.

Optimization Model of BWBUG

Problems Existing in the Traditional SBO Method

Efficient Surrogate-Based Optimization Method

Shape Parameterization and Constraint Gradient Computation

Results and Discussion

Conclusions