An Adjoint Optimization Prediction Method for Partially Cavitating Hydrofoils

Author:

Anevlavi Dimitra,Belibassakis Kostas

Abstract

Much work has been done over the past years to obtain a better understanding, predict and alleviate the effects of cavitation on the performance of lifting surfaces for hydrokinetic turbines and marine propellers. Lifting-surface sheet cavitation, when addressed as a free-streamline problem, can be predicted up to a desirable degree of accuracy using numerical methods under the assumptions of ideal flow. Typically, a potential solver is used in conjunction with geometric criteria to determine the cavity shape, while an iterative scheme ensures that all boundary conditions are satisfied. In this work, we propose a new prediction model for the case of partially cavitating hydrofoils in a steady flow that treats the free-streamline problem as an inverse problem. The objective function is based on the assumption that on the cavity boundary, the pressure remains constant and is evaluated at each optimization cycle using a source-vorticity BEM solver. The attached cavity is parametrized using B-splines, and the control points are included in the design variables along with the cavitation number. The sensitivities required for the gradient-based optimization are derived using the continuous adjoint method. The proposed numerical scheme is compared against other methods for the NACA 16-series hydrofoils and is found to predict well both the cavity shape and cavitation number for a given cavity length.

Publisher

MDPI AG

Subject

Ocean Engineering,Water Science and Technology,Civil and Structural Engineering

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3