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Surrogate-Based Optimization Using an Open-Source Framework: The Bulbous Bow Shape Optimization Case

1
DICCA, Dipartimento di Ingegneria Civile, Chimica e Ambientale, Università degli Studi di Genova, 16145 Genova, Italy
2
DITEN, Dipartimento di Ingegneria Navale, Elettrica, Elettronica e delle Telecomunicazioni, Università degli Studi di Genova, 16145 Genova, Italy
*
Author to whom correspondence should be addressed.
Math. Comput. Appl. 2018, 23(4), 60; https://doi.org/10.3390/mca23040060
Received: 25 May 2018 / Revised: 16 September 2018 / Accepted: 11 October 2018 / Published: 13 October 2018
(This article belongs to the Special Issue Numerical and Evolutionary Optimization)
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Abstract

Shape optimization is a very time-consuming and expensive task, especially if experimental tests need to be performed. To overcome the challenges of geometry optimization, the industry is increasingly relying on numerical simulations. These kinds of problems typically involve the interaction of three main applications: a solid modeler, a multi-physics solver, and an optimizer. In this manuscript, we present a shape optimization work-flow entirely based on open-source tools; it is fault tolerant and software agnostic, allows for asynchronous simulations, and has a high degree of automation. To demonstrate the usability and flexibility of the proposed methodology, we tested it in a practical case related to the naval industry, where we aimed at optimizing the shape of a bulbous bow in order to minimize the hydrodynamic resistance. As design variables, we considered the protrusion and immersion of the bulbous bow, and we used surrogate-based optimization. From the results presented, a non-negligible resistance reduction is obtainable using the proposed work-flow and optimization strategy. View Full-Text
Keywords: surrogate-based optimization; numerical simulations; shape morphing; bulbous bow; open-source framework surrogate-based optimization; numerical simulations; shape morphing; bulbous bow; open-source framework
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Guerrero, J.; Cominetti, A.; Pralits, J.; Villa, D. Surrogate-Based Optimization Using an Open-Source Framework: The Bulbous Bow Shape Optimization Case. Math. Comput. Appl. 2018, 23, 60.

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