Volume 18, Issue 3 (2018)                   Modares Mechanical Engineering 2018, 18(3): 311-322 | Back to browse issues page

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bidoki M, mortazavi M, sabzeparvar M. A new robust multidisciplinary design optimization framework for conceptual design of an autonomous underwater vehicle. Modares Mechanical Engineering. 2018; 18 (3) :311-322
URL: http://mme.modares.ac.ir/article-15-8981-en.html
1- aerospace department, amirkabir university of technology
Abstract:   (3854 Views)
The design process of an Autonomous Underwater Vehicle (AUV) requires mathematical model of subsystems or disciplines such as guidance and control, payload, hydrodynamic, propulsion, structure, trajectory and performance and their interactions. In early phases of design, an AUV are often encountered with a high degree of uncertainty in the design variables and parameters of system. These uncertainties present challenges to the design process and have a direct effect on the AUV performance. Multidisciplinary Design Optimization (MDO) is an approach to find both optimum and feasible design and robust design is an approach to make the system performance insensitive to variations of design variables and parameters. It is significant to integrate robust design and MDO for designing complex engineering systems in optimal, feasible and robust senses. In this paper, an improved robust MDO methodology is developed for conceptual design of an AUV under uncertainty with considering tactic and system design simultaneously. In this methodology, Uncertain MultiDisciplinary Feasible (UMDF) framework is introduced as uncertain MDO framework. Two evolutionary algorithms are also used as Pareto-based Multi-Objective optimizers and results of two algorithms are compared. The results of this research illustrate that the new proposed robust multidisciplinary design optimization framework can carefully set a robust design for an AUV with coupled uncertain disciplines.
Article Type: Research Article | Subject: Marine Structures
Received: 2017/12/1 | Accepted: 2018/01/30 | Published: 2018/03/2

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