Discussion: “A Multi-Objective Optimization Approach on Spiral Grooves for Gas Mechanical Seals” (Wang, X., Shi, L., Huang, W., and Wang, X., 2018, ASME J. Tribol., 140(4), p. 041701)

2018 ◽  
Vol 141 (2) ◽  
Author(s):  
Itzhak Green
Keyword(s):  
Optimization Approach ◽  
Multi Objective Optimization ◽  
Mechanical Seals ◽  
Multi Objective ◽  
Spiral Grooves

A Multi-Objective Optimization Approach on Spiral Grooves for Gas Mechanical Seals

2018 ◽  
Vol 140 (4) ◽  
Author(s):  
Xiuying Wang ◽  
Liping Shi ◽  
Wei Huang ◽  
Xiaolei Wang
Keyword(s):  
Optimization Approach ◽  
Multi Objective Optimization ◽  
Mechanical Seals ◽  
Independent Variables ◽  
Multi Objective ◽  
Pareto Optimal Set ◽  
Conflicting Objectives ◽  
Collinearity Diagnostics ◽  
Film Stiffness ◽  
Spiral Grooves

Spiral groove is one of the most common types of structures on gas mechanical seals. Numerical research demonstrated that the grooves designed for improving gas film lift or film stiffness often lead to the leakage increase. Hence, a multi-objective optimization approach specially for conflicting objectives is utilized to optimize the spiral grooves for a specific sample in this study. First, the objectives and independent variables in multi-objective optimization are determined by single objective analysis. Then, a set of optimal parameters, i.e., Pareto-optimal set, is obtained. Each solution in this set can get the highest dimensionless gas film lift under a specific requirement of the dimensionless leakage rate. Finally, the collinearity diagnostics is performed to evaluate the importance of different independent variables in the optimization.

Experimental verification of textured mechanical seal designed using multi-objective optimization

2019 ◽  
Vol 71 (6) ◽  
pp. 766-771 ◽  
Author(s):  
Xiuying Wang ◽  
Michael Khonsari ◽  
Siyuan Li ◽  
Qingwen Dai ◽  
Xiaolei Wang
Keyword(s):  
Leakage Rate ◽  
Free Form ◽  
Optimization Approach ◽  
Multi Objective Optimization ◽  
Mechanical Seals ◽  
Content Type ◽  
Multi Objective ◽  
Load Carrying ◽  
And Control ◽  
Good Agreement

Purpose This study aims to simultaneously enhance the load-carrying capacity and control the leakage rate of mechanical seals by optimizing the texture shape. Design/methodology/approach A multi-objective optimization approach is implemented to determine the optimal “free-form” textures and optimal circular dimples. Experiments are conducted to validate the simulation results. Findings The experimental coefficient of friction (COF) and leakage rate are in good agreement with the calculated results. In addition, the optimal “free-form” texture shows a lower COF and a lower leakage in most cases. Originality/value This work provides a method to optimize the surface texture for a better combination performance of mechanical seals.

scholarly journals Multi-Objective Multidisciplinary Design Optimization of a Robotic Fish System

2021 ◽  
Vol 9 (5) ◽  
pp. 478
Author(s):  
Hao Chen ◽  
Weikun Li ◽  
Weicheng Cui ◽  
Ping Yang ◽  
Linke Chen
Keyword(s):  
Design Optimization ◽  
Optimization Algorithm ◽  
Multidisciplinary Design Optimization ◽  
Robotic Fish ◽  
Multidisciplinary Design ◽  
Optimization Approach ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Cfd Method ◽  
The Individual

Biomimetic robotic fish systems have attracted huge attention due to the advantages of flexibility and adaptability. They are typically complex systems that involve many disciplines. The design of robotic fish is a multi-objective multidisciplinary design optimization problem. However, the research on the design optimization of robotic fish is rare. In this paper, by combining an efficient multidisciplinary design optimization approach and a novel multi-objective optimization algorithm, a multi-objective multidisciplinary design optimization (MMDO) strategy named IDF-DMOEOA is proposed for the conceptual design of a three-joint robotic fish system. In the proposed IDF-DMOEOA strategy, the individual discipline feasible (IDF) approach is adopted. A novel multi-objective optimization algorithm, disruption-based multi-objective equilibrium optimization algorithm (DMOEOA), is utilized as the optimizer. The proposed MMDO strategy is first applied to the design optimization of the robotic fish system, and the robotic fish system is decomposed into four disciplines: hydrodynamics, propulsion, weight and equilibrium, and energy. The computational fluid dynamics (CFD) method is employed to predict the robotic fish’s hydrodynamics characteristics, and the backpropagation neural network is adopted as the surrogate model to reduce the CFD method’s computational expense. The optimization results indicate that the optimized robotic fish shows better performance than the initial design, proving the proposed IDF-DMOEOA strategy’s effectiveness.

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