Structural Optimisation of Cross-Chiral Metamaterial Structures via Genetic Algorithm

2021 ◽  
pp. 115035
Author(s):  
Jiaqi Dong ◽  
Chao Hu ◽  
John Holmes ◽  
Qing-Hua Qin ◽  
Yi Xiao
2012 ◽  
Vol 60 (2) ◽  
pp. 239-245
Author(s):  
M. S. Alam

Flexible robotic manipulators pose various challenges in modelling, design, structural optimisation and control. This paper presents investigations into practical dynamic modelling of a flexible manipulator system using genetic algorithm (GA). Conventional genetic algorithms (GAs) often converge prematurely to a suboptimal region and fail to provide effective solutions due to lack of diversity in the population set as the algorithm proceeds. In order to improve and maintain diversity in the population set, a relatively new variant of GA, namely, fitness sharing based replacement genetic algorithm (FSR-GA1) is employed where some individuals are replaced periodically based on a fitness sharing method. The algorithm is utilised to extract dynamic model of 1-DOF (degree of freedom) motion of a flexible manipulator system. A comparative assessment between FSR-GA and conventional GA is presented in the same application to highlight the novelty of the used GA. Results show that the FSR-GA significantly improves the searching capability of the optimisation process compared to conventional GA. Time domain and frequency domain results clearly reveal the potential of the proposed method in modelling flexible manipulator systems.DOI: http://dx.doi.org/10.3329/dujs.v60i2.11526 Dhaka Univ. J. Sci. 60(2): 239-245, 2012 (July) 


2016 ◽  
Author(s):  
Lin Wang ◽  
Athanasios Kolios ◽  
Maria Martinez Luengo ◽  
Xiongwei Liu

Abstract. A wind turbine tower supports the main components of the wind turbine (e.g. rotor, nacelle, drive train components, etc.). The structural properties of the tower (such as stiffness and natural frequency) can significantly affect the performance of the wind turbine, and the cost of the tower is a considerable portion of the overall wind turbine cost. Therefore, an optimal structural design of the tower, which has a minimum cost and meets all design criteria (such as stiffness and strength requirements), is crucial to ensure efficient, safe and economic design of the whole wind turbine system. In this work, a structural optimisation model for wind turbine towers has been developed based on a combined parametric FEA (finite element analysis) and GA (genetic algorithm) model. The top diameter, bottom diameter and thickness distributions of the tower are taken as design variables. The optimisation model minimises the tower mass with six constraint conditions, i.e. deformation, ultimate stress, fatigue, buckling, vibration and design variable constraints. After validation, the model has been applied to the structural optimisation of a 5MW wind turbine tower. The results demonstrate that the proposed structural optimisation model is capable of accurately and effectively achieving an optimal structural design of wind turbine towers, which significantly improves the efficiency of structural optimisation of wind turbine towers. The developed framework is generic in nature and can be employed for a series of related problems, when advanced numerical models are required to predict structural responses and to optimise the structure.


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