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Structure optimization of tower crane jib based on multi-fidelity surrogate model
Published:2024-11-21 author:ZHANG Jiankang, LIU Fuwen, GUO Guanchen, et al. Browse: 103 Check PDF documents
Structure optimization of tower crane jib based 
on multi-fidelity surrogate model


ZHANG Jiankang1, 2, LIU Fuwen1, 2, GUO Guanchen1, 2, 
ZHANG Shuai1, 2, SONG Xueguan1, 2, SUN Tian3,LI Zilu3


(1.School of Mechanical Engineering, Dalian University of Technology, Dalian 116024, China; 2.State Key Laboratory 

Hing-performance Precision Manufacturing, Dalian University of Technology, Dalian 116024, China;

3.Fushun Yongmao Construction Machinery Co., Ltd., Fushun 113000, China)


Abstract:  The jib, an essential operational component of a tower crane, was entrusted with the task of hoisting and transporting construction materials. The production costs and energy consumption of the jib were directly tied to its weight. The necessity of optimizing jib weight was emphasized. An efficient optimization approach for the design of a tower crane's jib was introduced. Firstly, based on the finite element method, the ultimate stress and deformation under different arm amplitudes were calculated, and the most dangerous working condition was determined, which was used as the basis for optimizing the design. Then, 12 structural parameters related to the jib were selected as design variables for the undertaking of parametric modeling, Latin hypercube sampling (LHS) was employed in selecting the sample points. Based on finite element simulation data, three surrogate models based on radial basis function (RBF) were constructed and their accuracy was assessed. Finally, based on a high-precision multi-fidelity surrogate model (MFS), with the optimization objective of minimizing the weight of the jib, a mathematical model for the jib optimization problem was constructed, and the genetic algorithm (GA) was utilized to execute the optimization design. The research results demonstrate that the optimized jib meets both strength and stiffness requirements, ensuring structural integrity and stability, while achieving a 25.03% reduction in weight. Moreover, the deviation between the anticipated and simulated results of the multifidelity surrogate model is less than 3%, validating the precision of the multi-fidelity surrogate model and the effectiveness of the jib optimization method grounded on the multi-fidelity surrogate model.

Key words: tower crane with movable jib; lightweight design of jib structure; multi-fidelity surrogate model(MFS); genetic algorithm(GA); optimization design; latin hypercube sampling(LHS); radial basis function(RBF)

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