Mechanical Engineering Science

Dynamic optimization analysis of hydraulic pipeline system based on a developed response surface method

QUHongquan, SUNJianlin, YANXu, ZHANGYuanlin, LIUXuefeng, YUTao, HANHuawei, XULangjun

Abstract


When designing a complex pipeline with long distance and multi-supports for offshore platform, it is necessary to analyze the vibration characteristics of the complex pipeline system to ensure that there is no harmful resonance in the working conditions. Therefore, the optimal layout of support is an effective method to reduce the vibration response of hydraulic pipeline system. In this paper, a developed dynamic optimization method for the complex pipeline is proposed to investigate the vibration characteristics of complex pipeline with multi-elastic supports. In this method, the Kriging response surface model between the support position and pipeline is established. The position of the clamp in the model is parameterized and the optimal solution of performance index is obtained by genetic algorithm. The number of clamps and the interval between clamps are considered as the constraints of layout optimization, and the optimization objective is the natural frequencies of pipeline. Taking a typical offshore pipeline as example to demonstrate the effectiveness of the proposed method, the results show that the vibration performance of the hydraulic pipeline system is distinctly improved by the optimization procedure, which can provide reasonable guidance for the design of complex hydraulic pipeline system.


Keywords


Hydraulic pipeline; Multi-Support; Response surface method; Optimization analysis

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References


Kwong, A.H.M.; Edge, K.A. A method to reduce noise in hydraulic systems by optimizing pipe clamp locations. Proceedings of The Institution of Mechanical Engineers Part I Journal of Systems & Control Engineering, 1998, 212(4):267-280.

Wang, D.; Jiang, J.S.; Zhang, W.H. Optimization of support positions to maximize the fundamental frequency of structures. International Journal for Numerical Methods in Engineering, 2004, 61(10):1584-1602.

Wang, D. Optimization of support positions to minimize the maximal deflection of structures. International Journal of Solids & Structures, 2004, 41(26):7445-7458.

Liu, Y.S.; He, X.D.; Zhu, Y.H. et al. Dynamical strength and design optimization of pipe-joint system under pressure impact load. Proceedings of the Institution of Mechanical Engineers, 2012, 226(G8):1029-1040.

Li, X.; Zhang, L.J.; Wang, S.P. et al. Impedance analysis and clamp locations optimization of hydraulic pipeline system in aircraft. International Conference on Fluid Power & Mechatronics, Ha Erbin, China, 2015.08.05, pp.1023-1028.

Gao, P.X.; Li, J.W.; Zhai, J.Y. et al. A novel optimization layout method for clamps in a pipeline system. Applied Sciences. 2020, 10(1): 390.

Box G, Wilson K. On the experimental attainment of optimum condition. Journal of the Royal Statistical Society, 1951, 13(1): 1-45.

Xiao, M.H.; Shen, X.J.; Liu, X. Study on properties of 45 Carbon Steel Ni-P electroless plating reinforced by Si3N4-Al2O3 particle based on response surface method. Journal of Nanoscience and Nanotechnology. 2020, 20, 4761-4772.

Zhang, T.; Zhou, X.P.; Liu, X.F. Reliability analysis of slopes using the improved stochastic response surface methods with multicollinearity. Engineering Geology. 2020, 271, doi: 10.1016/j.enggeo.2020.105617.

Abba, S.I.; Usman A.G.; Isik, S. Simulation for response surface in the HPLC optimization method development using artificial intelligence models: A data-driven approach. Chemometrics and Intelligent Laboratory Systems. 2020,201, doi: 10.1016/j.chemolab.2020.104007.

Gao, L.; Gegentana; Liu, Z.Z.; Sun. B.Z.; Li, S.H. Multi-objective optimization of thermal performance of packed bed latent heat thermal storage system based on response surface method. Renewable Energy. 2020, 153, pp. 169-180.

Perwez, A.; Siddiqui, N.A.; Alqahtani, A.S.; Haque, A. Response surface methodology-based optimization of ultrasound-assisted extraction of beta-sitosterol and lupeol from astragalus atropilosus (roots) and validation by HPTLC method. Asian Pacific Journal of Tropical Biomedicine. 2020, 10, pp. 281-292.

Heddam, S.; Keshtegar, B.; Kisi, O. Predicting total dissolved gas concentration on a daily scale using kriging interpolation, response surface method and artificial neural network: Case Study of Columbia River Basin Dams, USA. Natural Resources Research. 2020, 29, pp. 1801-1818.

Xie, Y.W.; Hu, P.F.; Zhu, N.; Lei, F.; Xing, L.; Xu, .L.H. Collaborative optimization of ground source heat pump-radiant ceiling air conditioning system based on response surface method and NSGA-II. Renewable Energy.2020, 147, 149-167.

Shirazi, M.; Khademalrasoul, A.; Ardebili, S.M.S. Multi-objective optimization of soil erosion parameters using response surface method (RSM) in the Emamzadeh watershed. Acta Geophysica.2020, 68, pp.505-517.

Xue, X.F.; Wang, Y.Z.; Lu, C. Sinking velocity impact-analysis for the carrier-based aircraft using the response surface method-based improved kriging algorithm. Advances in Materials Science And Engineering. 2020, 202, 10.1155/2020/5649492.

Solmaz, H.; Ardebili, S.M.S.; Aksoy, F.; Calam, A.; Yilmaz, E. Arslan. Optimization of the operating conditions of a beta-type rhombic drive stirling engine by using response surface method. Energy. 2020, 198, doi: 10.1016/j.energy.2020.117377.

Bai, B.; Li, H.; Zhang, W.; Cui, Y.C. Application of extremum response surface method-based improved substructure component modal synthesis in mistuned turbine bladed disk. Journal of Sound and Vibration. 2020, 472, doi: 10.1016/j.jsv.2020.115210.

Su, Y.; Fu, G. Wan, Bo. et al. Fatigue reliability design for metal dual inline packages under random vibration based on response surface method. Microelectronics Reliability, 2019, 100, 113404.

Ferreira, S.; Bruns, R.; Ferreira, H. et al. Box-Behnken design: an alternative for the optimization of analytical methods. Analytica Chimica Acta, 2007, 597(2):179-186.




DOI: https://doi.org/10.33142/mes.v2i2.3161

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Copyright (c) 2020 Hongquan QU, Jianlin SUN, Xu YAN, Yuanlin ZHANG, Xuefeng LIU, Tao YU, Huawei HAN, Langjun XU

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