Application of Quantum Genetic Algorithm to Inverse Calculationof Comprehensive Elastic Modulus of Concrete Gravity Dam

CAO Ming-jie, CAO Xin, XU Zheng-zhi

Journal of Changjiang River Scientific Research Institute ›› 2016, Vol. 33 ›› Issue (4) : 111-114.

PDF(805 KB)
PDF(805 KB)
Journal of Changjiang River Scientific Research Institute ›› 2016, Vol. 33 ›› Issue (4) : 111-114. DOI: 10.11988/ckyyb.20140916
HYDRAULIC STRUCTURE AND MATERIAL

Application of Quantum Genetic Algorithm to Inverse Calculationof Comprehensive Elastic Modulus of Concrete Gravity Dam

  • CAO Ming-jie, CAO Xin, XU Zheng-zhi
Author information +
History +

Abstract

Physical and mechanical parameters of hydraulic structure under complex operation conditions tend to vary with the growth of time, and it is important to obtain these parameters in time for mastering working state, and guiding safety monitoring of hydraulic structures. In this paper, on the basis of quantum genetic algorithm (QGA) and finite element model, we establish an inverse model for mechanical parameters of dam. Through coding by using MATLAB, we build the interface of command calling for finite element software, and establish objective fitness function in association with calculated data of finite element model and measured data. Structural parameter inversion of hydraulic building is completed by intelligent optimization of QGA. In order to verify the algorithm in this paper, we take a concrete gravity dam as an example to carry out inverse analysis of comprehensive elastic modulus for dam concrete and rock in the foundation. Results show that the inversion accuracy and computing speed of the method above are better than those of traditional genetic algorithm. Finally, the research can be referenced for similar projects.

Key words

quantum genetic algorithm / inverse analysis / concrete gravity dam / elastic modulus / optimization algorithm / finite element method

Cite this article

Download Citations
CAO Ming-jie, CAO Xin, XU Zheng-zhi. Application of Quantum Genetic Algorithm to Inverse Calculationof Comprehensive Elastic Modulus of Concrete Gravity Dam[J]. Journal of Changjiang River Scientific Research Institute. 2016, 33(4): 111-114 https://doi.org/10.11988/ckyyb.20140916

References

[1] 吴中如.水工建筑物安全监控理论及其应用.北京:高等教育出版社,2003.
李 波, 徐宝松, 武金坤,等. 基于最小二乘支持向量机的大坝力学参数反演. 岩土工程学报, 2008,30(11):1722-1725.
FRISWELL M I. A Combined Genetic and Eigensensitivity Algorithm for the Location of Damage in Structures. Computers and Structures, 1998, 69(5):547-556.
SANKAR K N. Velocity Inversion in Cross-hole Seismic Tomography by Counter-propagation Neural Network, Genetic Algorithm and Evolutionary Programming Techniques. Geophysical Journal International,1999,138(1):108-124.
李守巨, 刘迎曦, 王登刚. 基于模拟退火算法的含水层参数非线性反演. 西安交通大学学报, 2001, (5):546-548.
李守巨, 刘迎曦, 陈昌林,等. 基于混合遗传算法的混凝土大坝力学参数反演. 大连理工大学学报, 2004, 44(2):195-199.
赵 莉, 董玉民. 基于量子遗传的混合粒子群优化算法. 计算机工程与设计, 2014, 35(7): 2566-2577.
梁昌勇, 柏 桦, 蔡美菊,等. 量子遗传算法研究进展. 计算机应用研究, 2012, (7):2401-2405.
王竹荣, 杨 波, 吕兴朝,等. 一种改进的量子遗传算法研究. 西安理工大学学报, 2012, 28(2): 145-151.
许 波, 彭志平, 余建平. 一种基于云模型的改进型量子遗传算法. 计算机应用研究, 2011, 28(10): 3684-3686.
向 衍, 郑东健, 何旭升,等. 基于MSC.Marc的物理力学参数反演. 水电能源科学, 2003, 21(4): 7-10.
杨俊安, 解光军, 庄镇泉,等. 量子遗传算法及其在图像盲分离中的应用研究. 计算机辅助设计与图形学学报, 2003, (7):847-852.
范胜辉. 量子进化算法及其应用研究. 南京:南京航空航天大学, 2010.
罗红明. 量子遗传算法及其在地球物理反演中的应用研究. 武汉:中国地质大学, 2007.
PDF(805 KB)

Accesses

Citation

Detail

Sections
Recommended

/