基于实数编码遗传算法的桥梁有限元模型修正方法

韩万水; 刘修平; 邓露; 杜群乐; 李光玲

doi:10.19818/j.cnki.1671-1637.2019.02.002

基于实数编码遗传算法的桥梁有限元模型修正方法

doi: 10.19818/j.cnki.1671-1637.2019.02.002

1.
长安大学公路学院, 陕西西安 710064
2.
湖南大学土木工程学院, 湖南长沙 410082
3.
石家庄市交通运输局, 河北石家庄 050051

基金项目:

国家自然科学基金项目 51878058

详细信息

作者简介:
韩万水(1977-), 男, 河南开封人, 长安大学教授, 工学博士, 从事风-车-桥耦合振动研究

中图分类号: U441.22
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出版历程
- 收稿日期: 2018-10-23
- 刊出日期: 2019-04-25

Updating method of bridge finite element model based on real coded genetic algorithm

1.
School of Highway, Chang'an University, Xi'an 710064, Shaanxi, China
2.
College of Civil Engineering, Hunan University, Changsha 410082, Hunan, China
3.
Shijiazhuang Transport Bureau, Shijiazhuang 050051, Hebei, China

More Information

Author Bio:
HAN Wan-shui (1977-), male, professor, PhD, hws_freedom@163.com

摘要

摘要: 为克服传统桥梁有限元模型修正迭代优化过程中存在的局部收敛和提高模型修正精度, 提出了联合实数编码遗传算法与静动力实测数据的有限元模型修正方法; 引入四边形等参元理论和牛顿迭代法编制宏命令, 实现有限元模型中车辆荷载的快速自动加载; 基于结构有限元模型静动力特性构造目标函数, 以实数编码遗传算法为优化策略, 采用MATLAB平台建立了有限元模型修正框架; 通过对一个简支框架结构的数值模拟, 对比了所提出优化方法与其他方法的收敛效率和修正结果, 以验证所提出方法的有效性; 采用拉丁超立方体抽样分析了有限元模型参数变化对桥梁动力响应的影响, 以确定待修正参数, 并采用所提方法修正了一座改建的空心板桥梁的实体有限元模型。分析结果表明: 零阶算法和一阶算法对参数的敏感性和修正范围依赖大, 选用敏感性较小的参数或者参数修正范围大于50%将会导致错误的修正结果; 实数编码遗传算法对初始输入不敏感, 可避免局部收敛的情况; 采用灵敏度分析得到的主要待修正参数有空心板弹性模量、现浇层弹性模量以及支座横桥向和顺桥向的约束刚度; 修正后的空心板弹性模量增幅约为19.13%, 现浇层弹性模量增幅约为16.00%, 横向约束刚度增幅约为46.21%, 纵向约束刚度增幅约为72.72%, 修正后的有限元模型的静动力特性与实测响应吻合良好, 各测点静力响应误差均小于4%, 动力响应误差小于3%。
- 桥梁工程 /
- 有限元模型 /
- 修正方法 /
- 实数编码遗传算法 /
- 静动力特性 /
- 目标函数 /
- 基准模型
Abstract: To overcome the local convergence and improve the corrective accuracy in the modified iterative optimization process of traditional finite element model, an updating method was proposed by combining the real coded genetic algorithm (RCGA) and measured data of static and dynamic characteristics. The quadrilateral isoparametric element theory and Newton iteration method were used to compile the macro command to realize the fast automatic loading of vehicle loads in the FEM. The objective function was constructed by the static and dynamic characteristics of the finite element model of the structure, the RCGA was taken as the optimization strategy, and the modification frame of the model was established by the MATLAB platform. Through the numerical simulation of a frame structure, the convergence efficiencies and updating results of the proposed optimization method and other methods were compared to verify the effectiveness of the proposed method. To determine the modified parameters, the Latin hypercube sampling method was used to analyze the parametric influence of finite element model on the dynamic responses of the bridge, and the proposed method was applied to modify the solid finite element model of a reconstructed hollow slab bridge. Analysis result shows that the zero order algorithm and the first order algorithm are depended on the sensibilities and correction ranges of the parameters. When the parameters have less sensitivities or the correction ranges are greater than 50%, the correction result of the model is erroneous. The RCGA is insensitive to the initial inputs, so the local convergence can be avoided. The main parameters to be corrected by the sensitivity analysis are the elastic modulus of hollow slab, the elastic modulus of cast-in-situ layer and the longitudinal and transversal restraint stiffnesses of the supports. After correction, the elastic modulus of hollow slab increases by about 19.13%, the elastic modulus of cast-in-situ layer increases by about 16.00%, the lateral restraint stiffness increases by about 46.21%, and the longitudinal restraint stiffness increases by about 72.72%. The static and dynamic characteristics of the modified finite element model are in good agreement with the measured responses, the errors of static responses are less than 4%, and the errors of dynamic responses are less than 3%.
- bridge engineering /
- finite element model /
- updating method /
- RCGA /
- static and dynamic characteristic /
- baseline model /

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图 1 车轮荷载分配

Figure 1. Wheel load distribution

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图 2 四节点等参元关系

Figure 2. Isoparametric relationship of four nodes

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图 3 有限元模型优化流程

Figure 3. Optimization flow of FEM

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图 4 简支框架结构(单位: m)

Figure 4. Simple supported frame structure (unit: m)

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图 5 优化函数最小值

Figure 5. Optimized function minima

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图 6 CPU运行时间

Figure 6. CPU runtimes

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图 7 基于RCGA的收敛过程

Figure 7. Convergence process based on RCGA

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图 8 竖向位移对比

Figure 8. Comparison of vertical displacements

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图 9 竖弯模态频率对比

Figure 9. Comparison of vertical bending modal frequencies

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图 10 空心板

Figure 10. Hollow slab

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图 11 静力加载工况(单位: m)

Figure 11. Static loading conditions (unit: m)

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图 12 自振特性测试工况

Figure 12. Test condition of self-vibration characteristics

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图 13 主振动方向的实测振型

Figure 13. Measured vibration modes in main vibration direction

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图 14 参数灵敏度

Figure 14. Sensitivities of parameters

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图 15 部分参数迭代过程

Figure 15. Iterative processes of partial parameters

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图 16 目标函数收敛过程

Figure 16. Convergence process of objective function

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图 17 中载工况竖向位移对比

Figure 17. Comparison of vertical displacements under medium loading conditions

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图 18 偏载工况竖向位移对比

Figure 18. Comparison of vertical displacements under unbalance loading conditions

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表 1 静力工况下竖向位移对比

Table 1. Comparison of vertical displacements under static condition

测试点	初始模型位移/mm	试验模型位移/mm	误差/%
4	0.258	0.347	25.70
6	0.331	0.447	25.88
7	0.318	0.429	25.89
15	0.258	0.342	24.65
17	0.331	0.439	24.55
18	0.318	0.421	24.55

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表 2 动力工况下竖弯模态频率对比

Table 2. Comparison of vertical bending modal frequencies under dynamic condition

振动模态	初始模型位移/Hz	试验模型位移/Hz	误差/%
S₁	9.35	8.09	15.62
S₂	37.16	32.02	16.07
S₃	61.39	60.27	1.86
S₄	82.60	70.71	16.82

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表 3 修正结果对比

Table 3. Comparison of modification results

刚度系数组合	RCGA	ANSYS零阶优化算法	ANSYS一阶优化算法
I: (1.0, 1.0, 1.0)	(0.53, 0.97, 0.98)	(1.44, 0.10, 0.53)	(0.74, 0.75, 0.99)
II: (0.6, 1.0, 1.0)	(0.53, 0.97, 0.98)	(0.34, 1.13, 0.52)	(0.55, 0.95, 0.99)
III: (0.3, 1.0, 1.0)	(0.53, 0.97, 0.98)	(0.65, 0.82, 1.48)	(0.41, 1.09, 1.00)

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表 4 材料特性

Table 4. Material properties

弹性模量/GPa	泊松比	密度/ (kg·m^-3)
34.5	0.2	2 500

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表 5 初始边界条件

Table 5. Initial boundary condition

K_y/ (MN·m^-1)	K_z/ (kN·m^-1)	K_x/ (kN·m^-1)
140	660	660

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表 6 修正前后结构频率对比

Table 6. Comparison of structure frequencies before and after modification

频率	初始值/Hz	实测值/Hz	初始误差/%	修正值/Hz	修正误差/%
H	1.732	2.083	16.830	2.077	0.270
L	1.733	2.264	23.450	2.261	0.120
V₁	8.280	8.748	5.350	8.869	-1.390
V₂	27.102	28.261	4.100	28.830	-2.010

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表 7 有限元模型修正前后参数比较

Table 7. Parameters comparison before and after FEM modification

参数	E_c/GPa	E_g/GPa	E_p/GPa	D_g/ (kg·m^-3)	D_h/ (kg·m^-3)	K_x/ (kN·m^-1)	K_z/ (kN·m^-1)
修正前	34.50	34.50	34.50	2 500.00	2 500.00	660.00	660.00
修正后	40.02	41.10	35.54	2 540.00	2 543.00	1 139.95	964.98
变化幅度/%	16.00	19.13	3.01	1.60	1.72	72.72	46.21

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