Construction of Stiffness and Flexibility for Substructure-Based Model Updating

Weng, Shun; Zhu, Hong; Xia, Yong; Ye, Ling; Hu, Xian Yan

doi:10.1155/2013/706798

Cited by 10 publications

(7 citation statements)

References 28 publications

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“…Sensors were intensely arranged on this substructure to obtain detailed measurements for the comparative study, as shown in Figure 5. As long as the analytical model is accurate and reliable, the stiffness of the substructure can be estimated through model-updating (Weng et al, 2013) or minimization of modal dynamic residuals as Zhu et al (2016) implemented on a space frame bridge.…”

Section: Experimental Methodsmentioning

confidence: 99%

Modal testing and detection of pretension deviation in a cable dome structure

Liu

Dong

Liang

2018

Advances in Structural Engineering

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Pretension deviation may cause stiffness degradation and overstress that can compromise the safety of tensile structures, which can be diagnosed by modal identification. This article presents modal tests on a 1:10 scaled model of a herringbone-ribbed cable dome structure. An optimal sensor placement scheme is proposed to observe the geometric stiffness change induced by pretension deviation. Based on the tests, different output-only modal identification techniques were implemented. A substructure strategy was adopted to overcome the limited measurement quantity and provide localized diagnoses. The experimental results show that operational modal analysis methods based on output-only data can effectively identify major modes of massive structures. The sensitivity of modal characteristics to pretension deviation is also evaluated via experimental comparisons, and modifications are implemented in an analytical finite element model to approximate the test model. The identified modal information can help locate stiffness degradation and thereby pretension loss in tensile structures. A modified modal strain energy method is proposed to detect pretension loss from decentralized testing and is verified by the test results.

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Section: Experimental Methodsmentioning

confidence: 99%

Modal testing and detection of pretension deviation in a cable dome structure

Liu

Dong

Liang

2018

Advances in Structural Engineering

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“…One of the essential components in modeling vehiclebridge interaction is the bridge subsystem. In FEM, a bridge is typically discretized as finite elements and solved by the stiffness method [2,4,41,73,[76][77][78][79][80][81][82][83][84]. Rieker et al studied the influence of discretization of beams on the dynamic response of elastic beams under moving load [1].…”

Section: Introductionmentioning

confidence: 99%

Coupled Dynamics of Vehicle‐Bridge Interaction System Using High Efficiency Method

Sun

Zhao

2021

Advances in Civil Engineering

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Vehicle-bridge interaction is the core for a variety of applications, including vehicle vibration, bridge vibration, bridge structural health monitoring, weight-in-motion, bridge condition inspection, and load rating. These applications give rise to a great interest in pursuing a high-efficiency method that can tackle intensive computation in the context of vehicle-bridge interaction. This paper studies the accuracy and efficiency of discretizing the beam in space as lumped masses using the flexibility method and as finite elements using the stiffness method. Computational complexity analysis is carried out along with a numerical case study to compare the accuracy and efficiency of both methods against the analytical solutions. It is found that both methods result in a similar level of accuracy, but the flexibility method overperforms the stiffness method in terms of computational efficiency. This high efficiency algorithm and corresponding discretization schema are applied to study the dynamics of vehicle-bridge interaction. A system of coupled equations is solved directly for a simply supported single-span bridge and a four-degree-of-freedom vehicle modeling. Pavement roughness significantly influences dynamic load coefficient, suggesting preventative maintenance or timely maintenance of pavement surface on a bridge, to reduce pavement roughness, is of significant importance for bridge’s longevity and life-cycle cost benefit. For class A and B level pavement roughness, the dynamic load coefficient is simulated within 2.0, compatible with specifications of AASHTO standard, Australian standard, and Switzerland standard. However, the Chinese code underestimates the dynamic load coefficient for a bridge with a fundamental frequency of around 4 Hz. The proposed method is applicable to different types of bridges as well as train-bridge interaction.

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“…The model updating based on the sensitivity of FRFs attracted wide attention in the early 1990 s [23]. Sipple et al [24] proposed a new FE model updating method that uses numerical sensitivity instead of analytical sensitivity to solve inverse problems, which does not need model reduction and data extension, and has good robustness, stability and fault tolerance; Weng et al [25] proposed a new iterative substructuring method to accurately obtain the characteristic solution and characteristic sensitivity of the structure, which is suitable for model updating of large and complex structures; Jiang et al [26] expressed the thermal dependent elastic constants and thermal expansion coefficients as intermediate function by temperature independent variables, and used the perturbation method to calculate the sensitivity for parameter identification; On the basis of the basic concept of unconstrained optimization problem and three regularization solutions, Mohammad et al [27] proposed a novel sensitivity based FE model updating method, and simultaneously updated the element mass matrix and stiffness matrix of the FE model; Esfandiari et al [28] proposed a FE model updating method using incomplete strain data in frequency domain to detect variations in stiffness and mass parameters.…”

Section: Introductionmentioning

confidence: 99%

Model Updating Using Frequency Response Functions Based on Sherman–Morrison Formula

Zhu

Cao

et al. 2020

Applied Sciences

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Model updating plays an important role in dynamics modeling with high accuracy, which is widely used in mechanical engineering. In this paper, a model updating method using frequency response function (FRF) is proposed based on Sherman–Morrison formula, in which only the initial FRFs and parameter perturbations are employed to calculate the sensitivity avoiding repeated finite element (FE) analyses and improving the computational efficiency. Firstly, the sensitivity of FRFs to the design parameters is calculated by Sherman–Morrison formula based on the QR decomposition of the system dynamic stiffness matrix variation after parameter perturbations, then the influence of damping on the amplitude of FRFs is considered to select an appropriate frequency range, and finally conduct the model updating according to the sensitivity of the FRFs. By employing simulation examples of a truss and a solar wing and the experiment of an aluminum frame, the updating error is still within ±1.00% in the condition of 5% random white noise, which shows the proposed method has high accuracy and a certain anti-noise capability. When only a few numbers of frequency points are selected near the resonance peak of the FRFs, the result shows that selecting the appropriate frequency range and points can reduce the computational cost. The results of the experiment study show that the proposed method can effectively identify the structural parameters. The above results verify the feasibility and effectiveness of proposed model updating method using FRFs.

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Construction of Stiffness and Flexibility for Substructure-Based Model Updating

Cited by 10 publications

References 28 publications

Modal testing and detection of pretension deviation in a cable dome structure

Modal testing and detection of pretension deviation in a cable dome structure

Coupled Dynamics of Vehicle‐Bridge Interaction System Using High Efficiency Method

Model Updating Using Frequency Response Functions Based on Sherman–Morrison Formula

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