Structure Statics Finite Element Model Updating Based on Response Surface Methodology

Deng, Miao Yi; Li, Guang Hui

doi:10.4028/www.scientific.net/amr.255-260.1939

Cited by 4 publications

(5 citation statements)

References 5 publications

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“…To cut down the cost, the response surface methodology is used in the optimization design. the detailed descriptions of the Response surface method can be found in research results [4][5][6].Generally, an objective function of design optimization can be formulated as follows [7]: Minimize:…”

Section: Mathematical Model Of the Methodsmentioning

confidence: 99%

The Multi-Objective Optimization of the Planet Carrier in Wind Turbine Gearbox

Dong

Chen

2012

AMM

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In order to improve the reliability of a planet carrier, a simulation method based on multi-objective design optimization was developed in this paper. The objective of the method was to reduce the stress concentration, the deformation, and the quality of the planet carrier by optimizing the structure dimension. A parametric finite element model, which enables a good understanding of how the parameters affect the reliability of planet carrier, was established and simulated by ANSYS-WORKBENCH. The efficiency of the design optimization was improved by using a polynomials response surface to approximate the results of finite element analysis and a screening algorithm to determine the direction of optimization. Furthermore, the multi-objective optimization was capable of finding the global minimum results in the use of the minimum principle on the response surface. Computer simulation was carried out to verify the validity of the presented optimization method, by which the quality and the stability of the planet carrier were significantly reduced and improved, respectively. The methodology described in this paper can be effectively used to improve the reliability of planet carrier.

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Section: Mathematical Model Of the Methodsmentioning

confidence: 99%

The Multi-Objective Optimization of the Planet Carrier in Wind Turbine Gearbox

Dong

Chen

2012

AMM

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“…One possible way to improve computational efficiency is to use some machine learning methods in the process of model calibration. For example, Karimi et al [13] used the artificial neural network (ANN) and Deng et al [14] used the response surface model instead of the FEM to calculate the modal parameters of a structure during the optimizing search process. Response surfaces, ANN and some other traditional machine learning methods are based on the empirical risk minimization (ERM) [15], which requires a large amount of training samples and may cause an over-fitting problem.…”

Section: Introductionmentioning

confidence: 99%

The dynamic finite element model calibration method of concrete dams based on strong-motion records and multivariate relevant vector machines

Cheng¹,

Zheng²,

Tong³

et al. 2016

J. vibroeng.

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In this work, a new finite element (FE) model calibration method of concrete dams based on strong-motion records and multivariate relevant vector machines (MRVM) is proposed. The modal features of a dam are extracted using second order blind identification (SOBI) based method at first. For some selected combinations of uncertain parameters of the FE model using the Latin hypercube design, the corresponding structural modal features are calculated using the finite element method (FEM). With these data, a procedure to calibrate the uncertain parameters of a dam's dynamic FE model is developed. By taking the uncertain parameters as inputs and the calculated structural modal features using FEM as outputs, the MRVM model is trained to record the complex relationship between them. Then, the genetic algorithm (GA) is adopted to solve the optimization problem corresponding to the dynamic FE model calibration problem, and the trained MRVM model, instead of FEM, is used to obtain the modal parameters of a dam for different feasible solutions during the optimization search process to improve the computational efficiency. Using the simulated seismic response records of a numerical example the accuracy, robustness and computation efficiency of the proposed dynamic FE model calibration method is verified. The analysis result using the strong-motion records of a realistic concrete dam indicates that the proposed dynamic FE model calibration method has good performance.

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“…A comprehensive description of RSM theory can be found in [20]. Apart from chemistry and other realms of industry, RSM has also been introduced into the reliability analysis and model validation of mechanical and civil structures [21][22][23] and, moreover, it has been found to possess the capability of model updating [24][25][26]. By adopting the design of experiment (DOE) [27], RSM requires much lower training and construction efforts than the conventional FEMU-or NNbased methods.…”

Section: Introductionmentioning

confidence: 99%

“…The stiffness quantities and modal frequencies were used as input parameters and responses, respectively, and the authors found that, compared with the sensitivitybased FEMU, the RSM-based method gave likewise accurate predictions but was much more cost efficient than the former. Deng et al [25] utilized uniform design to generate an RS model for updating a numerical two-span continuous beam and it was observed that, compared with the conventional FEMUbased methods, the RSM-based method considerably improved updating efficiency without losing prediction accuracy. In another piece of research performed by Ren and Chen [26], the FD and the CCD with the modal frequencies as the responses were successfully applied to update a numerical beam and a tested full-scale box girder bridge, and similar conclusions as stated in [24] and [25] were found.…”

Section: Introductionmentioning

confidence: 99%

“…Deng et al [25] utilized uniform design to generate an RS model for updating a numerical two-span continuous beam and it was observed that, compared with the conventional FEMUbased methods, the RSM-based method considerably improved updating efficiency without losing prediction accuracy. In another piece of research performed by Ren and Chen [26], the FD and the CCD with the modal frequencies as the responses were successfully applied to update a numerical beam and a tested full-scale box girder bridge, and similar conclusions as stated in [24] and [25] were found.…”

Section: Introductionmentioning

confidence: 99%

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A response surface methodology based damage identification technique

Fang

Perera

2009

Smart Mater. Struct.

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Response surface methodology (RSM) is a combination of statistical and mathematical techniques to represent the relationship between the inputs and outputs of a physical system by explicit functions. This methodology has been widely employed in many applications such as design optimization, response prediction and model validation. But so far the literature related to its application in structural damage identification (SDI) is scarce. Therefore this study attempts to present a systematic SDI procedure comprising four sequential steps of feature selection, parameter screening, primary response surface (RS) modeling and updating, and reference-state RS modeling with SDI realization using the factorial design (FD) and the central composite design (CCD). The last two steps imply the implementation of inverse problems by model updating in which the RS models substitute the FE models. The proposed method was verified against a numerical beam, a tested reinforced concrete (RC) frame and an experimental full-scale bridge with the modal frequency being the output responses. It was found that the proposed RSM-based method performs well in predicting the damage of both numerical and experimental structures having single and multiple damage scenarios. The screening capacity of the FD can provide quantitative estimation of the significance levels of updating parameters. Meanwhile, the second-order polynomial model established by the CCD provides adequate accuracy in expressing the dynamic behavior of a physical system.

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Structure Statics Finite Element Model Updating Based on Response Surface Methodology

Cited by 4 publications

References 5 publications

The Multi-Objective Optimization of the Planet Carrier in Wind Turbine Gearbox

The Multi-Objective Optimization of the Planet Carrier in Wind Turbine Gearbox

The dynamic finite element model calibration method of concrete dams based on strong-motion records and multivariate relevant vector machines

A response surface methodology based damage identification technique

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