Abstract
The dynamic modeling of structures in a thermal environment has become a new research topic in structural dynamics. The amount of calculation caused by the complexity of the structure and the size of the FEM, which increase the difficulty in modeling the structural dynamic thermal effects are considered. In this study, model updating in thermal temperature environment is proposed based on the hierarchical method and improved SVR, and an iterative procedure is presented. First, the dynamic problem of structure under a thermal environment is classified into a thermal model and a structural dynamic model, and they are both constructed with the FE method. As a result, the model updating process is conducted for both the thermal model and structural dynamic model. Different from the variables in other model updating methods, the updating variables, which are composed of the mechanical characteristics and thermal parameters, in the proposed method are dominated by the temperature distribution of the structure. A surrogate model based on improved SVR is adopted in the hierarchical model updating approach to make the updating process more efficient. Finally, the improved SVR method is validated on a typical nonlinear function, and the proposed method is validated by updating the model of an elastic thin plate and a wing structure in a thermal environment.
Highlights
Gosselin summarized the application of genetic algorithms to heat transfer problems, mainly for thermal system design, heat transfer inverse problems and heat transfer correlations [6]. Sahoo and his colleagues used segment-by-segment linear fit, polynomial fit and a cubic spline approach to investigate the heat transfer inverse problem for hypervelocity vehicle test data, and the results showed that only the polynomial fit and the cubic spline approach obtained results that were consistent with the test data
Thermophysical Parameters Identification of Aluminum Alloy Plate. This numerical example shows the general process of identifying the thermophysical parameters, which vary with the temperature of some aluminum alloy plates according to the heat transfer coefficient, with temperature dependence based on SVR
A structural dynamic model updating method with thermal effects based on improved SVR is proposed
Summary
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. Cui [9] proposed a complex variable differentiation method to calculate the sensitivity matrix, the thermophysical properties of the material with temperature are identified by the conjugate gradient method, the functional form of the unknown parameters is not required in the calculation, and the computational efficiency and computational accuracy of the algorithm are verified using numerical calculations. Cappelli and his coworkers proposed a MSIS to identify the parameters involved in the elastic, viscoelastic in presence of uncertainty and by considering more general piezo-electric materials at each pertinent scale of the structure [10,11]. The thermophysical parameter identification method and dynamic model updating approach proposed in this manuscript were discussed and verified by several simulation examples
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