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Buckling of axial compressed cylindrical shells with stepwise variable thickness
H.G. Fan,Z.P. Chen,W.Z. Feng,F. Zhou,X.L. Shen,G.W. Cao 국제구조공학회 2015 Structural Engineering and Mechanics, An Int'l Jou Vol.54 No.1
This paper focuses on an analytical research on the critical buckling load of cylindrical shells with stepwise variable wall thickness under axial compression. An arctan function is established to describe the thickness variation along the axial direction of this kind of cylindrical shells accurately. By using the methods of separation of variables, small parameter perturbation and Fourier series expansion, analytical formulas of the critical buckling load of cylindrical shells with arbitrary axisymmetric thickness variation under axial compression are derived. The analysis is based on the thin shell theory. Analytic results show that the critical buckling load of the uniform shell with constant thickness obtained from this paper is identical with the classical solution. Two important cases of thickness variation pattern are also investigated with these analytical formulas and the results coincide well with those obtained from other authors. The cylindrical shells with stepwise variable wall thickness, which are widely used in actual engineering, are studied by this method and the analytical formulas of critical buckling load under axial compression are obtained. Furthermore, an example is presented to illustrate the effects of each strake’s length and thickness on the critical buckling load.
Buckling of axial compressed cylindrical shells with stepwise variable thickness
Fan, H.G.,Chen, Z.P.,Feng, W.Z.,Zhou, F.,Shen, X.L.,Cao, G.W. Techno-Press 2015 Structural Engineering and Mechanics, An Int'l Jou Vol.54 No.1
This paper focuses on an analytical research on the critical buckling load of cylindrical shells with stepwise variable wall thickness under axial compression. An arctan function is established to describe the thickness variation along the axial direction of this kind of cylindrical shells accurately. By using the methods of separation of variables, small parameter perturbation and Fourier series expansion, analytical formulas of the critical buckling load of cylindrical shells with arbitrary axisymmetric thickness variation under axial compression are derived. The analysis is based on the thin shell theory. Analytic results show that the critical buckling load of the uniform shell with constant thickness obtained from this paper is identical with the classical solution. Two important cases of thickness variation pattern are also investigated with these analytical formulas and the results coincide well with those obtained from other authors. The cylindrical shells with stepwise variable wall thickness, which are widely used in actual engineering, are studied by this method and the analytical formulas of critical buckling load under axial compression are obtained. Furthermore, an example is presented to illustrate the effects of each strake's length and thickness on the critical buckling load.
Transport and thermodynamic properties ofSr3Ru2O7near the quantum critical point
Zhou, Z. X.,McCall, S.,Alexander, C. S.,Crow, J. E.,Schlottmann, P.,Bianchi, A.,Capan, C.,Movshovich, R.,Kim, K. H.,Jaime, M.,Harrison, N.,Haas, M. K.,Cava, R. J.,Cao, G. American Physical Society 2004 Physical review. B, Condensed matter and materials Vol.69 No.14
An improved radial basis function network for structural reliability analysis
H. Z. Dai,W. Zhao,Z. G. Cao 대한기계학회 2011 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.25 No.9
Approximation methods such as response surface method and artificial neural network (ANN) method are widely used to alleviate the computation costs in structural reliability analysis. However most of the ANN methods proposed in the literature suffer various drawbacks such as poor choice of parameter setting, poor generalization and local minimum. In this study, a support vector machine-based radial basis function (RBF) network method is proposed, in which the improved RBF model is used to approximate the limit state function and then is connected to a reliability method to estimate failure probability. Since the learning algorithm of RBF network is replaced by the support vector algorithm, the advantage of the latter, such as good generalization ability and global optimization are propagated to the former, thus the inherent drawback of RBF network can be defeated. Numerical examples are given to demonstrate the applicability of the improved RBF network method in structural reliability analysis, as well as to illustrate the validity and effectiveness of the proposed method.
Wei, L.,Cao, X.,Wang, Z.,Gao, Y.,Hu, S.,Wang, L.,Wu, G.,Shen, D. Published for the American Association of Physicis 2017 Medical physics Vol.44 No.12
<P>Conclusions: The proposed new learning-based registration method have tackled the challenging issues in registering infant brain images acquired from the first year of life, by leveraging the multi-output random forest regression with auto-context model, which can learn the evolution of shape and appearance from a training set of longitudinal infant images. Thus, for the new infant image, its deformation field to the template and also its template-like appearances can be predicted by the learned models. We have extensively compared our method with state-of-the-art deformable registration methods, as well as multiple variants of our method, which show that our method can achieve higher accuracy even for the difficult cases with large appearance and shape changes between subject and template images. (C) 2017 American Association of Physicists in Medicine</P>
A novel evidence theory model and combination rule for reliability estimation of structures
Y.R. Tao,Q. Wang,L. Cao,S.Y. Duan,Z.H.H. Huang,G.Q. Cheng 국제구조공학회 2017 Structural Engineering and Mechanics, An Int'l Jou Vol.62 No.4
Due to the discontinuous nature of uncertainty quantification in conventional evidence theory(ET), the computational cost of reliability analysis based on ET model is very high. A novel ET model based on fuzzy distribution and the corresponding combination rule to synthesize the judgments of experts are put forward in this paper. The intersection and union of membership functions are defined as belief and plausible membership function respectively, and the Murfhy’s average combination rule is adopted to combine the basic probability assignment for focal elements. Then the combined membership functions are transformed to the equivalent probability density function by a normalizing factor. Finally, a reliability analysis procedure for structures with the mixture of epistemic and aleatory uncertainties is presented, in which the equivalent normalization method is adopted to solve the upper and lower bound of reliability. The effectiveness of the procedure is demonstrated by a numerical example and an engineering example. The results also show that the reliability interval calculated by the suggested method is almost identical to that solved by conventional method. Moreover, the results indicate that the computational cost of the suggested procedure is much less than that of conventional method. The suggested ET model provides a new way to flexibly represent epistemic uncertainty, and provides an efficiency method to estimate the reliability of structures with the mixture of epistemic and aleatory uncertainties.