Can supervise: YES
Feng, Y, Gao, W, Wu, D & Tin-Loi, F 2019, 'Machine learning aided stochastic elastoplastic analysis', Computer Methods in Applied Mechanics and Engineering, vol. 357.View/Download from: Publisher's site
© 2019 Elsevier B.V. The stochastic elastoplastic analysis is investigated for structures under plane stress/strain conditions. A novel uncertain nonlinear analysis framework, namely the machine leaning aided stochastic elastoplastic analysis (MLA-SEPA), is presented herein via finite element method (FEM). The proposed MLA-SEPA is a favourable alternative to determine structural reliability when full-scale testing is not achievable, thus leading to significant eliminations of manpower and computational efforts spent in practical engineering applications. Within the MLA-SEPA framework, an extended support vector regression (X-SVR) approach is introduced and then incorporated for the subsequent uncertainty quantification. By successfully establishing the governing relationship between the uncertain system parameters and any concerned structural output, a comprehensive probabilistic profile including means, standard deviations, probability density functions (PDFs), and cumulative distribution functions (CDFs) of the structural output can be effectively established through a sampling scheme. Consequently, the nonlinear performance of the structure against both serviceability and strength limit states can be effectively investigated with the consideration of various system uncertainties. Three numerical examples are thoroughly investigated to illustrate the accuracy, applicability and effectiveness of the proposed MLA-SEPA approach.
Yu, Y, Chen, X, Gao, W, Wu, D & Castel, A 2019, 'Modelling non-isothermal chloride ingress in unsaturated cement-based materials', Construction and Building Materials, vol. 217, pp. 441-455.View/Download from: UTS OPUS or Publisher's site
Yu, Y, Wu, D, Wang, Q, Chen, X & Gao, W 2019, 'Machine learning aided durability and safety analyses on cementitious composites and structures', International Journal of Mechanical Sciences, vol. 160, pp. 165-181.View/Download from: Publisher's site
Wu, D, Liu, A, Huang, Y, Huang, Y, Pi, Y & Gao, W 2019, 'Time dependent uncertain free vibration analysis of composite CFST structure with spatially dependent creep effects', Applied Mathematical Modelling, vol. 75, pp. 589-606.View/Download from: Publisher's site
Li, K, Wu, D, Gao, W & Song, C 2019, 'Spectral stochastic isogeometric analysis of free vibration', Computer Methods in Applied Mechanics and Engineering, vol. 350, pp. 1-27.View/Download from: Publisher's site