Stochastic analysis model of uncertain temperature characteristics for embankment in warm permafrost regions

• Published in: Cold regions science and technology Vol. 109; pp. 43 - 52
• Main Authors: Wang, Tao, Zhou, Guoqing, Wang, Jianzhou, Zhao, Xiaodong, Yin, Qixiang, Xia, Lijiang, Liu, Yuyi
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.01.2015
• Subjects: Boundary conditions; Embankment in warm permafrost region; Embankments; Finite element method; Local average; Mathematical models; Matlab; Random field; Soil (material); Stochastic finite element; Stochastic processes; Stochasticity; Uncertain temperature characteristic; Uncertain temperature characteristic; Random field; Stochastic finite element; Local average; Embankment in warm permafrost region
• ISSN: 0165-232X; 1872-7441
• DOI: 10.1016/j.coldregions.2014.09.013

For embankments in cold regions, the soil properties and the upper boundary conditions are stochastic because of complex geological processes and changeable atmospheric environment. In this study, we model the soil properties as random fields and the upper boundary conditions as stochastic processes. A triangular local average (TLA) method is used to discretize the two-dimensional (2D) random fields. The random temperature fields of an embankment in a cold region are investigated by Neumann stochastic finite element method (NSFEM), and the computational formulas of mean and standard deviation are developed. In the calculation flow chart, a stochastic finite element (FE) program has been compiled by Matrix Laboratory (MATLAB) software. The results show that TLA method perfectly matches with triangular FE method. The randomness of soil properties and boundary conditions lead to the randomness of temperature. The results will improve our understanding of the random temperature field of embankments in cold regions. The proposed method can be used to solve other uncertain thermodynamic problems. •We model soil properties as random fields and boundary conditions as stochastic processes.•Triangular local average method is used to discretize two-dimensional random field.•A stochastic analysis model is established to calculate the random temperature field.•The stochastic model can be directly used by other uncertain thermodynamic problems.