Research On Stochastic Temperature Field And Deformation Reliability Of Qinghai-Tibet Railway Roadbed

Qinghai-Tibet Railway is a great project of the Western Development in China. Researches on frozen soil problems become more and more important because of its fatal effect to the railway. Based on the analysis of thermal regime of the railway roadbed, the deformation and reliability of the roadbed were studied systemically in the thesis according to current situation and demand of frozen soil engineering. The main contents of the thesis are summarized as follows:1. Based on the analysis of the characteristics of permafrost engineering and the detailed review of the past research achievements, an evaluation system for thermal regime calculating and deformation evaluating of permafrost roadbed was made for the first time. It can be used as a basis for evaluating the effect of the structure, guiding and ameliorating the design of construction.2. The conception of random fields was introduced and stochastic finite element formulas were formed by use of perturbation stochastic finite element method. At the same time, random temperature field of frozen soil roadbed in Bailu River of Qinghai-Tibet Railway is calculated as an example. The result shows that the randomicity of environmental temperature is the main factor affecting the random temperature field of the roadbed. The temperature-standard deviation is remarkable at the top of the roadbed and diminishes with the depth, and it increases sharply with the time and the rising of coefficient of variation of thermal parameters.3. Aiming at current methods have their disadvantage on deformation calculation of permafrost engineering, the BP neural network was introduced and the non-linear function of deformation and its influence factors were established by BP neural network. The deformation of permafrost roadbed in Bailu River of Qinghai-Tibet Railway was predicted as an example. The result shows the process of the freezing heaving and thawing of the frozen soil roadbed and indicates the accuracy and practicability of BP neural network.4. Reliability index was used instead of safety factor to evaluate the stability of permafrost roadbed. An optimal model was built up for the calculation of reliability index according to its geometry meaning. Penalty function and genetic algorithm were given to deal with the problems of complexity and slow convergence in the solution of the model.5. Response Surface method was used for the engineering problem that their ultimate condition equation couldn't be exactly expressed. Adoption of BP-ANN method, the Response Surface Reliability Analysis method was used to form the Response Surface function and get the reliability index.6. The evaluation model was used to analysis the reliability of frozen soil roadbed in Bailu River of Qinghai-Tibet and reliability index and failure probability were obtained. The result shows that the reliability of the roadbed is determined mainly by the temperature deviation. With the rising of temperature deviation, the reliability index decreases quickly and the failure probability increases sharply.7. Against the deficiency of the traditional design principles based on experience, a prediction and evaluation method for the deformation of permafrost roadbed was established based on the measurement data. Quantitative and scientific design can be achieved by using of this method for the improvement and reinforcement of the roadbed.