Study And Application On Random Inverse Analysis In Geomechanical Engineering

ABSTRACTAccording to the defect of the conventional Bayes' method in the geomechanical engineering back analysis, expanding Bayes' method was established in this paper. With the applications of the probability theory and the mathematical statistics principle, the geomechanical engineering random back analysis objects function was founded based on the AIC criterion of the decision information theory and the maximum entropy criterion, a the matching question between the observed information and the previous information of the conventional Bayes' method were proposed. In addition, the least square method, maximum likelihood method and conventional Bayes' method were unified in form. The predicted model can be identified by quality and quantity from the observed values.Two objects functions were deduced, which of the maximum likelihood method and the conventional Bayes' method, with the application of principle of maximum entropy. Under the information theory, more applications are provided to those back analysis methods.Based on the Duncan-Chang E-B model, which can simulate earth-rock dam's non-linear mechanics behavior well, the paper introduced the nature coordinate system to the stress space. In this way, hydrostatic stress and stress deviator were decomposed each other. Therefore, a partial derivative formulation about displacement and parameter in finite element evaluation was derived in a closed form. On the same time, a displacement-weighted method was suggested to resolve the behavior of displacement factor in the parameter sensitivity analysis.Using the soft of object-orient, PowerBuilder, and DLL theory, an object-oriented back analysis method was studied, which defined the relationship of object classes, established a message flow of finite element, and also made program of friendly interface and efficient operation.The models and analytical methods presented above were verified by some numerical examples, and were applied successfully to the Huanghe XiaoLangDiHydro-Junction Project softy monitoring system. The results show that the models and methods proposed in this paper have so good foundation and emulation that a wide range of application can be provided.