基于改进遗传算法的岩体结构面幂函数模型参数辨识

Improved GA-based identification method of power function model for rock joints

沿结构面的剪切滑移是工程岩体主要的破坏模式之一,选择恰当的岩体结构面本构模型是分析岩体结构面破坏的重要一环。当前常用的结构面本构模型有指数型模型、曲线型模型和幂函数型模型,其模型参数都是根据工程实际经验或室内试验所得,不能很好的模拟实际变形情况。指数型模型得出的模拟值偏大,曲线型模型得出的模拟值偏小,幂函数型模型在较低的法向应力下能较好的模拟剪切变形过程,但在较高的法向应力下得出的模拟值偏小。为此,通过改进的遗传算法对岩体结构面幂函数模型参数进行辨识,得出由"等效参数"构成的幂函数模型。实例验证结果说明,通过改进的遗传算法辨识出的由"等效参数"构成的幂函数模型能够很好的模拟实际变形情况,能够很好的适应于不同的工程实际应用。

Engineering practice shows that shear slip is the major failure mode of rock, so to choose the appropriate constitutive model of rock joints is an important part of analysis for failure of rock joints. Current commonly used constitutive models for deformation of rock are exponential model, curve model and power function model, their parameters come from actual experience or laboratory tests, cannot simulate well the actual deformation. Analog values derived from exponential model are too large, derived from curve model are too small, derived from power function model are too small at high stress. Due to that, a pervasive constitutive model of rock surface structure has been proposed in this paper, then its analog values have been identified through improved genetic algorithm, finally constitutive model of rock surface structure composed by ‘equivalent parameters’ has been proposed. Results from verification examples show that the constitutive model identified by improved genetic algorithm can simulate well the actual deformation, can be well adapted to different engineering applications.