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Identification of parameters in nonlinear geotechnical models using extenden Kalman filter

机译:使用扩展卡尔曼滤波器的非线性岩土模型参数识别

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Direct measurement of relevant system parameters often represents a problem due to different limitations. In geomechanics, measurement of geotechnical material constants which constitute a material model is usually a very diffcult task even with modern test equipment. Back-analysis has proved to be a more effcient and more economic method for identifying material constants because it needs measurement data such as settlements, pore pressures, etc., which are directly measurable, as inputs. Among many model parameter identification methods, the Kalman filter method has been applied very effectively in recent years. In this paper, the extended Kalman filter – local iteration procedure incorporated with finite element analysis (FEA) software has been implemented. In order to prove the effciency of the method, parameter identification has been performed for a nonlinear geotechnical model.
机译:由于不同的限制,直接测量相关的系统参数通常会带来问题。在地质力学中,即使使用现代测试设备,构成材料模型的岩土材料常数的测量通常也是非常困难的任务。事实证明,反向分析是一种识别材料常数的更有效,更经济的方法,因为它需要直接测量的诸如沉降,孔隙压力等测量数据作为输入。在许多模型参数识别方法中,卡尔曼滤波方法近年来得到了非常有效的应用。在本文中,已实现了扩展卡尔曼滤波器-结合有限元分析(FEA)软件的局部迭代程序。为了证明该方法的有效性,已经对非线性岩土模型进行了参数识别。

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