Diaz Manuel I, Aquino Wilkins, Bonnet Marc
Department of Civil and Environmental Engineering, Duke University, Durham, North Carolina 27708 USA.
POems (UMR 7231 CNRS-ENSTA-INRIA), Dept. of Appl. Math., ENSTA, Paris, France.
Comput Methods Appl Mech Eng. 2015 Nov 1;296:129-149. doi: 10.1016/j.cma.2015.07.025.
This paper presents a methodology for the inverse identification of linearly viscoelastic material parameters in the context of steady-state dynamics using interior data. The inverse problem of viscoelasticity imaging is solved by minimizing a modified error in constitutive equation (MECE) functional, subject to the conservation of linear momentum. The treatment is applicable to configurations where boundary conditions may be partially or completely underspecified. The MECE functional measures the discrepancy in the constitutive equations that connect kinematically admissible strains and dynamically admissible stresses, and also incorporates the measurement data in a quadratic penalty term. Regularization of the problem is achieved through a penalty parameter in combination with the discrepancy principle due to Morozov. Numerical results demonstrate the robust performance of the method in situations where the available measurement data is incomplete and corrupted by noise of varying levels.
本文提出了一种在稳态动力学背景下利用内部数据对线性粘弹性材料参数进行逆识别的方法。通过最小化本构方程中的修正误差(MECE)泛函,并满足线性动量守恒,解决了粘弹性成像的逆问题。该处理方法适用于边界条件可能部分或完全未明确指定的构型。MECE泛函测量连接运动学上许可应变和动力学上许可应力的本构方程中的差异,并在二次惩罚项中纳入测量数据。通过惩罚参数结合莫罗佐夫差异原理实现问题的正则化。数值结果表明,在可用测量数据不完整且受到不同水平噪声干扰的情况下,该方法具有稳健的性能。