We consider the identifiability and stable numerical estimation of multiple parameters in a Cahn-Hilliard model for phase separation. Spatially resolved measurements of the phase fraction are assumed to be accessible, with which the identifiability of single and multiple parameters up to certain scaling invariances is established. A regularized equation error approach is proposed for the stable numerical solution of the parameter identification problems, and convergence of the regularized approximations is proven under reasonable assumptions on the data noise. The viability of the theoretical results and the proposed methods is demonstrated in numerical tests.
翻译:我们认为,Cahn-Hilliard 模型中多种参数的可识别性和稳定的数值估计是分阶段分离的。对阶段分数的空间分辨率测量假定是无障碍的,可以据此确定某种伸缩差异之前的单项和多重参数的可识别性。为参数识别问题的稳定数字解决方案提出了常规方程式错误方法,在对数据噪音的合理假设下,对正统近似值的趋同得到了证明。理论结果和拟议方法的可行性在数字测试中得到了证明。