Burman Erik, Oksanen Lauri
Department of Mathematics, University College London, Gower Street, London, WC1E 6BT UK.
Numer Math (Heidelb). 2018;139(3):505-528. doi: 10.1007/s00211-018-0949-3. Epub 2018 Feb 10.
We consider data assimilation for the heat equation using a finite element space semi-discretization. The approach is optimization based, but the design of regularization operators and parameters rely on techniques from the theory of stabilized finite elements. The space semi-discretized system is shown to admit a unique solution. Combining sharp estimates of the numerical stability of the discrete scheme and conditional stability estimates of the ill-posed continuous pde-model we then derive error estimates that reflect the approximation order of the finite element space and the stability of the continuous model. Two different data assimilation situations with different stability properties are considered to illustrate the framework. Full detail on how to adapt known stability estimates for the continuous model to work with the numerical analysis framework is given in "Appendix".
我们考虑使用有限元空间半离散化对热方程进行数据同化。该方法基于优化,但正则化算子和参数的设计依赖于稳定有限元理论中的技术。空间半离散系统被证明有唯一解。结合离散格式数值稳定性的精确估计和不适定连续偏微分方程模型的条件稳定性估计,我们随后推导出反映有限元空间逼近阶数和连续模型稳定性的误差估计。考虑了两种具有不同稳定性的不同数据同化情况以说明该框架。关于如何使连续模型的已知稳定性估计适用于数值分析框架的完整细节在“附录”中给出。