In the context of mathematical modeling, it is sometimes convenient to employ models of different dimensionality simultaneously, even for a single physical phenomenon. However, this type of combination might entail difficulties even when individual models are well-understood, particularly in relation to well-posedness. In this article, we focus on combining two diffusive models, one defined over a continuum and the other one over a curve. The resulting problem is of mixed-dimensionality, where here the low-dimensional problem is embedded within the high-dimensional one. We show unconditional stability and convergence of the continuous and discrete linked problems discretized by mixed finite elements. The theoretical results are highlighted with numerical examples illustrating the effects of linking diffusive models. As a side result, we show that the methods introduced in this article can be used to infer the solution of diffusive problems with incomplete data. The findings of this article are of particular interest to engineers and applied mathematicians and open an avenue for further research connected to the field of data science.
翻译:在数学建模方面,有时可以同时使用不同维度的模型,即使是单一的物理现象,但这种组合可能带来困难,即使个别模型非常清楚,特别是井井有条。在本条中,我们侧重于将两种不同维度模型结合起来,一种是连续的,另一种是曲线的。由此产生的问题是混合维度问题,其中低维问题嵌入高维问题。我们显示了由混合的有限要素分离的连续和离散的相关问题的无条件稳定性和趋同性。理论结果以数字例子来突出说明连接不同维度模型的效果。作为副结果,我们表明,本条采用的方法可以用来推断用不完整的数据解决不同维度问题的方法。这一条的发现对工程师来说特别有意义,并应用数学家,为与数据科学领域有关的进一步研究开辟了一条途径。