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Discontinuous Galerkin solver for the unsteady advection-reaction-diffusion equation. Applications to the simulation and parameter identification of a root growth model

机译:非平稳对流反应扩散方程的不连续Galerkin求解器。在根生长模型的仿真和参数识别中的应用

摘要

Root systems are important for plants but they are difficult to study because of heavy constraints of field experiments. Modelling and simulation of root systems are crucial tools to better understand root systems, but also to design new experiments. Among the various modelling approaches, the density approach consists in following the evolution over time and space of the root biomass density in the soil. The root density satisfies an unsteady advection-reaction-diffusion equation with coefficients varying in space and time according to the physiological phases of the root growth. At the moment there is no direct field experiment that can estimate or measure some of the coefficients of the equation. But since we know how to estimate the root density the missing coefficients are determined by solving an inverse problem. The problem is solved on unstructured meshes so that it allows the treatment of complex geometries and mesh refinements. It is well known that the Lagrange finite element method suffers from a lack of stability because of the advection term. Since our applications require the treatment of discontinuous parameters for example in the case of a stratified soil, we implemented an approximation based on Discontinuous Galerkin (DG) method. In the talk, we briefly present the DG method applied to root growth simulations. Then, we address the inverse problem of parameter identification which reduces to a non linear optimization problem and we show some numerical experiments. (Résumé d'auteur)
机译:根系对植物很重要,但由于田间试验的严格限制,很难进行研究。根系统的建模和仿真是更好地了解根系统以及设计新实验的关键工具。在各种建模方法中,密度方法在于跟踪土壤中根系生物量密度随时间和空间的演变。根部密度满足不稳定的对流反应扩散方程,其系数根据根部生长的生理阶段而在空间和时间上变化。目前,还没有直接的现场实验可以估算或测量方程的某些系数。但是,由于我们知道如何估计根密度,因此可以通过解决反问题来确定缺失的系数。该问题在非结构化网格上得以解决,因此可以处理复杂的几何形状和网格细化。众所周知,由于对流项,拉格朗日有限元法缺乏稳定性。由于我们的应用需要处理不连续的参数,例如在分层土壤的情况下,因此我们基于不连续Galerkin(DG)方法实现了近似值。在演讲中,我们简要介绍了应用于根生长模拟的DG方法。然后,我们解决了参数识别的反问题,该问题被简化为非线性优化问题,并展示了一些数值实验。 (Résuméd'auteur)

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