Defeaturing consists in simplifying geometrical models by removing the geometrical features that are considered not relevant for a given simulation. Feature removal and simplification of computer-aided design models enables faster simulations for engineering analysis problems, and simplifies the meshing problem that is otherwise often unfeasible. The effects of defeaturing on the analysis are then neglected and as of today, there are basically very few strategies to quantitatively evaluate such an impact. Understanding well the effects of this process is an important step for automatic integration of design and analysis. We formalize the process of defeaturing by understanding its effect on the solution of Poisson equation defined on the geometrical model of interest containing a single feature, with Neumann boundary conditions on the feature itself. We derive an a posteriori estimator of the energy error between the solutions of the exact and the defeatured geometries in ℝn, n ∈{2, 3}, that is simple, reliable and efficient up to oscillations. The dependence of the estimator upon the size of the features is explicit.

中文翻译：

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分析感知特征：问题设置和后验估计

特征化包括通过删除被认为与给定模拟无关的几何特征来简化几何模型。计算机辅助设计模型的特征去除和简化可以更快地模拟工程分析问题，并简化通常不可行的网格划分问题。然后忽略了特征化对分析的影响，截至今天，基本上很少有策略可以定量评估这种影响。很好地理解这个过程的影响是设计和分析自动集成的重要一步。我们通过了解其对定义在包含单个特征的感兴趣的几何模型上的泊松方程的解的影响来正式化特征化过程，在特征本身上具有 Neumann 边界条件。我们得出一个后验的精确几何解和特征几何解之间的能量误差估计器ℝn,n ∈{2, 3}，即简单、可靠且高效，直至振荡。估计器对特征大小的依赖性是明确的。