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 the Laplace 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 $\mathbb{R}^n$, $n\in\{2,3\}$, that is simple, efficient and reliable up to oscillations. The dependence of the estimator upon the size of the features is explicit.

翻译：偏差在于通过去除被认为与某一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性去除和简化使工程分析问题模拟速度更快,简化了本来通常不可行的网状问题。对分析的失败效应随后被忽略,而且从今天起,基本上很少有量化评估这种影响的策略。了解这一过程的效果是自动整合设计和分析的一个重要步骤。我们正式确定失败过程,了解它对于包含单一特征的几何利益模型中界定的占位方程式的解决方案的影响,该方程式本身就含有一个单一特征,而纽曼边界条件。我们用 $\mathbb{R ⁇ n\n\in ⁇ 2,3 ⁇ $,这是简单、高效和可靠的地标对地标大小的依赖性是明确的。