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epsilon-maps: Characterizing, detecting and thickening thin features in geometric models

机译:epsilon贴图:表征,检测和加厚几何模型中的薄特征

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We focus on the analysis of planar shapes and solid objects having thin features and propose a new mathematical model to characterize them. Based on our model, that we call an is an element of-shape, we show how thin parts can be effectively and efficiently detected by an algorithm, and propose a novel approach to thicken these features while leaving all the other parts of the shape unchanged. When compared with state-of-the-art solutions, our proposal proves to be particularly flexible, efficient and stable, and does not require any unintuitive parameter to fine-tune the process. Furthermore, our method is able to detect thin features both in the object and in its complement, thus providing a useful tool to detect thin cavities and narrow channels. We discuss the importance of this kind of analysis in the design of robust structures and in the creation of geometry to be fabricated with modern additive manufacturing technology. (C) 2017 Elsevier Ltd. All rights reserved.
机译:我们专注于分析具有稀薄特征的平面形状和实体,并提出了表征它们的新数学模型。在模型的基础上,我们将an称为形状的元素,展示了如何通过算法有效地检测薄的部分,并提出了一种新颖的方法来加厚这些特征,同时保持形状的所有其他部分不变。与最先进的解决方案相比,我们的建议被证明是特别灵活,高效和稳定的,并且不需要任何直观的参数即可对过程进行微调。此外,我们的方法能够检测物体及其补充中的细小特征,从而提供了检测细小空腔和狭窄通道的有用工具。我们讨论了这种分析在设计坚固的结构以及创建采用现代增材制造技术制造的几何图形时的重要性。 (C)2017 Elsevier Ltd.保留所有权利。

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