首页> 外文会议>International Conference on Computational Science and Its Applications(ICCSA 2006) pt.1; 20060508-11; Glasgow(GB) >History-Based Selective Boolean Operations for Feature-Based Multi-resolution Modeling
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History-Based Selective Boolean Operations for Feature-Based Multi-resolution Modeling

机译:基于历史的选择性布尔运算,用于基于特征的多分辨率建模

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The feature-based multi-resolution models of a solid represent an object at different levels of detail (LOD), particularly in the unit of feature, according to a certain LOD criterion. The need of feature-based multi-resolution modeling is currently increasing for various engineering tasks, such as analysis, network-based collaborative design, virtual prototyping and manufacturing. To provide feature-based multi-resolution models, it is essential to generate a valid and unique solid model at each LOD after feature rearrangement. To meet this requirement, we propose the history-based selective Boolean operations that satisfy the commutative law between union and subtraction by considering the history of the Boolean operations for the features. Owing to the commutative properties, the feature-based multi-resolution modeling technique based on these operations guarantees the same resulting shape as the original, and provides a unique and reasonable shape at each intermediate LOD after arbitrary feature rearrangement.
机译:实体的基于特征的多分辨率模型根据特定的LOD准则以不同的详细程度(LOD)表示对象,尤其是以特征为单位。当前,针对各种工程任务(例如分析,基于网络的协作设计,虚拟原型设计和制造)的基于特征的多分辨率建模的需求正在增长。要提供基于特征的多分辨率模型,必须在特征重新排列后在每个LOD上生成有效且唯一的实体模型。为了满足此要求,我们提出了一种基于历史的选择性布尔运算,该运算通过考虑特征的布尔运算的历史来满足并与减之间的交换律。由于具有可交换性,基于这些操作的基于特征的多分辨率建模技术可保证与原始形状相同的结果形状,并在任意特征重新排列后在每个中间LOD处提供唯一合理的形状。

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