Pub Date : 2022-06-08DOI: 10.14733/cadconfp.2022.324-328
Zhongyuan Liao, Junjian Chen, Y. Cai
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Pub Date : 2022-06-08DOI: 10.14733/cadconfp.2022.267-270
Nanhua Huang, Ming Chen, Zhengqing Zhang, Shenglian Lu
Introduction Point cloud data is more and more widely used in reverse engineering, cultural relic restoration, architecture and many other fields. . In practice, the obtained data is often non-uniformly sampled and of noises. Feature exaction is a key step for the subsequent processing of point clouds such as matching, segmentation and recognition. How to identify point features for noisy point cloud and improve the efficiency are challenging at present. In previous studies, Nieet al. [2] used a surface smooth shrinkage index (SSI) to measure the degree of surface change, and judged feature points according to the absolute value of SSI of each point. This method has a good anti-noise ability and can extract sharp feature points, but it cannot work for smooth features. In practical applications, we find that the regions of smooth features (such as fillets) have a higher density than other non-featured places, as these interested regions are usually scanned multiple times or the scanning orientation is adjusted to obtain a relatively larger scanning point density at these places. Considering this fact, a combined index of density and SSI is proposed so as to recognize smooth features, and the recognition is also accelerated through octree data structure.
Pub Date : 2022-06-08DOI: 10.14733/cadconfp.2022.287-291
Gábor Valasek, Róbert Bán
Introduction: Signed distance functions (SDFs) are powerful implicit representations of curves and surfaces. Beyond encoding volume boundaries as their zero level-set, they also convey global geometric information about the scene as they map signed distances to all points in space. In real-time applications, their most common numerical representation is a regular grid of two or three dimensions. In conjunction with an interpolation method to infer a continuous approximation de ned on all points of space, these can be e ciently evaluated on the GPU such that even the most demanding applications can utilize them [4, 5]. Several authors proposed to use rst order approximations to the SDF at the samples, e.g. gradients [3] or plane equations [1]. In this paper, we present a straightforward generalization of this approach to higher orders and discuss various alternatives to the appropriate ltering of samples such that the inferred SDF reconstructs the given higher order derivatives at the samples. Our focus is on applications in high performance visualizations, as such, we prioritize run-time performance over optimal storage and restrict sampling topologies in our measurements to regular grids. We also discuss the shortcomings of this approach as means to decrease storage for complex shapes.
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Pub Date : 2022-06-08DOI: 10.14733/cadconfp.2022.271-276
Yifan Guo, Yongsheng Ma, Rafiq Ahmad
Introduction: Lattice structures (LSs) have been an emerging solution toward lightweight and mechanically efficient structures [2-3]. However, while the lattice structure presents a vast design space and advantage, it also poses a challenge to existing design methods. Existing LSs design methods rarely consider microstructures with functionalities, like negative Poisson's ratio [8] and extreme thermal expansion [5]; Therefore, this work proposes a method based on topology optimization and homogenization theory to design hybrid lattice structures with multiple functional microstructure configurations to fill the gap in the design approach for multi-functional lattice structures. The flow chart of the proposed method is shown in Fig 1. There are two steps in this method. At first, multiple functional microstructure lattice units are obtained through topology optimization and homogenization theory. Then, the microstructures are treated as homogeneous materials with effectively homogenized properties for macroscopic analysis, and the ordered SIMP (Solid isotropic material with penalization) interpolation method [7] is applied to achieve the interpolation of multiple microstructures. Finally, the obtained hybrid lattice structure theoretically has both the properties of macroscopic optimization and the functionalities of microstructure units. Both the microstructure and macrostructure design variables are updated by the Method of Moving Asymptote (MMA) algorithm [4]. To verify this proposed method, an optimization model that the functional microstructure is set to be zero thermal expansion coefficient, and a standard minimized compliance problem is considered in macroscale is created. Numerical examples and data comparisons are presented.
简介:晶格结构(LSs)已经成为一种新兴的轻量化和机械高效结构解决方案[2-3]。然而，在点阵结构呈现出广阔的设计空间和优势的同时，也对现有的设计方法提出了挑战。现有的LSs设计方法很少考虑具有功能的微观结构，如负泊松比[8]和极端热膨胀[5];因此，本工作提出了一种基于拓扑优化和均质化理论的多功能微结构混合晶格结构设计方法，以填补多功能晶格结构设计方法的空白。所提出方法的流程图如图1所示。这个方法有两个步骤。首先，通过拓扑优化和均匀化理论得到了多个功能微结构晶格单元。然后，将微结构作为具有有效均质特性的均质材料进行宏观分析，采用有序SIMP (Solid isotropic material with penization)插值方法[7]实现多个微结构的插值。最后，得到的杂化晶格结构在理论上既具有宏观优化的性质，又具有微观结构单元的功能。通过移动渐近线法(MMA)算法更新微观结构和宏观结构设计变量[4]。为验证该方法的有效性，建立了将功能微观结构设置为零热膨胀系数的优化模型，并在宏观尺度上考虑了标准的最小柔度问题。给出了数值算例和数据比较。
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Pub Date : 2022-06-07DOI: 10.14733/cadconfp.2022.1-5
E. Mussi, Michaela Servi, Y. Volpe, F. Facchini
The advent and consolidation of Reverse Engineering (RE) and Additive Manufacturing (AM) techniques in the medical field has significantly revolutionized the surgical approach, pushing towards a new perspective of treatment based on the respect of interindividual anatomical variability [3]. These technologies have also been exploited in the surgical treatment of microtia, a congenital malformation characterized by partial or complete lack of the external ear architecture. [5]. Such a surgical procedure involves the removal of a portion of the patient's costal cartilage, the manual modeling of the cartilage tissue in order to obtain a geometry that resembles the healthy auricular anatomy and the insertion of the cartilage framework thus obtained in a subcutaneous pocket in the malformed area [2].
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