In biomechanics, geometries representing complicated organic structures are consistently segmented from sparse volumetric data or morphed from template geometries resulting in initial overclosure between adjacent geometries. In FEA, these overclosures result in numerical instability and inaccuracy as part of contact analysis. Several techniques exist to fix overclosures, but most suffer from several drawbacks. This work introduces a novel automated algorithm in an iterative process to remove overclosure and create a desired minimum gap for 2D and 3D finite element models. The RBF Network algorithm was introduced by its four major steps to remove the initial overclosure. Additionally, the algorithm was validated using two test cases against conventional nodal adjustment. The first case compared the ability of each algorithm to remove differing levels of overclosure between two deformable muscles and the effects on mesh quality. The second case used a non-deformable femur and deformable distal femoral cartilage geometry with initial overclosure to test both algorithms and observe the effects on the resulting contact FEA. The RBF Network in the first case study was successfully able to remove all overclosures. In the second case, the nodal adjustment method failed to create a usable FEA model, while the RBF Network had no such issue. This work proposed an algorithm to remove initial overclosures prior to FEA that has improved performance over conventional nodal adjustment, especially in complicated situations and those involving 3D elements. The work can be included in existing FEA modeling workflows to improve FEA results in situations involving sparse volumetric segmentation and mesh morphing. This algorithm has been implemented in MATLAB, and the source code is publicly available to download at the following GitHub repository: https://github.com/thor-andreassen/femors
翻译:在生物机械学中,代表复杂有机结构的地貌结构始终由稀疏的体积数据分割而成,或由模板的地貌结构转变而成,导致相邻的地貌结构初步过度闭合。在FEA中,这些过度闭合导致数字不稳定和不准确,作为接触分析的一部分。有几种技术可以解决过度闭合,但大多数都存在一些缺陷。在迭接过程中引入了一个新颖的自动算法,以消除过度闭合,并为2D和3D 有限元素模型创造理想的最小差距。RBF网络算法是通过其四个主要步骤推出的,以消除最初的过错。此外,算法在常规节点调整中,用两个测试案例来验证。第一个案例比较了两种可变形肌肉之间的过度闭合能力,但多数都存在缺陷。第二个案例使用非变异形的Flickral-Feiltalal-altical 和变形变形的软体流变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形变形