Boss特徵之結構化實體網格自動化建構技術發展

NCUIR > Engineering College > Graduate Institute of Mechanical Engineering > Electronic Thesis & Dissertation > Item 987654321/84334

Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/84334

Title:	Boss特徵之結構化實體網格自動化建構技術發展
Authors:	張耀中;Chang, Yao-Chung
Contributors:	機械工程學系
Keywords:	結構式實體網格;實體網格自動化;特徵辨識;薄殼元件;凸起特徵;Boss特徵;管特徵;肋特徵;structured solid mesh;automatic solid mesh generation;feature recognition;thin-shell CAD model;protrusion;Boss feature;tube;rib
Date:	2020-07-29
Issue Date:	2020-09-02 19:06:01 (UTC+8)
Publisher:	國立中央大學
Abstract:	隨著模流分析所需的精度增加，傳統的四面體網格已無法符合需求，相反地，結合六面體與三角柱網格的結構式網格需求也日漸增加。本研究是針對薄殼元件中常見的Boss特徵，探討如何搭建結構式實體網格，利用科盛科技提供之函式庫，開發自動化建構結構式實體網格的演算法。在本研究中，會先使用本實驗室開發之特徵辨識技術，將Boss特徵與薄殼本體分離後，根據手動建構結構式網格的概念，產生所需之輔助幾何資料，再以一套實體網格的建構程序，進行演算法的開發，產生高品質的結構化實體網格。本研究分析Boss特徵之各種組成，發展適用於不同Boss型態之實體網格自動化建構方法，並且以多個範例驗證此一方法之可行性。;With the increasing in accuracy for mold flow analysis, traditional tetrahedral meshes are unable to satisfy the requirement. On the contrary, the demand for structured meshes combining hexahedral and prismatic meshes is increasing. This study is aimed at the meshing of boss features on thin-shell CAD models, and investigates how to build structured solid meshes by applying the meshing modules provided by Moldex3D for the development of an automatic meshing algorithm for bosses. In this study, we will first apply a feature recognition technology developed in our laboratory to isolate the bosses from the CAD model. Based on the concept of manual operation, auxiliary data required for mesh generation is generated. Then a procedure for automatic generation of structured mesh is developed, which can yield high quality of solid mesh. In addition, this study analyzes various components of bosses, and develops automatic meshing methods for all of them. Finally, several CAD examples are employed to demonstrate the feasibility of the proposed method.
Appears in Collections:	[Graduate Institute of Mechanical Engineering] Electronic Thesis & Dissertation

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