博碩士論文 107323082 詳細資訊




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姓名 張耀中(Yao-Chung Chang)  查詢紙本館藏   畢業系所 機械工程學系
論文名稱 Boss特徵之結構化實體網格自動化建構技術發展
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檔案 [Endnote RIS 格式]    [Bibtex 格式]    [相關文章]   [文章引用]   [完整記錄]   [館藏目錄]   至系統瀏覽論文 ( 永不開放)
摘要(中) 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。
摘要(英) 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.
關鍵字(中) ★ 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
關鍵字(英) ★ structured solid mesh
★ automatic solid mesh generation
★ feature recognition
★ thin-shell CAD model
★ protrusion
★ Boss feature
★ tube
★ rib
論文目次 摘要 i
Abstract ii
目錄 iii
圖目錄 vi
表目錄 xi
第一章 緒論 1
1.1 前言 1
1.2 文獻回顧 3
1.3 研究目的與方法 7
1.3.1 研究目的 7
1.3.2 研究方法 8
1.4 論文架構 13
第二章 網格建構方法 14
2.1 前言 14
2.2 網格建構函式功能 14
2.2.1 撒點功能 15
2.2.2 成長表面網格功能 17
2.2.3 成長實體網格功能 21
2.3 手動搭建實體網格的方法與自動化問題分析 24
2.3.1 薄殼元件特徵分離 24
2.3.2 手動搭建結構式實體網格 26
2.3.3 自動化搭建問題分析 32
第三章 Boss特徵實體網格自動化建構 37
3.1 前言 37
3.2 網格前處理資料計算 37
3.2.1 凸起物辨識資料 38
3.2.2 管網格資料建構 38
3.2.3 肋網格資料建構 46
3.3 Boss特徵結構式網格自動化建構方法 51
3.3.1 管的表面網格與實體網格建構 51
3.3.2 肋的表面網格與實體網格建構 53
第四章 案例測試與討論 64
4.1 前言 64
4.2 結果呈現 64
4.2.1 可處理之Boss類型 64
4.2.2 實際案例結果呈現 66
4.2.3 測試不同網格尺寸之結果分析 72
4.2.4 網格品質分析 77
4.2.5 模流分析結果 83
4.3 本研究無法處理之案例分析 88
第五章 結論與未來展望 93
5.1 結論 93
5.2 未來展望 94
參考文獻 96
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survey and progress,” International Journal for Numerical Methods in Engineering, Vol. 50, No. 12, 2001, pp. 2617-2642.
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[16] J. Y. Lai, P. P. Song, A. S. Hsiao, Y. C. Tsai and C. H. Hsu, “Recognition and classification of protrusion features on thin-wall parts for mold flow analysis,” Engineering with Computers, 2019, pp. 1-22.
[17] 張倢綜:〈CAD模型基礎擠出物之實體網格自動化建構技術發展〉,碩士論文,國立中央大學,2019。
[18] 吳家瑋:〈薄殼零件薄殼本體之結構化實體網格自動建構技術發展〉,碩士論文,國立中央大學,2020。
[19] J. R. Shewchuk, “Delaunay refinement algorithms for triangular mesh generation,” Computational geometry, Vol. 22, No. 1-3, 2002, pp. 21-74.
[20] 王明暄:〈應用於模流分析之CAD模型特徵辨識與實體網格品質提升之研究〉,博士論文,國立中央大學,2017。
[21] Rhinoceros, http://www.rhino3d.com
[22] openNURBS, http://www.rhino3d.com/tw/opennurbs
[23] B-rep data structure, http://wiki.mcneel.com/developer/brepstructure
[24] 科盛科技, http://www.moldex3d.com/en/
指導教授 賴景義(Jiing-Yih Lai) 審核日期 2020-7-29
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