傳統上，在進行模流分析時，工程師利用肉眼判斷需進行網格加密的部位，對於複雜模型時，若以肉眼判斷將花費大量時間，並且可能發生遺漏。本研究目的為提供一個對CAD模型進行自動化辨識技術，提供相關資訊給後續的CAE分析使用，然而需要辨識的特徵有很多種，本研究針對其中一項特徵進行辨識，以肋作為主要辨識的對象。在Rhino平台下發展一套辨識系統，利用CAD模型中的B-rep結構，取得CAD模型的拓樸資訊，並以此資訊為基礎，利用種子面的搜索方式，搜索CAD模型中可能為肋的部分，最後利用網路上搜索之CAD模型，利用CADdoctor進行比照與驗證，驗證本研究所發展的辨識系統的正確性與問題。

Traditionally, during the mold flow analysis, engineers modify and refine the meshes manually during the generation of the meshes from the CAD model. For complex model, however such a work usually requires significant efforts, which may lead to the occurrence of omission. The purpose of this study is to provide an automated feature recognition system for the CAD model, and provide useful information for the generation of the meshes in the CAE analysis. The main target of this study is for the cognition of ribs, a typically feature in most CAD models. A rib recognition algorithm is proposed under the Rhino platform, in which the B-rep data is employed to obtain the topological information of the CAD model. The topological information is employed as the basis to recognize the ribs through a series of seed faces. Several realistic CAD model are used to verify the feasibility of the proposed method. The results obtained from the proposed algorithm are compared with those from the CADdoctor, which is a commercial software. The advantages and drawbacks of the proposed algorithms are discussed also.

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