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結合類神經網路與有限元素法應用於奈米壓痕試驗分析 = Nanoinden...
~
C.L.Ke
結合類神經網路與有限元素法應用於奈米壓痕試驗分析 = Nanoindentation Characteristics using Finite Element Method combined with Abductive Network
Record Type:
Language materials, printed : monographic
Paralel Title:
Nanoindentation Characteristics using Finite Element Method combined with Abductive Network
Author:
柯正良,
Secondary Intellectual Responsibility:
方得華,
Secondary Intellectual Responsibility:
楊東昇,
Secondary Intellectual Responsibility:
國立虎尾科技大學
Place of Publication:
雲林縣
Published:
國立虎尾科技大學;
Year of Publication:
民96[2007]
Edition:
初版
Description:
88面圖,表 : 30公分;
Subject:
奈米壓痕;彈性係數;降伏強度;應變硬化率;類神經網路
Subject:
nanoindentation;elastic modulus;yield stress;
Online resource:
http://140.130.12.251/ETD-db/ETD-search-c/view_etd?URN=etd-0725107-145506
Summary:
奈米壓痕試驗分析目前主要應用於高科技精密工業,由於進行的壓痕尺寸過於微小不易由實驗儀器直接量測獲得所要的資料結果,因此在量測過程中係藉由壓痕器探針對試件進行壓痕,紀錄壓痕過程至完全卸載結束之載重與壓痕深度之曲線關係;另一方面,利用有限元素分析法模擬壓痕試驗分析,藉由多次改變材料之應力-應變關係式作壓痕模擬分析,而得到與奈米壓痕試驗所得到壓痕力量與位移ㄧ致的曲線,據以判定該測試材料之應力-應變關係。為了減少模擬次數,本文提出結合類神經網路與有限元素法應用於奈米壓痕試驗分析,首先以有限元素法對奈米壓痕進行一系列不同材料參數的壓痕分析,然後利用類神經網路整合這些分析結果之數據,經網路訓練後,獲得材料之應力-應變關係預測模組,再利用此預測模組預測材料之彈性模數、降伏強度及應變硬化率。本文以有限元素分析所做的模擬壓痕試驗結果作為類神經訓練資料庫,然而因實驗負載曲線與模擬負載曲線未必完全相符,為了有效及準確的分析金屬的機械性質,本文提出兩種預估方法,試圖由兩種方法預估分析金屬的機械性質,其最主要目的為節省利用有限元素所耗費之時間,並有效及準確的預估該金屬之機械性質。 The purpose of the present work was to investigate the nanoindentation process by FEM of metals, considering strain hardening effect of material. In order to verify the FEM simulation results of the mechanical parameters such as Young’s modulus, yield stress and strain hardening, and the experimental data are compared with the results of the current simulation. The abductive network was then applied to synthesize the data sets obtained from the numerical simulation. The predicted results of the mechanical properties from the prediction model are consistent with the results obtained from experiment. After employing the predictive model can provide valuable references in prediction of the mechanical parameters after nanoindentation tests. We used finite element method to is it keep mark test consumed time and metal mechanical range too big to select suitable materials difficult characteristics to avoid, can predict and analyzed the mechanical characteristics of the metal in the finite element method accurately by one kind of abductive network. But the simulation that does with finite element analysis presses the mark and tests the after treatment materials and trains the database for abductive network, because the experiment load curve has not conformed with imitate the load curve trend, and not enough to laminate, then in order to analyze the mechanical characteristics of the metal effectively , utilize two ways separately, attempt to be estimated the mechanical nature of analyzing the metal in advance by these two ways, but the time that its main purpose consumes in order to utilize the finite element in a large amount sparingly, effective and accurate mechanical characteristics and hardness of metals in advance.
結合類神經網路與有限元素法應用於奈米壓痕試驗分析 = Nanoindentation Characteristics using Finite Element Method combined with Abductive Network
柯, 正良
結合類神經網路與有限元素法應用於奈米壓痕試驗分析
= Nanoindentation Characteristics using Finite Element Method combined with Abductive Network / 柯正良撰 - 初版. - 雲林縣 : 國立虎尾科技大學, 民96[2007]. - 88面 ; 圖,表 ; 30公分.
參考書目:75-78面.
奈米壓痕;彈性係數;降伏強度;應變硬化率;類神經網路nanoindentation;elastic modulus;yield stress;
方, 得華
結合類神經網路與有限元素法應用於奈米壓痕試驗分析 = Nanoindentation Characteristics using Finite Element Method combined with Abductive Network
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奈米壓痕試驗分析目前主要應用於高科技精密工業,由於進行的壓痕尺寸過於微小不易由實驗儀器直接量測獲得所要的資料結果,因此在量測過程中係藉由壓痕器探針對試件進行壓痕,紀錄壓痕過程至完全卸載結束之載重與壓痕深度之曲線關係;另一方面,利用有限元素分析法模擬壓痕試驗分析,藉由多次改變材料之應力-應變關係式作壓痕模擬分析,而得到與奈米壓痕試驗所得到壓痕力量與位移ㄧ致的曲線,據以判定該測試材料之應力-應變關係。為了減少模擬次數,本文提出結合類神經網路與有限元素法應用於奈米壓痕試驗分析,首先以有限元素法對奈米壓痕進行一系列不同材料參數的壓痕分析,然後利用類神經網路整合這些分析結果之數據,經網路訓練後,獲得材料之應力-應變關係預測模組,再利用此預測模組預測材料之彈性模數、降伏強度及應變硬化率。本文以有限元素分析所做的模擬壓痕試驗結果作為類神經訓練資料庫,然而因實驗負載曲線與模擬負載曲線未必完全相符,為了有效及準確的分析金屬的機械性質,本文提出兩種預估方法,試圖由兩種方法預估分析金屬的機械性質,其最主要目的為節省利用有限元素所耗費之時間,並有效及準確的預估該金屬之機械性質。 The purpose of the present work was to investigate the nanoindentation process by FEM of metals, considering strain hardening effect of material. In order to verify the FEM simulation results of the mechanical parameters such as Young’s modulus, yield stress and strain hardening, and the experimental data are compared with the results of the current simulation. The abductive network was then applied to synthesize the data sets obtained from the numerical simulation. The predicted results of the mechanical properties from the prediction model are consistent with the results obtained from experiment. After employing the predictive model can provide valuable references in prediction of the mechanical parameters after nanoindentation tests. We used finite element method to is it keep mark test consumed time and metal mechanical range too big to select suitable materials difficult characteristics to avoid, can predict and analyzed the mechanical characteristics of the metal in the finite element method accurately by one kind of abductive network. But the simulation that does with finite element analysis presses the mark and tests the after treatment materials and trains the database for abductive network, because the experiment load curve has not conformed with imitate the load curve trend, and not enough to laminate, then in order to analyze the mechanical characteristics of the metal effectively , utilize two ways separately, attempt to be estimated the mechanical nature of analyzing the metal in advance by these two ways, but the time that its main purpose consumes in order to utilize the finite element in a large amount sparingly, effective and accurate mechanical characteristics and hardness of metals in advance.
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http://140.130.12.251/ETD-db/ETD-search-c/view_etd?URN=etd-0725107-145506
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圖書館B1F 博碩士論文專區
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