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  • 學位論文

少量樣本下應用重新抽樣法探討疲勞裂縫成長參數之分佈

Application of Resampling Methods to the Study of Fatigue Crack Growth Parameters

指導教授 : 吳文方

摘要


摘要 金屬疲勞實驗是一項相當花費時間的工作,因此如何有效率的應用既有但數量不夠多的疲勞實驗數據,以詳盡呈現金屬疲勞之成長特性,顯得相當重要;此外,考慮金屬疲勞裂縫成長行為具有相當的離散姓,我們更應該透過統計學上的一些方法來探討金屬疲勞裂縫之成長行為。本研究採用人們在統計學上常用的jackknife重新抽樣法,透過金屬疲勞裂縫成長實際實驗數據之重新抽樣,獲得較實驗數據更多的資料,來求得Paris方程式中裂縫成長參數之機率分佈,以為金屬疲勞裂縫成長可靠度評估的依據;並驗證此方法較先前人們所曾使用過的方法來得可靠。

並列摘要


Abstract As a result of scatter of the fatigue-crack–growth behavior, it is reasonable to analyze fatigue crack growth data by statistical methods. Since the fatigue test is a time-consuming work, it is even more important to make use of statistical techniques to analyze the experimental data. In the present paper the jackknife resampling method is employed to help us finding the probability distribution functions of those constants of Paris law. Useful information including fatigue reliability estimation can be drawn from the experimental data through such an approach.

參考文獻


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