不同於傳統合金的新型態合金，高熵合金成為近年來熱門的研究項目，主要是以多種元素以一定比例進行混合，因其特性，能夠展現不同於過去金屬的優異機械性能，其中CoCrFeMnNi，又稱為 Cantor alloy的高熵合金已經有了多年的研究，有針對其不同元素成分含量、不同熱處理過程、不同添加物進行各種不同的研究。而材料的開發需要高昂的時間及金錢成本，近年來因電腦軟體運算漸趨成熟，以電腦模擬進行設計，以降低開發成本成了近年來的趨勢，且電腦模擬已廣泛運用於各種不同的領域。
本研究以計算力學建立一套以晶體塑性有限元素法為基礎利用多晶代表性體積元素模型 針對非等原子 Cantor alloy合金進行拉伸模擬分析，並導入了 能夠考慮微觀下差排作用及析出物效應 的硬化模型，以更接近真實的力學行為。針對材料參數對於應力應變曲線及統計儲存差排密度和幾何必要差排密度的效應進行完整的探討後，利用真實實驗下所獲 得 的 SEM-BSE圖進行析出物的分析， 將實驗所得的材料基本參數進行 部分實驗 曲線的擬合，成功的利用參數反映出應力應變曲線加工硬化行為及析出物對差排的影響，能夠描述在不同的退火溫度下，退火1小時之應力應變曲線及差排密度增長。 並利用差排密度發展情形解釋材料應力應變曲線的硬化行為，接著將剩下未擬合之 實驗應力應變曲線 用以驗證參數預測的準確性 。
探討不同退火溫度下之析出物效應影響及差排密度後利用現有實驗資料以及擬合參數值，迴歸出預測方程式，預測 出沒有實驗數據之不同退火溫度下的應力應變曲線，達到利用現有的實驗數據進行預測，減少實驗成本並提供設計金屬的參考 。

This research is based on dislocation density crystal plasticity finite element method, using Dream 3D to establish polycrystalline representative volume element(RVE) model. After, simulate tensile test on CoCrFeMnNi RVE model ,and consider the microscopic Mechanical behavior like dislocation slip and precipitate.
Discussing the influence of material parameters on the stress-strain curve , Statistically stored dislocation density(SSD) and Geometrically necessary dislocation density(GND).The precipitates are analyzed using the SEM-BSE image and material parameters obtained from the experiment data which are used in the curve fitting ,these parameters successfully reflects the work hardening behavior of the stress-strain curve and the influence of precipitates on dislocation.
It can describe the stress-strain curve and the growth of the dislocation density after annealing for 1 hour at different annealing temperatures. And use the growth of the dislocation density to explain the hardening behavior of the material stress-strain curve, and then use the unfitted experimental stress-strain curve to verify the accuracy of the parameter prediction.
Finally ,discussing the precipitates and dislocation density at different annealing temperatures, using existing experimental data and fitting parameter values, regression prediction equations are used to predict the mechanical behavior at different annealing temperatures without experimental data.

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