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Prediction of subsurface damage duri...

Chen, Yujie.

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Prediction of subsurface damage during machining nickel-based superalloys.

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Prediction of subsurface damage during machining nickel-based superalloys./
作者:	Chen, Yujie.
面頁冊數:	194 p.
附註:	Source: Dissertation Abstracts International, Volume: 74-09(E), Section: B.
Contained By:	Dissertation Abstracts International74-09B(E).
標題:	Engineering, Automotive. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3564712
ISBN:	9781303138980

Prediction of subsurface damage during machining nickel-based superalloys.
Chen, Yujie.

Prediction of subsurface damage during machining nickel-based superalloys. - 194 p.

Source: Dissertation Abstracts International, Volume: 74-09(E), Section: B.

Thesis (Ph.D.)--Clemson University, 2013.

Nickel-based superalloys are widely utilized in hostile environments such as jet engines and gas turbines due to their high resistance to oxidation, high corrosion resistance, good thermal fatigue-resistance and fracture toughness. Subsurface damage is typically generated during the machining of these materials, and in particular, ?strengthened nickel-based superalloys. The depth of the subsurface damage is a critical requirement specified by the customer. Therefore, it is critical to predict, measure and control subsurface damage.

ISBN: 9781303138980Subjects--Topical Terms:

1018477
Engineering, Automotive.

Prediction of subsurface damage during machining nickel-based superalloys.
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100 1 $a Chen, Yujie. $3 2102415
245 1 0 $a Prediction of subsurface damage during machining nickel-based superalloys.
300 $a 194 p.
500 $a Source: Dissertation Abstracts International, Volume: 74-09(E), Section: B.
500 $a Advisers: Laine Mears; Thomas Kurfess.
502 $a Thesis (Ph.D.)--Clemson University, 2013.
520 $a Nickel-based superalloys are widely utilized in hostile environments such as jet engines and gas turbines due to their high resistance to oxidation, high corrosion resistance, good thermal fatigue-resistance and fracture toughness. Subsurface damage is typically generated during the machining of these materials, and in particular, ?strengthened nickel-based superalloys. The depth of the subsurface damage is a critical requirement specified by the customer. Therefore, it is critical to predict, measure and control subsurface damage.
520 $a This research specifically targets the development of a model to predict subsurface damage during the machining of ?strengthened nickel-based superalloys. To accomplish this, a modified Johnson-Cook model is developed to represent the plasticity behavior of the material using elevated temperature tests. The proposed model integrates a piece-wise method, strain hardening function, thermal sensitivity function, and flow softening function accurately model anomalous strength behavior. Material subroutines are developed for finite element analysis (FEA) simulation and applied with the ABAQUS/Explicit solver. Orthogonal cutting experiments are conducted to verify FEA results. Recrystallization techniques are utilized for estimation of the depth of subsurface damage. By comparing the subsurface damage between experimental and FEM simulation results, a threshold value is established for determining the depth of subsurface damage.
520 $a A high agreement between FEA simulation and experimental results is observed. From the cutting force aspect, the agreement is more than 90% for unaggressive cutting inputs. On the other hand, the model agreement is slightly lower, 85%, for aggressive machining conditions. This is due to the fact that the severe rake face wear cannot be comprehensively represented in the FEA simulation. In addition, the depth of subsurface damage predicted from the FEA simulations reached an agreement of 95% when compared to experimental findings. Therefore, a subsurface damage model between cutting inputs and depth of subsurface damage has been established based on the results derived from FEA simulations.
590 $a School code: 0050.
650 4 $a Engineering, Automotive. $3 1018477
690 $a 0540
710 2 $a Clemson University. $b Automotive Engineering. $3 1684493
773 0 $t Dissertation Abstracts International $g 74-09B(E).
790 $a 0050
791 $a Ph.D.
792 $a 2013
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3564712