| کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن | 
|---|---|---|---|---|
| 5439995 | 1509972 | 2017 | 23 صفحه PDF | دانلود رایگان | 
عنوان انگلیسی مقاله ISI
												Assessment of local conductivity distribution in stress corrosion crack region using direct current potential drop method
												
											ترجمه فارسی عنوان
													ارزیابی توزیع رسانایی محلی در منطقه ترک خوردگی تنش با استفاده از روش پتانسیل جریان مستقیم جریان 
													
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																																												موضوعات مرتبط
												
													مهندسی و علوم پایه
													مهندسی مواد
													سرامیک و کامپوزیت
												
											چکیده انگلیسی
												As an effort to enhance the precision of quantitative nondestructive evaluation on stress corrosion crack (SCC) sizing with eddy current testing (ECT) technique, the electrical conductivity distribution in the SCC region was investigated in this work through measurement and inversion of the direct current potential drop (DCPD) signals with a sliced specimen strategy. An inversion scheme, consisting of an efficient forward DCPD signal simulator and the conjugate gradient optimization algorithm, was proposed and implemented for the reconstruction of the two-dimensional (2D) conductivity distribution inside the SCC. The reasonable reconstruction results from the measured DCPD signals of the practical SCC specimens proved the validity of the proposed scheme. The 2D distribution obtained in this paper shows that the conductivity becomes larger when approaching the crack tip and is the minimum in the crack opening position. The obtained SCC conductivity information gives a good reference to enhance the crack sizing accuracy of ECT.
											ناشر
												Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Corrosion Science - Volume 123, 15 July 2017, Pages 197-208
											Journal: Corrosion Science - Volume 123, 15 July 2017, Pages 197-208
نویسندگان
												Wenlu Cai, Shejuan Xie, Cherdpong Jomdecha, Xiaojuan Wang, Cuixiang Pei, Yong Li, Zhenmao Chen, Noritaka Yusa, 
											