Corrosion Science and Technology

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ISSN(Print): 1598-6462
ISSN(Online): 2288-6524
Issue: Bimonthly (2,4,6,8,10,12)
Type: Journal
Language: English/Korean
History: v1 n1 Feb. 2002

Index:	ESCI (since 2017)
	KCI (since 2019)
	Scopus (since 2019)

Date: April 30, 2019
Vol: 18, Issue: 2

This is an Open-Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

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[Research Paper]

Pitting Corrosion Inhibition of Sprinkler Copper Tubes via Forming of Cu-BTA Film on the Inner Surface of Corrosion pits

Sang Hee Suh, Youngjoon Suh, Sohee Kim, Jun-Mo Yang, Gyungtae Kim

Keywords: Copper, Pitting corrosion inhibition, Benzotriazole, EDS, XPS

Corros. Sci. Tech. , 2019, 18(2) pp. 39-48

® 10.14773/CST.2019.18.2.39

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[Research Paper]

Stress Corrosion Cracking of Heat Exchanger Tubes in District Heating System

Sangwon Cho, Seon-Hong Kim, Woo-Cheol Kim, Jung-Gu Kim

Keywords: Pitting, Heat exchanger tube, Stress corrosion cracking, Corrosion fatigue cracking, Austenitic stainless steel

Corros. Sci. Tech. , 2019, 18(2) pp. 49-54

® 10.14773/CST.2019.18.2.49

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[Research Paper]

Corrosion Failure Analysis of the Convection Part of District Heating Peak Load Boiler

지역난방 첨두부하보일러 대류부 부식 파손 분석

Youngsu Kim, Hobyung Chae, Minki Hong, Min Ji Song, Jeongmin Cho, Woo Cheol Kim, Tae Baek Ha, Soo Yeol Lee

김영수, 채호병, 홍민기, 송민지, 조정민, 김우철, 하태백, 이수열

Keywords: District heating system, PLB convection, Dew point corrosion, Turbulator, IRIS inspection

Corros. Sci. Tech. , 2019, 18(2) pp. 55-60

® 10.14773/CST.2019.18.2.55

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[Research Paper]

Modeling of Flow-Accelerated Corrosion using Machine Learning: Comparison between Random Forest and Non-linear Regression

기계학습을 이용한 유동가속부식 모델링: 랜덤 포레스트와 비선형 회귀분석과의 비교

Gyeong-Geun Lee, Eun Hee Lee, Sung-Woo Kim, Kyung-Mo Kim, Dong-Jin Kim

이경근, 이은희, 김성우, 김경모, 김동진

Keywords: FAC, Statistical modeling, Machine learning, Random forest, Non-linear regression

Corros. Sci. Tech. , 2019, 18(2) pp. 61-71

® 10.14773/CST.2019.18.2.61

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