Long-term corrosion monitoring of carbon steels and environmental correlation analysis via the random forest method
Reads0
Chats0
TLDR
In this paper , the atmospheric corrosion of carbon steels was monitored at six different sites (and hence, atmospheric conditions) using Fe/Cu-type atmospheric corrosion monitoring technology over a period of 12 months.Abstract:
Abstract In this work, the atmospheric corrosion of carbon steels was monitored at six different sites (and hence, atmospheric conditions) using Fe/Cu-type atmospheric corrosion monitoring technology over a period of 12 months. After analyzing over 3 million data points, the sensor data were interpretable as the instantaneous corrosion rate, and the atmospheric “corrosivity” for each exposure environment showed highly dynamic changes from the C1 to CX level (according to the ISO 9223 standard). A random forest model was developed to predict the corrosion rate and investigate the impacts of ten “corrosive factors” in dynamic atmospheres. The results reveal rust layer, wind speed, rainfall rate, RH, and chloride concentration, played a significant role in the corrosion process. read more
Citations
More filters
Journal ArticleDOI
Corrosion characteristics of Q690qE high-strength bridge steel in simulated coastal–industrial environment and its influence on mechanical and corrosion fatigue behaviors
TL;DR: In this article , the corrosion behavior of Q690qE high-strength bridge steel in simulated coastal industrial environment was investigated through accelerated corrosion, and the corrosion features under different corrosion times were characterized.
Journal ArticleDOI
Effect of Hydrogen Charging on the Stress Corrosion Cracking Behavior of X70 Steel in Simulated Deep Seawater Environment
TL;DR: In this paper , the effects of hydrogen charging on the electrochemical and stress corrosion cracking (SCC) behavior of X70 steel in a simulated deep seawater environment were investigated by using electrochemical measurements, slow strain rate tensile (SSRT) tests, and corrosion morphology characterization through SEM.
Journal ArticleDOI
Data-mining and atmospheric corrosion resistance evaluation of Sn- and Sb-additional low alloy steel based on big data technology
Journal ArticleDOI
Mini-Review of Self-Healing Mechanism and Formulation Optimization of Polyurea Coating
TL;DR: In this article , extrinsic and intrinsic mechanisms are reviewed to address the efficiency of the self-healing process and formulation optimization and strategic improvement to ensure selfhealing within a shorter period of time with acceptable recovery of mechanical strength are also discussed.
Journal ArticleDOI
Investigation on the initial atmospheric corrosion of mild steel in a simulated environment of industrial coastland by thin electrical resistance and electrochemical sensors
TL;DR: In this paper , the initial corrosion behavior of carbon steel in a simulated industrial coastland atmosphere was in-situ monitored by thin electrical resistance (TER) and electrochemical impedance spectrum (EIS) sensors through cyclic wetting and drying test.
References
More filters
Journal ArticleDOI
Random Forests
TL;DR: Internal estimates monitor error, strength, and correlation and these are used to show the response to increasing the number of features used in the forest, and are also applicable to regression.
Journal Article
Scikit-learn: Machine Learning in Python
Fabian Pedregosa,Gaël Varoquaux,Alexandre Gramfort,Vincent Michel,Bertrand Thirion,Olivier Grisel,Mathieu Blondel,Peter Prettenhofer,Ron Weiss,Vincent Dubourg,Jake Vanderplas,Alexandre Passos,David Cournapeau,Matthieu Brucher,Matthieu Perrot,Edouard Duchesnay +15 more
TL;DR: Scikit-learn is a Python module integrating a wide range of state-of-the-art machine learning algorithms for medium-scale supervised and unsupervised problems, focusing on bringing machine learning to non-specialists using a general-purpose high-level language.
Book
Learning Deep Architectures for AI
TL;DR: The motivations and principles regarding learning algorithms for deep architectures, in particular those exploiting as building blocks unsupervised learning of single-layer modelssuch as Restricted Boltzmann Machines, used to construct deeper models such as Deep Belief Networks are discussed.
Machine learning with Python
TL;DR: This presentation is a case study taken from the travel and holiday industry and describes the effectiveness of various techniques as well as the performance of Python-based libraries such as Python Data Analysis Library (Pandas), and Scikit-learn (built on NumPy, SciPy and matplotlib).
Journal ArticleDOI
The cost of corrosion in China
Baorong Hou,Xiaogang Li,Xiumin Ma,Cuiwei Du,Dawei Zhang,Meng Zheng,Weichen Xu,Dongzhu Lu,Fubin Ma +8 more
TL;DR: Wang et al. as mentioned in this paper summarized the findings that arose from the landmark "Study of Corrosion Status and Control Strategies in China", a key consulting project of the Chinese Academy of Engineering in 2015, which sought to determine the national cost of corrosion and costs associated with representative industries in China.