Year: 2026 Language: English Author: Chao Liu, Bingqin Wang & Xiaogang Li Publisher: Wiley-VCH Edition: 1st ISBN: 978-3527355938 Format: PDF Quality: eBook Pages count: 611 Description: Bridges corrosion science and artificial intelligence to advance durable, high-performance marine steels Understanding and controlling the corrosion of steels in marine environments is a critical challenge for modern engineering, with far-reaching implications for safety, durability, and sustainability. Marine corrosion not only threatens the integrity of infrastructure such as bridges, offshore platforms, and railways but also leads to significant economic losses and environmental risks. Marine Corrosion of Steels:Mechanisms and AI-Driven Solutions provides a comprehensive exploration of the mechanistic processes underlying steel degradation and introduces innovative, data-driven approaches to improve corrosion resistance. Offering valuable insights into stress corrosion cracking, fatigue, and general degradation mechanisms in harsh marine conditions, the book systematically investigates corrosion behavior across a range of engineering steels, including high-manganese steel, titanium-steel composites, low-alloy rebar, and ductile iron. Beyond mechanistic analysis, dedicated chapters highlight pioneering applications of big data and artificial intelligence, such as predictive modeling, image recognition for pit analysis, and IoT-enabled real-time monitoring. These AI-driven approaches enable researchers and engineers to accelerate alloy design, optimize material selection, and implement proactive maintenance strategies. Combining deep scientific understanding with cutting-edge computational tools, Marine Corrosion of Steels:Mechanisms and AI-Driven Solutions: • Demonstrates how corrosion science is evolving toward intelligent, sustainable solutions for the most demanding industrial applications • Explores alloying strategies and material innovations to enhance corrosion resistance • Introduces novel electrochemical evaluation methods and image-based corrosion quantification • Presents real-world case studies, including corrosion fatigue in railway components and offshore steel performance • Discusses multi-modal frameworks combining physics, machine learning, and computer vision • Offers forward-looking insights on AI-driven alloy design for sustainability and cost reduction Connecting fundamental research to practical engineering solutions across multiple industries, Marine Corrosion of Steels:Mechanisms and AI-Driven Solutions is an essential resource for graduate-level courses in materials science, corrosion engineering, and mechanical engineering, particularly within programs in metallurgy, chemical engineering, and civil infrastructure. It is also a valuable reference for engineers, corrosion specialists, and researchers working in marine, aerospace, and energy industries. Additional info: About the Authors: Chao Liu is a professor at the Institute of Advanced Materials and Technology, University of Science and Technology Beijing, China. His research focuses on localized corrosion mechanisms, corrosion big data, and the development of advanced corrosion-resistant steels. Bingqin Wang is an assistant researcher at the Institute of Advanced Materials and Technology, University of Science and Technology Beijing, China. His work centers on corrosion big data, including predictive modeling of atmospheric corrosion and corrosion image quantification, advancing methodologies for steel performance assessment. Xiaogang Li is a professor at the Institute of Advanced Materials and Technology, University of Science and Technology Beijing, China and a leader in corrosion science. His research includes corrosion theory, new steel development, and performance optimization of weathering steels. Shasha Zhang is an engineer at the School of Advanced Engineering, University of Science and Technology Beijing, China. Her research applies artificial intelligence and IoT technologies to corrosion detection and data-driven corrosion protection strategies. Zhong Li is an associate professor at the Institute of Advanced Materials and Technology, University of Science and Technology Beijing, China. Her expertise lies in microbiologically induced corrosion, stress corrosion cracking, and advanced materials for corrosion resistance.
offtop if someone want know little bit more about economy of rust -> can start from such search NACE International initiated the International Measures of Prevention, Application, and Economics of Corrosion Technologies (IMPACT) study to examine the current role of corrosion management in industry and government and to establish best practices. The global cost of corrosion is estimated to be US$2.5 trillion, which is equivalent to 3.4% of the global Gross Domestic Product (GDP) (2013). By using available corrosion control practices, it is estimated that savings of between 15 and 35% of the cost of corrosion could be realized; i.e., between US$375 and $875 billion annually on a global basis, an astronomical savings. In addition, these costs typically do not include individual safety or environmental consequences. The high cost of corrosion has been known for years; Uhlig performed a comprehensive study in 1949 that revealed a cost of corrosion equivalent to 2.5% of the U.S. GDP.
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Marine Corrosion of Steels
Language: English
Author: Chao Liu, Bingqin Wang & Xiaogang Li
Publisher: Wiley-VCH
Edition: 1st
ISBN: 978-3527355938
Format: PDF
Quality: eBook
Pages count: 611
Description: Bridges corrosion science and artificial intelligence to advance durable, high-performance marine steels
Understanding and controlling the corrosion of steels in marine environments is a critical challenge for modern engineering, with far-reaching implications for safety, durability, and sustainability. Marine corrosion not only threatens the integrity of infrastructure such as bridges, offshore platforms, and railways but also leads to significant economic losses and environmental risks. Marine Corrosion of Steels:Mechanisms and AI-Driven Solutions provides a comprehensive exploration of the mechanistic processes underlying steel degradation and introduces innovative, data-driven approaches to improve corrosion resistance.
Offering valuable insights into stress corrosion cracking, fatigue, and general degradation mechanisms in harsh marine conditions, the book systematically investigates corrosion behavior across a range of engineering steels, including high-manganese steel, titanium-steel composites, low-alloy rebar, and ductile iron. Beyond mechanistic analysis, dedicated chapters highlight pioneering applications of big data and artificial intelligence, such as predictive modeling, image recognition for pit analysis, and IoT-enabled real-time monitoring. These AI-driven approaches enable researchers and engineers to accelerate alloy design, optimize material selection, and implement proactive maintenance strategies.
Combining deep scientific understanding with cutting-edge computational tools, Marine Corrosion of Steels:Mechanisms and AI-Driven Solutions:
• Demonstrates how corrosion science is evolving toward intelligent, sustainable solutions for the most demanding industrial applications
• Explores alloying strategies and material innovations to enhance corrosion resistance
• Introduces novel electrochemical evaluation methods and image-based corrosion quantification
• Presents real-world case studies, including corrosion fatigue in railway components and offshore steel performance
• Discusses multi-modal frameworks combining physics, machine learning, and computer vision
• Offers forward-looking insights on AI-driven alloy design for sustainability and cost reduction
Connecting fundamental research to practical engineering solutions across multiple industries, Marine Corrosion of Steels:Mechanisms and AI-Driven Solutions is an essential resource for graduate-level courses in materials science, corrosion engineering, and mechanical engineering, particularly within programs in metallurgy, chemical engineering, and civil infrastructure. It is also a valuable reference for engineers, corrosion specialists, and researchers working in marine, aerospace, and energy industries.
Additional info: About the Authors:
Chao Liu is a professor at the Institute of Advanced Materials and Technology, University of Science and Technology Beijing, China. His research focuses on localized corrosion mechanisms, corrosion big data, and the development of advanced corrosion-resistant steels.
Bingqin Wang is an assistant researcher at the Institute of Advanced Materials and Technology, University of Science and Technology Beijing, China. His work centers on corrosion big data, including predictive modeling of atmospheric corrosion and corrosion image quantification, advancing methodologies for steel performance assessment.
Xiaogang Li is a professor at the Institute of Advanced Materials and Technology, University of Science and Technology Beijing, China and a leader in corrosion science. His research includes corrosion theory, new steel development, and performance optimization of weathering steels.
Shasha Zhang is an engineer at the School of Advanced Engineering, University of Science and Technology Beijing, China. Her research applies artificial intelligence and IoT technologies to corrosion detection and data-driven corrosion protection strategies.
Zhong Li is an associate professor at the Institute of Advanced Materials and Technology, University of Science and Technology Beijing, China. Her expertise lies in microbiologically induced corrosion, stress corrosion cracking, and advanced materials for corrosion resistance.
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if someone want know little bit more about economy of rust -> can start from such search
NACE International initiated the International Measures of Prevention, Application, and Economics of Corrosion Technologies (IMPACT) study to examine the current role of corrosion management in industry and government and to establish best practices. The global cost of corrosion is estimated to be US$2.5 trillion, which is equivalent to 3.4% of the global Gross Domestic Product (GDP) (2013). By using available corrosion control practices, it is estimated that savings of between 15 and 35% of the cost of corrosion could be realized; i.e., between US$375 and $875 billion annually on a global basis, an astronomical savings. In addition, these costs typically do not include individual safety or environmental consequences. The high cost of corrosion has been known for years; Uhlig performed a comprehensive study in 1949 that revealed a cost of corrosion equivalent to 2.5% of the U.S. GDP.
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