PDF(Pubmed)
Abstract：
Stress corrosion cracking (SCC) under harsh environmental conditions still poses a significant challenge, despite extensive research efforts. The intricate interplay among mechanical, chemical, and electrochemical factors hinders the accurate prognosis of material degradation and remaining service life. Furthermore, the demand for real-time monitoring and early detection of SCC defects adds further complexity to the prognostication process. Therefore, there is an urgent need for comprehensive review papers that consolidate current knowledge and advancements in prognosis methods. Such reviews would facilitate a better understanding and resolution of the challenges associated with SCC under harsh environmental conditions. This work aims to provide a comprehensive overview of various prognosis methods utilized for the assessment and prediction of SCC in such environments. The paper will delve into the following sections: exacerbating harsh environmental conditions, non-destructive testing (NDT) techniques, electrochemical techniques, numerical modeling, and machine learning. This review is inclined to serve as a valuable resource for researchers and practitioners working in the field, facilitating the development of effective strategies to mitigate SCC and ensure the integrity and reliability of materials operating in challenging environments. Despite considerable research, stress corrosion cracking in harsh environments remains a critical issue, complicated by the interplay of mechanical, chemical, and electrochemical factors. This review aims to consolidate current prognosis methods, including non-destructive testing, electrochemical techniques, numerical modeling, and machine learning. Key findings indicate that while traditional methods offer limited reliability, emerging computational approaches show promise for real-time, accurate predictions. The paper also briefly discusses notable SCC failure cases to underscore the urgency for improved prognosis techniques. This work aspires to fill knowledge gaps and serve as a resource for developing effective SCC mitigation strategies, thereby ensuring material integrity in challenging operational conditions.
摘要：
恶劣环境条件下的应力腐蚀开裂(SCC)仍然构成重大挑战,尽管进行了广泛的研究。机械之间复杂的相互作用，化学,和电化学因素阻碍了材料降解和剩余使用寿命的准确预测。此外，实时监测和早期检测SCC缺陷的需求进一步增加了预测过程的复杂性。因此,迫切需要综合综述论文,以巩固目前的知识和预后方法的进步.这种审查将有助于更好地理解和解决恶劣环境条件下与SCC相关的挑战。这项工作旨在全面概述用于评估和预测此类环境中SCC的各种预后方法。本文将深入研究以下几个部分：加剧恶劣的环境条件，无损检测（NDT）技术，电化学技术，数值建模,和机器学习。这篇评论倾向于作为在该领域工作的研究人员和从业人员的宝贵资源，促进制定有效的策略，以减轻SCC并确保在具有挑战性的环境中运行的材料的完整性和可靠性。尽管进行了大量研究，恶劣环境下的应力腐蚀开裂仍然是一个关键问题，由于机械的相互作用而变得复杂，化学,和电化学因素。这篇综述旨在巩固目前的预后方法，包括无损检测，电化学技术，数值建模,和机器学习。主要研究结果表明，虽然传统方法的可靠性有限，新兴的计算方法显示出实时的希望，准确的预测。本文还简要讨论了值得注意的SCC失败病例，以强调改善预后技术的紧迫性。这项工作渴望填补知识空白，并作为开发有效的SCC缓解策略的资源，从而确保在具有挑战性的操作条件下的材料完整性。
