Hamdan Hasan, Alsit Abdullah, Al Tahhan Aghyad B, Mughieda Omer, Mourad Abdel-Hamid I, Shehadeh Mutasem A, Alkhedher Mohammad
Department of Mechanical and Industrial Engineering, Abu Dhabi University, Abu Dhabi, PO 59911, United Arab Emirates.
Department of Civil Engineering, Abu Dhabi University, Abu Dhabi, PO 59911, United Arab Emirates.
Heliyon. 2024 Feb 1;10(3):e25276. doi: 10.1016/j.heliyon.2024.e25276. eCollection 2024 Feb 15.
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.
尽管进行了广泛的研究，但在恶劣环境条件下的应力腐蚀开裂（SCC）仍然是一个重大挑战。机械、化学和电化学因素之间复杂的相互作用阻碍了对材料降解和剩余使用寿命的准确预测。此外，对应力腐蚀开裂缺陷进行实时监测和早期检测的需求，给预测过程增加了更多复杂性。因此，迫切需要综合性的综述论文来整合当前预测方法的知识和进展。此类综述将有助于更好地理解和解决与恶劣环境条件下应力腐蚀开裂相关的挑战。这项工作旨在全面概述用于评估和预测此类环境中应力腐蚀开裂的各种预测方法。本文将深入探讨以下几个部分：恶劣环境条件加剧、无损检测（NDT）技术、电化学技术、数值建模和机器学习。这篇综述倾向于为该领域的研究人员和从业人员提供有价值的资源，促进制定有效的策略来减轻应力腐蚀开裂，并确保在具有挑战性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，但恶劣环境中的应力腐蚀开裂仍然是一个关键问题，机械、化学和电化学因素的相互作用使其变得更加复杂。本综述旨在整合当前的预测方法，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，但新兴的计算方法有望实现实时、准确的预测。本文还简要讨论了一些著名的应力腐蚀开裂失效案例，以强调改进预测技术的紧迫性。这项工作旨在填补知识空白，并为制定有效的应力腐蚀开裂缓解策略提供资源，从而确保在具有挑战性的运行条件下材料的完整性。
