Quantitative characterization of reinforcement cross-sectional roughness and prediction of cover cracking based on machine learning under the influence of pitting corrosion
Jiang C. Zhang X. Lun P. Ali Memon S. Luo Q. Sun H. Wang W. Wang X. Wang X.
October 2023Elsevier B.V.
Measurement: Journal of the International Measurement Confederation
2023#220
The roughness characteristics caused by pitting corrosion on the reinforcement surface have an important influence on cover cracking. This study proposes two new indicators, RMPC and CMPC, for quantitatively evaluating reinforcement roughness and concavity. Then a novel approach to predicting crack volume was introduced based on ML. Results show that, RMPC is more applicable than commonly used morphological indicators for reinforcement roughness evaluation. The dry-wet cycle corrosion produces more severe section roughness and concavity than the applied current corrosion, up to about 2.4 times. When the corrosion level exceeds 3%, average RMPC of the dry-wet cycle samples are consistently higher. When the corrosion level is less than 1%, the cross-section is typically concave. The introduction of roughness indicators significantly improves the accuracy of crack volume prediction, increasing R2 value from 0.646 to 0.956. Machine learning prediction models using ensemble learning algorithms demonstrate superior accuracy and stability compared to non-ensemble models.
Geometric characteristics , Machine learning , Reinforcement corrosion , Roughness , X-ray microtomography
Text of the article Перейти на текст статьи
Guangdong Provincial Key Laboratory of Durability for Marine Civil Engineering, College of Civil and Transportation Engineering, Shenzhen University, Shenzhen, 518060, China
Department of Civil Engineering and Environmental Engineering, School of Engineering and Digital Sciences, Nazarbayev University, Nur-Sultan, 010000, Kazakhstan
School of Architecture and Civil Engineering, Huangshan University, Huangshan, 245041, China
Guangdong Provincial Key Laboratory of Durability for Marine Civil Engineering
Department of Civil Engineering and Environmental Engineering
School of Architecture and Civil Engineering
10 лет помогаем публиковать статьи Международный издатель
Книга Публикация научной статьи Волощук 2026 Book Publication of a scientific article 2026