According to the latest ESI (Basic Science Indicators Database) data, Professor Shao Wei, member of the Port and Marine Engineering Safety and Disaster Prevention team, published his research paper Durability life prediction and Prevention in the Construction and Building Materials, a TOP journal of the first District of the Chinese Academy of Sciences horizontal bearing characteristics of CFRP composite piles in marine environments and Associate Professor Chao Zhiming published in Geotextiles and, a TOP journal of the first District of the Chinese Academy of Sciences The research paper Artificial intelligence algorithms for predicting peak shear strength of clayey soil-geomembrane interfaces and experimental validation was selected as highly cited papers by ESI, and the first completion unit of the two highly cited papers was Shanghai Maritime University.
Research on durability life prediction and horizontal bearing characteristics of CFRP composite piles under Marine environment
Carbon fiber reinforced composite (CFRP) is a new type of material composed of carbon fiber material and resin matrix. CFRP material has the advantages of low density, high tensile strength, good bending resistance, good fatigue resistance and good corrosion resistance, and has shown its unique advantages in the development of Marine construction field. In recent years, with the extensive application of CFRP materials in Marine engineering, the mechanical properties and durability of CFRP concrete members have become a hot topic of research at home and abroad. Professor Shao Wei's research group of Shanghai Maritime University proposed to use CFRP bars instead of ordinary steel bars to make CFRP composite pile foundation, and studied the durability life and horizontal bearing performance of composite pile foundation under different CFRP replacement rates. The research results have broad application prospects for extending the service life of pile foundation in Marine environment.
In this study, the durability of CFRP composite pile is divided into the initial corrosion stage of steel bar and the crack expansion stage of concrete protective layer. Based on the chloride ion diffusion model and Monte Carlo simulation method, the initial corrosion time of CFRP composite pile was predicted. Based on the thick-walled cylinder theory, the critical corrosion depth of the concrete protective layer is deduced, and the durability life prediction model of the crack expansion stage is established. Through the three-point bending test of CFRP composite pile, the reduction coefficient of flexural rigidity of CFRP composite pile under different displacement rate is obtained, and the decay law of flexural rigidity and horizontal bearing characteristics of CFRP composite pile under Marine environment are analyzed. This study provides a new method for improving the service life of Marine pile foundation. The research results have been published online in Construction and Building Materials (Area 1, impact factor 7.9). The first author of the paper is Professor Shao Wei, College of Marine Science and Engineering, Shanghai Maritime University. Since its publication, this paper has attracted wide attention from domestic and foreign peers, and has been selected as a highly cited paper by ESI.
The original link: https://doi.org/10.1016/j.conbuildmat.2022.130116
Thesis of Associate Professor Chao Zhiming: Artificial Intelligence algorithm for predicting the peak shear strength of clay-geomembrane interface and experimental verification
Geomembrane is a kind of waterproof barrier material with high polymer as the basic raw material, which has excellent environmental stress cracking resistance and chemical corrosion resistance, and has a long service life, and is widely used in landfill, dam seepage prevention and other projects. In practical engineering, relative movement and stress concentration occur at the interface between geomembrane and soil, which is the weak link in shear strength of the whole system. Therefore, the correct evaluation of the peak shear strength of soil-geomembrane interface is very important for the reasonable design and safe operation of related projects.
With the wide application of geosynthetic materials in practical engineering, the shear strength of soil-geomembrane interface has been the focus of research at home and abroad. Direct shear test is the main method to determine the peak shear strength of soil-geomembrane interface, but the method of laboratory test is time-consuming and laborious. In addition, the interaction mechanism between soil-geomembrane interface is complicated, so it is difficult to find an ideal empirical formula. In recent years, the development of artificial intelligence technology provides a new way to effectively predict the peak shear strength of the interface. The research group of Associate Professor Chao Zhiming from Shanghai Maritime University used the integrated algorithm of Thinking Evolution algorithm (MEA) and adaptive augmentation algorithm-back propagation Artificial Neural Network (ADA-BPANN) to predict the peak shear strength of clay-geomembrane interface, which has a broad application prospect in predicting the peak shear strength of the structure-geosynthetic materials interface with complex mechanism of action.
The peak shear strength of clay-geomembrane interface is an important parameter for the design of relevant engineering infrastructure. Based on the results of 623 direct shear experiments at the interface, a machine learning model was established to predict the peak shear strength of the clay-geomembrane interface, combined with the integrated algorithm of the Thought Evolution algorithm (MEA) and the adaptive augmentation algorithm-back Propagation Artificial Neural Network (ADA-BPANN). By comparing with traditional machine learning algorithms, including particle swarm optimization (PSO) and Genetic algorithm (GA) optimized ADA-BPANN, MEA-optimized support vector Machine (SVM) and Random Forest (RF), the results show that MEA-optimized ADA-BPANN has higher prediction accuracy and shorter training time. The problems of local optimization and overfitting are reduced to a large extent. In addition, the sensitivity of the parameters is analyzed using the model, and the study shows that the normal stress has the greatest influence on the peak shear strength, followed by the roughness of the geomembrane. Finally, an analytical equation is proposed to predict the peak shear strength of the interface, so as to extend the application of the research results to non-professionals and realize the universality of the research results.
This study provides a more accurate and efficient way to predict the peak shear strength of clay-geomembrane interface. The research has been published online in Geotextiles and Geomembranes (Zone 1, Impact Factor 5.2). The lead author is Associate Professor Zhiming Chao, School of Marine Science and Engineering, Shanghai Maritime University. Since its publication, this paper has attracted wide attention from domestic and foreign peers, and has been selected as a highly cited paper by ESI.
The original link: https://doi.org/10.1016/j.geotexmem.2022.10.007
FIG. 1 Professor Shao Wei's thesis: Durability life prediction and horizontal bearing characteristics study of CFRP composite piles in Marine environment
FIG.2 Associate Professor Chao Zhiming's thesis: Artificial intelligence algorithm and experimental verification for predicting the peak shear strength of clay-geomembrane interface