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Data-driven approach to solve vertical drain under time-dependent loading

Frontiers of Structural and Civil Engineering 2021年第3期15卷 696-711页

作者： Trong NGHIA-NGUYEN Mamoru KIKUMOTO Samir KHATIR salisa chaiyaput HNGUYEN-XUAN Thanh CUONG-LE Department of Civil Engineering Yokohama National UniversityYokohama 240-8501Japan Faculty of Civil Engineering Ho Chi Minh City Open UniversityHo Chi Minh City 70000Vietnam Department of Electrical Energy MetalsMechanical Constructions and SystemsFaculty of Engineering and ArchitectureGhent UniversityGhent 9000Belgium Department of Civil Engineering School of EngineeringKing Mongkut’s Institute of Technology LadkrabangBangkok 10520Thailand CIRTECH Institute Ho Chi Minh City University of Technology(HUTECH)Ho Chi Minh City 708300Vietnam

Currently,the vertical drain consolidation problem is solved by numerous analytical solutions,such as time-dependent solutions and linear or parabolic radial drainage in the smear zone,and no artificial intelligence(AI)approach has been ***,in this study,a new hybrid model based on deep neural networks(DNNs),particle swarm optimization(PSO),and genetic algorithms(GAs)is proposed to solve this *** DNN can effectively simulate any sophisticated equation,and the PSO and GA can optimize the selected DNN and improve the performance of the prediction *** the present study,analytical solutions to vertical drains in the literature are incorporated into the DNN–PSO and DNN–GA prediction models with three different radial drainage patterns in the smear zone under timedependent *** verification performed with analytical solutions and measurements from three full-scale embankment tests revealed promising applications of the proposed approach.

关键词： vertical drain artificial neural network time-dependent loading deep learning network genetic algorithm particle swarm optimization

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Electrochemical Behavior and Microstructure of Recyclable Aluminiummagmesium Alloy Hot-dip Coating Deposited on Low Carbon Steel Substrates

引用

Journal of Iron and Steel Research(International) 2015年第8期22卷 746-751页

作者： Panomkorn KWAKHONG Apichart ARTNASEAW chaiyaput KRUEHONG Department of Chemical Engineering Faculty of Engineering Khon Kaen University

With the abundance and good corrosion resistance of aluminium, hot-dip technique was used to prepare the recycled Al with 8.2 mass% Mg alloy coating on low carbon steel substrates. Electrochemical behavior of this coating was investigated by an- odic polarization and open circuit potential measurement. Its microstructure and composition were observed by scanning electron microscope and energy-dispersive X-ray spectrometry, respectively. The long lasting corrosion performance of coated steels was in- vestigated under the salt fog spray test. From anodic polarization curves and open circuit potential, recycled Al with 8.2 mass% Mg coating performed adequate sacrificial ability. At 0.40 V, current density of recycled Al with 8.2 mass% Mg alloy coating was about 200 000 times higher than that of pure recycled Al coating, and was about 0.5 times lower than that of Zn coating. The microstruc- ture of recycled Al with 8.2 mass% Mg alloy coating on the steel substrate consisted ofAl3Mg2, Al-Fe intermetallic compound and Al matrix. The results from salt fog spray test showed that recycled Al with 8.2 mass% Mg alloy coated steel had similar corrosion resistance ability to Zn coated steel.

关键词： recycled A1-Mg alloy sacrificial ability anodic polarization corrosion

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