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RISS 인기검색어
- 검색키워드
- 저자 : Danial Jahed Armaghani (검색결과 3 건)
- 무료
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Intelligent design of retaining wall structures under dynamic conditions
Haiqing Yang,Mohammadreza Koopialipoor,Danial Jahed Armaghani,Behrouz Gordan,Majid Khorami,M.M. Tahir 국제구조공학회 2019 Steel and Composite Structures, An International J Vol.31 No.6
The investigation of retaining wall structures behavior under dynamic loads is considered as one of important parts for designing such structures. Generally, the performance of these structures is under the influence of the environment conditions and their geometry. The aim of this research is to design retaining wall structures based on smart and optimal systems. The use of accuracy and speed to assess the structures under different conditions is one of the important parts sought by designers. Therefore, optimal and smart systems are able to have better addressing these problems. Using numerical and coding methods, this research investigates the retaining wall structure design under different dynamic conditions. More than 9500 models were constructed and considered for modelling design. These designs include height and thickness of the wall, soil density, rock density, soil friction angle, and peak ground acceleration (PGA) variables. Accordingly, a neural network system was developed to establish an appropriate relationship between data to obtain safety factor (SF) of retaining walls under different seismic conditions. Different parameters were analyzed and the effect of each parameter was assessed separately. According to these analyses, the structure optimization was performed to increase the SF values. The optimal and smart design showed that under different PGA conditions, the structure performance can be appropriately improved while utilization of the initial (or basic) parameters leads to the structure failure. Therefore, by increasing accuracy and speed, smart methods could improve the retaining structure performance in controlling the wall failure. The intelligent design process of this study can be applied to some other civil engineering applications such as slope stability.
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Evaluating the bond strength of FRP in concrete samples using machine learning methods
Juncheng Gao,Mohammadreza Koopialipoor,Danial Jahed Armaghani,Aria Ghabussi,Shahrizan Baharom,Armin Morasaei,Ali Shariati,Majid Khorami,Jian Zhou 국제구조공학회 2020 Smart Structures and Systems, An International Jou Vol.26 No.4
In recent years, the use of Fiber Reinforced Polymers (FRPs) as one of the most common ways to increase the strength of concrete samples, has been introduced. Evaluation of the final strength of these specimens is performed with different experimental methods. In this research, due to the variety of models, the low accuracy and impact of different parameters, the use of new intelligence methods is considered. Therefore, using artificial intelligent-based models, a new solution for evaluating the bond strength of FRP is presented in this paper. 150 experimental samples were collected from previous studies, and then two new hybrid models of Imperialist Competitive Algorithm (ICA)-Artificial Neural Network (ANN) and Artificial Bee Colony (ABC)-ANN were developed. These models were evaluated using different performance indices and then, a comparison was made between the developed models. The results showed that the ICA-ANN model's ability to predict the bond strength of FRP is higher than the ABC-ANN model. Finally, to demonstrate the capabilities of this new model, a comparison was made between the five experimental models and the results were presented for all data. This comparison showed that the new model could offer better performance. It is concluded that the proposed hybrid models can be utilized in the field of this study as a suitable substitute for empirical models.
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Xiangyang Zhang,Vahid Bayat,Mohammadreza Koopialipoor,Danial Jahed Armaghani,Weixun Yong,Jian Zhou 국제구조공학회 2020 Smart Structures and Systems, An International Jou Vol.26 No.3
Structural damage to an arch dam is often of major concern and must be evaluated for probable rehabilitation to ensure safe, regular, normal operation. This evaluation is crucial to prevent any catastrophic or failure consequences for the life time of the dam. If specific major damage such as a large crack occurs to the dam body, the assessments will be necessary to determine the current level of safety and predict the resistance of the structure to various future loading such as earthquakes, etc. This study investigates the behavior of an arch dam cracked due to water pressure. Safety factors (SFs), of shear and compressive tractions were calculated at the surfaces of the contraction joints and the cracks. The results indicated that for cracking with an extension depth of half the thickness of the dam body, for both cases of penetration and non-penetration of water load into the cracks, SFs only slightly reduces. However, in case of increasing the depth of crack extension into the entire thickness of the dam body, the friction angle of the cracked surface is crucial; however, if it reduces, the normal loading SFs of stresses and joints tractions reduce significantly.
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