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Strengthening of bolted shear joints in industrialized ferrocement construction
M. Ismail,M. Shariati,A.S.M. Abdul Awal,C.E. Chiong,E. Sadeghipour Chahnasir,A. Porbar,A. Heydari,M. Khorami 국제구조공학회 2018 Steel and Composite Structures, An International J Vol.28 No.6
This paper highlights results of some experimental work that deals with strengthening of bolted shear joints in thin-walled ferrocement structure where steel wires, bent into U-shape are considered as simple inserts around the bolt hole. The parameters investigated include the number of layers of wire mesh, edge distance of bolt hole, size and location of the inserts. Test results have shown that for small edge distance, failure occurred either in cleavage or shearing mode, and the strength of the joint increased with an increase in the edge distance. This continued up to an upper limit set by either tension or bearing failure. The experimental study further revealed that for a given edge distance the strength of a joint can significantly be enhanced by using U-inserts. The equations developed for predicting joint strength in ferrocement composites can also be modified to include the effects of the inserts with a good level of accuracy.
Majid Khorami,Masoud Khorami,Hedayatollah Motahar,Mohammadfarid Alvansazyazdi,Mahdi Shariati,Abdolrahim Jalali,M.M. Tahir 국제구조공학회 2017 Structural Engineering and Mechanics, An Int'l Jou Vol.63 No.2
In this paper, the incremental nonlinear dynamic analysis is used to evaluate the seismic performance of steel moment frame structures. To this purpose, three special moment frame structure with 5, 10 and 15 stories are designed according to the Iran\'s national building code for steel structures and the provisions for design of earthquake resistant buildings (2800 code). Incremental Nonlinear Analysis (IDA) is performed for 15 different ground motions, and responses of the structures are evaluated. For the immediate occupancy and the collapse prevention performance levels, the probability that seismic demand exceeds the seismic capacity of the structures is computed based on FEMA350. Also, fragility curves are plotted for three high-code damage levels using HASUS provisions. Based on the obtained results, it is evident that increase in the height of the frame structures reduces the reliability level. In addition, it is concluded that for the design earthquake the probability of exceeding average collapse prevention level is considerably larger than high and full collapse prevention levels.9.
Distribution of shear force in perforated shear connectors
Xing Wei,M. Shariati,Y. Zandi,Shiling Pei,Zhibin Jin,S. Gharachurlu,M.M. Abdullahi,M.M. Tahir,M. Khorami 국제구조공학회 2018 Steel and Composite Structures, An International J Vol.27 No.3
A perforated shear connector group is commonly used to transfer shear in steel–concrete composite structures when the traditional shear stud connection is not strong enough. The multi-hole perforated shear connector demonstrates a more complicated behavior than the single connector. The internal force distribution in a specific multi-hole perforated shear connector group has not been thoroughly studied. This study focuses on the load-carrying capacity and shear force distribution of multi-hole perforated shear connectors in steel.concrete composite structures. ANSYS is used to develop a three-dimensional finite element model to simulate the behavior of multi-hole perforated connectors. Material and geometric nonlinearities are considered in the model to identify the failure modes, ultimate strength, and load–slip behavior of the connection. A three-layer model is introduced and a closed-form solution for the shear force distribution is developed to facilitate design calculations. The shear force distribution curve of the multi-hole shear connector is catenary, and the efficiency coefficient must be considered in different limit states.
Portland cement structure and its major oxides and fineness
A. Nosrati,Y. Zandi,M. Shariati,K. Khademi,M. Darvishnezhad Aliabad,A. Marto,M.A. Mu’azu,E. Ghanbari,M.B. Mahdizadeh,A. Shariati,M. Khorami 국제구조공학회 2018 Smart Structures and Systems, An International Jou Vol.22 No.4
Predicting the compressive strength of concrete has been considered as the initial phase across the cement production processing. The current study has focused on the integration of the concrete compressive strength in 28 days with the mix of the major oxides and fine aggregates as an experimental formula through the use of two types of Portland cement resulting the compressive strength of the concrete highly dependent on time.
Chahnasir, E. Sadeghipour,Zandi, Y.,Shariati, M.,Dehghani, E.,Toghroli, A.,Mohamad, E. Tonnizam,Shariati, A.,Safa, M.,Wakil, K.,Khorami, M. 국제구조공학회 2018 Smart Structures and Systems, An International Jou Vol.22 No.4
The factors affecting the shear strength of the angle shear connectors in the steel-concrete composite beams can play an important role to estimate the efficacy of a composite beam. Therefore, the current study has aimed to verify the output of shear capacity of angle shear connector according to the input provided by Support Vector Machine (SVM) coupled with Firefly Algorithm (FFA). SVM parameters have been optimized through the use of FFA, while genetic programming (GP) and artificial neural networks (ANN) have been applied to estimate and predict the SVM-FFA models' results. Following these results, GP and ANN have been applied to develop the prediction accuracy and generalization capability of SVM-FFA. Therefore, SVM-FFA could be performed as a novel model with predictive strategy in the shear capacity estimation of angle shear connectors. According to the results, the Firefly algorithm has produced a generalized performance and be learnt faster than the conventional learning algorithms.
E. Sadeghipour Chahnasir,Y. Zandi,M. Shariati,E. Dehghani,A. Toghroli,E. Tonnizam Mohamad,A. Shariati,M. Safa,K. Wakil,M. Khorami 국제구조공학회 2018 Smart Structures and Systems, An International Jou Vol.22 No.4
The factors affecting the shear strength of the angle shear connectors in the steel-concrete composite beams can play an important role to estimate the efficacy of a composite beam. Therefore, the current study has aimed to verify the output of shear capacity of angle shear connector according to the input provided by Support Vector Machine (SVM) coupled with Firefly Algorithm (FFA). SVM parameters have been optimized through the use of FFA, while genetic programming (GP) and artificial neural networks (ANN) have been applied to estimate and predict the SVM-FFA models' results. Following these results, GP and ANN have been applied to develop the prediction accuracy and generalization capability of SVM-FFA. Therefore, SVM-FFA could be performed as a novel model with predictive strategy in the shear capacity estimation of angle shear connectors. According to the results, the Firefly algorithm has produced a generalized performance and be learnt faster than the conventional learning algorithms.
Portland cement structure and its major oxides and fineness
Nosrati, A.,Zandi, Y.,Shariati, M.,Khademi, K.,Aliabad, M. Darvishnezhad,Marto, A.,Mu'azu, M.A.,Ghanbari, E.,Mahdizadeh, M.B.,Shariati, A.,Khorami, M. 국제구조공학회 2018 Smart Structures and Systems, An International Jou Vol.22 No.4
Predicting the compressive strength of concrete has been considered as the initial phase across the cement production processing. The current study has focused on the integration of the concrete compressive strength in 28 days with the mix of the major oxides and fine aggregates as an experimental formula through the use of two types of Portland cement resulting the compressive strength of the concrete highly dependent on time.
Khosro Shahpoori Arani,Yousef Zandi,Binh Thai Pham,M.A. Mu’azu,Javad Katebi,Mohammad Mohammadhassani,Seyedamirhesam Khalafi,Edy Tonnizam Mohamad,Karzan Wakil,Majid Khorami 사단법인 한국계산역학회 2019 Computers and Concrete, An International Journal Vol.23 No.1
This paper presents a computational rational model to predict the ultimate and optimized load capacity of reinforced concrete (RC) beams strengthened by a combination of longitudinal and transverse fiber reinforced polymer (FRP) composite plates/sheets (flexure and shear strengthening system). Several experimental and analytical studies on the confinement effect and failure mechanisms of fiber reinforced polymer (FRP) wrapped columns have been conducted over recent years. Although typical axial members are large-scale square/ rectangular reinforced concrete (RC) columns in practice, the majority of such studies have concentrated on the behavior of small-scale circular concrete specimens. A high performance concrete, known as polymer concrete, made up of natural aggregates and an orthophthalic polyester binder, reinforced with non-metallic bars (glass reinforced polymer) has been studied. The material is described at micro and macro level, presenting the key physical and mechanical properties using different experimental techniques. Furthermore, a full description of non-metallic bars is presented to evaluate its structural expectancies, embedded in the polymer concrete matrix. In this paper, the mechanism of mechanical interaction of smooth and lugged FRP rods with concrete is presented. A general modeling and application of various elements are demonstrated. The contact parameters are defined and the procedures of calculation and evaluation of contact parameters are introduced. The method of calibration of the calculated parameters is presented. Finally, the numerical results are obtained for different bond parameters which show a good agreement with experimental results reported in literature.
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.
Evaluation of the parameters affecting the Schmidt rebound hammer reading using ANFIS method
Ali Toghroli,Ehsan Darvishmoghaddam,Yousef Zandi,Mahdi Parvan,Maryam Safa,Mu’azu Mohammed Abdullahi,Abbas Heydari,Karzan Wakil,Saad A.M. Gebreel,Majid Khorami 사단법인 한국계산역학회 2018 Computers and Concrete, An International Journal Vol.21 No.5
As a nondestructive testing method, the Schmidt rebound hammer is widely used for structural health monitoring. During application, a Schmidt hammer hits the surface of a concrete mass. According to the principle of rebound, concrete strength depends on the hardness of the concrete energy surface. Study aims to identify the main variables affecting the results of Schmidt rebound hammer reading and consequently the results of structural health monitoring of concrete structures using adaptive neuro-fuzzy inference system (ANFIS). The ANFIS process for variable selection was applied for this purpose. This procedure comprises some methods that determine a subsection of the entire set of detailed factors, which present analytical capability. ANFIS was applied to complete a flexible search. Afterward, this method was applied to conclude how the five main factors (namely, age, silica fume, fine aggregate, coarse aggregate, and water) used in designing concrete mixture influence the Schmidt rebound hammer reading and consequently the structural health monitoring accuracy. Results show that water is considered the most significant parameter of the Schmidt rebound hammer reading. The details of this study are discussed thoroughly.