http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
Mahdi Shariati,Mohammad Grayeli,Ali Shariati,Morteza Naghipour 국제구조공학회 2020 Steel and Composite Structures, An International J Vol.36 No.5
In recent years, the composite columns have been widely used in the structures. These columns are mainly used to construct the structures with a large span and high floor height. Concrete filled tubes (CFTs) are a type of composite column, which are popular nowadays due to their numerous benefits. The purpose of this study is to investigate such frames at elevated temperatures. The method used in this research is based on section 2.2 of Eurocode 4. First, for the verification purpose, a comparison was made between the experimental results and the numerical model of the concrete filled tube. Then a composite frame was analyzed under fire temperature with different parameters. The results showed that the failure time decreased with increasing the friction of different models. Moreover, investigation of the concrete moisture content revealed that an increase in the concrete moisture content from 3% to 10% led to extended failure time for different models. For instance, in the second frame model, the failure time has increased up to 8%.
Mahdi Shariati,Mohammad Saeed Mafipour,Peyman Mehrabi,Yousef Zandi,Davoud Dehghani,Alireza Bahadori,Ali Shariati,Nguyen Thoi Trung,Musab N.A. Salih,Shek Poi-Ngian 국제구조공학회 2019 Steel and Composite Structures, An International J Vol.33 No.3
This study is aimed to predict the behaviour of channel shear connectors in composite floor systems at different temperatures. For this purpose, a soft computing approach is adopted. Two novel intelligence methods, including an Extreme Learning Machine (ELM) and a Genetic Programming (GP), are developed. In order to generate the required data for the intelligence methods, several push-out tests were conducted on various channel connectors at different temperatures. The dimension of the channel connectors, temperature, and slip are considered as the inputs of the models, and the strength of the connector is predicted as the output. Next, the performance of the ELM and GP is evaluated by developing an Artificial Neural Network (ANN). Finally, the performance of the ELM, GP, and ANN is compared with each other. Results show that ELM is capable of achieving superior performance indices in comparison with GP and ANN in the case of load prediction. Also, it is found that ELM is not only a very fast algorithm but also a more reliable model.
Application of waste tire rubber aggregate in porous concrete
Mahdi Shariati,Arian Heyrati,Yousef Zandi,Hossein Laka,Ali Toghroli,Peiman Kianmehr,Maryam Safa,Musab N.A. Salih,Shek Poi-Ngian 국제구조공학회 2019 Smart Structures and Systems, An International Jou Vol.24 No.4
This study aimed to categorize pervious rubberized concrete into fresh and hardened concrete analyzing its durability, permeability and strength. During the globalization of modern life, growing population and industry rate have signified a sustainable approach to all aspects of modern life. In recent years, pervious concrete (porous concrete) has significantly substituted for pavements due to its mechanical and environmental properties. On the other hand, scrap rubber tire has been also contributed with several disposal challenges. Considering the huge amount of annually tire wastes tossing out, the conditions become worse. Pervious concrete (PC) gap has graded surface assisted with storm water management, recharging groundwater sources and alleviate water run-offs. The results have shown that the use of waste tires as aggregate built into pervious concrete has tremendously reduced the scrap tire wastes enhancing environmental compliance.
Mahdi Shariati,Morteza Naghipour,Ghazaleh Yousofizinsaz,Ali Toghroli,Nima Pahlavannejad Tabarestani 국제구조공학회 2020 Steel and Composite Structures, An International J Vol.34 No.3
A concrete filled steel tube (CFT) column with stiffeners has preferable behavior subjected to axial loading condition due to delay local buckling of the steel wall than traditional CFT columns without stiffeners. Welding lines in welded built-up steel box columns is expected to behave as longitudinal stiffeners. This study has presented a numerical investigation into the behavior of built-up concrete filled steel tube columns under axial pressure. At first stage, a finite element model (FE) has been built to simulate the behavior of built-up CFT columns. Comparing the results of FE and test has shown that numerical model passes the desired conditions and could accurately predict the axial performance of CFT column. Also, by the raise of steel tube thickness, the load bearing capacity of columns has been increased due to higher confinement effect. Also, the raise of concrete strength with greater cross section is led to a higher load bearing capacity compared to the steel tube thickness increment. In CFT columns with greater cross section, concrete strength has a higher influence on load bearing capacity which is noticeable in columns with more welding lines.
Shariati, Mahdi,Rafie, Shervin,Zandi, Yousef,Fooladvand, Rouhollah,Gharehaghaj, Behnam,Mehrabi, Peyman,Shariat, Ali,Trung, Nguyen Thoi,Salih, Musab N.A.,Poi-Ngian, Shek Techno-Press 2019 Advances in concrete construction Vol.8 No.3
Although applying self-consolidating concrete (SCC) in many modern structures is an inevitable fact, the high consumption of cement in its mixing designs has led to increased production costs and adverse environmental effects. In order to find economically viable sources with environmentally friendly features, natural pozzolan pumice and blast furnace slag in 10-50% of replacement binary designs have been investigated for experiments on the properties of fresh concrete, mechanical properties, and durability. As a natural pozzolan, pumice does not require advanced equipment to prepare for consumption and only needs to be powdered. Pumice has been the main focus of this research because of simple preparation. Also to validate the results, in addition to the control specimens of each design, fly ash as a known powder has been evaluated. Moreover, ternary mixes of pumice and silica fume were investigated to enhance the obtained results of binary mixes. It was concluded that pumice and slag powders indicated favorable performance in the high percentage of replacement.
Mahdi Shariati,Mohammad Saeed Mafipour,Peyman Mehrabi,Masoud Ahmadi,Karzan Wakil,Nguyen Thoi Trung,Ali Toghroli 국제구조공학회 2020 Smart Structures and Systems, An International Jou Vol.25 No.2
Mineral admixtures have been widely used to produce concrete. Pozzolans have been utilized as partially replacement for Portland cement or blended cement in concrete based on the materials' properties and the concrete's desired effects. Several environmental problems associated with producing cement have led to partial replacement of cement with other pozzolans. Furnace slag and fly ash are two of the pozzolans which can be appropriately used as partial replacements for cement in concrete. However, replacing cement with these materials results in significant changes in the mechanical properties of concrete, more specifically, compressive strength. This paper aims to intelligently predict the compressive strength of concretes incorporating furnace slag and fly ash as partial replacements for cement. For this purpose, a database containing 1030 data sets with nine inputs (concrete mix design and age of concrete) and one output (the compressive strength) was collected. Instead of absolute values of inputs, their proportions were used. A hybrid artificial neural network-genetic algorithm (ANN-GA) was employed as a novel approach to conducting the study. The performance of the ANN-GA model is evaluated by another artificial neural network (ANN), which was developed and tuned via a conventional backpropagation (BP) algorithm. Results showed that not only an ANN-GA model can be developed and appropriately used for the compressive strength prediction of concrete but also it can lead to superior results in comparison with an ANN-BP model.
Evaluation of seismic performance factors for tension-only braced frames
Mahdi Shariati,Majid Lagzian,Shervin Maleki,Ali Shariati,Nguyen Thoi Trung 국제구조공학회 2020 Steel and Composite Structures, An International J Vol.35 No.4
The tension-only braced frames (TOBFs) are widely used as a lateral force resisting system (LFRS) in low-rise steel buildings due to their simplicity and economic advantage. However, the system has poor seismic energy dissipation capacity and pinched hysteresis behavior caused by early buckling of slender bracing members. The main concern in utilizing the TOBF system is the determination of appropriate performance factors for seismic design. A formalized approach to quantify the seismic performance factor (SPF) based on determining an acceptable margin of safety against collapse is introduced by FEMA P695. The methodology is applied in this paper to assess the SPFs of the TOBF systems. For this purpose, a trial value of the R factor was first employed to design and model a set of TOBF archetype structures. Afterwards, the level of safety against collapse provided by the assumed R factor was investigated by using the non-linear analysis procedure of FEMA P695 comprising incremental dynamic analysis (IDA) under a set of prescribed ground motions. It was found that the R factor of 3.0 is appropriate for safe design of TOBFs. Also, the system overstrength factor (Ω0) was estimated as 2.0 by performing non-linear static analyses.
Mahdi Shariati,Mohammad Saeed Mafipour,James H. Haido,Salim T. Yousif,Ali Toghroli,Nguyen Thoi Trung,Ali Shariati 국제구조공학회 2020 Steel and Composite Structures, An International J Vol.34 No.1
Different parameters potentially affect the properties of corroded reinforced concrete beams. However, the high number of these parameters and their dependence cause that the effectiveness of the parameters could not be simply identified. In this study, an adaptive neuro-fuzzy inference system (ANFIS) was employed to determine the most influencing parameters on the properties of the corrosion-damaged reinforced concrete beams. 207 ANFIS models were developed to analyze the collected data from 107 reinforced concrete (RC) beams. The impact of 23 input parameters on nine output factors was investigated. The results of the paper showed the order of influence of each input parameter on the outputs and revealed that the input parameters regarding the uncorroded properties of concrete beams are the most influencing factors on the corresponding corroded properties of the beams.
Mahdi Shariati,Farzad Tahmasbi,Peyman Mehrabi,Alireza Bahadori,Ali Toghroli 국제구조공학회 2020 Steel and Composite Structures, An International J Vol.35 No.2
Shear connectors are essential elements in the design of steel-concrete composite systems. These connectors are utilized to prevent the occurrence of potential slips at the interface of steel and concrete. The two types of shear connectors which have been recently employed in construction projects are C- and L-shaped connectors. In the current study, the behavior of C and L-shaped angle shear connectors is investigated experimentally. For this purpose, eight push-out tests were composed and subjected to monotonic loading. The load-slip curves and failure modes have been determined. Also, the shear strength of the connectors has been compared with previously developed relationships. Two failure modes of shear connectors were observed: 1) concrete crushing–splitting and 2) shear connector fracture. It was found that the L-shaped connectors have less shear strength compared to C-shaped connectors, and decreasing the angle leg size increases the shear strength of the C-shaped connectors, but decreases the relative ductility and strength of L-shaped connectors.
Estimation of moment and rotation of steel rack connections using extreme learning machine
Mahdi Shariati,Nguyen Thoi Trung,Karzan Wakil,Peyman Mehrabi,Maryam Safa,Majid Khorami 국제구조공학회 2019 Steel and Composite Structures, An International J Vol.31 No.5
The estimation of moment and rotation in steel rack connections could be significantly helpful parameters for designers and constructors in the initial designing and construction phases. Accordingly, Extreme Learning Machine (ELM) has been optimized to estimate the moment and rotation in steel rack connection based on variable input characteristics as beam depth, column thickness, connector depth, moment and loading. The prediction and estimating of ELM has been juxtaposed with genetic programming (GP) and artificial neural networks (ANNs) methods. Test outcomes have indicated a surpass in accuracy predicting and the capability of generalization in ELM approach than GP or ANN. Therefore, the application of ELM has been basically promised as an alternative way to estimate the moment and rotation of steel rack connection. Further particulars are presented in details in results and discussion.