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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.
M. Safa,M. Shariati,Z. Ibrahim,A. Toghroli,Shahrizan Bin Baharom,Norazman M. Nor,Dalibor Petković 국제구조공학회 2016 Steel and Composite Structures, An International J Vol.21 No.3
Structural design of a composite beam is influenced by two main factors, strength and ductility. For the design to be effective for a composite beam, say an RC slab and a steel I beam, the shear strength of the composite beam and ductility have to carefully estimate with the help of displacements between the two members. In this investigation the shear strengths of steel-concrete composite beams was analyzed based on the respective variable parameters. The methodology used by ANFIS (Adaptive Neuro Fuzzy Inference System) has been adopted for this purpose. The detection of the predominant factors affecting the shear strength steel-concrete composite beam was achieved by use of ANFIS process for variable selection. The results show that concrete compression strength has the highest influence on the shear strength capacity of composite beam.
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.
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.
Mahdi Shariati,Shervin Safaei Faegh,Peyman Mehrabi,Seyedmasoud Bahavarnia,Yousef Zandi,Davood Rezaee Masoom,Ali Toghroli,Nguyen-Thoi Trung,Musab N.A. Salih 국제구조공학회 2019 Steel and Composite Structures, An International J Vol.33 No.4
Corrugated steel plate shear wall (CSPSW) as an innovative lateral load resisting system provides various advantages in comparison with the flat steel plate shear wall, including remarkable in-plane and out-of-plane stiffnesses and stability, greater elastic shear buckling stress, increasing the amount of cumulative dissipated energy and maintaining efficiency even in large story drifts. Employment of low yield point (LYP) steel web plate in steel shear walls can dramatically improve their structural performance and prevent early stage instability of the panels. This paper presents a comprehensive structural performance assessment of corrugated low yield point steel plate shear walls having circular openings located in different positions. Accordingly, following experimental verification of CSPSW finite element models, several trapezoidally horizontal CSPSW (H-CSPSW) models having LYP steel web plates as well as circular openings (for ducts) perforated in various locations have been developed to explore their hysteresis behavior, cumulative dissipated energy, lateral stiffness, and ultimate strength under cyclic loading. Obtained results reveal that the rehabilitation of damaged steel shear walls using corrugated LYP steel web plate can enhance their structural performance. Furthermore, choosing a suitable location for the circular opening regarding the design purpose paves the way for the achievement of the shear wall's optimal performance.
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.