M
Mohammad Ali Naghsh
Researcher at Isfahan University of Technology
Publications - 7
Citations - 77
Mohammad Ali Naghsh is an academic researcher from Isfahan University of Technology. The author has contributed to research in topics: Finite strip method & Buckling. The author has an hindex of 3, co-authored 7 publications receiving 15 citations.
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Performance of fixed beam without interacting bars
Aydin Shishegaran,Behnam Karami,Timon Rabczuk,Arshia Shishegaran,Mohammad Ali Naghsh,Mohammreza Mohammad Khani +5 more
TL;DR: In this article, a transferred stress system (TSS) on longitudinal reinforcement bars was developed for increasing the bending capacity of reinforced concrete (RC) elements. But, the authors did not evaluate the performance of the TSS fixed beam compared to the ordinary fixed beam.
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Static and dynamic instability analysis of tapered CNTRC sandwich plates under uniform and non-uniform in-plane loadings using spline finite strip method
TL;DR: The buckling analysis of rectangular sandwich plates with pure polymeric tapered cores and functionally graded carbon nanotube (FG-CNT) reinforced composite face sheets under static and harmonic dynamic loads is presented in this article.
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An innovative model for predicting the displacement and rotation of column-tree moment connection under fire
Mohammad Ali Naghsh,Aydin Shishegaran,Behnam Karami,Timon Rabczuk,Arshia Shishegaran,Hamed Taghavizadeh,Mehdi Moradi +6 more
TL;DR: In this article, the performance of column-tree moment connection (CTMC) under fire and static loads was analyzed using nonlinear finite element simulations, and the results indicated that the rotation and deflection of the CTMC depend on the temperature.
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Prediction of the load-carrying capacity of reinforced concrete connections under post-earthquake fire
Aydin Shishegaran,Aydin Shishegaran,Mehdi Moradi,Mohammad Ali Naghsh,Behnam Karami,Arshia Shishegaran +5 more
TL;DR: In this article, a finite element (FE) model is developed for simulating the performance of reinforced concrete connections under post-earthquake fire (PEF), and surrogate models, including multiple linear regression, multiple natural logarithm (Ln) equation regression (MLnER), gene expression programming (GEP), and an ensemble model, are used to predict the remaining load-carrying capacity of an RCC under PEF.
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Surrogate models for the prediction of damage in reinforced concrete tunnels under internal water pressure
Alireza Bigdeli,Aydin Shishegaran,Aydin Shishegaran,Mohammad Ali Naghsh,Behnam Karami,Arshia Shishegaran,Gholamreza Alizadeh +6 more
TL;DR: In this article, the performance of reinforced concrete tunnel (RCT) under internal water pressure is evaluated by using nonlinear finite element analysis and surrogate models, including principal component regression (PCR), Multi Ln equation regression (MLnER), and gene expression programming (GEP) for predicting the percentage of damaged surfaces (PDS), the effective tensile plastic strain (ETPS), the maximum deflection of the RCT, and the maximum deformation of crown of RCT.