mina Mortazavi

Dr. mina Mortazavi


Research Focus & Metrics

Academic Career Length

9Years (2018-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 January 2018 in Automation in Construction
Verified
Journal Article
Closed access
Pejman SharafiPejman Sharafi
Pejman Sharafi
mina Mortazavimina Mortazavi
mina Mortazavi
BSBijan Samali
Bijan Samali
HRHamid Ronagh
Hamid Ronagh

1 September 2018 in Thin-Walled Structures
Verified
Journal Article
Closed access
PSPezhman Sharafi
Pezhman Sharafi
mina Mortazavimina Mortazavi
mina Mortazavi
NUNima Usefi
Nima Usefi
KKKamyar Kildashti
Kamyar Kildashti
HRHamid Ronagh
Hamid Ronagh
BSBijan Samali
Bijan Samali

1 June 2018 in Journal of Architectural Engineering
Verified
Journal Article
Closed access
PSPezhman Sharafi
Pezhman Sharafi
MRMaria Rashidi
Maria Rashidi
Bijan SamaliBijan Samali
Bijan Samali
HRHamid Ronagh
Hamid Ronagh
mina Mortazavimina Mortazavi
mina Mortazavi

17 March 2023 in Buildings
Verified
Journal Article
Open access
PDF file
SHShaoyong Han
Shaoyong Han
ZZZhun Zhu
Zhun Zhu
mina Mortazavimina Mortazavi
mina Mortazavi
Ahmed M. El-SherbeenyAhmed M. El-Sherbeeny
Ahmed M. El-Sherbeeny
PMPeyman Mehrabi
Peyman Mehrabi
The aim of this paper is to study the performance of a composite floor system at different heat stages using artificial intelligence to derive a sustainable design and to select the most critical factors for a sustainable floor system at elevated temperatures. In a composite floor system, load bearing is due to composite action between steel and concrete materials which is achieved by using shear connectors. Although shear connectors play an important role in the performance of a composite floor system by transferring shear force from the concrete to the steel profile, if the composite floor system is exposed to high temperature conditions excessive deformations may reduce the shear-bearing capacity of the composite floor system. Therefore, in this paper, the slip response of angle shear connectors is evaluated by using artificial intelligence techniques to determine the performance of a composite floor system during high temperatures. Accordingly, authenticated experimental data on monotonic loading of a composite steel-concrete floor system in different heat stages were employed for analytical assessment. Moreover, an artificial neural network was developed with a fuzzy system (ANFIS) optimized by using a genetic algorithm (GA) and particle swarm optimization (PSO), namely the ANFIS-PSO-GA (ANPG) method. In addition, the results of the ANPG method were compared with those of an extreme learning machine (ELM) method and a radial basis function network (RBFN) method. The mechanical and geometrical properties of the shear connectors and the temperatures were included in the dataset. Based on the results, although the behavior of the composite floor system was accurately predicted by the three methods, the RBFN and ANPG methods represented the most accurate values for split-tensile load and slip prediction, respectively. Based on the numerical results, since the slip response had a rational relationship with the load and geometrical parameters, it was dramatically predictable. In addition, slip response and temperature were determined as the most critical factors affecting the shear-bearing capacity of the composite floor system at elevated temperatures.

1 August 2018 in Journal of Constructional Steel Research
Verified
Journal Article
Closed access
mina Mortazavimina Mortazavi
mina Mortazavi
Pejman SharafiPejman Sharafi
Pejman Sharafi
HRHamid Ronagh
Hamid Ronagh
BSBijan Samali
Bijan Samali
KKKamyar Kildashti
Kamyar Kildashti

1 April 2019 in Journal of Constructional Steel Research
Verified
Journal Article
Closed access
KKKamyar Kildashti
Kamyar Kildashti
BSBijan Samali
Bijan Samali
mina Mortazavimina Mortazavi
mina Mortazavi
HRHamid Ronagh
Hamid Ronagh
Pejman SharafiPejman Sharafi
Pejman Sharafi