Milad Jahangiri
@scholar.google.com
Department of Civil and Environmental Engineering
Department of Civil and Environmental Engineering
Milad Jahangiri currently works at the Department of Civil and Environmental Engineering, Shiraz University of Technology (SUTech).
Milad conducts research in Structural and Earthquake Engineering.
EDUCATION
Doctor of Philosophy;
Ph.D. Research Assistant at Shiraz University of Technology (SUTech);
RESEARCH INTERESTS
Structural Damage Detection; Structural Health Monitoring; Engineering Optimization; Reliability Analysis; Sensitivity Analysis; Signal Processing; Ambient Vibration; Microtremor Measurement; Earthquake Engineering; Environmental Investigations and Improvements.
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Scopus Publications
Alireza Babaali, Mohammad Ali Hadianfard, and Milad Jahangiri
Elsevier BV
Milad Jahangiri, Mohammad Ali Hadianfard, Mohammad Amir Najafgholipour, Mehdi Jahangiri, and Shahabeddin Hatami
Springer Science and Business Media LLC
Milad Jahangiri, Antonio Palermo, Soroosh Kamali, Mohammad Ali Hadianfard, and Alessandro Marzani
Elsevier BV
Milad Jahangiri, Mohammad Ali Hadianfard, Mohammad Amir Najafgholipour, and Mehdi Jahangiri
World Scientific Pub Co Pte Ltd
The conventional modal strain energy (MSE), as a practical objective function, suffers from the lack of access to the damaged stiffness matrix and uses the intact stiffness matrix of the structure instead. To overcome the aforementioned deficiency of the MSE, this study proposes a reformed elastic strain energy-dissipation criterion called the “augmented modal strain energy” (AMSE) which is composed of relative differences of natural frequency and mode shape. In the AMSE not only the effects of the energy-dissipation criterion as a function of natural frequency but also the equilibria of the elastic strain energy as a function of mode shape are considered. Hereupon, the AMSE is implemented along with the interactive autodidactic school (IAS) optimization algorithm to investigate the effectiveness of the proposed identification method. In this regard, the AMSE is verified by assessing three benchmark truss and frame structures. The obtained results confirm the reliable performance of AMSE in both terms of intensification and diversification. Furthermore, it is observed that despite using noise-polluted modal data, the proposed AMSE not only identifies the damage location accurately, but also anticipates the extent of damage precisely. Consequently, the proposed energy-dissipation-based objective function (AMSE) is suggested, along with the IAS optimization algorithm, as a robust technique for the damage detection of structures.
Mohammad Ali Hadianfard, Milad Jahangiri, and Shahrokh Shojaei
Elsevier BV
Milad Jahangiri, Mohammad Ali Hadianfard, and Shahrokh Shojaei
Elsevier BV
Amin Hosseini, Touraj Taghikhany, and Milad Jahangiri
SAGE Publications
In the past few years, many studies have proved the efficiency of Simple Adaptive Control (SAC) in mitigating earthquakes’ damages to building structures. Nevertheless, the weighting matrices of this controller should be selected after a large number of sensitivity analyses. This step is time-consuming and it will not necessarily yield a controller with optimum performance. In the current study, an innovative method is introduced to tuning the SAC’s weighting matrices, which dispenses with excessive sensitivity analysis. In this regard, we try to define an optimization problem using intelligent evolutionary algorithm and utilized control indices in an objective function. The efficiency of the introduced method is investigated in 6-story building structure equipped with magnetorheological dampers under different seismic actions with and without uncertainty in the model of the proposed structure. The results indicate that the controller designed by the introduced method has a desirable performance under different conditions of uncertainty in the model. Furthermore, it improves the seismic performance of structure as compared to controllers designed through sensitivity analysis.
Milad Jahangiri, Mohammad Ali Hadianfard, Mohammad Amir Najafgholipour, and Mehdi Jahangiri
Elsevier BV
Mehdi Jahangiri, Milad Jahangiri, and Mohammadamir Najafgholipour
Elsevier BV
Milad Jahangiri, Mohammad Ali Hadianfard, Mohammad Amir Najafgholipour, Mehdi Jahangiri, and Mohammad Reza Gerami
Elsevier BV
Milad Jahangiri and Mohammad Ali Hadianfard
Springer Science and Business Media LLC
Milad Jahangiri, M.A. Najafgholipour, S.M. Dehghan, and M.A. Hadianfard
Elsevier BV