Iman Behmanesh
Research Subjects
Iman Behmanesh has a total of 4 co-authors. Here are the top co-authors by number of shared publications:
- Babak Moaveni
Department of Civil and Environmental Engineering, Tufts University, Medford, MA 02155, USA
2 shared publications Amin Nozari
1 shared publication- Andreas Stavridis
University at Buffalo Buffalo NY USA
1 shared publication Seyedsina Yousefianmoghadam
1 shared publication
Latest Publications
- 1 July 2018
- Published by Elsevier in Mechanical Systems and Signal Processing
- Vol. 107, 502-514
Uncertainty quantification and propagation in dynamic models using ambient vibration measurements, application to a 10-story building
- 1 July 2018
- Published by Elsevier in Mechanical Systems and Signal Processing
- Vol. 107, 502-514
Uncertainty quantification and propagation in dynamic models using ambient vibration measurements, application to a 10-story building
- 17 April 2018
- Published by American Society of Civil Engineers (ASCE)
- p. 222-232
Design Optimization of Shear Wall High-Rise Building Structures
Design optimization of building structures are usually performed by minimizing an objective function defined as total weight or cost of material. The building code strength requirements or drift limitations are defined as optimization constraints. The violated constraints will be added to the main objective function after adjustment by a weight factor. This objective function is often not differentiable since the violated constraints change at every iteration. Plus, the weight factor that adjust the violated constraint with the main objective function can affect the optimization results and its value may not be reasonably justified or substantiated. In this paper, a new structural design optimization is proposed for shear wall building structures. The objective function for this optimization process is defined based on the estimated demand to capacity ratios of the shear walls. Other design criteria such as drift limits or link beam designs are also considered, but are not directly included in the proposed objective function. By pushing the demand to capacity ratios to the possible highest, the thicknesses of shear wall are reduced. The proposed objective function is derived by assuming a beta distribution for the shear force demand to capacity ratios of the shear walls. Monte Carlo samples are generated to find the maximum of the objective function and for sensitivity analysis. The optimization framework is applied on a 70 story building. The correlation between the proposed objective function and the cost associated with the lateral system is presented. The generated Monte Carlo samples are also used to design the shear wall thickness at different level of conservativeness.
- 17 April 2018
- Published by American Society of Civil Engineers (ASCE)
- p. 222-232
Design Optimization of Shear Wall High-Rise Building Structures
Design optimization of building structures are usually performed by minimizing an objective function defined as total weight or cost of material. The building code strength requirements or drift limitations are defined as optimization constraints. The violated constraints will be added to the main objective function after adjustment by a weight factor. This objective function is often not differentiable since the violated constraints change at every iteration. Plus, the weight factor that adjust the violated constraint with the main objective function can affect the optimization results and its value may not be reasonably justified or substantiated. In this paper, a new structural design optimization is proposed for shear wall building structures. The objective function for this optimization process is defined based on the estimated demand to capacity ratios of the shear walls. Other design criteria such as drift limits or link beam designs are also considered, but are not directly included in the proposed objective function. By pushing the demand to capacity ratios to the possible highest, the thicknesses of shear wall are reduced. The proposed objective function is derived by assuming a beta distribution for the shear force demand to capacity ratios of the shear walls. Monte Carlo samples are generated to find the maximum of the objective function and for sensitivity analysis. The optimization framework is applied on a 70 story building. The correlation between the proposed objective function and the cost associated with the lateral system is presented. The generated Monte Carlo samples are also used to design the shear wall thickness at different level of conservativeness.
- 1 July 2016
- Published by Elsevier in Journal of Sound and Vibration
- Vol. 374, 92-110
Accounting for environmental variability, modeling errors, and parameter estimation uncertainties in structural identification
- 1 July 2016
- Published by Elsevier in Journal of Sound and Vibration
- Vol. 374, 92-110
Accounting for environmental variability, modeling errors, and parameter estimation uncertainties in structural identification