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.
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