Robust Optimal Damper Placement of Nonlinear Oil Dampers With Uncertainty Using Critical Double Impulse

A new robust method for optimal damper placement is presented for building structures under the critical double impulse. Oil dampers are treated here as representative supplemental dampers to control the seismic response of high-rise buildings. Such oil dampers usually obey a bi-linear force-velocity relation in controlling the maximum damping force through a relief mechanism to avoid the occurrence of excessive design forces in surrounding frames. The influence of uncertainty in characteristics of those bi-linear oil dampers on building structural safety is investigated. For the efficient evaluation of dynamic performance, the resonant critical double impulse is used as the base input instead of actual earthquake ground motions. Since the critical double impulse is determined to maximize the input energy to the objective building by changing the second impulse timing, uncertainties in input ground motions can be taken into account in a robust manner. To consider these various uncertainties, the robustness function based on the Info-Gap model is used in the robust optimization to assess structural performance variations caused by various uncertainties in the structural design phase. In this paper, a new innovative objective function in the robust optimal damper placement problem is proposed to enhance the robustness of structural performance under the variation of structural parameters by comparing the robustness function of the robust design with that of an ordinary optimal damper placement without considering uncertainties. Numerical examples of the robust optimal design of linear and bi-linear oil damper placements are shown for 10-story and 20-story planar building frame models. Structural performances of the robust optimal design to the conventional design earthquake ground motions are examined to investigate the validity of using the critical double impulse in the structural design under uncertainties.

Uncertainty-based robust optimal design of cleanroom air-conditioning systems considering life-cycle performance

Strict and simultaneous space temperature and humidity controls are often required in many applications, such as hospitals, laboratories, cleanrooms for pharmaceutical and semiconductor manufacturing. The energy intensity in such applications can be up to 100 times than typical office buildings, mainly due to the improper system design and control. Although some uncertainty-based design methods have been developed for air-conditioning systems, most of the existing systems are designed based on a certain ventilation mode while neglecting the life-cycle performance of the components. This study, therefore, proposes a robust optimal design method for cleanroom air-conditioning systems, considering the uncertainties in design parameters for inputs and operation strategies as well as the life-cycle performance of components. An adaptive full-range decoupled ventilation strategy, which incorporated five operation modes, was adopted in the design optimization. Two maintenance modes were adopted and compared to consider the flexibility of maintenance. The proposed design method has been implemented and validated in the design optimization of an existing air-conditioning system. The results showed that, compared with the conventional design, up to 54% reduction of life-cycle costs and superior satisfaction of services could be achieved by using the proposed method.