Even though there are so many studies upon optimization of supplemental damping devices integrated to structural systems, the vast majority of them remain only as a subject of the research articles of the Journals and...
详细信息
Even though there are so many studies upon optimization of supplemental damping devices integrated to structural systems, the vast majority of them remain only as a subject of the research articles of the Journals and cannot find a place itself in common practice due to lack of the regulations about the issue in codes and standards. In this paper, the issue is dealt with the most fundamental inputs and outputs of a general problem. All efforts are made to show how the procedure could frequently be used in common practice and what the attained benefits could be from the design and application point of view. The analysis of the structural systems in which the "seismic response control systems" have been adapted requires considering the special numerical analysis techniques which provide "solutions in frequency domain". By this means, not only the "dynamic response characteristics" of the structure shall be determined but also the variation of this response with the change of the "design parameters forming the structural control systems" shall be able to be investigated from the optimization point of view. Since conventional analysis tools and methods are not capable of providing such information, advanced numerical analysis method based on the "state-space approach" is considered along with the "gradient based optimization algorithm" in the proposed study. In this paper, viscous fluid dampers are examined as a supplemental damping devices in the analysis of a multi degree of freedom structure. Dampers are modelled with the Maxwell model in which the spring and the dash-pot are placed in series. For a given brace stiffness, viscous damping coefficients and the distribution of the damping devices between stories are optimized by a procedure to reach a "target performance level". The optimization is achieved by minimizing an "objective function" which rates the structural responses of the controlled system with the uncontrolled one. Generally, mean square responses of th
Parameter estimation of the impinging signal in the sensor arrays is one of the challenging issues in Phased Array Radar (PAR). Most often, a PAR operates in the presence of jammers deployed in its near field. In orde...
详细信息
Parameter estimation of the impinging signal in the sensor arrays is one of the challenging issues in Phased Array Radar (PAR). Most often, a PAR operates in the presence of jammers deployed in its near field. In order to mitigate the jammers signals, it is important that PAR must know the exact Direction Of Arrival (DOA) and ranges of the jammers along with the DOAs of the actual targets located in the far field. This information is crucial for the PAR to steer the mainbeam and nulls in the desired and undesired (jammers) directions, respectively. In this work, we consider a PAR that simultaneously receives the desired plane waves and the undesired spherical waves from the far field targets and near field jammers respectively. The plane waves are the function of the unknown DOA, whereas the spherical waves depend on the DOAs and ranges of the jammers. A novel approach based on the gradientbased Optimizer (GBO) algorithm and Marine Predators algorithm (MPA) is proposed to estimate jointly the unknown parameters related to the far field targets and near field jammers. The GBO uses two operators called gradient Search Rule (GSR) and Local Escaping Operator (LEO). The GSR enhances the convergence rate and improves the exploration tendency to obtain the better solution in the search space, while the LEO helps the algorithm avoid getting stuck in the local optima. The MPA uses different velocities ratios based on predators and prey movement in the ocean to achieve better exploration and exploitation in the search domain. A cost function is developed and optimized using GBO and MPA, which is based on the Penalty Function (PF) and Mean Square Errors (MSE) of the system. The PF controls the deviation in the MSE from the desired result during the optimization process. The proposed schemes are not only compared with each other but also with the state-of-the-art MUSIC algorithm. Extensive Monte Carlo simulations are enacted for diverse scenarios to justify the legitimacy of t
暂无评论