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Showing 3 results for Kamgar

R. Kamgar , R. Rahgozar,
Volume 5, Issue 4 (7-2015)

In this paper, based on maximizing the outrigger-belt truss system’s strain energy, a methodology for determining the optimum location of a flexible outrigger system is presented. Tall building structures with combined systems of framed tube, shear core, belt truss and outrigger system are modeled using continuum approach. In this approach, the framed tube system is modeled as a cantilevered beam with box cross section. The effect of outrigger and shear core systems on framed tube’s response under lateral loading is modeled by a rotational spring placed at the location of belt truss and outrigger system. Optimum location of this spring is obtained when energy absorbed by the spring is maximized. For this purpose, first derivative of the energy equation with respect to spring location as measured from base of the structure, is set to zero. Optimum location for outrigger and belt truss system is calculated for three types of lateral loadings, i.e. uniformly and triangularly distributed loads along structure’s height, and concentrated load at top of the structure. Accuracy of the proposed method is verified through numerical examples. The results show that the proposed method is reasonably accurate. In addition, for different stiffness of shear core and outrigger system, several figures are presented that can be used to determine the optimum location of belt truss and outrigger system.
A. Heidari, J. Raeisi , R. Kamgar,
Volume 8, Issue 1 (1-2018)

Cumulative absolute velocity (CAV), Arias intensity (AI), and characteristic intensity (CI) are measurable characteristics to show collapse potential of structures, evaluation of earth movement magnitude, and detection of structural failure in an earthquake. In this paper, parameters which describe three characteristics of ground motion have been investigated by using wavelet transforms (WT). In fact, in this paper, a series of twenty eight earthquake records (ER) are decomposed to a pre-defined certain levels by the use of WT. The high and low frequencies are separated. Since higher frequencies do not have any significant effect on the ER, then the low frequencies of ER have been used. For this purpose, each ER is decomposed into 5 levels. Then, for low frequencies of ER, the CAV, AI, and CI are calculated for each level and the results are compared with the values of CAV, AI, and CI which have been computed for the original ER. The results indicate that the value of error is less than 1 percent in the first and second level and this value is less than 10 percent for the third level. In addition, this value is more than 15 percent for the fourth and fifth levels. If the acceptable value for error is considered to be less than 10 percent, it is recommended to use the third level of decomposition for determining these parameters, since the value of error is low and also, the required time is reduced.

R. Kamgar, M. Khatibinia, M. Khatibinia,
Volume 9, Issue 2 (4-2019)

Many researches have focused on the optimal design of tuned mass damper (TMD) system without the effect of soil–structure interaction (SSI), so that ignoring the effect of SSI may lead to an undesirable and unrealistic design of TMD. Furthermore, many optimization criteria have been proposed for the optinal design of the TMD system. Hence, the main aim of this study is to compare different optimization criteria for the optimal design of the TMD system considering the effects of SSI in a high–rise building. To acheive this purpose, the optimal TMD for a 40–storey shear building is firstly evaluated by expressing the objective functions in terms of the reduction of structural responses (including the displacement and acceleration) and the limitation of the scaled stroke of TMD. Then, the best optimization criterion is selected, which leads to the best performance for the vibration control of the structure. In this study, the whale optimization algorithm (WOA) is employed to optimize the parameters of the TMD system. The numerical results show that the soil type and selected objective function efficiently affect the optimal design of the TMD system.

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