m. vajdian

Acceptable seismic performance, ease and low cost in design and implementation are advantages of passive dampers, but fixed performance parameters corresponding to the type and amount of input energy reduce their efficiency. In this research, a new two-level passive damper in rigid connections with variable stiffness, strength, and energy absorption capacity is introduced and its seismic performance in 5, 10, and 15-story steel frames is evaluated with nonlinear dynamic analysis using SAP2000 software. The results show that, despite the different dynamic parameters in the selected seismic records, such as the frequency content and duration of ground motions, the performance of the structures under all earthquakes has improved significantly, which confirms the effectiveness of the proposed damper in rigid connections on improving the seismic performance structures. Besides, results prove the proposed damper effectiveness on decreasing the structural response such as maximum displacement and base shear. The average displacements reduced by 61%, 51% and 16% compared to those of BSEEP-4ES connections for the 5, 10 and 15-story frames, respectively. Besides, maximum base shear forces reduced by average of 29% and 15% compared to those of BSEEP-4ES connections for the 5 and 10-story frames, respectively.

Investigating the behavior of the box-shaped column panel zone has been one of the major concerns of scientists in the field.  In the American Institute of Steel Construction the shear capacity of I-shaped cross- sections with low column thickness is calculated. This paper determines the shear capacity of panel zone in steel columns with box-shaped cross-sections by using artificial neural network (ANN) and genetic algorithm (GA). It also compares ABAQUS finite element software outputs and AISC relations. Therefore, neural networks were trained using parametric information obtained from 510 connection models in ABAQUS software. The results show that the predicted shear capacity of the NN and the GA in comparison with the AISC relations use a wide range of all effective parameters in the calculation of the shear capacity of panel zone. Therefore, the use of artificial intelligence can be a good choice. Finally, the GA, along with optimization of a mathematical relation, has been able to minimize the error in determining the shear capacity of panel zones of steel-based columns, even at high column thicknesses.