Experimental Investigation and Modeling of Dynamic Properties of slag Ballast and Limestone Ballast

Seismic designs and numerical analyses required fundamental parameters such as damping ratio and shear modulus. In this study, large-scale triaxial cyclic tests were used to investigate the dynamic properties of limestone ballast and electric arc furnace (EAF) slag ballast. The term ‘shear stiffness’ is typically reported in a normalized form using shear modulus. As the laboratory test results showed, an increase in confining pressure, loading frequency and anisotropy raises the shear modulus of materials. Shear modulus and damping ratio values do not appear to be significantly affected by an increase in loading cycles. Loading frequency plays the most significant role in changing damping ratio values. An adaptive neuro-fuzzy inference system (ANFIS) was also used to predict the normalized shear modulus and the damping ratio in this study. The results of the developed model were consistent with those of the laboratory tests. Moreover, the relations among the dynamic properties were estimatedly determined using the nonlinear regression method.

Keywords:

Ballast , Shear Modulus , Damping Ratio , Large-scale cyclic triaxial test , adaptive neuro-fuzzy inference system , Nonlinear regression model