## 1 Introduction  
Seismic performance assessments are vital to understand and mitigate the risk of earthquake events on structures. In performance-based seismic evaluations, probabilistic seismic demand analysis is one important component that merges seismic hazard with the structural response to ground motions, thus helping with the prediction of possible damage and giving guidance for design decisions [1, 2, 3]. Ground motion intensity measures (IMs) are essential to this process of connecting seismic hazard and structural response [4]. The selection of an optimal intensity measure (IM) is critical, as it directly influences the accuracy of predictions for structural performance and the efficiency of seismic assessments. A good IM must minimize variability, be practical for real application, and capture key features of both ground motion and structural behavior [5, 6]. Recent studies have concentrated on distinguishing between non-structure-specific IMs, which only consider the characteristics of ground motion such as PGA or peak ground displacement (PGD), and structure-specific IMs, which integrate both the characteristics of ground motion and structural properties, such as modal vibrations [3, 4, 5, 6, 7]. In [3], the authors concluded that there are no specific IMs that are appropriate for all structuresregardless of the structure features (type of the structural system, construction material, number of stories, design details, etc.). Non-structure-specific IMs have been found to be less effective in predicting structural responses due to their weak correlation with actual damage indicators, particularly in complex or high-rise structures [4; 7; 8; 9]. Based on the analysis from [9], with 320 frame models for each of the 4-, 8-, and 12-story building frames, in terms of efficiency and proficiency, PGV was the optimal IM. Consequently, research has increasingly shifted toward the development and optimization of structure-specific IMs that account for the nuanced interplay between structural dynamics and seismic excitations [4; 5; 8; 10]. In [4], the authors stated that PGV can be efficient in representing the critical seismic intensities that cause the collapse of super-high-rise buildings. These enhancements in the selection of IMs and seismic modeling have been instrumental in improving the predictive capacity of seismic assessments. In parallel to such effectiveness, the selection of the proper appropriate ground motion records is also associated, reflecting both the seismicity of a region and some particular characteristics concerning the buildings themselves [3; 5]. In addition to efforts in structural modeling, there has been considerable study correlating ground motion parameters (GMPs) with some structural damage indicator variables, such as interstory drift or input energy. Among the GMPs, PGA, PGV, and spectral acceleration (SA) are the most commonly adopted, while in recent years some evidence suggests that more advanced IMs, such as spectral-based parameters, would be better correlated with structural damage, especially in nonlinear systems [2; 3; 5; 11; 12]. The results from [8] revealed that spectrum intensity parameters, having the strongest correlation, are superior to other parameters, such as peak ground velocity, peak ground acceleration, and spectral acceleration. These conclusions represent an ongoing investigation that is very much necessary for re-finessing seismic vulnerability assessments and improving the prediction of damage, particularly for those structures in high-seismic zones [5; 7]. Studies reveal varying correlations between IMs and damage measures (DMs), with advanced parameters like Housner Intensity (HI) and velocity spectrum intensity (VSI) outperforming traditional measures [13; 14]. In particular, Housner spectrum intensity (HI), PGV, and cumulative absolute velocity (CAV) were the optimal IMs, according to the study presented in [12]. Conversely, Arias intensity (Ia) demonstrates very low correlations with the demand parameters [12].