This study analyzes the progression, utilization, and inherent challenges of traditional non-linear static procedures (NSPs) such as the capacity spectrum method, the displacement coefficient method, and the N2 method for evaluating seismic performance in structures. These methods, along with advanced versions such as multi-mode, modal, adaptive, and energy-based pushover analysis, help determine seismic demands, enriching our grasp on structural behaviors and guiding design choices. While these methods have improved accuracy by considering major vibration modes, they often fall short in addressing intricate aspects such as bidirectional responses, torsional effects, soil-structure interplay, and variations in displacement coefficients. Nevertheless, NSPs offer a more comprehensive and detailed analysis compared to rapid visual screening methods, providing a deeper understanding of potential vulnerabilities and more accurate predictions of structural performance. Their efficiency and reduced computational demands, compared to the comprehensive nonlinear response history analysis (NLRHA), make NSPs a favored tool for engineers aiming for swift seismic performance checks. Their accuracy and application become crucial when gauging seismic risks and potential damage across multiple structures. This paper underscores the ongoing refinements to these methods, reflecting the sustained attention they receive from both industry professionals and researchers.

This study evaluates the performance of SAP2000, and AxisVM in conducting pushover analyses, with a focus on the manual (user) definition of plastic hinges versus the automatic definitions provided by the software. Three structures, namely a single column subjected to a point load, a 2D reinforced concrete (RC) frame model, and a 3D RC model, are considered. It explores the performance of the three models in different conditions, including, application of the different software, the use of user defined (manual) hinges, and automatically generated hinges to assess their response to various analytical excitations. The need for engineers to focus on understanding the application of defining the hinge properties according to existing guidelines, including FEMA-356, ASCE 41-13/17, and Eurocodes, is highly emphasized, in addition to the existing methods as found in the literature. This is achieved by considering and comparing the capacity curves generated by the software. The results vary in some instances, especially when comparing results from user-defined and automatic hinges. It is also found that when used with precision, the results are almost similar, it is also important to use software that allows ultimate precision for better results.

Nonlinear Static Analysis otherwise known as pushover analysis will be used in this study to evaluate the seismic performance of an existing reinforced concrete (RC) hospital structure. This method aids in determining the structure’s ability to withstand lateral loads and calculating its local and global deformation requirements. The study begins with a thorough analysis of the geometry, materials, and structural elements of the structure, followed by a review of pertinent building regulations and codes. A finite element model in three dimensions of the hospital building is created, encapsulating the main features of the structure’s behavior under seismic loading. The lateral force method of analysis and static pushover analysis is then carried out and compared, and the findings are used to pinpoint crucial weak places, potential failure mechanisms, and regions needing additional research or fortification. Recommendations are given to improve the seismic performance of the current RC hospital building based on the pushover analysis’s findings. These adjustments can be made to the structural system via retrofitting techniques or to non-structural elements. For engineers, architects, and legislators concerned with the seismic assessment and renovation of hospital buildings and other crucial infrastructure, the findings from this study are valuable.

The research intends to validate pushover methods through the lens of the incremental dynamic analysis technique. This study will contrast conventional with enhanced pushover strategies, specifically as they are applied to a 2D steel frame, a 3D RC frame, and a reinforced concrete moment-resisting frame structure. For an exhaustive evaluation, state-of-the-art analysis software tools like SAP2000, OpenSees, Etabs, Seismostruct, and AxisVM are to be employed . The aim of the study is to offer insights into how these methodologies fare in predicting the behavior of these structural configurations under varied seismic conditions. Although traditional pushover approaches, such as the Capacity Spectrum Method, Displacement Coefficient Method, and Target Displacement (N2) Method, are appreciated for their simplicity, they also come with inherent limitations. Notably, they tend to overlook the influences of higher modes both horizontally and vertically. To bridge these gaps, the research will explore Adaptive Pushover Analysis (APA), an advanced pushover technique. Given the importance of understanding the seismic behavior of structures, our investigation will focus on how these advanced pushover techniques can be aptly applied to the structural types. We propose an innovative design approach that integrates these advanced pushover analyses with the principles of performance-based seismic design (PBSD). Furthermore, we suggest the inclusion of structural control systems within the realm of pushover analysis. Such systems, engineered to combat external disruptions like seismic events, can significantly mitigate the seismic demands on structures. By modulating the structural response to these external forces, they ensure enhanced safety. Merging these systems with pushover analysis promises a more comprehensive seismic design strategy, making structures more resilient against seismic threats. Once the research concludes, a range of case studies will be deployed to gauge the efficacy of the proposed methodology against traditional pushover tactics. The research's insights will be consolidated and presented in a detailed final report.

This study proposes a digital twin (DT) and machine learning (ML) framework to predict nonlinear pushover responses of reinforced concrete (RC) shear walls using analytically derived data. Two hundred SAP2000 layered shell models were analyzed, and monotonic lateral capacity curves were processed via SPO2FRAG for bilinear parameter extraction. Key response features—initial stiffness (K0), yield displacement (), and post-yield stiffness ratio ()were identified. Ten input variables including wall geometry, material properties, reinforcement ratios, axial load, and opening ratio were used to train Random Forest regressors for predicting the pushover curve descriptors. Model accuracy was validated using nested cross-validation, yielding mean test R² values of 0.996 for, 0.995 for, and 0.925 for, while uncertainty measures (Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), 95% confidence intervals) supported robustness. The DT surrogate reconstructs pushover curves in under 2 seconds per specimen, supporting rapid parametric analysis and seismic scenario assessments without the need for repetitive finite element simulations. The study also documents model limitations and outlines guidance for extending the approach to shear-dominated walls and experimental validation.