A General Hysteresis Model for Applications in Structural Dynamics

This paper presents a novel hysteresis model designed to accurately capture the complex behavior of structural components under cyclic loading. Traditional hysteresis models require parameters within mathematical functions to model hysteresis tracks and are often challenged with fitting data that exhibit varying damage patterns that require extensive parameterization. The general hysteresis model presented in this study addresses these limitations by employing shape functions, which are independent of specific data, and a new cumulative damage model for interpolating condensed data points. This approach enables automatic fitting to experimental data. The generalized model is capable of capturing a wide range of hysteresis patterns and curve shapes, making it potentially applicable to various structural components and materials, including concrete, steel, and wood. In this study, validation was performed on connections in wood structures; however, further research is needed to demonstrate its applicability to other materials. We validated the model using two examples: a withdrawal screw test and a different displacement protocol with multiple cycles at each peak displacement level. The results demonstrated that the new hysteresis model accurately predicts hysteresis forces and cumulative energy dissipation, even under varying loading conditions and hysteresis shapes. The model’s ability to automatically fit large data sets and handle different hysteresis patterns makes it a powerful tool for performance-based design and research in structural engineering. The findings indicate that the new hysteresis model can significantly improve the accuracy of dynamic response predictions and enhance the resilience of structures subjected to dynamic loads, including seismic and wind loads. This advancement in hysteresis modeling provides a robust foundation for future research and practical applications in ensuring the safety and durability of buildings and other infrastructure.