These technologies have evolved from simulating only prismatic beams to including geometrical and material nonlinearities. Structural dynamic modeling of buildings has come a long way in the last 50 years, due to the competition of software development companies and the increased availability of computational resources. As for the model, the results show us that it performs well in prediction scenarios. Results show that among these algorithms, the DE algorithm outperformed its counterpart in most situations. Not having much expertise on structural modeling, the present paper is focused on two aspects: the proposed model’s performance and the optimization algorithms performance. The authors’ approach is the following: having a nonlinear dynamic model (in this case, a multi-segment inverted pendulum on a cart with mass-spring-damper rotational joints) and at least two datasets of a building, the parameters of the building’s model are estimated using optimization algorithms: Particle Swarm Optimization (PSO) and Differential Evolution (DE). Due to the dynamics and non-linear response of the structures, advanced analytical procedures were implemented over time. It began more than 100 years ago when seismic regulations adopted static analyzes with lateral loads of about 10% of the weight of the structure.
Structural analysis is a key component of seismic design and evaluation. Having this in mind, the authors propose a simple nonlinear model for studying the behavior of buildings in the case of earthquakes. Structural dynamic modeling is a key element in the analysis of building behavior for different environmental factors.
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