The present paper investigates the coupled effect of the supporting soil flexibility and pounding between neighbouring, insufficiently separated equal height buildings under earthquake excitation. Two adjacent three-storey structures, modelled as inelastic lumped mass systems with different structural characteristics, have been considered in the study. The models have been excited using a suit of ground motions with different peak ground accelerations and recorded at different soil types. A nonlinear viscoelastic pounding force model has been employed in order to effectively capture impact forces during collisions. Spring-dashpot elements have been incorporated to simulate the horizontal and rotational movements of the supporting soil. The results of the numerical simulations, in the form of the structural nonlinear responses as well as the time-histories of energy dissipated during pounding-involved vibrations, are presented in the paper. In addition, the variation in storeys peak responses and peak dissipated energies for different gap sizes are also shown and comparisons are made with the results obtained for colliding buildings with fixed-base supports. Observations regarding the incorporation of the soil-structure interaction and its effect on the responses obtained are discussed. The results of the study indicate that the soil-structure interaction significantly influences the pounding-involved responses of equal height buildings during earthquakes, especially the response of the lighter and more flexible structure. It has been found that the soil flexibility decreases storey peak displacements, peak impact forces

Abstract:In this paper, logical analysis of data (LAD) is used to predict the seismic response of building structures employing the captured dynamic responses. In order to prepare the data, computational simulations using a single degree of freedom (SDOF) building model under different ground motion records are carried out. The selected excitation records are real and of different peak ground accelerations (PGA). The sensitivity of the seismic response in terms of displacements of floors to the variation in earthquake characteristics, such as soil class, characteristic period, and time step of records, peak ground displacement, and peak ground velocity, have also been considered. The dynamic equation of motion describing the building model and the applied earthquake load are presented and solved incrementally using the Runge-Kutta method. LAD then finds the characteristic patterns which lead to forecast the seismic response of building structures. The accuracy of LAD is compared to that of an artificial neural network (ANN), since the latter is the most known machine learning technique. Based on the conducted study, the proposed LAD model has been proven to be an efficient technique to learn, simulate, and blindly predict the dynamic response behaviour of building structures subjected to earthquake loads.

No abstract

No abstract