Jose´ L. Zapico

TL;DR: In this article, a seismic damage identification method for buildings with steel moment-frame structure is presented, which is based on artificial neural networks and modal variables, and the results are successful as concern as the robustness of the method.

TL;DR: In this article, a method for seismic damage identification in buildings with steel moment-frame structure based on artificial neural networks and natural frequencies is presented. But the method is simulated on a four-storey building under conditions as close as possible to reality and the statistical analysis of the results is successful, but it reveals that the predictions are quite sensitive to data errors.

TL;DR: This paper deals with the parametric identification of a small-scale bridge model that was intended to approximately reproduce the transversal dynamic behaviour of its corresponding prototype and shows that the model could be improved by using a non linear approach for the dissipative forces.

TL;DR: In this article, the authors presented an experimental and analytical dynamic study of a small-scale steel frame, which was physically built and dynamically tested on a shaking table in series of different configurations obtained from the original one by changing the mass and by causing structural damage.

TL;DR: In this paper, the authors dealt with a method for seismic damage identification in buildings with steel moment-frame structure, which is based on artificial neural networks and natural frequencies and used a simplified finite element model to obtain the data needed for training the nets.