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Masonry infill walls are commonly used in reinforced concrete (RC) frame structures, also in seismically active areas, although they often experience serious damage during earthquakes. One of the main reasons for their poor behaviour is the connection to the frame, which is usually constructed using mortar. This paper describes the novel solution for infill/frame connection based on application of elastomeric material between them. The system called INODIS (Innovative Decoupled Infill System) has the aim to postpone the activation of infill in in-plane direction and at the same time to provide sufficient out-of-plane support. First, experimental tests on infilled frame specimens are presented and the comparison of the results between traditionally infilled frames and infilled frames with the INODIS system are given. The results are then used for calibration and validation of numerical model, which can be further employed for investigating the influence of some material parameters on the behaviour of infilled frames with the INODIS system.
Wind loads have great impact on many engineering structures. Wind storms often cause irreparable damage to the buildings which are exposed to it. Along with the earthquakes, wind represents one of the most common environmental load on structures and is relevant for limit state design. Modern wind codes indicate calculation procedures allowing engineers to deal with structural systems, which are susceptible to conduct wind-excited oscillations. In the codes approximate formulas for wind buffeting are specified which relate the dynamic problem to rather abstract parameter functions. The complete theory behind is not visible in order to simplify the applicability of the procedures. This chapter derives the underlying basic relations of the spectral method for wind buffeting and explains the main important applications of it in order to elucidate part of the theoretical background of computations after the new codes. The stochasticity of the wind processes is addressed, and the analysis of analytical as well as measurement based power spectra is outlined. Short MATLAB codes are added to the Appendix 3 which carry out the computation of a single sided auto-spectrum from a statistically stationary, discrete stochastic process. Two examples are presented.