Abstract

Abstract

Most of buildings and structures are usually projected according to two main axes. However, the geographical position of these buildings varies randomly. Such random distributions of the azimuthal positions of structures, in most of the cities, generally, are not accounted for when assessing their seismic risk; certainly, the direction of the seismic loads is another highly random variable. Moreover, an additional important source of uncertainty is related to the structural response, mainly due to the random character of the mechanical properties. There is a consensus that uncertainties must be considered for adequately assessing the seismic risk of structures, but these directionality effects have not been deeply explored so far. In this article, the influence of the high uncertainty involved in these input variables on the expected seismic damage is analysed. Thus, an actual earthquake, which affected the southern part of Spain, is studied. Notably, damages on a group of affected buildings, located close to the epicentre, are analysed and discussed in detail. The results show that the influence of the random azimuthal position of structures is an important source of uncertainty and that it should be taken into account when estimating the expected seismic risk in urban areas.

Abstract

The incremental dynamic analysis is a powerful tool for evaluating the seismic vulnerability and risk of buildings. It allows calculating the global damage of structures for different PGAs and representing this result by means of damage curves. Such curves are used by many methods to obtain seismic risk scenarios at urban level. Even if the use of this method in a probabilistic environment requires a relevant computational effort, it should be the reference method for seismic risk evaluation. In this article we propose to assess the seismic expected damage by using nonlinear dynamic analysis. We will obtain damage curves by means of the incremental dynamic analysis combined with the damage index of Park & Ang. The uncertainties related to the mechanical properties of the materials and the seismic action will be considered. The probabilistic damage curves obtained can be used to calculate not only seismic risk scenarios at urban level, but also to estimate economic losses.

Abstract

Abstract

Uncertainties are a daily issue to deal with in aerospace engineering and applications. Robust optimization methods commonly use a random generation of the inputs and take advantage of multi-point criteria to look for robust solutions accounting with uncertainty definition. From the computational point of view, the application to coupled problems, like computational fluid dynamics (CFD) or fluid–structure interaction (FSI), can be extremely expensive. This study presents a coupling between stochastic analysis techniques and evolutionary optimization algorithms for the definition of a stochastic robust optimization procedure. At first, a stochastic procedure is proposed to be applied into optimization problems. The proposed method has been applied to both CFD and FSI problems for the reduction of drag and flutter, respectively.

Abstract

Abstract

Abstract

The uncertainties of parameters quantification due to various known and unknown conditions are crucial to understand structural health monitoring (SHM) systems. For instance, the amplitudes and the variation of loading conditions play a vital rule how the structural parameters are going to be changed. Hence, the aforementioned issue leads to an additional challenge in the area of SHM that requires attention. This study observed the behaviour of a steel bridge experimentally by employing multi-sensors scenarios e.g. accelerometers and laser triangulation sensor. The dynamical properties such as the peak (e.g. maximum-minimum) accelerations and displacements are evaluated. Additionally, the frequencies and damping ratio from the measured data of the tested bridge has been estimated by utilizing the fast Fourier transform (FFT) estimation. The outcome shows that the variation of input excitations (i.e., random, free-decay, extra-loading) effects the investigated properties as well as on their magnitudes considerably. Therefore, the findings suggest that before making a final judgement based on the identified/estimated properties from measured data, the underlying uncertainties need to be considered to avoid sub-optimal assessment strategy.

Abstract