Abstract

Abstract

Abstract

Abstract

The probabilistic analysis of the seismic performance of a structure requires quantifying the uncertainties of the involved variables and parameters, including the seismic action and mechanical properties of its elements. In this article, the seismic performance of high-rise, mid-rise and low-rise of steel buildings, subjected to long duration seismic actions like those of Mexico City, is analyzed. The analysis is conducted by using a probabilistic approach. The seismic actions are selected to be compatible with the design spectra of the Mexican seismic code for soft soils and long duration earthquakes, characteristic for this region. The dynamic analyses are performed by using Monte Carlo simulations. The strength and ductility of the beams and columns are considered random variables; the seismic actions are also modelled in a probabilistic way. The damage index of Park and Ang is used. The results show that the uncertainties expected in the response are significant, being the randomness of the seismic action the main cause. From the comparison between the mean values of the probabilistic approach and those corresponding to the deterministic case, a good consistency of the result obtained for low-rise and mid-rise buildings is observed. Nevertheless, the consistency is lower in the case of high-rise buildings. The analyzed low-rise and mid-rise buildings show a good seismic performance to seismic actions, but the high-rise buildings show slight or moderate damage. It is concluded that the probabilistic approach provides a more complete information on the structural response.

Abstract

The present analysis addresses the primary balance response to the debt of the Spanish Autonomous Communities (ACs) from 1987 to 2015. Overall, the results of this study provide evidence on a nonlinear relationship, which point to a situation of fiscal fatigue and reduced fiscal space. The empirical framework builds mainly on the works of Bohn (1998) and Gosh et al. (2013), thereby focusing also on uncertainty issues. In 2015 the debt ratio stood at 26.8% of ACs’ Gross Value Added, slightly above our estimates for the lower limit (24%) and well below the upper limit (36%). These results have a backward-looking orientation, that is, fiscal reaction for the coming years is not necessarily determined by past behaviour. That being said, a reduced fiscal space of ACs calls for measures to ensure a sustainable debt trajectory and regain some room to deal with potential negative shocks.

Abstract

L’elevat endeutament públic és un dels llegats de la gran crisi, i en especial pel que fa a les comunitats autònomes. Aquesta situació és especialment preocupant atesa la responsabilitat d’aquestes en la prestació de serveis bàsics de l’estat del benestar. Els treballs de Bohn (1998) i Gosh et al. (2013) ens permeten plantejar una aproximació al llindar on la sostenibilitat del deute pot ser qüestionada. L’any 2015 la ràtio del deute se situava a la banda baixa de la regió que comprèn aquest llindar, en concret, entre el 24% i el 36% del VAB. La prudència aconsella disposar d’un marge de maniobra suficient (en termes de capacitat d’endeutament) per poder afrontar xocs negatius plausibles.

Abstract

Faced with the problem of wind speed in generation and the difficulty that this entails in the economic future of electric power, mathematical formulations (functions), called uncertainty costs, have been developed. The term is used in a model composed of two parts, an implication of penalization costs for overestimation and the other due to the underestimation of a programmed power. Through analytical mathematics and Monte Carlo simulations, we have found the expected value of the costs of uncertainty, the stability of primary resources through the distribution of probability. However, the results can not be evaluated accurately from an analytical point of view, without taking into account the variability around the average value. In this article we calculate the analytical function of the variance, we understand as a measure of dispersion of the expected values of uncertainty costs for the specific case of wind operators; Likewise, this formulation has been validated through Monte Carlo simulations. The function found is used to observe the dispersion of the data around its expected average value, by applying the standard deviation.

Abstract

We derive analytical relationships between the spatial covariance of the (natural) logarithm of hydraulic conductivity (K) and that of representative soil particle sizes and porosity. The latter quantities can be directly measured during routine sedimentological analyses of soil samples and provide a way of incorporating K estimates into groundwater flow models at a relatively modest experimental cost. Here we rely on widely used empirical formulations requiring measurements of representative particle diameters and, in some cases, of medium porosity. We derive exact formulations relating the spatial covariance of these quantities and K and present workable approximations on the basis of perturbation methods. Our formulations provide a direct link between key geostatistical descriptors of sedimentological and hydraulic parameters of heterogeneous aquifers which can be employed in classical estimation and simulation procedures. The approach and theoretical results are tested on an extensive data set comprising 411 particle size curves collected at 12 boreholes in a small-scale alluvial aquifer.

Abstract

'''In the spare parts supply network, there are many uncertain factories, such as unpredictable demands and changeable lead times. The spare parts shortage caused by those uncertainties may lead to severe losses. To solve the uncertainty of supply network, a determined optimization model is developed and then reformulated as a robust counterpart. In the robust model, it is only necessary to know the moment information of the uncertain parameters rather than the true probability distribution. The solution obtained by the robust model can satisfy the constraints in the worst-case, that is, feasible for any probability distribution within the moment based ambiguity set. Two moment based robust models are studied in this work. The result of the experiment indicates that the robustness of the robust model is stronger than that of the determined model and chance constraint model, and the effect of safety tolerance on the robustness is revealed by sensitivity analysis. Finally, the second order moment model is verified be superior to the first order moment model in spare parts supply network optimization.