A unified approach for the design of high ductility steel frames with concentric braces in the framework of Eurocode 8

Eurocode 8 (EC8) stipulates design methods for frames with diagonal braces and for chevron braced frames, which differ as regards the numerical model adopted, the value of the behavior factor q and the estimation of the lateral strength provided by braces. Instead, in this paper, the use of the same design method is suggested for both types of concentrically braced frames. The design method is a generalization of the one proposed for chevron braced frames in a previous study. A numerical investigation is conducted to assess the reliability of this design method. A set of concentrically braced frames is designed according to the EC8 and proposed design methods. The seismic response of these frames is determined by nonlinear dynamic analysis. Finally, it is demonstrated that the proposed design method is equivalent to those provided by EC8, because it can ensure the same level of structural safety which would be expected when using EC8. Copyright © 2013 John Wiley & Sons, Ltd.     

Exploiting Maximum Entropy method and ASTER data for assessing debris flow and debris slide susceptibility for the Giampilieri catchment (north‐eastern Sicily,Italy)

This study aims at evaluating the performance of the Maximum Entropy method in assessing landslide susceptibility, exploiting topographic and multispectral remote sensing predictors. We selected the catchment of the Giampilieri stream, which is located in the north‐eastern sector of Sicily (southern Italy), as test site. On 1 October 2009, a storm rainfall triggered in this area hundreds of debris flow/avalanche phenomena causing extensive economical damage and loss of life. Within this area a presence‐only‐based statistical method was applied to obtain susceptibility models capable of distinguishing future activation sites of debris flow and debris slide, which where the main source of failure mechanisms for flow or avalanche type propagation. The set of predictors used in this experiment comprised primary and secondary topographic attributes, derived by processing a high resolution digital elevation model, CORINE land cover data and a set of vegetation and mineral indices obtained by processing multispectral ASTER images. All the selected data sources are dated before the disaster. A spatially random partition technique was adopted for validation, generating 50 replicates for each of the two considered movement typologies in order to assess accuracy, precision and reliability of the models. The debris slide and debris flow susceptibility models produced high performances with the first type being the best fit. The evaluation of the probability estimates around the mean value for each mapped pixel shows an inverted relation, with the most robust models corresponding to the debris flows. With respect to the role of each predictor within the modelling phase, debris flows appeared to be primarily controlled by topographic attributes whilst the debris slides were better explained by remotely sensed derived indices, particularly by the occurrence of previous wildfires across the slope. The overall excellent performances of the two models suggest promising perspectives for the application of presence‐only methods and remote sensing derived predictors. Copyright © 2016 John Wiley & Sons, Ltd.     

A stochastic model for daily subsurface CO2 concentration and related soil respiration

Near-surface soil CO₂ gas-phase concentration (C) and concomitant incident rainfall (P_i) and through-fall (P_t) depths were collected at different locations in a temperate pine forest every 30 min during the 2005 and 2006 growing seasons (and then averaged to the daily timescale). At the daily scale, C temporal variations were well described by a sequence of monotonically decreasing functions interrupted by large positive jumps induced by rainfall events. A stochastic model was developed to link rainfall statistics responsible for these jumps to near-surface C dynamics. The model accounted for the effect of daily rainfall variability, both in terms of timing and amount of water, and permitted an analytical derivation of the C probability density function (pdf) using the parameters of the rainfall pdf. Given the observed positive correlation between daily C and soil CO₂ fluxes to the atmosphere (F_s), the effects of various rainfall regimes on the statistics of F_s can be deduced from the behavior of C under different climatic conditions. The predictions from this analytical model are consistent with flux measurements reported in manipulative experiments that varied rainfall amount and frequency.