Inelastic seismic demand estimation of wood-frame houses subjected to mainshock-aftershock sequences

An active aftershock sequence, triggered by a large mainshock, can cause major destruction to urban cities. It is important to quantify the aftershock effects in terms of nonlinear responses of realistic structural models. For this purpose, this study investigates the aftershock effects on seismic fragility of conventional wood-frame houses in south-western British Columbia, Canada, using an extensive set of real mainshock-aftershock earthquake records. For inelastic seismic demand estimation, cloud analysis and incremental dynamic analysis are considered. A series of nonlinear dynamic analyses are carried out by considering different seismic input cases and different analysis approaches. The analysis results indicate that consideration of aftershocks leads to 5–20 % increase of the median inelastic seismic demand curves when a moderate degree of structural response is induced. The findings of this investigation facilitate the extension of the existing approaches for inelastic seismic demand estimation to incorporate the aftershock effects.     

Stability of the time‐domain analysis method including a frequency‐dependent soil–foundation system

A number of methods have been proposed that utilize the time‐domain transformations of frequency‐dependent dynamic impedance functions to perform a time‐history analysis. Though these methods have been available in literature for a number of years, the methods exhibit stability issues depending on how the model parameters are calibrated. In this study, a novel method is proposed with which the stability of a numerical integration scheme combined with time‐domain representation of a frequency‐dependent dynamic impedance function can be evaluated. The method is verified with three independent recursive parameter models. The proposed method is expected to be a useful tool in evaluating the potential stability issue of a time‐domain analysis before running a full‐fledged nonlinear time‐domain analysis of a soil–structure system in which the dynamic impedance of a soil–foundation system is represented with a recursive parameter model. Copyright © 2015 John Wiley & Sons, Ltd.     

Examination of chloritization of biotite as a tool for reconstructing the physicochemical parameters of mineralization and associated alteration in the Zafarghand porphyry copper system,Ardestan, Central Iran: mineral-chemistry and stable isotope analyses

Mineralogy and Petrology - The chloritization of biotite and stable isotopes of silicate have been studied for the Zafarghand porphyry copper deposit, Ardestan, Iran. The studied area, in the...     

3D Gravity Inversion using Tikhonov Regularization

Subsalt exploration for oil and gas is attractive in regions where 3D seismic depth-migration to recover the geometry of a salt base is difficult. Additional information to reduce the ambiguity in seismic images would be beneficial. Gravity data often serve these purposes in the petroleum industry. In this paper, the authors present an algorithm for a gravity inversion based on Tikhonov regularization and an automatically regularized solution process. They examined the 3D Euler deconvolution to extract the best anomaly source depth as a priori information to invert the gravity data and provided a synthetic example. Finally, they applied the gravity inversion to recently obtained gravity data from the Bandar Charak (Hormozgan, Iran) to identify its subsurface density structure. Their model showed the 3D shape of salt dome in this region.     

Upscaling of the permeability by multiscale wavelet transformations and simulation of multiphase flows in heterogeneous porous media

We describe a new approach for simulation of multiphase flows through heterogeneous porous media, such as oil reservoirs. The method, which is based on the wavelet transformation of the spatial distribution of the single-phase permeabilities, incorporates in the upscaled computational grid all the relevant data on the permeability, porosity, and other important properties of a porous medium at all the length scales. The upscaling method generates a nonuniform computational grid which preserves the resolved structure of the geological model in the near-well zones as well as in the high-permeability sectors and upscales the rest of the geological model. As such, the method is a multiscale one that preserves all the important information across all the relevant length scales. Using a robust front-detection method which eliminates the numerical dispersion by a high-order total variation diminishing method (suitable for the type of nonuniform upscaled grid that we generate), we obtain highly accurate results with a greatly reduced computational cost. The speed-up in the computations is up to over three orders of magnitude, depending on the degree of heterogeneity of the model. To demonstrate the accuracy and efficiency of our methods, five distinct models (including one with fractures) of heterogeneous porous media are considered, and two-phase flows in the models are studied, with and without the capillary pressure.     

The Cimmerian Orogeny in northern Iran: tectono-stratigraphic evidence from the foreland

From the Permian onwards, the Gondwana-derived Iran Plate drifted northward to collide with Eurasia in the Late Triassic, thereby closing the Palaeotethys. This Eo-Cimmerian Orogeny formed the Cimmeride fold-and-thrust belt. The Upper Triassic–Middle Jurassic Shemshak Group of northern Iran is commonly regarded as the Cimmerian foreland molasse. However, our tectono-stratigraphic analysis of the Shemshak Group resulted in a revised and precisely dated model for the Triassic–Jurassic geodynamic evolution of the Iran Plate: initial Cimmerian collision started in the Carnian with subsequent Late Triassic synorogenic peripheral foreland deposition (flysch, lower Shemshak Group). Subduction shifted south in the Norian (onset of Neotethys subduction below Iran) and slab break-off around the Triassic–Jurassic boundary caused rapid uplift of the Cimmerides followed by Liassic post-orogenic molasse (middle Shemshak Group). During the Toarcian–Aalenian (upper Shemshak Group), Neotethys back-arc rifting formed a deep-marine basin, which developed into the oceanic South Caspian Basin during the Late Bajocian–Late Jurassic.     

Flooding and its relationship with land cover change,population growth,and road density

Bangladesh experiences frequent hydro-climatic disasters such as flooding.These disasters are believed to be associated with land use changes and climate variability.However,identifying the factors that lead to flooding is challenging.This study mapped flood susceptibility in the northeast region of Bangladesh using Bayesian regularization back propagation(BRBP)neural network,classification and regression trees(CART),a statistical model(STM)using the evidence belief function(EBF),and their ensemble models(EMs)for three time periods(2000,2014,and 2017).The accuracy of machine learning algorithms(MLAs),STM,and EMs were assessed by considering the area under the curve-receiver operating char-acteristic(AUC-ROC).Evaluation of the accuracy levels of the aforementioned algorithms revealed that EM4(BRBP-CART-EBF)outperformed(AUC＞90％)standalone and other ensemble models for the three time periods analyzed.Furthermore,this study investigated the relationships among land cover change(LCC),population growth(PG),road density(RD),and relative change of flooding(RCF)areas for the per-iod between 2000 and 2017.The results showed that areas with very high susceptibility to flooding increased by 19.72％between 2000 and 2017,while the PG rate increased by 51.68％over the same period.The Pearson correlation coefficient for RCF and RD was calculated to be 0.496.These findings highlight the significant association between floods and causative factors.The study findings could be valuable to policymakers and resource managers as they can lead to improvements in flood management and reduction in flood damage and risks.     

Hydraulic conductivity prediction based on grain-size distribution using M5 model tree

The hydraulic conductivity, K_s, is one of the most important hydraulic properties which controls the water and solute movement into the soil. It is measured on soil specimens in the laboratory. On the other hand, sometimes it is obtained by tests carried out in the field by a number of researchers. Therefore, several experimental formulas have developed to predict it. Recently, soft computing tools have been used to evaluate the hydraulic conductivity. However, these tools are not as transparent as empirical formulas. In this study, another soft computing approach, i.e. model trees, have been used for predicting the hydraulic conductivity. The main advantage of model trees is that, unlike the other data learning tools, they are easier to use and represent understandable mathematical rules more clearly. In this paper, a new formula that includes some parameters is derived to estimate the hydraulic conductivity. To develop the new formulas, experimental data sets of hydraulic conductivity were used. A comparison is made between the estimated hydraulic conductivity by this new formula and formulas given by other’s researches.     

Fluoride hydrogeochemistry and bioavailability in groundwater and soil of an endemic fluorosis belt,central Iran

Presence of fluoride in groundwater is a public health problem in the so-called endemic fluorosis belt of the central Iran, where the groundwater is the major source of drinking water in most urban and rural areas. Therefore, an attempt has been made to determine the hydrogeochemical factors controlling fluoride enrichment in the groundwater resources at this belt. Fluoride concentrations ranged from 0.20 to 1.99 mg/L (1.02 ± 0.47) in groundwater samples. The presence of different F-bearing minerals and also clay minerals in the soils and aquifer materials was confirmed using XRD analysis. To identify probable sources of dissolved F^? and investigate groundwater quality, multivariate statistical analyses were carried out. Geochemical modeling indicated that all samples were undersaturated with respect to fluorite, halite, gypsum and anhydrite and mostly oversaturated with respect to calcite and dolomite. Contrary to most high-fluoride regions in the World, the high F^? content was dominated by Na–Cl- and Ca–SO₄-type groundwater in the study area. Besides, fluoride showed negative relationship with pH and HCO₃ ^? in groundwater. In order to assess the bioavailability of fluoride in soils, a two-step chemical fractionation method was applied. The results showed that fluoride in soils mostly accompanied with the residual and water-soluble fractions and was poorly associated with soil’s bonding sites. Calculated aqueous migration coefficient demonstrated that fluoride in the studied soils was mobile to easily leachable to the groundwater. Finally, the results demonstrated that combination of water–rock interaction and influence of clay minerals is geochemical mechanism responsible for controlling fluoride enrichment in groundwater.     

Optimization approach to retrieve soil surface parameters from single-acquisition single-configuration SAR data

This study suggests a novel approach to the retrieval of soil surface parameters using a single-acquisition single-configuration synthetic-aperture radar (SAR) system. Soil surface parameters such as soil moisture and surface roughness are key elements for many environmental studies, including Earth surface water cycles, energy exchange, agriculture, and geology. Remote sensing techniques, especially SAR data, are commonly used to retrieve such soil surface parameters over large areas. Several backscattering models have been proposed for soil surface parameters retrieval from SAR data. However, commonly, these backscattering models require multi configuration SAR data, including multi-polarization, multi-frequency, and multi-incidence angle. Here we propose a methodology that employs single-acquisition single-configuration SAR data for the retrieval of soil surface parameters. The originality is to use single-acquisition single-configuration SAR data to retrieve the soil surface parameters using an optimization approach by the genetic algorithm (GA); we have used the modified Dubois model (MDM) in HH polarization as the backscattering model. Three HH polarization and C band data sets from Quebec (Radarsat-1), Ontario (SIR-C), and Oklahoma (AIRSAR) were analyzed. The retrieved values of soil moisture and soil surface roughness were then compared to ground truth measurements with corresponding parameters. We employed diverse criteria, including the mean absolute error (MAE), the root mean square error (RMSE), the coefficient of performance (CP), and the correlation coefficient to investigate the performance of the proposed methodology. This analysis suggests the capability of the GA for the retrieval of soil surface parameters. Based on our findings, this method presents a viable alternative approach to the retrieval of soil surface parameters when only single-acquisition single-configuration SAR data is available.