Strong ground motion record selection for the reliable prediction of the mean seismic collapse capacity of a structure group

How to select a limited number of strong ground motion records (SGMRs) is an important challenge for the seismic collapse capacity assessment of structures. The collapse capacity is considered as the ground motion intensity measure corresponding to the drift‐related dynamic instability in the structural system. The goal of this paper is to select, from a general set of SGMRs, a small number of subsets such that each can be used for the reliable prediction of the mean collapse capacity of a particular group of structures, i.e. of single degree‐of‐freedom systems with a typical behaviour range. In order to achieve this goal, multivariate statistical analysis is first applied, to determine what degree of similarity exists between each selected small subset and the general set of SGMRs. Principal Component analysis is applied to identify the best way to group structures, resulting in a minimum number of SGMRs in a proposed subset. The structures were classified into six groups, and for each group a subset of eight SGMRs has been proposed. The methodology has been validated by analysing a first‐mode‐dominated three‐storey‐reinforced concrete structure by means of the proposed subsets, as well as the general set of SGMRs. The results of this analysis show that the mean seismic collapse capacity can be predicted by the proposed subsets with less dispersion than by the recently developed improved approach, which is based on scaling the response spectra of the records to match the conditional mean spectrum. Copyright © 2010 John Wiley & Sons, Ltd.     

Hydrogeochemistry of Groundwater and Its Suitability for Drinking and Agricultural Use in Nahavand,Western Iran

Groundwater is the major source of drinking water in Nahavand city. However, the groundwater quality at the agricultural areas has been deteriorating in recent years. Ground water quality monitoring is a tool which provides important information for water management and sustainable development of the water resources in Nahavand. Hydrochemical investigations were carried out in an agricultural area in Nahavand, western Iran, to assess chemical composition of groundwater. In this study, 64 representative groundwater samples were collected from different irrigation wells and analyzed for pH, electrical conductivity, major ions, and nitrate. The results of the chemical analysis of the groundwater showed that concentrations of ions vary widely and the most prevalent water type is Ca–Mg–HCO₃, followed by other water types: Ca–HCO₃, Ca–Na–HCO₃, and Na–Cl, which is in relation with their interactions with the geological formations of the basin, dissolution of feldspars and chloride and bicarbonate minerals, and anthropogenic activities. Thirty-seven percent of the water samples showed nitrate (NO₃ ⁻) concentrations above the human affected value (13 mg L⁻¹). The phosphorous (P) concentration in groundwater was between 0.11 and 0.90 mg L⁻¹, with an average value of 0.30 mg L⁻¹, with all of the samples over 0.05 mg L⁻¹. The most dominant class C2-S1 (76.5%) was found in the studied area, indicating that sodicity is very low and salinity is medium, and that these waters are suitable for irrigation in almost all soils. Agronomic practices, such as cultivation, cropping, and irrigation water management may decrease the average NO₃ ⁻ concentration in water draining from the soil zone.     

Nitrate pollution of groundwater in Toyserkan,western Iran

A total of 95 groundwater samples were collected from Toyserkan, western Iran to assess the chemical composition and nitrate (NO₃ ⁻) status of groundwater. The most prevalent water type is Ca–HCO₃ followed by water types Ca–Mg–HCO₃. In comparison with the World Health Organization (WHO) drinking water guideline of 50 mg l⁻¹ for NO₃ ⁻, a total of nine wells (9.5%) showed higher concentrations. In 36% of samples (34) NO₃ ⁻ concentration was low (<20 mg l⁻¹), and in 53.7% of samples (51), in the range of 20–50 mg l⁻¹. The samples were classified into four groups based on NO₃ ⁻ and chloride (Cl⁻) concentrations. Of the samples, 40% were classified as group 4 and were relatively high in Cl⁻ and NO₃ ⁻ (Cl⁻ > 47 mg l⁻¹, NO₃ ⁻ > 27 mg l⁻¹). The high correlation between NO₃ ⁻ and Cl⁻ (r = 0.86, p < 0.01) is consistent with a manure source, resulting from the practice of adding salt to animal feed. Pollution of groundwaters appeared to be affected by the application of inorganic fertilizer at greater than agronomic rates, Cl-salt inputs, and irrigation practice.     

Geodynamic setting and emplacement of mylonitic granitoids within the North Golpayegan shear zone,Iran

The metamorphic complex of the North Golpayegan is part of the Sanandaj-Sirjan Zone. There are at least three distinct stages of deformation in this complex. Throughout the first stage, Paleozoic and Mesozoic sedimentary rocks have experienced regional metamorphism during Late Jurassic tectonic events related to the subduction of the Neo-Tethys oceanic lithosphere under the Iranian microcontinent. During the second deformation stage in the Late Cretaceous-Paleocene, the rocks have been mylonitized. The third stage of deformation in the region has led to folding and faulting superimposed on previous structures, and to exhumation of the metamorphic complex. This stage has determined the current morphology and N70E strike of the complex. The mylonitic zones of the second stage of deformation have been formed along the dextral transpressional faults. During the third stage of deformation and exhumation of the metamorphic complex, the mylonitic zones have been uplifted to the surface. The granitoids in the metamorphic complex have been injected along the extensional shear fractures related to the dextral transpressional displacements. The granitoids have been transformed into mylonites within the synthetic or antithetic shear zones. These granitoids are recognized as syncollision type (CCG) and have been formed at the end of orogenic events synchronous to the collision between the Arabian and the Iranian plates at the Late Cretaceous-Paleocene.     

Optimal design of structures for earthquake loads by a hybrid RBF-BPSO method

The optimal seismic design of structures requires that time history analyses （THA） be carried out repeatedly. This makes the optimal design process inefficient, in particular, if an evolutionary algorithm is used. To reduce the overall time required for structural optimization, two artificial intelligence strategies are employed. In the first strategy, radial basis function （RBF） neural networks are used to predict the time history responses of structures in the optimization flow. In the second strategy, a binary particle swarm optimization （BPSO） is used to find the optimum design. Combining the RBF and BPSO, a hybrid RBF-BPSO optimization method is proposed in this paper, which achieves fast optimization with high computational performance. Two examples are presented and compared to determine the optimal weight of structures under earthquake loadings using both exact and approximate analyses. The numerical results demonstrate the computational advantages and effectiveness of the proposed hybrid RBF-BPSO optimization method for the seismic design of structures.     

Assessment of future changes in the maximum temperature at selected stations in Iran based on HADCM3 and CGCM3 models

Identification and assessment of climate change in the next decades with the aim of appropriate environmental planning in order to adapt and mitigate its effects are quite necessary. In this study, maximum temperature changes of Iran were comparatively examined in two future periods (2041-2070 and 2071-2099) and based on the two general circulation model outputs (CGCM3 and HADCM3) and under existing emission scenarios (A2, A1B, B1 and B2). For this purpose, after examining the ability of statistical downscaling method of SDSM in simulation of the observational period (1981-2010), the daily maximum temperature of future decades was downscaled by considering the uncertainty in seven synoptic stations as representatives of climate in Iran. In uncertainty analysis related to model-scenarios, it was found that CGCM3 model under scenario B1 had the best performance about the simulation of future maximum temperature among all of the examined scenario-models. The findings also showed that the maximum temperature at study stations will be increased between 1°C and 2°C in the middle and the end of 21st century. Also this maximum temperature changes is more severe in the HADCM3 model than the CGCM3 model.     

Spatio-temporal analysis of crime by developing a method to detect critical distances for the Knox test

The present study examined and compared spatio–temporal interaction of the theft of car parts, shop burglary and motorcycle theft in the central business district (CBD) of the city of Zanjan in Iran. The Knox test was selected to detect spatio–temporal interaction. This test has been criticized as being subjective because the selection of critical distances is arbitrary; thus, a method is proposed to detect critical distances in the Knox test using the mean distance, natural breaks classification of nearest neighbour (NN) distance and Ripley’s k function. Results show obvious differences between the spatio-temporal clusters of the three sets of crimes. They also indicate that changing the spatial cut-offs within a cluster creates different temporal patterns. Of the three criteria for determining critical distances, NN classification based on natural breaks showed more interactions than the other methods.     

The effect of magnetic field morphology on the structure of massive IRDC clumps

Infrared dark clouds (IRDCs) have dense elongated clumps and filaments with the favorable viewing condition of being on the near-side of a bright mid-infrared background. The clumps usually have multiple cores around the center. In this work, we study the effect of magnetic field morphology on the structure of massive IRDC clumps. To achieve this goal, we consider an axisymmetric isothermal oblate IRDC clump, embedded into a constant external magnetic field. We assume a polynomial function for the magnetic field morphology inside the clump. We use the numerical iterative methods to solve the equations: the successive over-relaxation method to find the magnetic and gravitational fluxes, and then the biconjugate gradient method to find the optimized values of mass and current densities. The results show that the IRDC clump will be very elongated along the perpendicular direction of the external magnetic field lines. Also, the assumption of choosing of a polynomial function for the magnetic field morphology leads to the formation of dense regions around the center. The greater the density of the central region, the larger the density of these dense regions and the closer to the center. The presence of these dense regions can lead to the formation of cores at these points.