Wave data assimilation using a hybrid approach in the Persian Gulf

The main goal of this study is to develop an efficient approach for the assimilation of the hindcasted wave parameters in the Persian Gulf. Hence, the third generation SWAN model was employed for wave modeling forced by the 6-h ECMWF wind data with a resolution of 0.5°. In situ wave measurements at two stations were utilized to evaluate the assimilation approaches. It was found that since the model errors are not the same for wave height and period, adaptation of model parameter does not result in simultaneous and comprehensive improvement of them. Therefore, an approach based on the error prediction and updating of output variables was employed to modify wave height and period. In this approach, artificial neural networks (ANNs) were used to estimate the deviations between the simulated and measured wave parameters. The results showed that updating of output variables leads to significant improvement in a wide range of the predicted wave characteristics. It was revealed that the best input parameters for error prediction networks are mean wind speed, mean wind direction, wind duration, and the wave parameters. In addition, combination of the ANN estimated error with numerically modeled wave parameters leads to further improvement in the predicted wave parameters in contrast to direct estimation of the parameters by ANN.     

Estimating the Shapes of Gravity Sources through Optimized Support Vector Classifier (SVC)

In gravity interpretation methods, an initial guess for the approximate shape of the gravity source is necessary. In this paper, the support vector classifier (SVC) is applied for this duty by using gravity data. It is shown that using SVC leads us to estimate the approximate shapes of gravity sources more objectively. The procedure of selecting correct features is called feature selection (FS).In this research, the proper features are selected using inter/intra class distance algorithm and also FS is optimized by increasing and decreasing the number of dimensions of features space. Then, by using the proper features, SVC is used to estimate approximate shapes of sources from the six possible shapes, including: sphere, horizontal cylinder, vertical cylinder, rectangular prism, syncline, and anticline. SVC is trained using 300 synthetic gravity profiles and tested by 60 other synthetic and some real gravity profiles (related to a well and two ore bodies), and shapes of their sources estimated properly.     

Hydraulic Conductivity of Fly Ash-Amended Mine Tailings

The objective of this study was to evaluate the effect of fly ash addition on hydraulic conductivity (k) of mine tailings. Mine tailings used in this study were categorized as synthetic tailings and natural tailings; two synthetic tailings were developed via blending commercially-available soils and natural tailings were collected from a garnet mine located in the U.S. Two fly ashes were used that had sufficient calcium oxide (CaO) content (17 and 18.9 %) to generate pozzolanic activity. Hydraulic conductivity was measured on pure tailings and fly ash-amended tailings in flexible-wall permeameters. Fly ash was added to mine tailings to constitute 10 % dry mass of the mixture, and specimens were cured for 7 and 28 days. The influence of fly ash-amendment on k of mine tailings was attributed to (1) molding water content and (2) plasticity of the mine tailings. Tailings that classified as low-plasticity silts with clay contents less than 15 % exhibited a decrease in k when amended with fly ash and prepared wet of optimum water content (w _opt ). Tailings that classified as low-plasticity clay exhibited a one-order magnitude increase in k with addition of fly ash for materials prepared dry or near w _opt . The decrease in k for silty tailings was attributed to formation of cementitious bonds that obstructed flow paths, whereas the increase in k for clayey tailings was attributed to agglomeration of clay particles and an overall increase in average pore size. The results also indicated that the effect of curing time on k is more pronounced during the early stages of curing (≤7 days), as there was negligible difference between k for 7 and 28-days cured specimens.     

Lithospheric structure of NW Iran from P and S receiver functions

We computed P and S receiver functions to investigate the lithospheric structure beneath the northwest Iran and compute the Vp/Vs ratio within the crust of this seismologically active area. Our results enabled us to map the lateral variations of the Moho as well as those of the lithosphere–asthenosphere boundary (LAB) beneath this region. We selected data from teleseismic events (M_b?>?5.5, epicentral distance between 30° and 95° for P receiver functions and M_b?>?5.7, epicentral distance between 60° and 85° for S receiver functions) recorded from 1995 to 2008 at 8 three-component short-period stations of Tabriz Telemetry Seismic Network. Our results obtained from P receiver functions indicate clear conversions at the Moho boundary. The Moho depth was firstly estimated from the delay time of the Moho converted phase relative to the direct P wave. Then we used the H-Vp/Vs stacking algorithm of Zhu and Kanamori to estimate the crustal thickness and Vp/Vs ratio underneath the stations with clear Moho multiples. We found an average Moho depth of 48 km, which varies between 38.5 and 53 km. The Moho boundary showed a significant deepening towards east and north. This may reveal a crustal thickening towards northeast possibly due to the collision between the Central Iran and South Caspian plates. The obtained average Vp/Vs ratio was estimated to be 1.76, which varies between 1.73 and 1.82. The crustal structure was also determined by modeling of P receiver functions. We obtained a three-layered model for the crust beneath this area. The thickness of the layers is estimated to be 6–11, 18–35, and 38–53 km, respectively. The average of the shear wave velocity was calculated to be 3.4 km/s in the crust and reaches 4.3 km/s below the Moho discontinuity. The crustal thickness values obtained from P receiver functions are in good agreement with those derived by S receiver functions. In addition, clear conversions with negative polarity were observed at ~8.7 s in S receiver functions, which could be related to the conversion at the LAB. This may show a relatively thin continental lithosphere of about 85 km implying that the lithosphere was influenced by various geodynamical reworking processes in the past.     

Seismic evaluation of rocking structures through performance assessment and fragility analysis

Numerical studies have been conducted for low- and medium-rise rocking structures to investigate their efficiency as earthquake-resisting systems in comparison with conventional structures. Several non-linear time-history analyses have been performed to evaluate seismic performance of selected cases at desired ground shaking levels, based on key parameters such as total and flexural story drifts and residual deformations. The Far-field record set is selected as input ground motions and median peak values of key parameters are taken as best estimates of system response. In addition, in order to evaluate the probability of exceeding relevant damage states, analytical fragility curves have been developed based on the results of the incremental dynamic analysis procedure. Small exceedance probabilities and acceptable margins against collapse, together with minor associated damages in main structural members, can be considered as superior seismic performance for medium-rise rocking systems. Low-rise rocking systems could provide significant performance improvement over their conventional counterparts notwithstanding certain weaknesses in their seismic response.     

Earthquake relocation in the Central Alborz region of Iran using a non-linear probabilistic method

In this study, we calculate accurate absolute locations for nearly 3,000 shallow earthquakes (≤20 km depth) that occurred from 1996 to 2010 in the Central Alborz region of northern Iran using a non-linear probabilistic relocation algorithm on a local scale. We aim to produce a consistent dataset with a realistic assessment of location errors using probabilistic hypocenter probability density functions. Our results indicate significant improvement in hypocenter locations and far less scattering than in the routine earthquake catalog. According to our results, 816 earthquakes have horizontal uncertainties in the 0.5–3.0 km range, and 981 earthquakes are relocated with focal-depth errors less than 3.0 km, even with a suboptimal network geometry. Earthquake relocated are tightly clustered in the eastern Tehran region and are mainly associated with active faults in the study area (the Mosha and Garmsar faults). Strong historical earthquakes have occurred along the Mosha and Garmsar faults, and the relocated earthquakes along these faults show clear north-dipping structures and align along east–west lineations, consistent with the predominant trend of faults within the study region. After event relocation, all seismicity lies in the upper 20 km of the crust, and no deep seismicity (>20 km depth) has been observed. In many circumstances, the seismicity at depth does not correlate with surface faulting, suggesting that the faulting at depth does not directly offset overlying sediments.     

Testing the weak stationarity of a spatio-temporal point process

A common assumption in analyzing spatial and spatio-temporal point processes is stationarity, while in many real applications because of the environmental effects the stationarity condition is not often met. We propose two types of test statistics to test stationarity for spatio-temporal point processes, by adapting, Palahi, Pukkala & Mateu (2009) and by considering the square difference between observed and expected (under stationarity) intensities. We study the efficiency of the new statistics by simulated data, and we apply them to test the stationarity of real data.     

Frequency analysis of climate extreme events in Zanjan, Iran

In this study, generalized extreme value distribution (GEV) and generalized Pareto distribution (GPD) were fitted to the maximum and minimum temperature, maximum wind speed, and maximum precipitation series of Zanjan. Maximum (minimum) daily and absolute annual observations of Zanjan station from 1961 to 2011 were used. The parameters of the distributions were estimated using the maximum likelihood estimation method. Quantiles corresponding to 2, 5, 10, 25, 50, and 100 years return periods were calculated. It was found that both candidate distributions fitted to extreme events series, were statistically reasonable. Most of the observations from 1961 to 2011 were found to fall within 1–10 years return period. Low extremal index (θ) values were found for excess maximum and minimum temperatures over a high threshold, indicating the occurrence of consecutively high peaks. For the purpose of filtering the dependent observations to obtain a set of approximately independent threshold excesses, a declustering method was performed, which separated the excesses into clusters, then the de-clustered peaks were fitted to the GPD. In both models, values of the shape parameters of extreme precipitation and extreme wind speed were close to zero. The shape parameter was less negative in the GPD than the GEV. This leads to significantly lower return period estimates for high extremes with the GPD model.