The behaviour of an artificially cemented sandy gravel

The major section of the city of Tehran, Iran has been developed on cemented coarse-grained alluvium. This deposit consists of gravely sand to sandy gravel with some cobbles and is dominantly cemented by carbonaceous materials. In order to understand the mechanical behaviour of this soil, a series of undrained triaxial compression tests and unconfined compression tests were performed on uncemented and artificially cemented samples. Portland cement type I was used as the cementation agent for preparing artificially cemented samples. Uncemented samples and lightly cemented samples (1.5% cement) tested at high confining pressure showed contractive behaviour accompanied with positive excess pore water pressure and a barrelling failure mode. However, cemented samples and uncemented samples tested at low confining pressure (25 and 50 kN/m²) showed dilative behaviour accompanied with negative excess pore water pressure. Shear zones were formed in these samples and a clear peak in excess pore water pressure and stress ratio against strain could be observed. Test results showed that the limiting stress ratio surface for cemented samples is curved and expands as the cementation and density increase. Unconfined compression strength of cemented samples increases with increases in cementation and density as well.     

Carbonate diagenesis of the upper Jurassic successions in the west of Binalud — Eastern Alborz (NE Iran)

The upper Jurassic carbonate settings in Iran are widely exposed in north and northeastern parts. Five stratigraphic columns were selected in the north eastern Iran. Their thickness ranges from 330 to 500 m. The various diagenetic processes identified include, micritization, cementation, compaction (physical and chemical), dissolution, neomorphism, pyritization, hematitization, silicification and dolomitization, which affected these carbonates. Elemental and stable isotopes analysis indicated that these deposits have undergone both meteoric and burial diagenesis in a relatively open system with moderate water-rock interaction. The positive trend between trace elements and oxygen isotope depletion also support these burial conditions. Lighter δ^l8O values of the dolomite samples may be related to an increase in temperature during the burial, which correspond to coarser euhedral crystals. Relatively higher δ¹⁸O values in finer dolomite crystals indicate their formation at lower burial depths relative to coarser crystals. Petrographic evidences such as coarse euhedral crystals with bright and dull zonation prove this interpretation. Chert nodules also have lighter ¹⁸O values relative to carbonate host rock, thus indicating the influence of burial diagenetic processes in their formation. The average environmental palaeotemperature was estimated to be 26°C on the basis of oxygen isotope values of less altered lime-mudstones.     

Landslide susceptibility mapping at Vaz Watershed (Iran) using an artificial neural network model: a comparison between multilayer perceptron (MLP) and radial basic function (RBF) algorithms

Landslide susceptibility and hazard assessments are the most important steps in landslide risk mapping. The main objective of this study was to investigate and compare the results of two artificial neural network (ANN) algorithms, i.e., multilayer perceptron (MLP) and radial basic function (RBF) for spatial prediction of landslide susceptibility in Vaz Watershed, Iran. At first, landslide locations were identified by aerial photographs and field surveys, and a total of 136 landside locations were constructed from various sources. Then the landslide inventory map was randomly split into a training dataset 70 % (95 landslide locations) for training the ANN model and the remaining 30 % (41 landslides locations) was used for validation purpose. Nine landslide conditioning factors such as slope, slope aspect, altitude, land use, lithology, distance from rivers, distance from roads, distance from faults, and rainfall were constructed in geographical information system. In this study, both MLP and RBF algorithms were used in artificial neural network model. The results showed that MLP with Broyden–Fletcher–Goldfarb–Shanno learning algorithm is more efficient than RBF in landslide susceptibility mapping for the study area. Finally the landslide susceptibility maps were validated using the validation data (i.e., 30 % landslide location data that was not used during the model construction) using area under the curve (AUC) method. The success rate curve showed that the area under the curve for RBF and MLP was 0.9085 (90.85 %) and 0.9193 (91.93 %) accuracy, respectively. Similarly, the validation result showed that the area under the curve for MLP and RBF models were 0.881 (88.1 %) and 0.8724 (87.24 %), respectively. The results of this study showed that landslide susceptibility mapping in the Vaz Watershed of Iran using the ANN approach is viable and can be used for land use planning.     

A change-detection application on the evolution of Kahak playa (South Khorasan province, Iran)

Kahak salt playa in South Khorasan province of Iran, have special geomorphological characteristics by the presence of ephemeral saline lakes, wetlands, salt crusts, surface accumulations of salt and zones of patterned ground. Salt crusts in the soil surface are unique in the region and have laminated horizons in the playa soil. Soil-surface salt accumulations are dominated by NaCl and gypsum. It has been found that distribution of chemical soluble is not uniform across the playa landscape, and this result influences on the variety form of patterned ground. In this study, the percent changes in some of the chemical elements such as NaCl, gypsum and also brine extent have been calculated in the playa. Indicating changes in Kahak salt playa is the main aim of this study by using remote sensing and GIS techniques. In this paper, techniques such as spectral un-mixing, maximum likelihood classification, band rationing, fuzzy classification and correlation relationships are discussed. This contribution presents modeling of temporal and spatial changes of salinity and playa developing using combined approaches that incorporate different data-fusion and data-integration techniques for two periods of date. Furthermore, percent changes in the surface-patterned ground of the playa have been calculated using texture and pattern analysis of the PCA1. Results have revealed that, in the playa developing, chemical materials such as sodium, NaCl, gypsum and also brine extent are positively correlated with each other and the most increased changes are related to gypsum and the most decreased changes are related to the NaCl. Also changes in the amount of agricultural area in the playa-lakes margin, show low effects in the desertification process.     

Comparison of two-dimensional flood propagation models: SRH-2D and Hydro_AS-2D

This article presents a comparison between two two-dimensional finite volume flood propagation models: SRH-2D and Hydro_AS-2D. The models are compared using an experimental dam-break test case provided by Soares-Frazão (J Hydraul Res, 2007. doi: 10.1080/00221686.2007.9521829). Four progressively refined meshes are used, and both models react adequately to mesh and time step refinement. Hydro_AS-2D shows some unphysical oscillations with the finest mesh and a certain loss of accuracy. For that test case, Hydro_AS-2D is more accurate for all meshes and generally faster than SRH-2D. Hydro_AS-2D reacts well to automatic calibration with PEST, whereas SRH-2D has some difficulties in retrieving the suggested Manning’s roughness coefficient.     

Evaluating the impact of management scenarios and land use changes on annual surface runoff and sediment yield using the GeoWEPP: a case study from the Lighvanchai watershed,Iran

This study was undertaken to evaluate land use change impact and management scenarios on annual average surface runoff (SR) and sediment yield (SY) using the GeoWEPP tool in the Lighvanchai watershed (located in northwestern Iran). Following a sensitivity analysis, the WEPP model was calibrated (2005–2007) and validated (2008–2010) against monthly observed SY and SR. The coefficient of determination (R ²), Nash–Sutcliffe efficiency (NSE), mean bias error (MBE), and root-mean-square error (RMSE) were applied to quantitatively evaluate the WEPP model. The results indicate a satisfactory model performance with R ² > 0.80 and NSE > 0.60. Therefore, the model for current land use (scenario 1) was run for a 30-year time period (1982–2011). The annual average of SR and sediment load were predicted as 93,584 m³/year and 4340 ton/year, respectively. To reduce the annual average surface runoff and sediment yield at the watershed scale, the second scenario (alfalfa cultivation with suitable tillage) and the third scenario (grassland development) as two management scenarios of land use changes were defined by identifying the critical hillslopes. The rate of SR and sediment load in the second scenario were 42,096 m³/year and 429 ton/year, respectively. For the third scenario, the model predictions were 30,239 m³/year and 226 ton/year, respectively. Compared to the first scenario, the reduction rates in annual average of sediment load were about 90 and 94%, respectively. Moreover, for the second and third management scenarios, the reduction rates in annual average of SR were about 55 and 67%, respectively.     

A new developed approach for the prediction of ground vibration using a hybrid PSO-optimized ANFIS-based model

Ground vibration is one of the common environmental effects of blasting operation in mining industry, and it may cause damage to the nearby structures and the surrounding residents. So, precise estimation of blast-produced ground vibration is necessary to identify blast-safety area and also to minimize environmental effects. In this research, a hybrid of adaptive neuro-fuzzy inference system (ANFIS) optimized by particle swarm optimization (PSO) was proposed to predict blast-produced ground vibration in Pengerang granite quarry, Malaysia. For this goal, 81 blasting were investigated, and the values of peak particle velocity, distance from the blast-face and maximum charge per delay were precisely measured. To demonstrate the performance of the hybrid PSO–ANFIS, ANFIS, and United States Bureau of Mines empirical models were also developed. Comparison of the predictive models was demonstrated that the PSO–ANFIS model [with root-mean-square error (RMSE) 0.48 and coefficient of determination (R ²) of 0.984] performed better than the ANFIS with RMSE of?1.61 and R ² of 0.965. The mentioned results prove the superiority of the newly developed PSO–ANFIS model in estimating blast-produced ground vibrations.     

Automated classification of sloan digital sky survey (SDSS) stellar spectra using artificial neural networks

Automated techniques have been developed to automate the process of classification of objects or their analysis. The large datasets provided by upcoming spectroscopic surveys with dedicated telescopes urges scientists to use these automated techniques for analysis of such large datasets which are now available to the community. Sloan Digital Sky Survey (SDSS) is one of such surveys releasing massive datasets. We use Probabilistic Neural Network (PNN) for automatic classification of about 5000 SDSS spectra into 158 spectral type of a reference library ranging from O type to M type stars.     

Collapse capacity of soil‐structure systems under pulse‐like earthquakes

In this paper, a comprehensive study is carried out to examine the possibility of dynamic instability produced in soil‐structure systems using an ensemble of 50 pulse‐like records. A number of structural models with various vibration periods varying from 0.1 to 2 s are used in this study. The superstructure is simulated as a non‐linear SDOF oscillator with a two‐segment backbone curve having negative post‐yield stiffness. The soil is idealized based on the cone model concept widely used for practical purposes. The results of this investigation demonstrate that as the pulse period increases, the collapse relative lateral strength ratio decreases and probability of dynamic instability enhances. Moreover, soil flexibility makes the system dynamically more unstable, and as the non‐dimensional frequency increases, the collapse relative lateral strength ratio highly reduces. Additionally, the aspect ratio has insignificant effects on the collapse relative lateral strength ratio. Furthermore, comparison of the collapse relative lateral strength ratios resulting from pulse‐like motions with those obtained from studies under non‐pulse‐like motions (Miranda and Akkar; FEMA 440) for fixed‐base conditions shows that high‐velocity pulses exacerbate the dynamic instability problem and decrease the collapse relative lateral strength ratio. Copyright © 2014 John Wiley & Sons, Ltd.