Journal of Engineering Geology

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In this research, one of the new methods for seismic landslides hazard zonation (CAMEL) to predict the behavior of these types of landslides have been discussed.  It is also tried to eveluate this method with the proposed Mahdavifar method.  For achieving this result, the influence of  Sarein earthquake (1997), have been selected as a case study. In order to apply seismic hazard zonation, the methodology of Computing with Words (CW), an approach using fuzzy logic systems in which words are used in place of numbers for computing and reasoning is employed. First, the required information which includes disturbance distance, ground strength class, moisture content, shake intensity, slope angle, slope height, soil depth, terrain roughness, and vegetation have been collected using air photos, Landsat Satellite images, geological and topographic maps, and site investigation of the studied region. The data is digitized and weighted using Geological Information System (GIS). At the next step, the hazard rate and areal concentrations with respect to landslide types are calculated using CAMEL program and then, landslides hazard map produced by the above mentioned method is compared with landslides occurred as a result of Sarein earthquake. Finally, for evaluating on prediction of the earthquake-induced landslides, empirical comparison have been done between CAMEL and Mahdavifar methods.

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In the present study, landslides occurred during 1997 Sarein, Iran earthquake are discussed and evaluated. In order to meet the objectives, the Computing with Words (CW), an approach using fuzzy logic systems in which words are used in place of numbers for computing and reasoning is applied. Firstly, the necessary information which include disturbance distance, ground class, moisture, shaking intensity, slope angle, slope height, soil depth, terrain roughness, and land-use have been collected using air photos, LANDSAT satellite images, geological and topographic maps, and site investigation of the studied region. The data is digitized and weighted using ARCGIS software. At the next step, the hazard rate and predicted areal concentrations of landslides with respect to their types are calculated using CAMEL software (Miles & Keefer, 2007). CAMEL provides an integrated framework for modeling all types of earthquake-induced landslides using geographical information system(GIS). Finally, landslides hazard map is compared to landslides triggered by Sarein earthquake.

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Landslides are natural hazards that make a lot of economical and life losses every year. Landslide hazard zonation maps can help to reduce these damages. Taleghan watershed is one the susceptible basin to landslide that has been studied. In this paper, landslide hazard zonation of the study area is performed at a scale of 1:50,000. To achieve this aim, layers information such as landslides distribution, slope, aspect, geology (lithology), distance from the faults and distance from rivers using artificial neural network-based Radial Basis Function (RBF) and perceptron neural network (MLP), has been studied. Principal of RBF method is similar to perceptron neural network (MLP), which its ability somewhat has been identified up to now and there are several structural differences between these two neural networks. The final results showed that the maps obtained from both methods are acceptable but the MLP method has a higher accuracy than the RBF method.

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Carbonate soils are different from silicate soils respect to their origination and engineering behavior. Particles of these soils are mainly residual or debris of sea animals or plants with large amount of calcium carbonate. They also may be chemical sedimentation of calcium carbonate over other soil particles in specific region of seas and oceans. The most important characteristic of these soils is the crushability of their aggregates under loading which is mainly due their shape and also small voids inside of them.  Crushability and subsequent volume changes in carbonate soils have caused many engineering problems in some geotechnical structures such as ...../files/site1/files/0Extended_Abstract5.pdf

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The present work is conducted to investigate the effect of texture and carbonate content on internal friction angle of carbonate soils. Carbonate soils are majorly found in the bed of shallow waters and also offshores in tropical regions. Recently there is a huge construction projects including oil and gas extraction platform and facilities, harbors, refineries, huge bridges and other big construction projects in many offshore and onshore areas around the world. One of these area is located on southern part of Iran. We collected soil samples from different parts of northern coasts of Persian Gulf, then the following experiments were performed, carbonate content, three-dimensional grain size, angularity, relative density & direct shear. The results showed that the average of internal friction angle of carbonate soil is higher respect to known silicate sands. This angle is affected by effective grain size, grain angularity, and calcium carbonate content. Based on the experimental results of this study, one of the results was that the internal friction angle of carbonate soils decreases as their effective size of soil aggregates increases.