Journal of Engineering Geology

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In this paper, using Mononobe & Okabe method, seismic force and its effects on thin masonry retaining wall inside structural frame (Masonry retaining infill) are presented. In this method, retaining wall has been assumed to be rigid and the prevailing failure mode is sliding of wall bed joint or wall rotation around its toe, whereas the prevailing failure mode of masonry retaining infill is usually flexural cracking in middle zone of wall under out of plane seismic force. In this case, the seismic force distribution is important. Accordingly in this paper, a distribution for seismic forces on masonry retaining infill has been proposed. Also with regard to out of plane behavior of masonry retaining infill in terms of strength and acceptance criteria aspect, failure in body of wall due to out of plane loads has been analyzed. Then, the desired seismic rehabilitation method in case of vulnerable masonry retaining infills has been presented and as a practical example, results of the proposed method with the results of numerical software have been controlled. Finally, according to various conditions predicted for masonry retaining infills, Seismic Retrofit solutions are presented for practical applications.

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The shape of slip surface of the wedge creating lateral thrust on rigid retaining walls plays an important role in the magnitude, distribution, and height of point of application of lateral thrust.  Considering the shape of slip surface as linear, circular, logarithmic spiral, or a combination of them has been used in the literature. In the Coulomb lateral earth pressure method, a linear distribution of soil pressure on retaining walls is tentatively assumed and thus the point of application of total thrust is placed at one third of the wall height from the wall bottom. However, some experimental studies have revealed non-linear distribution of lateral earth pressures and that the point of application of resultant thrust is placed upper than one third of the wall height. In the present study, a plasticity equation is used to determine the reaction of the stable soil on cohesionless backfill supported by a retaining wall using an empirical equation derived from experiments performed in the field by others. A new analytical solution for determining the total resultant thrust on the wall is introduced and the distribution of pressures and the point of application of total thrust are computed. The results have been compared with some analytical methods, experimental data, and also with available data reported from field, demonstrating the accuracy and capability of the developed method. The results show that the distribution of the active lateral earth pressure is nonlinear and the point of application of total thrust is located about 0.42H from the wall bottom (H=wall height). In addition, the application point of total thrust is nonlinear function of soil-soil, wall-backfill soil friction angels and the height of the wall

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Shear wave velocity (Vs) is a basic engineering soil property implemented in evaluating the soil shear modulus. Due to a few limitations, sometimes it is preferable to determine Vs indirectly by in situ tests, such as standard penetration test (SPT). However, inaccuracies in measurement or estimation of the influencing parameters have always been a major concern, and thus various statistical approaches have been proposed to subdue the effect of such inaccuracies in predictions of future events. In this article, an innovative approach based on robust optimization has been utilized to enumerate the effect of such uncertainties. In order to assess the merits of the proposed approach a database containing 326 data points of case histories from Adapazari, Turkey were gathered from renowned references. The identification technique used in this article is based on the robust counterpart of the least square problem which is a second order cone problem and is efficiently solved by interior point method. A definition of uncertainty based on frobenius norm of the data is introduced and examined against correlation coefficient of various correlation parameters and optimum values are determined. Finally the results of new correlation are compared with those utilizing a commonly used statistical method and the advantages and possibilities of the proposed correlation over the conventional method are highlighted

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Wave velocity and attenuation are among the most important attributes of stress waves that propagate through geomaterials. Utilizing these attributes, it is possible to acquire useful information about porous geomaterials such as soil and rock and also the fluids that saturate the pores of geomaterials. The key point in order to gain this information is to establish an accurate link between field measurements of wave attributes and physical properties of geomaterials’ skeleton and pore fluid. The pore fluids and their inhomogeneous distribution fluid are among factors that affect wave velocity and attenuation to a considerable extent. Patchy saturation of pores which occurs on the scale larger than grains size but smaller than wavelength is one of the reasons that causes inhomogeneity in pore fluid distribution. The influence of such inhomogeneity is studied in present paper. Two different attenuation mechanisms including relative movement of fluid with respect to solid phase and also attenuation caused by grain to grain contact are implemented to fully assess wave attenuation. It is observed that the former attenuation is more dominant at higher frequencies compared to the latter attenuation.

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Determining the precise shear strength parameters of the fine grained soils is always a difficult task. In order to conduct the shear strength tests and determine the mechanical parameters of the soil, achieving an untreated high quality sample is a problem with a high degree of importance. Therefore, during the recent decades many researchers have attempted to provide relations between strength parameters and soil physical characteristics in a specific structure and so to provide the possibility of estimating the strength parameters based on these characteristics. The aim of this research is to estimate the shear strength parameters of a wide region of fine grained alluvial soil located in southern Tehran, Iran. In this regard, the geotechnical data including physical and shear strength parameters of 294 boreholes were firstly collected from the site. Then, the obtained data were statistically and independently analyzed. Based on the results of analyzes, the soil geotechnical parameters were presented for various depths with an acceptable level of reliability. Moreover, they were considered as a basis for providing a nonlinear regression model to estimate the soil shear strength parameters and based on the index physical characteristics of the fine grained soil (water content and plasticity index). The developed model is capable to predict the soil drained shear strength parameters and also other similar soil properties with a very good accuracy

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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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In a perforated well, fluids enter the wellbore through arrays of perforation tunnels. These perforations are typically distributed in a helical pattern around the wellbore. Available numerical models to simulate production flow into cased-and-perforated vertical wells have complicated boundary conditions or suffer from high computational costs. This paper presents a simple and at the same time efficient finite element model to simulate flow around a well with helically symmetric perforations. In the proposed model, by taking advantage of the symmetry, only a thickness of perforated interval containing a single perforation tunnel needs to be meshed. Angular phasing between adjacent perforations is considered by applying periodic boundary conditions on the upper and lower boundaries of the representative reservoir thickness. These boundary conditions involve periodic-pressure and periodic-velocity parts. Unlike the periodic-pressure part, the method of imposing the periodic-velocity condition within a single-variable flow problem is rather vague. In this regard, it is proved that in the proposed model, periodic-velocity condition is automatically satisfied in a weak sense. The accuracy and the computational efficiency of the proposed model are verified through comparison with available models. The model results, in terms of skin factor, are compared with the common semi-analytical model as well, and good agreement is obtained. The proposed model can readily be used as a numerical tool to study inflow of wells with helically symmetric perforations.
 

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Introduction
The discussion of modeling the interaction of soil-pile groups due to a large number of parameters involved in is one of the complex topics and it has been one of the interests to researchers in recent years and has been dealt with in various ways. In recent years, the artificial neural network method has been used in many issues related to geotechnical engineering, including issues related to piles.. In this study, firstly it was tried to explain the importance of soil - structure interaction in calculating the dynamic response of bridges. Then, the effect of different effective parameters in calculating the interaction stiffness of the pile - soil group using artificial neural network was studied.  For this purpose, firstly, Sadr Bridge ( The intersection of Modarress and Kaveh Boulevard because the presence of tallest piers ) in the transverse direction, considering and without considering of the effect of soil - structure interaction was analyzed. The analysis was carried out in which the substructure soil was replaced with a set of springs and dashpots along the piles. Considering the fact that many factors are involved in determining the equivalent stiffness of springs, in the second stage, the effect of different factors on the stiffness of spring equations using artificial neural network was investigated. Finally, the artificial neural network method was used as a suitable method in order to estimate the equivalent stiffness values, the equivalent stiffness of the pile - soil group was introduced for different input values. equivalent stiffness of the substructure soil using the artificial neural network ,has not been used by researchers yet, so estimation of the optimal length and diameter of piles used in constructions and estimating the seismic performance of the bridge system after its implementation could be effective .
Material and methods
In this paper, spring-dashpot method is proposed to the non-uniform analysis of single-pier bridges which led to a 5-degree freedom model in the case of Sadr Bridge. This study also endeavors to investigate the SSI effect in dynamic analysis of bridges. This method is based on the traditional spring-dashpot method but in this method, non-linear stiffness is used along the piles, instead of linear stiffness and upgraded shape functions and coefficients are applied to make more precise mass, stiffness and damping matrices. Then the seismic responses of Sadr Bridge are compared in different conditions including or excluding the SSI effects. Considering the fact that in the present study to calculate the stiffness of the soil-pile group at depth, due to the effect of soil - structure interaction, the recommended method by API is used, the study of neural network analysis was used and the effect of different parameters used to determine the complexity of the soil-pile group system has been evaluated. The multi-layer feeder network, which has the most application in engineering issues, has an input layer, an output layer and one or more layers of hidden content, has been used for this purpose.  The best model of the neural network with a topology of 1-20-6 was provided using the hyperbolic sigmoid activation function, and the Levenberg Marquardt model and the training cycle 84, which had the least error mean square and the best regression coefficient. The effect of internal friction angle, soil density, pile diameter and the resistance per unit length has been evaluated with this method.
Results and discussion
[8] ارائه شده است صورت می پذیرد In this study, the importance of considering the effect of soil - structure interaction on the dynamic response of the Sadr Bridge was studied. Dynamic stiffness of the soil around the pile group was calculated based on the equivalent linear method and using the p-y springs. So, the effect of substructure soil was considered in dynamic analysis of the system . The artificial neural network was used to predict the stiffness of the soil - pile group, based on various input parameters and the stiffness sensitivity analysis of the calculated output values was conducted. In hard soils, the stiffness of the pile - soil group increases with increasing the diameter of the pile in the range of 1 to 1.5 m in diameter. However, in the range of 0.5 to 1 m in diameter, the diameter of the pile does not have much effect on the stiffness of the system and also stiffness decreases in the range of 1.5 to 2 m in diameter by increasing the pile diameter. Soil specific weight and angle of internal friction can change the system stiffness but the effect of the soil specific density is much greater on the stiffness of the soil-pile group system. Generally, the specific density in the range of 1000 to 2300 (kg/m³) will increase the stiffness of the system. In general, the ultimate strength of the soil among 100 to 550 (kN/m) affects the system stiffness. This effect within the ultimate strength between 100 and 220 (kN/m) causes increasing in the interaction stiffness value of the system and in the range of 220 to 550 (kN/m) causes reducing the stiffness of the system . The ultimate strength values ​​in a unit of length outside of the above range have little effect on the system interference stiffness. Despite the fact that the problem of calculating the soil - pile interaction stiffness is a direct solution, the use of the proposed neural network model can help in predicting optimal values ​​of diameter and length of the pile to achieve maximum soil- pile stiffness and especially for long bridges it will has a significant impact on reducing cost and seismic design of the bridge.
Conclusion
The results of this study are as follows:
The results showed that considering the interaction effect, although it increases the relative displacement of the deck, reduces the maximum base shear and moment. This suggests that considering the maximum base shear and moment in the interaction conditions may not lead to a seismic design for certainty, although closer to reality.
Artificial neural network is an efficient way and new method to predict the stiffness of the soil-pile group system based on different input values that have not been used yet. So that with the physical and mechanical properties of the soil as well as the geometric properties of the piles, it is possible to predict the interaction stiffness values with the proper precision.
According to the results and diagrams obtained from the neural network model, which are mainly sinusoidal, the optimal values ​​of the interaction stiffness can be obtained by obtaining the pile diameter, specific gravity, the internal soil friction soil to achieve optimal interaction strength. It is also possible for each site to estimate the depth of the piles in order to achieve optimal hardness. 
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In current paper the effects of surface unreinforced / reinforced sand layers coupled with and without single and group sand columns on the bearing capacity – settlement behavior of soft clays has been investigated. In this regard behavior of soft clay, clay + unreinforced / reinforced sand layer, clay + single / group sand piles and clay + unreinforced / reinforced sand layer + single / group piles samples has been assessed. Geogrid was adopted as the reinforcement, a circular plate 5cm in diameter as the loading surface and C.B.R. apparatus as the loading system. Results show that employing unreinforced / reinforced sand layers at a settlement ratio of 5% improves bearing capacity by 4 t0 7 times the soft clay. Coupling the surface unreinforced / reinforced sand layers with single / group sand piles further increases the bearing capacity by 7 to 9 times that of soft clay.

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