Journal of Geotechnical Geology
Volume:13 Issue: 2, Summer and Autumn 2017

The aim of this study is investigation of the swelling potential of the Bonab city’s soils and created the empirical relations between physicochemical properties of the clayey soils of Bonab with the swelling potential. The studied area is located about 130 km southwest of Tabriz in northwest of Iran. Geologically Bonab is covered by the Quaternary alluvials and recent soils which mostly is fine-grained contains different amounts of clay minerals where causes several events like swelling. In order to assessment of the swelling potential and characteristics of Bonab soils and establish relationships between these properties, the extensive field study especially on the agricultural fields (Bonab is the agricultural-based city), sampling and laboratory tests (classified in physical, chemical and mechanical) are conducted. For the reducing the investigation’s errors, the 20 different location is selected and sampling is taken as representative. The results of laboratory tests are classified based on United States Department of Agriculture (USDA) classification which indicated the most of Bonab soils are clay, clay loam and silty clay with the sandy clay and salt. Also, according to the swelling potential indirect assessment, these soils are located in medium to high swellability.

The blasting operations in open-pit mines are one of the most sensitive and complex mining methods which are defined under special circumstances and specific purposes. The suitable and optimal pattern selection where could be capable to covering the various environmental factors and affected on economic, technical, engineering and safety is the main goal of the operation. The genetic algorithm (GA) is the recommended method to utilizing the optimized pattern for the blasting pattern selection under the many effective parameters which is the variety of noteworthy detected on selected pattern from different mines. In this work the GA used to propose optimal blasting operation pattern by consideration of good coverage with field and geo-parametric in open-pit mine. For this purpose, the optimal design simulation of blasting pattern for open pit mines with one and two work-faces (for two standard 100×100 and 70×40m sides) by the Python programming language was conducted. Based on the results, this algorithm is quite successful in simulating the blasting pattern which it providing field decorations, the collapse (damage) rate and maximized exploitation (excavation).

Application of empirical rock-slope engineering classifications to the stability assessment of rock slopes is considered a basic rule that is obeyed by most of the geological engineers around the world. Some of these classification methods that are applied for special design and assessment in geo-structures such as: slope stability, mining activities, excavation, road/railway cutting, etc. are effectively used for reinforcement. The Q-slope classification system which is developed to describe is continuous rock-slope conditions is used for engineering judgment regarding slope stability. This work is focused on the Assalouyeh anticline’s south side which is located in the South Pars Zone (SPZ) in southern Iran. According to the results of the study on 55slopes in the SPZ and implementation of the Q-slope system, a major part of the slopes in terms of sustainability possess critical/uncertain conditions (25 cases), 10 slopes are considered as unstable and 20slopes are classified as stable.

Concrete is the most important material in geotechnical projects and constructions which that due to the cyclical loading and fatigues were always under failures. The fatigue is natural events were occurred in under cyclical loaded materials which causes very complex failures in under low stress and in elastic behavior. Although the concrete behavior and changes under axial loading are studied, but failure mechanism of fatigue and crack propagation on concrete (as the main factor to failure) is on obscurity. The investigation of crack propagation process from the beginning to failure under cyclic axial loading can be identified the fatigue mechanism. This study tired to monitoring and modeling the crack propagation mechanism under the cyclic uniaxial compressive strength (UCS ) in axial loading of concrete specimens which help to understands of crack propagation and developed path in the body. For this purpose, the concrete specimens are tested by UCS , take photos repetitively (in 5 loading-unloading cycles) and used the image-processing techniques (IPT) for crack detection, propagation and simulation of the failure in concrete. The simulation results shown the IPT is good performance to crack propagation detections and propagation process is perfectly simulated by IPT.

Solar energy as the most important source of renewable energy is an important alternative to fossil and non-renewable energies. This energy source, in addition to many benefits, is also very sensitive to environmental changes. Atmospheric changes can be expressed as a main factor in reducing the performance of Solar Cells. In this study, by using particle swarm optimization algorithm, the amount of solar energy dissipation in solar panels affected by atmospheric changes (the most important factor), including radiation, precipitation and wind, has been investigated. For this purpose, a comparative method with the base state has been used and the amount of difference between the two results in the solar cells is measured. In this regard, created solar cells in Maragheh city are considered as the basis for analysis. Based on the results of measurements and simulation by particle swarm optimization algorithm, the maximum atmospheric effect is related to the variations curve of the precipitation and then the variations curve of the radiation (shadow). Also, wind changes have had the least impact on reducing the performance of solar panels in the area.

Several regulations and manual have been presented for assessing the resources of rock aggregate for use of rock in breakwaters and shore protection structures. Although there are differences between these regulations, many experiments are required, which are often time-consuming, costly and sometimes difficult to implement in the early stages of the project. One of the fast, easy and low-cost methods is the Petrographic Number (PN) method, which according to rock thin sections, has suggestions for expressing the quality of rock materials. In this paper, the application of the PN method in some of the sources of rock aggregate in Iran has been addressed. For this purpose, 33 samples of carbonate rocks used in marine protection structures on the south coast and inland dams were collected. More than 350 experiments were carried out on these specimens. Also, in order to determine the PN, rock thin sections were prepared and the percentage of the components of the petrography including the type of allochem, porosity, cement and matrix, carbonate and non-carbonate minerals are obtained. Then, in order to evaluate the accuracy and efficiency of the PN method, correlation coefficient and comparison of the results of PN with the results of Iranian regulation has been used. Results have shown that a link between the PN with regulations and testing results. The results indicate a significant correlation between some of the engineering properties of samples with the PN. There is also a good correlation between the PN and the total score of the Iranian manual with R2=0.86. However, a single method cannot replace the set of experiments, but for the early stages of the aggregate resource study, it can provide a proper view of the quality of carbonate rock resources.

Investigating the possibility of detection of the concealed military structures is one of the complicated problems. This structures is created a significant conductivity in opposite of the earth which can be detected using electromagnetic method. Airborne electromagnetic method is considered as an important geophysical method that is used in the airborne survey. This method is characterized by high speed, extensive coverage, cost-effective and performance capabilities for implementation in sever topographical relief. In this paper, we used electromagnetic data to solve the problem. In order to analyze this problem, both forward and inverse problems are treated in this contribution. In the forward problem, with the assumption of the known size and position of the structure, secondary magnetic field signal is modeled. Then, using the modeled signals, some points about the detectability of the structures are discussed. Finally, both of the forward and inverse problems are implemented based on simulated data and some suggestions are made to decrease the probability of detectability of the underground military targets.

Pressuremeter is one of the most reliable in-situ tests in geotechnical engineering. Soil deformation modulus has been related empirically to the pressuremeter modulus (E ) obtained from the pressurevolume change curve from this test. In general, the pressuremeter test is time-consuming and costly that requires experienced operators. Various parameters might also affect the test results. With these limitations, it is necessary to introduce equations and models for indirect determination of the E. Artificial neural network (ANN) is a very useful technique for modeling complex relationships between input and output data sets. The ANN models often produce more accurate results compared with the linear regression methods. The main purpose of this research is to introduce a new ANN model for prediction of the EPM. The data used in this research is taken from 41 pressuremeter tests in soils of Tehran. In order to estimate EPM, parameters such as grain size distribution, depth of test, and moisture content are considered as input (independent) variables. The coefficient of determination (R2) for the training, validation, and test data sets were 0.736, 0.906, and 0.801, respectively. Acceptable correlations and errors of network predictions in comparison with the actual values of EPM show the accuracy and efficiency of the designed model. Sensitivity analysis revealed that the grain size distribution is the most effective parameter among the variables on the EPM.