JOURNAL OF ENGINEERING GEOLOGY
Year:2018 | Volume:12 | Issue:1 |Papers Count:8

Introduction: Dimension stones market is considered as an important and profitable sector of mineral deposit business due to their share in national economic performance. There exist a number of technical reports highlighting a lack of rock quality control in the sequence of quarrying and dimension stones production procedures, which has lowered the production efficiency and consequently the profitability of this strategic mineral industry in Iran. The quality of dimension stones depends on several factors which fractures, joints, voids and fine beddings are the most important factors that down-grade the quality. Therefore, foremost the quality and desirability of the building stone must be precisely determined by sampling, compressive strength testing and preparing microscopic sections. All of the mentioned evaluation methods are destructive. Moreover, sampling and performing multiple tests on all parts of a quarry or on all quarried stone blocks, is not possible. Detection of fractures hidden into the dimension stone blocks is achievable using fast, low-cost, accurate and non-destructive ground-penetrating radar (GPR) method. GPR is a high-resolution geophysical method which uses electromagnetic waves with high-frequency in order to map structures and detect buried objects in subsurface without coring or any destruction of the medium.Materials and methods: In current research, GPR method has been applied to evaluate the quality of quarried travertine blocks at Haji-Abad quarry complex in Mahallat district, Markazi province, before starting any processing operation. To achieve this goal, the 2-D GPR responses of synthetic models resembling cubic dimension stone blocks containing fine layering and discontinuities, were primarily simulated using a modified 2-D finite-difference forward modeling program in the frequency-domain coded in MATLAB. Among the variety of available numerical methods, the finite-difference time-domain (FDTD) method has paid more attention due to having the simple understanding of the concepts, flexibility, simulation and modeling of complex environments and the acceptability of its responses in the applied cases. In this research, the simulation has been implemented for both calcareous and dolomitic rocks (including travertine and marbles) and granites. In the study area, the GPR data acquisition was carried out using a GPR system equipped with shielded 250 MHz central frequency antenna, 0.5 m antenna distance and 2 cm sampling intervals by monostatic common-offset reflection profiling method. In order to process, analyze and interpretation of data, Ground Vision and Radexplorer software were employed. The most important pre-processing and processing operations applied to the data to provide the final sections, comprising time-zero correction, dewowing (removing very low frequency components from the data), DC shift removal, Butterworth filtering, running average, background removal and types of amplitude gain.Results and Conclusion: The results of the forward modeling show that the GPR response of fine beddings interfaces and major discontinuities hidden in the volume of dimension stone blocks are clearly detectable. Interpretation of the actual radargrams taken from a real GPR case study (Haji-Abad quarry complex) after employing various B-scan pre-processing and filtering procedures, indicates that GPR method is highly capable to detect fine beddings and discontinuities in order to evaluate the quality of dimension stone before starting any quarrying process. Validation of the obtained results of the present research was carried out on one of the blocks with a predicted large oblique joint while the existence of the large joint was proven under the cutting saw in the stone processing plant. However, it should be noted that due to the existence of inherent heterogeneity encompassing fine beddings, in addition to noises from different sources and their associated multiple reflections in real radargrams, the response of shallow major discontinuities may mask the response of minor ones located underneath or deeper, so as a result may not be detectable with routing GPR radargrams.

Tunneling in soft grounds causes to changes in displacements and subsequently in-situ stresses around ground. These displacements may damage structural assets. Thus, estimating the magnitude and shape of settlement curve is necessary. There are several empirical and analytical methods for predicting settlement. For example, Peck’s empirical method is well known method for predicting settlement due to tunneling. Tunneling process is done by imposing volume loss in tunnel. Then, soil displacement is measured by using image processing technique and that data is fitted to Gaussian curve. By conducting tests in loose and dense sands, it is concluded that by increasing relative density of the soil, the magnitude of settlement decreases and the settlement trough width will be increased. Also soil volume loss is not the same as the tunnel volume loss.Introduction: Many researchers investigated settlement due to tunneling but there is a lack of research about the effect of relative density on settlement. Marshall et al. (2012) by conducting centrifuge tests in high density sandy soil, showed that settlement trough is affected by tunnel size, tunnel depth and tunnel volume loss. Zhou et al. (2014) by performing several tests in loose, medium and dense sand, examined the effect of relative density on settlement and showed that by decreasing the relative density the magnitude of settlement increases and settlement trough width will be decreased. In this paper by using 1g physical modeling (Figure 1) which is designed in Sahand University of Technology, the effect of relative density on settlement has been studied.Material and methods: Simulation of tunnel volume loss is carried out by using two different diameter tubes as a shield and lining (Figure 2), while pulling out the larger tube volume loss is imposed. Also by changing tube diameter different volume losses have been applied. Measuring of soil displacements is achieved by image processing technique. For this purpose, different photos are taken from the whole process of the test by digital camera and by using Geo PIV, settlement of ground is determined.Results and discussions: Experiments were conducted in loose and dense silica sands and the measured data have been fitted to Gaussian curve. The result showed that Peck equation fitted well to surface and sub-surface settlement data. As shown in Figures 3 and 4, contour of displacement curve versus normalized tunnel depth and distance versus normalized tunnel diameter indicate that in dense sands most of the displacement occurred in the region which placed in distance of 1.25 times tunnel diameter and in loose sands in the region of 0.6 times tunnel diameter. Thus, settlement trough width in loose sands is narrower. Also by measuring soil volume loss in loose and dense sands at different levels (Figure5) it is concluded that in loose sands due to less dilation, more volume loss is transferred to higher levels.Conclusion: The following main conclusion can be drawn: 1. Gaussian curve predicts well surface and subsurface transverse settlements but selection of its parameters requires more accuracy that may result in inaccurate prediction.2. Settlement curve in loose sands is narrower than dense sands.3. Displacement and soil volume loss in loose sand are more than dense sand.

Introduction: The effect of surface geology on seismic movement is known and acceptable and this effects can consider important factor in movement resulting from earthquake. studying intensity and dispersal of recent decade earthquake destruction indicated importance of construction effects and surface geology conditions more than ever. From view point of engineering, earthquake importance is in light of effects that these earthquakes is created in construct such as dams, powerhouses, bridges, residential areas and industrial installations that in most cases, this constructs are building not only on rack mass surface but on earth surface, e.g. alluvial layers placed on bed stone. The effect of soil layers on earthquake waves is result of complex processes that this effect can exist as dynamic support under stability soil conditions that is called as intensification from it.Material and methods: There are multiple methods in order to determining effect of construct and affecting in on earth potent movement features, that among them are covered less-cost numeral methods and more site output and beacuse of reason are using from these methods in order to analyzing respond to earthquake vibrations. In this paper try to using data resulting from drining 5 boreholes on Tabas city construction are studying the effect of and also comparing numeral methods of analyzing building such as equivalent linear and non-linear analysis for earthquake return periods of 75, 475, 2475 using NERA and EERA softwares.Results: Taken together reinforcement rate and also maximum velocity in earth surface can explain that Dehshak region and Tabas center areas include more intensification conditions. On the other hand, south zone of Sarasyab sector and then Imamzade area include higher solidity and least intensification. Based on done studies are suggested to guided urban development programm more toward Hossein – ebne - Mousakazem Emamzadeh in order to exert from more suitable buildings. Also, regarding to EERA high-leval evalution and non-linear soil bahavior for earthquake with 2475 high return period is used from NERA software for analyzing construction effect to obtain maxium more realistic surface velocity.

Introduction: The presence of potentially toxic elements in the environment and especially in soil has been one of the greatest concerns due to their health implications. Potentially toxic elements from anthropogenic sources tend to be more mobile than those from lithogenic or pedogenic sources. Generally, the distribution of potentially toxic elements is influenced by the nature of parent materials, climatic conditions, and their relative mobility depending on soil parameters, such as mineralogy, texture and class of soil. In the inhabited, and industrial areas, vicinity to the un-engineered landfills, excess accumulation of toxic elements in surface soils can directly threaten wellbeing of exposed inhabitants via ingestion, inhalation and dermal contact routes. A few studies conducted on risk assessment of potentially toxic elements in soils of Kermanshah province, west of Iran. Soil in the study area is susceptible to contamination by anthropogenic activities in the form of industrial wastewater, agricultural activities, solid waste, runoff, atmospheric deposition and especially un-engineered landfills. The presence of toxic elements in soil around of un-engineered landfills without proper consideration to the environmental protection measures, will certainly lead to a significant environmental hazard in Kermanshah province. Therefore, the main purposes of this study are to evaluate the contamination levels, health risk assessment, and source identification of As, Cd, Cr, Cu, Ni, Pb and Zn in the Gasre Shirin, Gilane Gharb, Paveh, Javanrood, Eslamshahr, Ravansar, Kermanshah and Sanghar un-engineered landfills.Material and methods: A total of 30 topsoil samples were collected (0-20 cm depth) from the eight un-engineered landfills of the Kermanshah province. In order to achieve a representative sample, composite samples were prepared by mixing the four subsamples taken at each corners of 2×2 m square cell because composite sampling yields homogenized samples for analyses. The subsamples were mixed and a final sample of 1 kg was taken by repeated coning and quartering. To determine background concentration of heavy metals, eight soil samples were collected from areas far from known sources of contamination (40-60 cm depth). The collected samples were immediately stored in polyethylene bags and air-dried in the laboratory at room temperature. Then, samples passed through a 2mm stainless steel sieve. The<2mm fraction was ground in an agate mortar and pestle and passed through a 63 micron sieve. In order to determine the concentration of As, Cd, Cr, Cu, Ni, Pb and Zn complete dissolution of soil samples (approximately 1 g of each) was carried out using a mixture of HF, HNO3, HClO4 and H2O2 in a Teflon beaker on sand bath at atmospheric pressure. The concentrations of the selected elements were measured by an accredited commercial laboratory (Zar Azma Laboratory, Iran) using ICP-MS methods. Data quality was ensured through the use of internal duplicates, blanks, and HRM. The precision and accuracy of measurements are 95% and+/-5% respectively. The assessment of soil contamination was carried out using geochemical indices including contamination factor (CF), modified degree of contamination (mCd) and enrichment factor (EF). The methodology used for the health risk assessment was based on the guidelines and Exposure Factors Handbook of US Environmental Protection Agency. The average daily doses (ADDs) of heavy metals received through ingestion, inhalation, and dermal contact for both adults and children were calculated. In this study, hazard quotient (HQ), hazard index (HI) and carcinogenic risk (RI) methods were used to estimate non-carcinogenic and carcinogenic effects of heavy metals. The HQ was calculated by subdividing ADD of a heavy metal to its reference dose (RfD) for the same exposure pathway (s). If the ADD exceeds the RfD, HQ>1, it is likely that there will be adverse health effects, whereas if the ADD is less than the RfD, HQ<1, it is considered that there will be no adverse health effects. A hazard index (HI), the sum of HQs, which means the total risk of non- carcinogenic element via three exposure pathways for single element of<1 indicates no adverse health effects, while HI values>1 show possible adverse health effects.Carcinogenic risk is regarded as the probability of an individual developing any type of cancer in the whole life time due to exposure to carcinogenic hazards and was calculated for As and Cd as follows: (1) The value of SF represents the probability of developing cancer per unit exposure level of mg/kg day. The acceptable risk range for carcinogens is set to 10-6 to by the USEPA, so that RI values below 10-6 do not require further action, while risks greater than 10-4 are considered to be of concern and require additional action to reduce the exposure and resulting risk.Results and discussion: The soil pH ranges from 7.01 to 8.06, with an average value of 7.51 suggesting neutral conditions. Organic carbon (OC) contents of soil samples ranged from 0.06% to 4.91% (average 1.59%). In this study, based on the USDA textural triangle the main soil textures are loamy, clay loam and sandy loam, respectively. The average abundance order of selected elements content is: Zn>Ni>Pb>Cr>Cu>As>Cd. Comparison of mean concentration of the potentially toxic elements in the soil samples with mean worldwide values reveals higher Zn, Pb and Ni contents in this area. The results of contamination factor indicate very high contamination for Cd, Cu, Pb and Zn. Modified Degree of Contamination (mCd) calculated based on background values proves very high degrees of contamination for selected trace elements in Gasre Shirin and Eslamshahr landfills soil samples The results of enrichment factor evaluation similarity to contamination factor indicate that Cd, Cr, Pb, Cu and Zn have more influence from anthropogenic sources. The maximum EF of Pb, Zn and Cd and Cu is 346.7, 124 and 51.9 respectively, which means very high enrichment in Ghasre Shirin landfill soil samples. Exposure doses of 7 heavy metals in soil samples of un-enggenerd landfills for children and adults were calculated. The total exposure HQs calculated based on adults from ingestion, dermal contact, and inhalation for Cd, Cu, Ni, Zn, As and Pb was less than 1 (except Ghasreshirin landfill). The hazard quotient values based on the adult risk for Cr were greater than 1.0. The results show that HQ for Pb and As in children by dermal and ingestion pathway is exceeded 1.0 in soil samples of Paveh, Javanrood, Ravansar, Kermanshah and Sangher landfills and Ghasreshirin and Eslamshahr landfills, respectively.Conclusion: The concentration, pollution level, potential sources and health risk of potentially toxic elements in eight landfills top soil of Kermanshah province were investigated in this study. The following conclusions were drawn from this research.- Compared with the background values of As, Cd, Cr, Cu, Ni, Pb and Zn in soils of Kermanshah Province, landfills soil have elevated metal concentrations as a whole.- According to high contamination level and health risk of some studied potentially toxic elements, and also due to the proximity of contamination sources to residential district of the study area, more attention should be paid to manage and reduce contamination.- These results provide basic information of toxic elements pollution control and environment management in the area.

In this research seismic, electrical sounding and geoelectrical tomography methods are used to assess the distribution of strength of foundations, the earth's natural period (T0), layering conditions and petrophysical characteristics of the underlying soil. The bridge is built on alluvial sediments of the Haraz river in Mazandaran province. The bridge consists of two lateral and three intermediate bases. The Haraz river passes through the eastern and adjacent intermediate base. This research indicates that: 1- based on seismic studies, the average shear wave velocity to a depth of 30 meters at the eastern base of the bridge is significantly more than that of the western base. Therefore, the stiffness and loading capability in both bases of the bridge are different, 2- geoelectrical sounding shows that the eastern side of the bridge, most likely composed of silt and clay and there is a possibility of subsidence at the east side of the bridge, 3- electrical resistivity tomography maps in E-W section is asymmetric and shows lateral changes of soil structures along bridge. In other words, distribution of stress on eastern and middle basis of the bridge with considering mentioned reasons is stirred with probably subsidence in the last few decades utilization and appearing of defects in the body of the bridge.Introduction: Many factors such as floods, earthquakes, hurricanes, tsunamis, improper exploitation conditions and other factors have threatened historic buildings and urban infrastructure. Iran is one of the active seismic areas of the world and unfortunately many of the historical monuments have been damaged or completely destroyed during different earthquakes. Bam citadel, the largest mud structure in the world, is an example of a cultural heritage which was completely destroyed in deadly earthquake of January 2003. In many large cities of the world such as Tehran, more than hundred bridges have been constructed to solve the traffic jam. Insecure and improper utilization may threat the strength of bridges and decrease their longevity. Today, the soil behavior under loading cycles and dynamic condition is very important in urban active seismic areas. In most cases the physical properties of soil are obtained by laboratory tests and in situ methods including refraction seismic method, reflection seismic method, SASW method, well logging, cross-hole and also geo-electrical and other geophysical methods. The relation between seismic wave velocities and stress in soils and mineral materials are to the interest of seismologist and seismic specialists. Today in exploration seismic the relation between stress and velocity of seismic waves can be used in AVO analysis and also to predicting and monitoring the hydrocarbon and thermal fields of reservoirs in 4D exploration seismic. There are many researches in this subject and established some experimental relationships between stress and elastic modulus of rocks with wave velocities. The aim of this research was to identify the seismic characteristics and geological conditions of soil beneath foundations of bridge in north of Iran mainly for investigating possibilities for strengthening the city historical oldest bridge. In this study we used simultaneously refraction seismic, electrical sounding and geoelectrical tomography methods. Seismic method used to estimate the stiffness of soil, average shear wave velocity of upper 30 m and determination of site classes. Electrical sounding and geoelectrical tomography have used to identify subsurface geology, differentiation and identifying electrical resistivity of soil profile and distribution of electrical resistivity in tomography section for understanding distribution of stress in soil. The bridge is built on alluvial sediments of the Haraz River. Mazandaran-Khazar fault is located 7 km south of study area in east-west direction. The bridge consists of two lateral and three intermediate bases. The Haraz River passes through the eastern and adjacent intermediate base.Field surveying: Several seismic profiles surveyed in this are and five of them used in current research. Linear array are employed with P-wave and S-wave. Distance between geophones is 2 m respectively. The lengths of profiles were different due to space constrains. Length of profiles considering offsets was up to 86 m. Impulse impact is transmitted to the soil by sledge hammer equipped with a trigger element. For P- wave profiles, vertical hit on steel plate and for S-eave profiles, horizontal hit on special I-beam steel were used. In order to improve the signal to noise ratio (S/N), an average of ten hammer blows were stacked for each record. Length of records is one second with sampling interval one millisecond. The first arrival times of refraction seismic data were interpreted with considering characteristic of first arrivals in layered condition and continuous medium. The results of average shear wave velocities to the depth of 30 m in the five profiles (S1 to S5) were 774 m/s, 629 m/s, 540 m/s, 581m/s, and 563 m/s consequently. The average shear wave velocity in the upper 30 m was globally adopted after the National Earthquake Hazard Reduction Program (NEHPR) classification in the USA. Profile S1 is located near the western base of the bridge, profile S3 near the eastern base of the bridge, profiles S2 and S6 at the middle of bridge and profile S5 about 200 m of eastern base. The average sheer wave velocity in the upper 30 m of soil in western base (Vs30=774) is more than eastern base (Vs30=540). According to the average shear wave velocities, the type of underlying soil in western base falls to B class (760<<1500) and in eastern base falls to C class (360<<760). It means that the natural periods of soil and reflection coefficient of bridge in both sides are different. Vertical electrical sounding is another geophysical method that used to separate the layers, thicknesses and electrical resistivities of underlying sediments at the eastern base of the bridge. The resistivity measurements carried out by injecting electrical current into the ground through the two current electrodes, and measuring the resulting voltage difference at two potential electrodes. We used symmetrical four electrode schlumberger array. The type of experimental sounding curve is AH. It means that soil profile under the eastern base of the bridge consists of 4 layers with interbedded low resistivity layer. Interpretation of geoelectrical curve shows that the first layer has a thickness of 4 m with resistivity of 800 ohm-m. Surface evidence indicates that this layer is composition of sand, gravel and conglomerate. The second layer has a thickness of 16 m with the resistivity of 334 ohm-m. This layer most probably is composition of saturated sand and conglomerate. The third layer has a thickness of 14 m with resistivity of 43 ohm-m. Low electrical resistivity shows that the grain size is fine and matches with silt and clay. The last layer as a basement starts from the depth of 34 m with electrical resistivity of more than 1000 ohm-m. Geoelectrical tomography is another method that used to determine the lateral changes of electrical resistivity and identifying the pattern of distribution of stress in underlying soil at the middle of the bridge. Geoelectrical tomography profiles were in east-west direction. The distance between measuring points was 1 m. Electrical resistivity of sedimentary rocks and soils generally depends on porosity, mineral type, depth, stress, moisture content, structure and texture and temperature. Variation of electrical resistivity verses depth shows that the distribution of electrical resistivity of the subsurface material is not uniform and increase with depth. It also shows that the distribution of electrical resistivity in soil under the base is asymmetric in E-W direction.Conclusions and result: Integrated geophysical studies were conducted in three stages with three different methods. The following conclusions are extracted based on study: According to seismic data the average shear wave velocity at the western side of the bridge (m/s, m/s) is more than the East (m/s, m/s) and middle of the bridge (m/s, m/s). The high velocity of S waves in the western side of the bridge shows that the stiffness of soil materials in the west side of the bridge is more than of the east side. According to NEHPR site classes, the type of underlying soil in western base falls to B class and in eastern base falls to C class. It means that the natural periods of soil and reflection coefficient of bridge in both sides are different. In other word the response of bridge respect to vibration of soil generating by traffic in both sides is different. The Haraz River passes through the eastern and adjacent intermediate base about 4 m under ground level of the middle bases. Geoelectrical sounding show that the eastern side of the bridge most likely composed of silt and clay. Therefore there is a possibility of subsidence at the east side of the bridge. This bridge connects the eastern side of the river to the western side and asphalted road passes through western base and intermediate base. It means that the vehicle traffics continuously compacts underlying soil in western base respect to eastern base. Electrical resistivity tomography map in E-W section is asymmetric and shows lateral changes of soil structures along bridge. In other words distribution of stress on eastern and middle basis of the bridge with considering mentioned reasons is stirred with probably subsidence in the last few decades of utilization and generation of lateral stress due to truck traffic impacts in eastern bases and underlying soil. The change of lateral or transverse stress changes the porosity of soil profile and change of porosity changes the electrical resistivity. Existing cracks in the beam of studied bridge agrees with the available results of research.

Drilling and cutting stones as types of the engineering operations have encountered a lot of extensive and determining applications in different technical and engineering aspects of the mining. Estimating the drillability and cutability of stones by using drilling equipment and diamond wire saw have important roles in estimating the expenses and also designing mines. In this article some samples of carbonate ornamental stones from different mines in Iran have been studied in order to estimate and predict the drilling and also cutability rate. In order to evaluate the effect of the textural specifications on the rate of drilling and cutability, first a picture was provided from the thin microscopic surface of every stone sample and then the area, perimeter, diameter the longest diagonal and the shortest diagonal of the grains in the sections were determined and the other textural specifications were also determined through using mathematical relations and equations. After that the relationship between the abovementioned parameters with the drilling and cutting rate were determined by using univariate fitting. And finally to achieve more correlation coefficient multivariate fitting was applied for the data. Among the textural specifications affecting the drilling rate textural coefficient, the diameter of the grain, dequi, the ratio of the grain condition and the index of grain size homogeneity had a significant relationship with the drillability rate and also among those affecting the cutting rate, textural coefficient, the diameter of the grain, dequi, density, shape factor, index of interlocking, and the index of grain size homogeneity had significant relationships with the cutting rate and at the end the final equation to predicate the drillability and cutability was produced for these parameters.

Introduction: The prediction of landslide occurrence in a region is very important in reducing the risks and damages caused by this.landslide as a natural disaster in Iran caused a lot of life and financial losses to Iran annually. According to the National Committee on Natural Disaster Reduction of the Ministry of the Interior in 1994, the share of annual damage caused by mass movements in Iran is estimated at 500 billion rials. In the meantime Kurdistan province is the third province in terms of landslide phenomenon after Mazandaran and Golestan. If considering the area is at a higher level. The city of Bijar in this province has a high potential for a wide range of landslides with a combination of mainly mountain topographical factors, lithologic conditions and positioning between two major faults in the region. In this research, using quantitative methods and models on the quantitative factors of this phenomenon based on the level of information given by past mass movements and influential factors, focusing on artificial neural network method, susceptibility zones were determined by determining the possible risk level. Knowing such natural events requires proper management of the risks posed by them. On the other hand, artificial neural network as a quantitative model is capable of learning, generalization and decision making, and less need to analyze the accuracy of data in comparison to statistical methods. Map of the susceptibility of the areas to the landslide is an important tool for landuse planning. However, there are many issues in the formation of this phenomenon, which, due to the complexity of the natural processes arising from the relationship between the outcome (dependent variable) and the factors (independent variables), puts into question the general zoning of such areas. Methodology: Bijar is located in the northeastern part of Kurdistan province, along the longitude of 47 ' 29° to 47° 47' east, in latitude 35° 35 ' to 35' 59 °north. In recent years, the development of the Geographic Information System (GIS) and spatial analysis techniques have improved the risk of indirect zoning. In this regard, artificial neural networks can cover a significant part of these needs.Implementing the neural network model requires learning data. Without learning data, it's virtually impossible to make neural networks. In this paper, learning data shows the occurrence of landslides which have geographical coordinates and were obtained from the Kurdistan Province Natural Resources Organization. In general, learning data in GIS and remote sensing can include data or raster, which in this paper is a point phenomenon and has 144 cases. However, because of the large extent of the study area and the low number of them, as well as the lack of risk of any landslide zone (from low to very high), the points should be classified as well, and, in terms of numbers, Acceptance. Also, the number of points of relative value In terms of numbers, the conditions are the Normal and the same (that is, the appropriate geographical distribution and distribution in each class) would be more accurate; thus, to create a classifiable spectrum of the AHP Was used. It should be noted that all the maps were standardized in the format and format of the Raster in a matrix (698 rows in 897 columns) identical with a size of 30 * 30 meters. This means that each map has 626, 106 pixels of varying value and somewhat similar. In addition, the AHP model was used to categorize the studied area from very desirable (hazardous) to very undesirable (very dangerous) areas. Also, 33 points were added to the learning data on different levels of the map derived from the AHP model. But in order to verify accurately the model, only landslide occurrences were considered. In order to find out the factors of landslide in Bijar, a map of slope, Aspect, elevation, distance from the fault, distance from the road, distance from the river, Drainage density, lithology and land use using ArcGIS software were prepared and digitized. After compiling and categorizing these variables, at first, each of the effective criteria in the field was divided into six sub-criteria (land suitability for landslide) from very desirable to very undesirable conditions. The present study utilizes the technique of multi-layer propspert neural networks using post-propagation algorithm (BP). In addition to correcting and editing the layers, the neural network model was implemented using the classification method and applying two types of functions (linear and sigmoid). Then, using the test-error method, the study of the magnitude of the error and the period of the repetition and the change in the number of hidden layers and weights, both functions were performed. Finally, the sigmoid function, which yielded a better result, was selected as the proposed and final function.Order to verify the (accuracy) of the map taken with the existing landslide zones, the final map of the neural network model was again transferred to the ArcGIS software. Finally, the available landscapes on the map resulted from the adaptive neural network model, which, by comparison, gave a percentage and amount Accuracy of each class was achieved.Result: The input layer were calculated to six classes based on the desirability of mass movements. This decision approach reduces the complexity of the network and improves its performance. For this purpose. The AHP method was used to define non-slip pixels and range classification. To implement this method, 9 variables discussed, were scaled up to the most suitable and un suitable range. The final weight of these variables was obtained by using the Thomas saati pair comparison (Table 4), the study area was divided into five categories according to the map for land suitability for landslide hazard. From each class, the 20-pixel from AHP model was selected for network learning in a completely randomized manner. The proposed model is an artificial neural network of MLP multi-layered perceptron with levenberg-marquardt learning algorithm. An early stopping method was used to improve network optimization. Several hidden layers were tested to find the best results. It should be noted that in the structure of all networks, at least the optimal design with the middle one is used, but in their structural composition they are also used with mid-duplex networks. In this paper, the use of tow mid-layers showed better results. In all Simulations have been made, the mean square error index, as a guide, indicates the network performance in learning the existing model. By changing the number of intermediate neurons and changing the weights as try and error, the most appropriate network model was obtained for the purpose. In this study, the structure of the network with 9 input layers, 2 hidden layers, 1500 repetitions in both functions was accepted as the final structure. The main structure of the neural network with two linear and sigmoid functions was prepared with acceptable error, and the study area was analyzed with a total area of 564 km2 with 9 input variables converted into raster data to 30 × 30 pixels. From 564 km2 based on the sigmoid function 61.17% and based on the linear function, 72.76% of the area is unsuitable and very unsuitable in the area where expose to high risk. In both networks, there were very few areas in both optimal and moderate classes (Figures 16 and 17), which indicate the high talent of the area for landslide as a threat. Then, ArcGIS software was used to evaluate the efficiency and accuracy of the model. For this purpose, the point of landslide and zoning maps were combined, compared and anlayzed. The results showed in the sigmoid function 75 items of Landslides were in a very unsuitable range, which included 61% of the total of region.Conclusion: In the linear function, approximately 69% of the landslides are in a very unsuitable range and the unsuitable results are about 57%, which results in the success of the model designed in the neural networks (MLP). In the end, the network with sigmoid function is negligibly better than the linear function network.The results show that Bijar and its functions are relatively prone to occurrence of landslides, so that nearly 60% of the city' s area is a high risk area with a high risk and only 2% is a low-risk region. The hazardous areas are mainly located around the city of Bijar especially southern and southeast. These areas correspond to high altitudes and maximum fault density and lime lithology with marl (Qom Formation). The model can be very challenging, because of innovative nature of the research, that means need more detailed and comprehensive studies.