Assessment and Prediction of Liquefaction Potential Using Different Artificial Neural Network Models: A Case Study

Soil liquefaction as a transformation of granular material from solid to liquid state is a type of ground failure commonly associated with moderate to large earthquakes and refers to the loss of strength in saturated, cohesionless soils due to the build-up of pore water pressures and reduction of the effective stress during dynamic loading. In this paper, assessment and prediction of liquefaction potential of soils subjected to earthquake using two different artificial neural network models based on mechanical and geotechnical related parameters (model A) and earthquake related parameters (model B) have been proposed. In model A the depth, unit weight, SPT-N value, shear wave velocity, soil type and fine contents and in model B the depth, stress reduction factor, cyclic stress ratio, cyclic resistance ratio, pore pressure, total and effective vertical stress were considered as network inputs. Among the numerous tested models, the 6-4-4-2-1 structure correspond to model A and 7-5-4-6-1 for model B due to minimum network root mean square errors were selected as optimized network architecture models in this study. The performance of the network models were controlled approved and evaluated using several statistical criteria, regression analysis as well as detailed comparison with known accepted procedures. The results represented that the model A satisfied almost all the employed criteria and showed better performance than model B. The sensitivity analysis in this study showed that depth, shear wave velocity and SPT-N value for model A and cyclic resistance ratio, cyclic stress ratio and effective vertical stress for model B are the three most effective parameters on liquefaction potential analysis. Moreover, the calculated absolute error for model A represented better performance than model B. The reasonable agreement of network output in comparison with the results from previously accepted methods indicate satisfactory network performance for prediction of liquefaction potential analysis.     

A proposed geotechnical-based method for evaluation of liquefaction potential analysis subjected to earthquake provocations (case study: Korzan earth dam, Hamedan province, Iran)

During the earthquakes, a number of earth dams have had severe damages or suffered major displacements as a result of liquefaction, thus modeling by computer codes can provide a reliable tool to predict the response of the dam foundation against earthquakes. These modeling can be used in the design of new dams or safety assessments of existing ones. In this paper, on the basis of the field and laboratory tests and by combination of several software packages a seismic geotechnical-based analysis procedure is proposed and verified by comparison with computer model tests and field and laboratory experiences. Verification or validation of the analyses relies to the ability of the applied computer codes. By using the Silakhor earthquake (2006, M _s 6.1) as a basis in order to check the efficiency of the proposed framework, the procedure is applied to the Korzan earth dam of Iran which is located in Hamedan Province to analyze and estimate the liquefaction and safety factor. Design and development of a computer code by the authors which was named as the ??Abbas Converter?? with graphical user interface which operates as logic connecter function that can compute and model the soil profiles is the critical point of this study. The results confirmed and proved the ability of the generated computer code on the evaluation of soil behavior during earthquake excitations. Also, this code was able to facilitate this study better than previous ones have, taking over the encountered problem.     

An SVM-based machine learning method for the separation of alteration zones in Sungun porphyry copper deposit

Sungun porphyry copper deposit is in East Azarbaijan province, NW of Iran. There exist four hypogene alteration types in Sungun: potassic, propylitic, potassic–phyllic, and phyllic. Copper mineralization is essentially associated more with the potassic and less with the phyllic alterations and their separation is, therefore, quite important. This research has tried to separate these two alteration zones in Sungun porphyry copper deposit using the Support Vector Machine (SVM) method based on the fluid inclusion data, and seven variables including homogenization temperatures, salinity, pressure, depth, density and the Cu grade have been measured and calculated for each separate sample. To apply this method, use is made of the radial basis function (RBF) as the kernel function. The best values for λ and C (the most important SVM parameters) that perform well in the training and test data are 0.0001 and 1, respectively. If these values for λ and C are applied, the phyllic and potassic alteration zones in the training and test data will be separated with an accuracy of about 95% and 100%, respectively. This method can help geochemists in separating the alteration zones because classifying and separating samples microscopically is not only very hard, but also quite time and money consuming.     

Phosphorus export dynamics and hydrobiogeochemical controls across gradients of scale,topography and human impact

Concentration‐discharge (c‐Q) plots are routinely used as an integrated signal of watershed response to infer solute sources and travel pathways. However, the interpretation of c‐Q data can be difficult unless these data are fitted using statistical models. Such models are frequently applied for geogenic solutes, but it is unclear to what extent they might aid in the investigation of nutrient export patterns, particularly for total dissolved phosphorus (TDP) which is a critical driver of downstream eutrophication problems. The goal of the present study was therefore to statistically model c‐Q relations (where c is TDP concentrations) in a set of contrasting watersheds in the Northern Great Plains—ranging in size from 0.2 to 1000+ km²—to assess the controls of landscape properties on TDP transport dynamics. Six statistical models were fitted to c‐Q data, notably (a) one linear model, (b) one model assuming that c‐Q relations are driven by the mixing of end‐member waters from different landscape locations (i.e., hydrograph separation), (c) one model relying on a biogeochemical stationarity hypothesis (i.e., power law), (d) one model hypothesizing that c‐Q relations change as a function of the solute subsurface contact time (i.e., hyperbolic model), and (e) two models assuming that solute fluxes are mostly dependent on reaction rates (i.e., chemical models). Model performance ranged from mediocre (R² < 0.2) to very good (R² > 0.9), but the hydrograph separation model seemed most universal. No watershed was found to exhibit chemostatic behaviour, but many showed signs of dilution or enrichment behaviour. A tendency toward a multi‐model fit and better model performance was observed for watersheds with moderate slope and higher effective drainage area. The relatively poor model performance obtained outside these conditions illustrates the likely importance of controls on TDP concentrations in the region that are independent of flow dynamics.     

Nonlinear site response evaluation of earthquakes: A case study from Sirdjan Balvavard Bridge,Kerman province,Iran

The aim of this study is to illustrate the soil conditions encountered at the proposed bridge sites to analyze and evaluate the test conducted, submit recommendations regarding foundation design. At first by field investigation, the required data was collected and after primary processing the acceptable data was selected. For nonlinear analysis of elastic and rigid half space bed rock, standard hyperbolic model was selected and performed, and the results were compared. The study clearly showed that the effect of bed rock on soil behavior during earthquake is one of the main factors controlling prediction of ground response. A critical aspect of this work was to develop and use a computer code “Abbas Converter” developed by the authors that has several advantages, such as quick installation, acting as a connecter function between the used softwares which can generate the input data corresponding to a defined format and finally, the results of this computer code can be easily exported to the other softwares used in this study. Moreover this code can make it easy to solve the problems encountered.     

Evaluation of a nonlinear seismic geotechnical site response analysis method subjected to earthquake vibrations (case study: Kerman Province, Iran)

Equivalent static load and dynamic analyses methods are usually used for designing structures under and subjected to earthquake excitations. Estimation of site response from an earthquake is fundamental step to anticipate the possible damages and then to try to mitigate them. In this paper, the effect of nonlinearity on site response analyses summarized and evaluating ground surface response taking into account the local soil and subsurface soils properties for the proposed bridge over the river at Sirdjan Boulevard road subjected to earthquake vibration and provokes with assumption of rigid (viscoelastic) and elastic half space bedrock and quantify the site effect on the surface over a number of geotechnical areas has been notified. First, by field investigation, the required data were collected and by primary processing the acceptable data were selected. Then, in nonlinear analysis, for elastic and rigid half space bedrock, standard hyperbolic model was selected and executed, and then the results were compared to each other. The critical point of this work was to develop and use a computer code by the authors, named the “Abbas Converter”, with several advantages, such as work and quick installation, operating as a connecter function between the used softwares and generating the input data corresponding to defined format for them. Its output results can easily be exported to the other used softwares in this study. This code can make and render this study more easily than the previous softwares have done, and take over the encountered problem. This study clearly showed the applicability of the “Abbas Converter” for evaluation of site response with bedrock-type assumption on soil behavior under the earthquake excitations. The proposed scheme is used to analyze the ground motion data from the Bam earthquake in Kerman Province, Iran (2003, M_w 6.5).     

Enhancement of hydrothermal alteration zones using the spectral feature fitting method in Rabor area, Kerman, Iran

Rabor exploration area is in southeast of Kerman province, south of Urumieh-Dokhtar volcanic belt. Since there are many evidences of porphyry copper mineralization in this belt, prospecting and exploration of the intact and undiscovered places, especially the southern part of this belt, seems necessary. In this paper, use has been made of the “spectral feature fitting” (SFF) method to process ASTER satellite data (in Rabor exploratory area as a case study) for the identification and enhancement of hydrothermal alteration zones related to probable porphyry copper mineralization. The method is based on the comparison of absorption features in the image and the reference spectra. The distribution map of the indicator clay minerals, such as kaolinite, muscovite, illite, montmorillonite, alunite, pyrophyllite, dickite, chlorite, and epidote in Rabor exploratory area has been prepared with the help of this method. Identification and enhancement of alteration zones and overlaying Pay-Negin ore index on every individual zone reveal the capability and high efficiency of the SFF method in processing ASTER satellite data and preparing the distribution map of alteration minerals. Field and laboratory studies have shown that main alterations in this area are phyllic and argillic. These studies confirm the results obtained from remote sensing in the area.     

A comparison of the estimated effective elastic thickness of the lithosphere using terrestrial and satellite-derived data in Iran

The effective elastic thickness of the lithosphere has an important role in constraining compositional structure, geothermal gradient and tectonic forces within the lithosphere and the thickness of this layer can be used to evaluate the earthquakes’ focal depth. Hence, assessment of the elastic thickness of the lithosphere by gravitational admittance method in Iran is the main objective of this paper. Although the global geopotential models estimated from the satellite missions and surface data can portray the Earth’s gravity field in high precision and resolution, there are some debates about using them for lithosphere investigations. We used both the terrestrial data which have been provided by NCC (National Cartographic Center of Iran) and BGI (Bureau Gravimetrique International), and the satellite-derived gravity and topography which are generated by EIGEN-GL04C and ETOPO5, respectively. Finally, it is concluded that signal content of the satellite-derived data is as rich as the terrestrial one and it can be used for the determination of the lithosphere bending.     

Uncertainty and Reliability Analysis Applied to Slope Stability: A Case Study From Sungun Copper Mine

Nowadays, there are many new methods for slope stability analysis; including probabilistic methods assessing geotechnical uncertainties to develop safety factors. In this paper, a reliability index analysis for the Sungun copper mine slope stability is evaluated based on three methods of uncertainties consisting Taylor series method, Rosenblueth point estimate method and Monte-Carlo simulation method. Sungun copper mine will be one of the Iran’s biggest mines with final pit’s height of 700 meters. For this study two of its main slopes were assessed, one dipping to the NE (030) and the other to the SE (140). Probability density function of cohesion and angle of friction for the slopes were developed using limit equilibrium methods. These shear strengths were then used to determine the probability density function of safety factor and reliability index using the probabilistic methods. Results of the probabilistic analysis indicate that with ascending values of the uncertainties the reliability index decreases. Furthermore, it was determined that with the Monte Carlo simulation the seed number used has little effect on the reliability index of the safety factor especially with seed numbers in excess of 1200. Variations in the overall reliability index of safety factor were observed between the two slopes and this difference is explained by the differences in complexities of the geology within the cross-section.