Lead and zinc geochemical behavior based on geological characteristics in Parkam Porphyry Copper System, Kerman, Iran

Parkam (Sarah) porphyry system is located on the metallogenic belt of Kerman, Iran. Due to existence of some copper-rich resources in this region, finding out the exact statistical characteristics such as distribution of data population, mean, variance and data population behavior of elements like Cu, Mo, Pb and Zn is necessary for interpreting their geological behavior. For this reason, precise calculation of statistical characteristics of Pb and Zn grade datasets was performed and results were interpreted geologically. The natures of Pb and Zn distributions were initially identified and their distributions were normalized through statistical treatment. Subsequently, the variograms were calculated for each exploration borehole and show that both Pb and Zn geochemical variates are spatially correlated. According to the similarity of the behavior of Pb and Zn in these calculations, it is decided to measure their exact behavior applying K-means clustering method. K-means clustering results show that the Zn grade varies linearly relative to that of Pb values and their behavior is similar. Based on the geochemical behavior similarity of Pb and Zn, throughout the pervasive secondary hydrothermal activity, they are remobilized in the similar manner, from the deep to the shallow levels of the mineralization zones. However, statistical analysis suggests that hydrothermal activity associated with secondary waters in Parkam is effective in remobilizing and enriching both Pb and Zn since they have similar geochemical characteristics. However, the process does not result in generation of economic concentrations

A method for extracting anomaly map of Au and As using combination of U-statistic and Euclidean distance methods in Susanvar district, Iran

Quantitative descriptions of geochemical patterns and providing geochemical anomaly map are important in applied geochemistry. Several statistical methodologies are presented in order to identify and separate geochemical anomalies. The U-statistic method is one of the most important structural methods and is a kind of weighted mean that surrounding points of samples are considered in U value determination. However, it is able to separate the different anomalies based on only one variable. The main aim of the presented study is development of this method in a multivariate mode. For this purpose, U-statistic method should be combined with a multivariate method which devotes a new value to each sample based on several variables. Therefore, at the first step, the optimum p is calculated in p-norm distance and then U-statistic method is applied on p-norm distance values of the samples because p-norm distance is calculated based on several variables. This method is a combination of efficient U-statistic method and p-norm distance and is used for the first time in this research. Results show that p-norm distance of p=2 (Euclidean distance) in the case of a fact that Au and As can be considered optimized p-norm distance with the lowest error. The samples indicated by the combination of these methods as anomalous are more regular, less dispersed and more accurate than using just the U-statistic or other nonstructural methods such as Mahalanobis distance. Also it was observed that the combination results are closely associated with the defined Au ore indication within the studied area. Finally, univariate and bivariate geochemical anomaly maps are provided for Au and As, which have been respectively prepared using U-statistic and its combination with Euclidean distance method

Application of plate decomposition technique in nonlinear and post-buckling analysis of functionally graded plates containing crack

Nonlinear and post-buckling behaviors of internally cracked functionally graded plates subjected to uniaxial compressive loading have been presented in this paper. A general nonlinear mathematical model for cracked functionally graded plates has been developed based on the first order shear deformation theory within the framework of von-Karman nonlinearity. To approximate the primary variables, Legendre polynomials are used in the current research. The crack is modelled by decomposing the entire domain of the plate into several sub-plates and therefore, a plate decomposition technique is applied. In this study, the penalty technique is used to enforce interface continuity between the sub-plates. The integrals of the potential energy are numerically computed by Gauss-Lobatto quadrature formulas to get adequate accuracy. Finally, the obtained non-linear system of equations is solved by the well-known Newton-Raphson technique. Results are presented to show the influence of crack length, various locations of crack, crack direction, boundary conditions and volume fraction index in nonlinear behavior of functionally graded plates

A semi-analytical investigation on geometric nonlinear and progressive damage behavior of relatively thick laminated plates under lateral pressure and end-shortening

Because of applications of composites in aircraft structures such as skin panels in the wings subjected to lift forces, ultimate strength estimation of these structures is of great importance. In order to more realistically simulate these structures, relatively thick composite plates are analyzed under both end-shortening and lateral pressure loadings using a new simplified and reliable approach. Ultimate strength, progressive damage and geometric nonlinear analyses of such laminates under these loading conditions have not been done yet. Therefore, in the present study, first order shear deformation plate theory is considered with the assumptions of large deflections to perform the geometrically nonlinear and progressive failure analysis of moderately thick composite plates. In order to simulate the lift loads, two different types of lateral pressure distribution have been assumed to be applied on the plates; uniform and sinusoidal lateral pressure loads. The initial failure loads are calculated by means of elastic stress analyses. In this investigation, Hashin failure criteria have been selected for predicting failures. To modify the material properties, two geometric models have been considered to estimate the degradation zone around the failure location; degrading the material in regions of the plies or degrading the entire plies. The load is then increased step by step and for each given load, the stresses are reevaluated to inspect for possible failure. This procedure is repeated for each load increment until the final failure occurs and then ultimate strength is determined. To verify the proposed formulation, obtained results are compared with those calculated by finite element analyses. Plates having a range of thicknesses and with different intensities of pressure load have been analyzedv extensively

Energy based collocation method to predict progressive damage behavior of imperfect composite plates under compression

<div><p>Abstract A new collocation methodology is presented to predict failure and progressive damage behavior of composite plates in this paper. The present work deals with composite plates containing initial geometric imperfections and different boundary conditions under uniaxial in-plane compressive load. In the present study, the domain is discretized with Legendre-Gauss-Lobatto nodes and the approximation of displacement fields is performed by Legendre Basis Functions (LBFs). The onset of damage and damage evolution are predicted by Hashin’s failure criteria and by proposed material degradation models. Three geometric degradation models are also assumed to estimate the degradation zone around the failure location which are named complete, region and node degradation models.</p></div

Providing the bivariate anomaly map of Cu–Mo and Pb–Zn using combination of statistic methods in Parkam district, Iran

U-statistic method is one of the most important univariate structural methods which considers spatial situation of samples. The U-statistic method could be combined with other methods because it devotes a new value to each sample. However, this method separates anomaly based on one variable. The goal in present study is to use and extend this method in multivariate mode. For this purpose, the U-statistic method should be combined with a multivariate method which devotes a new value to each sample based on several variables. Therefore, the U-statistic was applied on Mahalanobis distance values of samples because Mahalanobis distance is calculated based on several variables. This method is a combination of efficient U-statistic and Mahalanobis distance and is used for the first time. Combination results for Cu, Mo, Pb and Zn elements in Parkam district, Kerman, Iran, led to better performance of these two methods. Results show that samples indicated by the combination of these methods as anomalous are more regular; less dispersed and are more accurate than using just one of them. Also it was observed that combination results (especially for Cu and Mo) are closely associated with the defined zone of potassic alteration in the study area. Finally, bivariate lithogeochemical maps of the study area are provided for Cu–Mo and Pb–Zn which have been prepared using combination of the U-statistic and the Mahalanobis distance methods