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Hydrogeochemical investigations of groundwater in Torbat-Zaveh plain have been carried out to assess the water quality for drinking and irrigation purposes. In this study, 190 groundwater samples were collected and analyzed for physicochemical parameters and major ion concentrations. The abundance of major cations and anions was in the following order: Na(+) > Mg(2+) > Ca(2+) > K(+), and Cl(-) > [Formula: see text] > [Formula: see text] > [Formula: see text]. As a result, alkaline element (Na(+)) exceeds alkaline earth elements (Mg(2+) and Ca(2+)), and strong acids (Cl(-) and [Formula: see text]) dominate weak acids ([Formula: see text] and [Formula: see text]) in majority of the groundwater samples. Statistical analyses including Spearman correlation coefficients and factor analysis display good correlation between physicochemical parameters (EC, TDS and TH) and Na(+), Mg(2+), Ca(2+), Cl(-) and [Formula: see text]. The results display that rock-weathering interactions and ion-exchange processes play important role in controlling groundwater chemistry. Saturation index values also indicate that water chemistry is significantly affected by carbonate minerals such as calcite, aragonite and dolomite. US Salinity Laboratory(USSL) and Wilcox diagrams together with permeability index values reveal that most of the groundwater samples are suitable for irrigation purpose. However, in some regions, the water samples do not indicate required irrigational quality.

Shot peening is one of the most effective surface treatments for improving the fatigue strength of machine elements. In this paper, a new finite element-based model to predict the effect of coverage on the surface state is proposed and critically discussed. By this model, the effects of Rayleigh damping, mesh size, and target dimensions on residual stress profile are investigated using a random impingement simulation of shot peening. Moreover, the model enables the realistic simulation of shot peening process with an affordable computational time with respect of present approaches without reducing the number of impacts and analysis accuracy: the computational time was reduced by 25% in comparison with the conventional finite element models using the proposed method. In addition, the required RAM capacity was reduced up to 80% while the calculated residual stresses and the resulting surface roughness are in good agreement with the experimental results

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