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Due to the correlation between water qualitative indices, their spatial variations are commonly estimated using semivariogram expressed methods, such as Kriging and cokriging. Some studies have tried applying multivariate statistics to identify the effect of various parameters on groundwater spatial variations; however, their estimations are eventually determined by Kriging family of methods. In this study, two multilevel Gaussian factor models (GF1 and GF2) are introduced to jointly model the multivariate data. Such an approach avoids the difficulties of maximum likelihood estimation, incorporating imperfect information to reach an effective decision. Thirty-five agricultural well samples were analyzed for EC and SAR, and other correlated variables over an area of about 1837 Km2 to prepare thematic maps of the groundwater quality classes, based on which administrative crops are suggested for the regional agriculture after selecting the best model for zoning groundwater quality. The GF2 model outperformed the ordinary Kriging in joint modelling of EC and Mg + Ca + Na. Moreover, the best fitting was obtained under Gaussian and Matern covariance functions. EC estimated values by Kriging and the multilevel Gaussian factor model were 2.18–5.17 ds/m and 2.53–4.54 ds/m, respectively. A notable resemblance was found between the spatial variation patterns obtained by the two methods in both EC and SAR variables. Despite relatively larger domains obtained from the Kriging model, such extreme values of EC and SAR covered small and insignificant zones of the study area. The areas estimated by the GF2 model and Kriging for the EC range 3–4.5 ds/m were relatively close (98.4% and 85.6% of the total area, respectively), while the values exceeding this range, covered very small, negligible fractions of total area (1.1% and 7.9%, respectively). Similar results were obtained for SAR estimates. The cultivable area signified by the two models were not significantly different, as shown by the allowable cultivation area maps generated. When GF2 model is applied, the whole study area is cultivable for all recommended crops in 90% and less yield potentials, while the limitations were insignificant, considering Kriging method. [ABSTRACT FROM AUTHOR]

Prediction of response values is a primary goal in many applications. The standard approach to this problem is kriging which is essentially a linear prediction using optimal least squares interpolation of the random field. However, the optimal predictor is not necessarily a linear one unless the geostatistical data support the Gaussian model. As data often exhibit non-normality, some of the most effective spatial processes are reviewed in the current study. The usefulness of the presented models is demonstrated based on the prediction of rainfall levels in Fars Province, Iran. The measurements were taken from 100 stations. To assess the predictive performance of the evaluated models, 15 stations were randomly withheld. Subsequently, the predicted values at these locations were evaluated against the measured ones. The results of the study indicated that, comparing to some well-known models, the skew Gaussian model introduced in this article demonstrated a better performance in the prediction. [ABSTRACT FROM AUTHOR]

In tunnels, convergences of sidewalls, roof and floor may be different, because of weight of the failed or plastic rock mass. In this paper, a closed-form analytical solution for a deep tunnel excavated in an elastoplastic rock mass is proposed. Using the proposed solution, the effects of the weight of the plastic or failed region developed around the tunnel are investigated. In the proposed method, brittle–plastic or elastic–perfectly plastic behavior and Mohr–Coulomb yield criterion and plastic potential function are used for the ground medium. The gravitational loading is considered as a radial body force being applied to the ground medium. Illustrative examples are given to demonstrate the performance of the proposed method and to examine the effects of the gravity loads. The results obtained by the proposed method show that the gravity loading may affect the tunnel convergence, considerably. [ABSTRACT FROM AUTHOR]

In some statistical issues, several continuous spatial outcomes are simultaneously measured at each sampling location. In such circumstances, it is common to model the data through a multivariate Gaussian model. As the normality assumption is often untenable, this paper proposes a multivariate skewed spatial model which, by virtue of its capacity for capturing skewness, is potentially more flexible than symmetric ones. Specifically, a multivariate version of the Gaussian-log Gaussian convolution process is developed. The resulting covariance for the multivariate process is in general nonseparable. We also discuss the other properties of the induced covariance function. Furthermore, Markov chain Monte Carlo methods are used to make Bayesian inferences. The performance of the method is investigated through simulation experiments and by analyzing a real soil pollution dataset obtained from Golestan province, North of Iran. [ABSTRACT FROM AUTHOR]

In this paper, an analytical method, for calculating seepage induced stresses and displacements in underwater lined circular pressure tunnels, is developed on the basis of a generalized effective stress law. The problem is considered as axisymmetric, and the lining and rock mass are assumed to be elastic, homogeneous and isotropic. The solution accounts for the seepage forces with the steady-state flow and hydro-mechanical pressures between adjacent zones. The proposed method can be applied for the analysis and design of pressure tunnels with concrete lining, prestressed concrete lining, grouted rock mass, as well as for the analysis of pressure tunnels considering the effects of the surrounding fractured or damaged zone. Illustrative examples are given to demonstrate the performance of the proposed method, and also to examine the effect of seepage forces on stability of pressure tunnels. It is concluded that, the classic solutions (Lame's solution), that is based on considering the internal pressure as a mechanical load applied to the tunnel surface, is not applicable to pervious media and results in unsafe designs. [ABSTRACT FROM AUTHOR]

Shredded cabbage (50 % v/ v) and Daikon radish cubes (57 % v/ v) with different salt concentrations (0.15, 0.5, 1, 1.5, and 1.85 %) were heated from 30 to 70 °C in a static ohmic heating cell at different voltages (65, 80, 100, 120, and 135 V) and frequencies (60, 2070, 5030, 7990, and 10,000 Hz) to evaluate their ohmic heating behaviour. Radish heated under 1.5 % salt, 120 V and 7990 Hz or 1 % salt, 135 V and 5030 Hz conditions gave the shortest heating time of 6 min from 30 to 70 °C, and cabbage gave the longest time of 128 min at 0.15 % salt, 100 V, and 5030 Hz. Regression models of heating rate as a quadratic function of the sample temperature gave R >0.98. The general trend observed was that the magnitude of the heating rate increased with frequency at high voltage but decreased at low voltage for cabbage, while the opposite trend was observed for radish. Heating was more efficient at higher salt concentration and applied voltage. Radish heated more rapidly than cabbage. A slight slope change was observed in all cases between 50 and 60 °C. The response surface models revealed linear, cross products and quadratic effects to be significant with R over 0.98. [ABSTRACT FROM AUTHOR]

Concentrated lime juice with 20% total soluble solids was dried using three levels of maltodextrin (40%, 50%, and 60% solid base) and a BÜCHI B-190 spray dryer. The drying air temperature and flow rate were 140 °C, 155 °C, and 170 °C and 47.1, 53.5, and 57.8 m/h, respectively. A total of 27 experiments were conducted (in triplicate) with the feed rate, temperature, and compressed air flow for the atomizer kept constant. Analysis of the data revealed that product recovery increased when the maltodextrin in the feed and drying air flow rate were increased, but the inlet air temperature had no significant ( P < 0.05) effect on powder recovery. The moisture content of the powder varied with the maltodextrin level, inlet air temperature, and air flow rate. Using scanning electron microscope images, larger particle size was observed with the increase of maltodextrin concentration. Powder bulk density also increased from 0.41 to 0.68 g/cm, depending on the level of maltodextrin, whereas the drying air temperature and flow rate were not as effective. The results of this study are beneficial for scaling up the spray drying of lime juice to the food industry. [ABSTRACT FROM AUTHOR]