جستجوی مقالات مرتبط با کلیدواژه "انتقال جرم" در نشریات گروه "آب و خاک"

Solute transport modeling in water bodies and especially rives, provides a useful tools for decision-makers and consumers, to take a timely decisions in order to prevent or avoid any catastrophic consequences. Many factors such as velocity, cross-section area, bedform and etc. affect the transport of any solute particle in the media. The aforementioned factors vary both in width and depth, which cause some of the particles to deviate from the main channel to areas in which the particle stays for a longer time. Those particles are released to the main channel gradually causing a heavy-tailed breakthrough curve in downstream of the injection point. The areas where solute spends more time than the main channel is called deadzones. Any area in the channel that reduce the velocity field to relatively zero could be categorized as deadzones, such as areas behind a boulder, in pocket beside the river, behind or inside a vegetation cluster. In streams containing deadzones the classical adevection-dispersion equation (ADE) cannot meet the requirements. Scholars proposed many different approaches to capture the heavy-tailed behavior. One of the renowned and novel approaches to quantify the role of deadzones in natural streams is using Fractional Calculus. This field of mathematics helps to change the fundamental assumption of ADE, which is laid upon “central limit theorem” and subsequently generate a new equation based on fractional partial derivatives, The Fractional Advection –Dispersion Equation (FADE). The FADE provides a better description of solute movement in natural streams, because of its general form and non-locality.
In this research, FADE for a non-uniform but steady condition in natural streams has been investigated. FADE is a product of central limit theorem generalization and hence can capture the anomalous behavior of solute transport in streams containing deadzones. One of the important points that can be inferred from tracer study in such streams is that the concentration of a point is influenced by the point in far upstream; that is either the solute particle comes faster than the main cloud or slower and defy the basic assumption. Since classic ADE just considers the points in the closest proximity of the study point to calculate the bearkthrough curve (BTC), it cannot be used in cases that the deadzones are involved; which calls for a more comprehensive consideration of the stream. Interestingly, factional derivatives are non-local; fractional derivatives consider the state of the function in its whole domain. Hence, FADE can accurately describe and calculate the BTC in streams affected by deadzones. The big difference between FADE and classic ADE is that, the former is based on Levy motion while the later developed and shows Brownian motion. Also, the order of spatial derivative in FADE is a value , unlike the classic ADE in which the order is fixed to . To investigate the FADE in depth standard Grunwald definition of fractional derivatives were employed for discretization, and an algorithm is proposed. The more the order of the fractional partial derivative decreases, the more would be the effect of the deadzones, this means that while the order is equal to , the streamflow do not experience any deadzones in its way. In order to fit the data, two variables in the FADE needs to be calibrated; the unknown parameters were estimated using Particle Swarm Optimization (PSO) technique.
The model was validated using a set of data from a small stream. The comparison shows that the model can accurately recreate the BTC and perform dramatically better than classic ADE which even in some stations is incapable of predicting the peak concentration and the arrival time of the particle to the station. Quantitatively, the difference between the FADE and observation represented by RMSE in average is 0.236 while for classic ADE is around 4 times higher. The difference in the first two stations is negligible for the stream does not contain any deadzones. This shows that not only the FADE is capable of considering deadzones, but also if needed it can easily reduce to classic ADE. This flexibility offers vast opportunity for application. In addition, the sensitivity of the model to the calibration parameter was analyzed, the analysis shows that both variables (order of the derivative and skewness parameter) should be treated with great care, since a little variation in their value drastically alter the shape of the BTC, and decrease the accuracy of the prediction. In this research, the capability of FADE were investigated and proved that this model performing far better in predicting solute transport in natural streams in which the variability of the morphology may hinder the solutes movement.

Accurate estimation of ET0 in any region is very important. The aim of this study is to compare and calibrate the 20 empirical methods of estimating evapotranspiration (ET0) based on three categories in monthly timescale at the Urmia Lake watershed. These categories are: 1) temperature-based models (Hargreaves (HG), Thornthwaite (TW), Blaney-Criddle (BC), Linacre (Lin)), 2) radiation-based model (the Doorenbos-Pruitt (DP), Priestly-Taylor (PT), Makkink (Mak), Jensen-Haise (JH), Turc (T), Abtew (A), McGuinness-Bordne (MB)) and 3) mass transfer-based model (Meyer (M), Dalton (D), Rohwer (R), Penman (P), Brockamp-Wenner (BW), Mahringer (Ma), Trabert (Tr), WMO and Albrecht (AL)). For this purpose, the information of 10 synoptic meteorological stations during the period of 1986-2010 was used. Results from the above mentioned methods were compared with the output of the FAO Penman-Monteith (PMF-56) method. Performance of the methods evaluated using the R2, RMSE, MBE and MAE statistics. The best and worst methods of each category were determined for the study area. The best methods of each category were calibrated for the area under study. Results indicated that there is a significant difference between the results of selected methods of each category and the PMF-56 method. Performance of the selected methods remarkably increased after calibration. Among the temperature-based group, the HG method having the median R2 value of 0.9597 was recognized as the best method. After calibration the medians of RMSE, MBE, and MAE were 72.09, 3.14 and 10.70 mm/ month, respectively. After HG, the Lin and BC found to be the best second and third methods in the study area. The TW showed Large error, therefore, it was not a suitable method for ET0 estimation in study area. Among the radiation-based group, the DP model was selected as the best method in the study area. Furthermore, the median of R2 values was 0.982. In this method, the medians of RMSE, MBE and MAE after calibration were 7.89. -0.62 and 6.03 mm/month, respectively. Following DP, the PT method was recognized as the 2nd best one. The methods namely M, JH, T, A and MB were put in the 3rd to seventh rank of the radiation category. Finally, among the mass transfer-based group, having R2=0.8945, the Meyer method was selected as the best method of this group for the study area. In the mentioned method (after calibration) the medians of RMSE, MBE, and MAE were 21.8, -8.7 and 17.3 mm per month, respectively. From mass transfer based group, the D method was found as the second best method in the study area. The methods namely R, P, BW, Ma, Tr, WMO and A were ranked 3rd to 7th, respectively. In general, the performance of radiation based methods was superior than others in Urmia Lake basin. Temperature based methods and mass transfer based methods were ranked second and third, respectively. Further examination of the performance resulted in the following rank of accuracy as compared with the PMF-56: DP (Radiation based), HG (Temperature based) and Meyer (Mass transfer). In general, it can be concluded that after calibration the DP method is suitable to estimate reference crop evapotranspiration among 20 selected methods in the Urmia Lake basin.

The aim of this study is to compare and calibrate nine different mass transfer-based reference crop evapotranspiration () estimation methods in monthly time scale at Urmia Lake basin. The selected methods were Meyer (M)، Dalton (D)، Rohwer (R)، Penman (P)، Brockamp and Wenner (BW)، Mahringer (Ma)، Trabert (T)، WMO and Albrecht (A) methods. For this purpose the information of ten synoptic weather stations in the period 1986-2010 were used. Results of the mentioned methods compared with the output of the FAO-56 Penman-Monteith (PM56) method. Calibration of methods performed in the case of every station and months in the mentioned time period. Performance of methods evaluated using the R2، RMSE، MBE، MAE and PE statistics. Results showed that before calibration larger biases existed for the selected methods comparing the PM56. Calibration of methods considerably improved their performances. The M method was recognized as a best method after calibration at the study watershed. The median of R2 value of this method was 0. 8945. In the mentioned method (after calibration) the median of the RMSE، MBE، MAE and PE was found to be equal to 21. 8، -8. 7، 17. 3 and 21. 5 mm per month. The Dalton method selected as the second best one. Methods namely، R، P، BW، Ma، T، WMO and A ordered as the third till ninth rank methods.

The microbial and enzyme activity in different points within cheese and quality of final product are determined by local concentrations of salt and moisture in aqueous phase. To predict the evolution of moisture content in different layers of the Iranian white cheese during brining, constant and variable moisture diffusion coefficients were determined using experimental moisture time–dependent concentration-distance profiles. These experimental profiles for Iranian white cheese were obtained in rectangular samples, ensuring semi-infinite unidirectional mass transfer within saturated solution of sodium chloride at different temperatures (6, 14, 19, 24 °C) and brining times (6, 24, 48 h). Results showed that moisture diffusivity increases with increasing temperature and moisture content in cheese aqueous phase. The variation of the moisture effective diffusivity as a function of temperature was represented by the Arrhenius’s relation. Finally, the relation of diffusivity with moisture content and temperature was developed. The predicted diffusivity values using the developed model showed a good agreement with the experimental values by using Boltzman variable method.

Rapid drying can increase brittleness of and induce internal cracks in the grain which predispose the product to breakage during subsequent activities. To fully understand the drying process requires an accurate description of the drying mechanism. Kernel equilibruim moisture content (EMC) is a property strongly related to agricultural products drying phenomena. Its accurate prediction can lead to optimisation of drying processes, especially in highly automated computer aided drying systems. In this study, a finite element formulation and solution of a set of coupled conductive heat and diffusive moisture transfer equations, to improve grain drying simulation of axisymmetric bodies are presented. Axisymmetric linear triangular elements with two degrees of freedom per node are used to discretize the rice grain in model for different equilibrium moisture content (from 7.5 to 0.12 d.b.%). For the purpose of this study, one medium grain, ‘Sepidrod CV.’, was used. During the thin layer drying, the drying air temperature of 69 °C and initial moisture content of 17.23 d.b.%, were adopted. A high relation has been observed when the output of model with 11.5 d.b.% EMC was compared to experimental data obtained by others. The least and most root mean square error analysis (RMSE) calculated for models at different EMC with experimental data were 0.0091 and 0.1025. The least and most mean relative deviation modulus were 1.394 and 5.129, respectively. Considering the mean errors of the models in relation to the obtained experimental data, the equilibrium moisture content for 11.5 d.b gave the best result.