Developing a Scaling Equation as a Function of Pressure and Temperature to Determine the Amount of Asphaltene Precipitation

A simple and applicable scaling equation as a function of pressure, temperature, molecular weight, dilution ratio (solvent), and weight percent of precipitated asphaltene has been developed. This equation can be used to determine the weight percent of precipitated asphaltene in the presence of difference precipitants (solvents) and the amount of solvent at onset point. Since increasing the pressure of crude oil decreases the amount of asphaltene precipitation, the effect of reservoir pressure has been taken into account in developing this equation. The results obtained by using this equation are substantially different and more accurate from other developed scaling equations for asphaltene precipitation. By considering the effect of reservoir pressure in developing the scaling equation and application of a genetic algorithm, the unknown parameters of the scaling equation are simultaneously and without any reservation obtained. The most important application of this unique equation is in the determination of critical point of asphaltene precipitation, known as onset point, and asphaltene precipitation in gas injection operations for enhanced oil recovery. The results predicted using the scaling equations are compared with the authors' experimental and literature precipitation data and it is shown that they are in good agreement with our experimental data. The scaling equation can be used in the design of gas-injected reservoir to prevent precipitation of the asphaltene aggregates in the reservoir.     

Synthesis, characterization, and electrochemical properties of ultrafine β-Ni(OH)2 nanoparticles

Nickel hydroxide was deposited via cathodic electrodeposition from low-temperature 0.005 M NiCl₂ bath without using any surfactant or template. The cathodic current density was 1 mA cm⁻² and stainless steel was used as the cathode. The XRD pattern confirmed that the prepared sample has a pure brucite crystal phase of β-Ni(OH)₂ and the broadening of diffraction peaks showed that the particles size of the prepared β-Ni(OH)₂ is extremely small. Thermal behavior and composition of the prepared β-Ni(OH)₂ were investigated by DSC-TG and FT-IR analyses. Morphological characterization by SEM and TEM revealed that β-Ni(OH)₂ is composed of well dispersed ultrafine particles with size of about 5 nm. The electrochemical properties of the prepared nanoparticles were studied by means of cyclic voltammetry (CV) and galvanostatic charge-discharge tests in 1 M KOH. The prepared β-Ni(OH)₂ nanoparticles showed excellent capacitance behavior of 740 F g⁻¹ in the potential window of 0-0.55 V vs. Ag/AgCl. These results make the β-Ni(OH)₂ nanoparticles as a promising candidate for the supercapacitor electrodes.     

A comparative study for synthesis methods of nano-structured (9Ni–2Mg–Y) alloy catalysts and effect of the produced alloy on hydrogen desorption properties of MgH2

9Ni–2Mg–Y alloy powders were prepared by arc melting, induction melting, mechanical alloying, solid state reaction and subsequent ball milling processes. The results showed that melting processes are not suitable for preparation of 9Ni–2Mg–Y alloy due to high losses of Mg and Y. Therefore, 9Ni–2Mg–Y alloy powder was prepared by three methods including: 1) mechanical alloying, 2) mechanical alloying + solid state reaction + ball milling, and 3) mixing + solid state reaction + ball milling. The prepared 9Ni–2Mg–Y alloy powders were compared for their catalytic effects on hydrogen desorption of MgH₂. It is found that 9Ni–2Mg–Y alloy powder prepared by mechanical alloying + solid state reaction + ball milling method has a smaller particle size (1–5 μm) and higher surface area (1.7 m² g⁻¹) than that of other methods. H₂ desorption tests revealed that addition of 9Ni–2Mg–Y alloy prepared by mechanical alloying + solid state reaction + ball milling to MgH₂ decreases the hydrogen desorption temperature of MgH₂ from 425 to 210 °C and improves the hydrogen desorption capacity from 0 to 3.5 wt.% at 350 °C during 8 min.     

On the numerical solution of generalized convection heat transfer problems via the method of proper closure equations – part II: Application to test problems

ABSTRACT

In part I of this paper, a new physical-based computational approach for the solution of convection heat transfer problems on co-located non-orthogonal grids in the context of an element-based finite volume method was discussed. The test problems are presented here, in part II of the paper. These problems include five steady two-dimensional convection heat transfer problems. In all test cases, the convergence history, the required under-relaxations for the iterative solution of the linearized equations, and the order of accuracy of the method are discussed and the streamlines as well as isotherms are presented. The computational results show that the proposed method is second order accurate and might occasionally need mild under-relaxation in relatively complex problems. Excellent match between the computational results and the corresponding reliable published results is observed.     

Relating Sediment Yield Estimations to the Wet Front Term Using Rainfall Simulator Field Experiments

Water Resources Management - Depth to wet front is generally considered as the amount of water that penetrates into soil and wets the internal soil layer. This is an important variable especially...     

Modeling Transient Evaporation from Descending Shallow Groundwater Table Based on Brooks–Corey Retention Function

In arid and semi-arid regions a large amount of rainfall and irrigation water that enters into the soil is lost through soil surface via evaporation. In such regions, there are some areas with shallow groundwater table, evaporating huge amounts of water and accumulating salts at the soil surface. Thus, the evaporation phenomenon not only is responsible for water loss but also is a major reason for soil salinization. The objective of this study was to develop and verify an analytical model for one dimensional transient unsaturated upward flow from water table to soil surface. Consequently, an analytical solution was developed based on the Richards equation with initial and boundary conditions governing evaporation phenomenon. The parametric Brooks and Corey retention function was used to describe water status in the vadose zone. Based on the proposed model, the saccumulative evaporation is estimated as function of water table drawdown and soil retention parameters. To collect the data required for model verification, nine large lysimeters were constructed and packed with sandy loam, silty clay loam, and silty clay soil textures. The results indicated reasonable agreements between the experimental data and those predicted with the proposed model. Although the overall predicted results were well resemble the real conditions, there were some underestimations for a certain period. This can be attributed to evaporation from side gap of columns, upward flow due to vapor phase movement of moisture, and the collapse of macropores resulting from soil packing.     

TOC determination of Gadvan Formation in South Pars Gas field, using artificial intelligent systems and geochemical data

Potentially, TOC content is affected by logging data in a source rock (density, sonic, neutron and resistivity logs). Hence, to analyze these logs, which we make a quick and reliable assessment of a source rock. So, it is a quick and economically cheaper method rather than direct geochemical analysis. A source rock interval poses to less density, lower velocity, higher sonic porosity, higher gamma ray values and increase in resistivity. In this research, Gadvan Formation was studied in two boreholes as potential of source rock. The log data of two wells were used to construct of intelligent models in a source rock of the South Pars Gas field in southwest of Iran. A suite of geophysical logs (neutron, density, sonic and resistivity logs) and cutting chip data samples data were applied for determining TOC content of this formation. Rock-Eval pyrolysis data reveal that Gadvan Formation is poor source rock (less than 0.5%). Hence we attempted a correlation between geophysical data and direct TOC content measurements of using ? Log R, Rock-Eval, neural network and fuzzy logic techniques.The results showed that intelligent models were successful for prediction of TOC content from conventional well logs data. Meanwhile, similar responses from other different intelligent methods indicated that their validity for solving complex problems.     

A Wavelet-ANFIS Hybrid Model for Groundwater Level Forecasting for Different Prediction Periods

Artificial neural network (ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS) have an extensive range of applications in water resources management. Wavelet transformation as a preprocessing approach can improve the ability of a forecasting model by capturing useful information on various resolution levels. The objective of this research is to compare several data-driven models for forecasting groundwater level for different prediction periods. In this study, a number of model structures for Artificial Neural Network (ANN), Adaptive Neuro-Fuzzy Inference System (ANFIS), Wavelet-ANN and Wavelet-ANFIS models have been compared to evaluate their performances to forecast groundwater level with 1, 2, 3 and 4 months ahead under two case studies in two sub-basins. It was demonstrated that wavelet transform can improve accuracy of groundwater level forecasting. It has been also shown that the forecasts made by Wavelet-ANFIS models are more accurate than those by ANN, ANFIS and Wavelet-ANN models. This study confirms that the optimum number of neurons in the hidden layer cannot be always determined by using a specific formula but trial-and-error method. The decomposition level in wavelet transform should be determined according to the periodicity and seasonality of data series. The prediction of these models is more accurate for 1 and 2 months ahead (for example RMSE?=?0.12, E?=?0.93 and R ²?=?0.99 for wavelet-ANFIS model for 1 month ahead) than for 3 and 4 months ahead (for example RMSE?=?2.07, E?=?0.63 and R ²?=?0.91 for wavelet-ANFIS model for 4 months ahead).     

Dependability analysis for characterizing Google cluster reliability

Cloud solutions are emerging as a new suitable way of transforming traditional IT data centers to highly available and reliable computing resources for hosting critical applications and data. However, software and hardware failures are a common problem in cloud datacenters that can lead to harmful damages. In this paper, we analyze the physical server failures in the Google cloud datacenter. We study the Google cluster properties to investigate the relationship among physical servers' failure rate and jobs failure events. The failure rate of Google cluster executed jobs and servers is taken into consideration during a 29‐day period. We present a reliability model for Google cluster physical machines using the continuous time Markov chains according to this observation. We attempt to analyze the obtained model through SHARPE software packages to improve the understanding of failure events in the Google cloud cluster. We also explore the cluster availability based on parameters like steady‐state availability, steady‐state unavailability, mean time to failure, and mean time to repair in the Google cluster.     

Robust stability of hybrid Roesser models against parametric uncertainty: a general approach

This paper aims at proposing a general framework for the establishement of LMI conditions to analyse the robust stability of a singular hybrid Roesser model subject to parametric uncertainties. The uncertain parameters are involved through implicit Linear Fractional Representations (LFR). Special focus is put on the influence of the number of uncertain parameters and the dimensionality of the model. More precisely it is shown that each dimension can nearly be regarded as an uncertain parameter and the other way around. Therefore, their influence on the conservatism of the obtained condition is very similar.