Analyzing electrical field effect on asphaltene deposition

Asphaltenes are the heaviest and most complicated fraction in a crude oil sample and consist of condensed polynuclear aromatics, small amounts of heteroatoms (e.g., S, N, and O), and some traces of metal elements (e.g., nickel and vanadium). The main mechanisms of asphaltene deposition are precipitation (formation of asphaltene solids out of liquid phase), aggregation (formation of larger asphaltene particles), and deposition (adsorption and adhesion onto the surface). Asphaltene deposition is a major unresolved flow assurance problem in the petroleum industry, which may occur anywhere in the production system consists of reservoir, wellbore, through flowing and the separator. Asphaltene moieties in crude oil are found to carry residual surface electric charge, so by exerting an electrical field in a specific length of pipe, asphaltenes will deposit and we will have no blockage problem. Determining asphaltene electric charge is an important issue that will be done by static experiment, and then effect of electrical field on asphaltene deposition in dynamic state should be investigated. This paper discusses electric field effect on asphaltene deposition and represents a way to deposit asphaltene moieties in specific location.     

The application of nanofluids for recovery of asphaltenic oil

In the recent years, requirement of suitable enhanced oil recovery (EOR) technique as a more proficient technology becomes significant because of increasing demand for energy. Nanofluids have great potential in order to improve oil recovery. In our study, the effect of SiO₂, Al₂O₃, and MgO nanoparticles on oil recovery was investigated by using core flooding apparatus. Zeta potential and particle size distribution measurements were carried out to investigate the stability of nano particles and results showed SiO₂ has more stability than other ones. Interfacial tension and contact angle measurements between nanofluids and crude oil used to demonstrate that how nanoparticles enhance oil recovery. Experimental data reveals that SiO₂ nanoparticles introduce as the greatest agent among these nanoparticles for enhanced oil recovery. Lowest damage for SiO₂ nanofluids was observed and also it was observed that the concentration and injection rate have straight effects on permeability reductions.     

Performance analysis of dehumidification rotating wheel using liquid desiccant

In the present work, theoretical and experimental evaluation of the effect of bed configuration and operating conditions on the performance of desiccant dehumidification system has been carried out. A new rotating absorption disk has been designed and constructed to be tested in the experimental work. The desiccant wheel has a cylindrical shape of 50-cm diameter and 10 cm thickness. The flow area of this bed is consisted of 350 narrow slots, which are uniformly distributed over the cross section of the cylindrical bed. Each slot has a cylindrical shape and constructed from a steel spring of 100 mm length and 20 mm inside diameter. To form the absorbing surface in the bed, each spring is coated with a thick cloth layer impregnated with lithium chloride solution, which is used as the working desiccant in these experiments.In the theoretical part of this study, a mathematical model has been developed where its output results are compared with the experimental data. The effect of different design parameters and operating conditions on the absorption and regeneration processes is discussed. The effect of regeneration air temperature, the process air and regeneration air inlet humidity, the rotational speed, the process and regeneration air velocity (or flow rates), the bed length, etc. on the amount of water absorbed/desorbed in a cycle is investigated.For the specific bed design parameters, actual recorded data show that an amount of 95 g of water can be absorbed in the absorption cycle per hour. This value changes with varying the operating conditions. From the theoretical investigation, it is found that at regeneration temperature of 85 °C, the amount of water absorbed is nearly equal to the amount of water desorbed (i.e. equilibrium condition) for a complete cycle. It is seen also that for moderate operating conditions (50% RH, 30 °C) and lower regeneration temperature which is suitable for solar energy application, the reduction in the humidity ratio of the process air reaches about 13% of its initial value. Finally, comparisons between theoretical and experimental results show good agreement.     

Experimental investigation on the adsorption/desorption processes using solid desiccant in an inclined-fluidized bed

This paper presents an experimental investigation on the adsorption and desorption operations in an inclined-fluidized bed using silica gel as the working desiccant. The experimental system involves a circular glass tube containing the particles of silica gel, which is tested at an inclination angle of 45°. The moisture capacity of the bed is measured using a gravimetric technique. Process air at nearly constant ambient parameters (humidity and temperature) and different values of flow rate are used during adsorption. Moisture concentration in the bed is analyzed through visual observation of the color of silica gel particles. Experimental measurements indicate that the regeneration and adsorption rates are highly dependent on the air stream velocity. A satisfactory regeneration rate is confirmed at regeneration temperature as low as 90 °C when inclined-fluidized bed is applied. The transient-state moisture transfer rates during adsorption and desorption are presented. Finally, observation of the movement and color of the particles in the bed show regular circulation and homogenous distribution of moisture concentration.     

Rules for Optimal Operation of Reservoir-River-Groundwater Systems Considering Water Quality Targets: Application of M5P Model

The aim of this paper is to develop rules for optimal reservoir operation and water withdrawal from river and aquifer considering water supply and pollution control targets. The general approach is making use of an integrated water quantity-quality management (IWQM) modeling in conjunction with accurate data mining techniques. The IWQM model generates data, including; optimal releases and water withdrawal from river and aquifer for different conditions, and M5P and Support Vector Regression (SVR) data mining models utilize the results of the IWQM model for the derivation of rules. The IWQM model minimizes the deviation from water supply and water quality targets during the planning horizon. This method for derivation of operating rules is applied to a real world case study, Zayandehrood system, in Iran, with serious water supply and water pollution problems. The IWQM model is analyzed for different hydrologic and water demands scenarios with total dissolved solids (TDS) as the water quality indicator. Results show that an integrated approach to reservoir-river-aquifer operation in the study area can reduce the TDS by 43 % in the downstream river.     

Prediction of Urmia Lake Water-Level Fluctuations by Using Analytical, Linear Statistic and Intelligent Methods

Undoubtedly, the most significant factor with wise decision making and designing hydrological structures along the lake coasts is an accurate model of lake level changes. This issue becomes more and more important as recent global climate changes have completely reformed the behavior of traditional lake level fluctuations. Subsequently, estimating lake levels becomes more important and at the same time more difficult. This paper deals with modeling lake level changes of Lake Urmia located in north-west of Iran, in terms of both simulator and predictor models. According to this, two traditional simulator models based on water budget are developed which benefit from most effective components on water budget namely precipitation, evaporation, inflow and the lake level antecedents, as model inputs. Most famous linear modeling tools, Autoregressive with exogenous input (ARX) and Box-Jenkins (BJ) models are employed with the same mentioned inputs for prediction purpose. In addition, two other methods that are, Multi-Layer Perceptron (MLP) neural network and also Local Linear Neuro-Fuzzy (LLNF) are applied to investigate capability of intelligent nonlinear methods for lake level changes prediction. All models performances are indicated using both graph and numerical illustrations and results are discussed. Comparative results reveal that the intelligent methods are superior to traditional models for modeling lake level behavior as complex hydrological phenomena.     

A critical evaluation of EA computational methods for Photovoltaic cell parameter extraction based on two diode model

Due to its ability to handle nonlinear functions regardless of the derivatives information, evolutionary algorithms (EA) are envisaged to be very effective for extracting parameter of photovoltaic (PV) cell. This paper presents critical evaluation of the parameters extraction of two diode PV model using three EA methods, namely Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and Differential Evolution (DE). For DE, two variations are proposed: (1) boundary based differential evolution (B-DE) and (2) penalty based differential evolution (P-DE). The performance of each method is evaluated based on several factors: accuracy and consistency of solution; speed of convergence; computational efficiency and the required number of control parameters. Comparisons are carried out using synthetic data and are validated by six PV modules of different types (multi-crystalline, mono-crystalline, and thin-film) from various manufacturers. Information derived from these critical evaluations can be useful to determine the best computational method to build an efficient and accurate PV system simulator.     

Energy efficiency improvement and input cost saving in kiwifruit production using Data Envelopment Analysis approach

In this study, Data Envelopment Analysis approach was used to analyze the energy efficiency of farmers, to find efficient and inefficient ones and to identify the wasteful uses of energy in kiwifruit production. Moreover, the effect of optimization of energy on improvement of input costs and energy indices was investigated. The results revealed that based on variable returns to scale model, 62.79% of growers were efficient, though, based on constant returns to scale model it was just 23.26%. The technical, pure technical and scale efficiencies of farmers were calculated as 0.942, 0.993 and 0.948, respectively. Total optimum energy requirement was found to be 26,604.11 MJ ha^?1; showing that 12.17% of input energy could be saved if the farmers follow the results recommended by this study. The contribution of chemical fertilizers input from total saving energy was about 78% which was the highest share. Optimization of energy use improved the energy use efficiency, specific energy and net energy by 13.86%, 12.17% and 22.56%, respectively. The results of economical analysis showed that optimization of energy decreases the total costs of production by 4.91%; and the benefit–cost ratio and productivity increased by 5.15% and 5.19%, respectively.     

Simple, fast and accurate two-diode model for photovoltaic modules

This paper proposes an improved modeling approach for the two-diode model of photovoltaic (PV) module. The main contribution of this work is the simplification of the current equation, in which only four parameters are required, compared to six or more in the previously developed two-diode models. Furthermore the values of the series and parallel resistances are computed using a simple and fast iterative method. To validate the accuracy of the proposed model, six PV modules of different types (multi-crystalline, mono-crystalline and thin-film) from various manufacturers are tested. The performance of the model is evaluated against the popular single diode models. It is found that the proposed model is superior when subjected to irradiance and temperature variations. In particular the model matches very accurately for all important points of the I-V curves, i.e. the peak power, short-circuit current and open circuit voltage. The modeling method is useful for PV power converter designers and circuit simulator developers who require simple, fast yet accurate model for the PV module.     

An analytic approach for CDMA output of feedforward power amplifier

In this paper, a novel method is introduced to predict the Code-Division Multiple-Access (CDMA) output spectrum of an RF power amplifier linearized with feedforward technique based on transfer function. In this method, an RF power amplifier is modeled mathematically by nonlinear complex envelope transfer function based on AM-AM and AM-PM distortion diagrams. Using this model, analytic expressions of CDMA output spectrum of power amplifier is calculated. Having mathematical model of RF power amplifier leads to derive analytic expressions for InterModulation (IM) products in feedforward amplifier. Based on these expressions, IM products are related to nonlinear complex envelope transfer function of feedforward amplifier. Then, CDMA output spectrum of feedforward linearization technique is predicted. The loops imbalances in feedforward technique are considered in analysis. Finally, the results of derived expressions in MATLAB software are compared with ADS simulations results and good agreements were achieved. Employing this method gives insight for feedforward analysis and loops imbalances effects in feedforward amplifier for CDMA applications.