Characterization and modeling of a crude oil desalting plant by a statistically designed approach

Oil produced in most of oil fields is accompanied by water and dissolved salts, mainly NaCl, which can cause considerable operational problem. Therefore, desalting and dehydration plants are often installed in crude oil production units to remove water soluble salts from an oil stream. This paper investigates experimentally the effect of five parameters (demulsifying agent concentration, temperature, wash water dilution ratio, settling time and mixing time with wash water) on performance of the desalting/dehydration process. The performance was evaluated by calculating the Salt Removal Efficiency (SRE) and the Water Removal Efficiency (WRE) based on the five process parameters. In order to investigate the effect of these parameters on desalting/dehydration efficiencies a 2^6 − 1 fractional factorial design with five other experiments at the center of the design for analysis of variance was applied. Based on the statistical analysis, SRE was expressed by a model for the whole range of variables while WRE was expressed with two models, each is valid in a part of variable domains. The models were satisfactorily evaluated with plant experimental data. For the SRE, the optimum values of demulsifying agent concentration, temperature, wash water dilution ratio, settling time and mixing time with wash water were fond to be 15 ppm, 77 °C, 10%, 3 min and 9 min respectively. As a result the optimum value of 93.28% salt removal efficiency was found. This value was 94.80% and 89.57% for water removal proposed models.     

Mathematical model evaluating for degradation of azo dye in contaminated water by UV/persulfate process

In the present study, the photooxidative degradation of Acid Red 14 (AR 14) was investigated in the UV/persulfate process, and the results of the degradation rate of AR 14 were parametrically represented by ordinary differential equations to find mathematical model for the degradation rate of AR 14 in this process. Our experimental observations led to a model for AR 14 degradation in the UV/persulfate system that could be used to predict removal efficiency by changes of S₂O₈²⁻ (X₁) and dye concentration (X₂), pH (X₃), temperature (X₄) and also distance of UV lamp from solution (X₅). It was found that persulfate and dye concentrations were the most important parameters for AR 14 degradation rate. Moreover, the results showed that the degradation rate was in good agreement with the first-order kinetics for all the parameter values studied. Moreover, the results of the mathematical model agree well with the experimental values (R² = 0.96). Our findings in this study showed that degradation efficiency of UV/S₂O₈²⁻ process for AR 14 was obtained as 98%. Therefore, this model could be applicable before scaling up the AR 14 degradation using UV/persulfate process.     

Preparation and characterization of novel derivatives of chitosan and trimethyl chitosan conjugated with dipeptides and vitamin B12 as candidates for oral delivery of insulin

Chitosan and its derivatives are widely used in drug delivery systems due to their bio-degradebility, bio-compatibility and absorption enhancing properties. Many peptide and protein derived therapeutics cannot be administered through oral rout because of the proteolytic condition of gastro-intestinal tract and their low bio-availability. Insulin is a peptide drug which is widely used in diabetics as repeated daily injection. Due to the fact that there are receptors for didpeptides and vitamine B12 in small intestine, in this research work novel derivatives of chitosan and trimethyl chitosan conjugated with glycyl-glycine, alanyl-alaninie and vitamine B12 were synthesized and characterized. The structure of conjugates as well as substitution of different functional groups was confirmed by different instrumental analytical methods such as Fourier transform infrared, magnetic resonance, and X-ray diffraction spectroscopy. Nano-particles of aforementioned loaded with insulin were prepared and their size, surface electrical charge and morphology characterized and their release profile were studied. The results are promising and reveal that these new chitosan and trimethyl chitosan derivatives are potential vehicles for protein and peptide drug molecules.     

Preliminary analysis of spatial development of karst using a geostatistical simulation approach

Earth science phenomena are primarily spatially dependent with variations occurring on varying scales. Geostatistics is a well-known approach for the assessment of spatial models of regionalized variables, such as porosity. In this study, we used the results of 953 Lugeon tests (402 tests in exploratory wells and 550 tests in grouting wells) to assess effective porosity and karst development at the Tangab Dam site, Iran. Lugeon values were first normalized, following which the variogram method (i.e., range, sill, and nugget effect) was used to identify the spatial variability of Lugeon values. A high correlation range of 200 m was obtained along the grout curtain galleries, while the range was about 40 m in the vertical direction. The simple kriging method with Gaussian variograms was determined to be the best method for estimating the Lugeon values in the study area using cross validation-criteria (e.g., RMSE = 0.835 and ρ = 0.914). Spatial variation of Lugeon values was mapped using a simulated annealing approach. The analysis revealed: (1) a higher potential for karst development on the left abutment of the Tangab Dam site, (2) the average of simulated Lugeon values decreased from values of about 180 close to the ground surface at 1,440 m a.s.l. to lower values of about 50 at 1,260 m a.s.l., and (3) high Lugeon values in the abutments of the dam site approximately followed the 15° bedrock dip, which confirms the potential development of karst features in the Asmari limestone. A schematic model for development of karst at the Tangab Dam site is proposed based on hydrogeological data and results of simulated Lugeon values around the dam site.     

Structural,Optical and Electrical Properties of ZnO Thin Films Prepared by Spray Pyrolysis: Effect of Precursor Concentration

ZnO thin films have been prepared using zinc acetate precursor by spray pyrolytic decomposition of zinc acetate on glass substrates at 450 °C. Effect of precursor concentration on structural and optical properties has been investigated. ZnO films are polycrystalline with (002) plane as preferential orientation. The optical transmission spectrum shows that transmission increases with decrease in the concentration and the maximum transmission in visible region is about 95% for ZnO films prepared with 0·1 M. The direct bandgap value decreases from 3·37 to 3·19 eV, when the precursor concentration increases from 0·1 to 0·4 M. Photoluminescence spectra at room temperature show an ultraviolet (UV) emission at 3·26 eV and two visible emissions at 2·82 and 2·38 eV. Lowest resistivity is obtained at 2·09 Ω cm for 0·3 M. The current– voltage characteristic of the ZnO thin films were measured in dark and under UV illumination. The values of photocurrent and photoresponsivity at 5 V are increased with increase in precursor concentration and reaches to maximum value of 1148 μA and 0·287 A/W, respectively which is correlated to structural properties of ZnO thin films.     

Dual-Rotation Speed Friction Stir Welding: Experimentation and Modeling

Implementing differential rotation speeds of pin and shoulder in the friction stir welding process is considered. Experimental investigations were carried out using a newly designed and fabricated apparatus for dual-rotation speed friction stir welding. Metallographic studies demonstrated that appropriate selection of separate pin and the shoulder rotation speeds not only results in defect-free joints, but also affects the weld zone by controlling the heat input delivered. An energy model for predicting maximum temperature was extended to the dual-rotation speed friction stir process. The model was verified using the previous experimental results reported in the literature.     

Entirely renewable energy-based electricity supply system (small scale & large scale)

Our future energy needs will be supplied by a combination of many different sources, ranging from small wind turbine to provide power for a single house to central power stations that provide power in very large scale fed into the national grid. Computer control systems will integrate the performance of all these systems to make sure that as much power as possible comes from environmentally friendlier sources. As alternative sources become more widely available, small scale systems meeting local needs may start to replace current large scale central power stations. The author is investigating the feasibility of an entirely renewable energy - based electricity supply system. The developed system find so many applications as it can be used as small scale power system for Remote Area Power Supply, wind energy/battery or solar energy/battery, as well as large scale for interconnection with national grid.     

Training based, moving digital filter method for real time heat flux function estimation

In this paper the neural networks is utilized to estimate the “filter coefficients” needed to estimate heat flux in a particular system. In developing the training phase of the network inspiration is drawn from the Burgraff's exact solution of the IHCP as well as the filter method. Thus, the estimation phase neither requires any temperature field nor the sensitivity coefficients calculations. The neural network used in this work is a 2-layer perceptron. It is shown via classical triangular heat flux test cases that the method can yield very accurate, very efficient as well as stable estimations.