In Situ Synthesis of Ultrahigh Molecular Weight Polyethylene/Graphene Oxide Nanocomposite Using the Immobilized Single-site Catalyst

We address the immobilization of single-site catalyst on the graphite oxide (GO) surface using methylaluminoxane. Ethylene polymerization was performed using the immobilized catalyst and the nanocomposite of ultrahigh molecular weight polyethylene (UHMWPE)/GO with less entanglement density was obtained. It was observed that the drawability, mechanical and thermal properties of the produced polymer significantly are affected by the anchoring of polymer chains to the GO nanosheets. The orientation and location of crystalline lamellae and nanosheets were verified by microscopic techniques. Besides, X-ray analysis demonstrated the dispersion of GO within the UHMWPE phase and crystallinity of UHMWPE/GO nanocomposites enhanced during drawing process.     

Optimizing the location of the gas injection well during gas assisted gravity drainage in a fractured carbonate reservoir using artificial intelligence

Gas assisted gravity drainage (GAGD) is a novel subdivision of gas injection method. In this method the injection wells are located in the upper bed of the oil zone, and the production wells are drilled at the bottom bed of the oil zone. Reservoir simulation is among the decision tools for investigating production rate and selecting the best scenarios for developing the oil and gas fields. Selecting the location of the injection wells for reaching the optimized pressure and production rate is one of the most significant challenges during the injection process. Recent experiences have shown that artificial intelligence (AI) is a reliable solution for taking the mentioned decision appropriately and in a least possible time. This study is attributed to the investigation of applying the artificial neural network (ANN) as an artificial intelligence method and a potent predictor for choosing the most proper location for injection in a GAGD process in a fractured carbonate reservoir. The results of this investigation clearly show the efficiency of the ANN as a powerful tool for optimizing the location of the injection wells in a GAGD process. The comparison between the results of ANN and black oil simulator indicated that the predictions obtained from the ANN is highly reliable. In fact the production flow rate and pressure can be obtained in every possible location of the injection well.     

A fast response hafnium selective polymeric membrane electrode based on N,N'-bis(alpha-methyl-salicylidene)-dipropylenetriamine as a neutral carrier

In this study a new hafnium selective sensor was fabricated from polyvinylchloride (PVC) matrix membrane containing neutral carrier N,N'-bis(alpha-methyl-salicylidene)-dipropylenetriamine (Mesaldpt) as a new ionophore, sodium tetraphenyl borate (NaTPB) as anionic discriminator and dioctyl phthalate (DOP) as plasticizing solvent mediator in tetrahydrofuran solvent. The electrode exhibits Nernstian response for Hf(4+) (Hafnium(IV)) over a wide concentration range (2.0 x 10(-7) to 1.0 x 10(-1)M) with the determination coefficient of 0.9966 and slope of 15.1+/-0.1 mVdecades(-1). The limit of detection is 1.9 x 10(-7)M. The electrode has a fast response time of 18s and a working pH range of 4-8. The proposed membrane shows excellent discriminating ability towards Hf(4+) ion with regard to several alkali, alkaline earth transition and heavy metal ions. It can be used over a period of 1.5 months with good reproducibility. It is successfully applied for direct determination of Hf(4+) in solutions by standard addition method for real sample analysis.     

Low temperature functional analysis of bitumen modified with composite of nano-SiO2 and styrene butadiene styrene polymer

Most parts of Iran have completely different climates in different seasons of year. In other words, in summer it is very warm and in winter it becomes very cold. Achieving modified bitumen that could function adequately in both high and low temperature has always been under attention of researchers. One of bitumen modifiers is styrene butadiene styrene polymer. Because bitumen modified by styrene butadiene styrene does not show expected field function in both high and low temperatures, largely due to phase separation of bitumen and polymer, in the present study it has been tried to analyze the low-temperature function of bitumen modified by combining nano-SiO₂ and styrene butadiene styrene polymer. The study reveals that adding nano-SiO₂ by 3% and 4% of bitumen weight to the double combination of bitumen and styrene butadiene styrene polymer has improved its function in low temperature. This study has innovation as it deals with the analysis of low temperature function of nano-SiO₂ and SBS in modification of bitumen for the first time in the world.     

Antiproliferative and antioxidative activities of cuttlefish (<Emphasis Type="Italic">Sepia pharaonis</Emphasis>) protein hydrolysates as affected by degree of hydrolysis

Bioactivities (including antioxidative and antiproliferative properties) of cuttlefish mantle protein hydrolysates (CPH) with the degree of hydrolysis (DH) of 20.9, 25.5, 30.6, 35.3 and 40.6% (shortened as 20, 25, 30, 35 and 40%, respectively) prepared using alcalase were evaluated. The results indicated that the CPH with 20, 30 and 40% DH showed the greatest activity against DPPH radical scavenging [5.2 µmol TE (torolox equivalent)/g sample], reducing power (0.4 absorbance at 700 nm) and total antioxidant capacity (0.6 mg ascorbic acid equivalent/g sample), which were 2.5, 6.5 and 13.8 times higher than the cuttlefish mantle protein isolate (CPI), respectively. The CPH with the DH of 20% had the highest effect against MDA-231 and T47D cancer cell lines with growth inhibition of 78.2 and 66.2%, which were 6.5 and 6 times higher activities compared to the CPI, respectively. The amino acid profile of CPH indicated that glutamine (15.7%) and asparagine (10.9%) were predominant.     

Liquefaction assessment using microtremor measurement,conventional method and artificial neural network (Case study: Babol,Iran)

Recent researchers have discovered microtremor applications for evaluating the liquefaction potential. Microtremor measurement is a fast, applicable and cost-effective method with extensive applications. In the present research the liquefaction potential has been reviewed by utilization of microtremor measurement results in Babol city. For this purpose microtremor measurements were performed at 60 measurement stations and the data were analyzed by suing Nakmaura’s method. By using the fundamental frequency and amplification factor, the value of vulnerability index (K _g ) was calculated and the liquefaction potential has been evaluated. To control the accuracy of this method, its output has been compared with the results of Seed and Idriss [1] method in 30 excavated boreholes within the study area. Also, the results obtained by the artificial neural network (ANN) were compared with microtremor measurement. Regarding the results of these three methods, it was concluded that the threshold value of liquefaction potential is K _g = 5. On the basis of the analysis performed in this research it is concluded that microtremors have the capability of assessing the liquefaction potential with desirable accuracy.     

Application of fuzzy c-means algorithm as a novel method to predict density of mixtures of Athabasca bitumen and heavy n-alkane

The significant number of oil reservoir are bitumen and heavy oil. One of the approaches to enhance oil recovery of these types of reservoir is dilution of reservoir oil by injection of a solvent such as tetradecane into the reservoirs to modify viscosity and density of reservoir fluids. In this investigation, an effective and robust estimating algorithm based on fuzzy c-means (FCM) algorithm was developed to predict density of mixtures of Athabasca bitumen and heavy n-alkane as function of temperature, pressure and weight percent of the solvent. The model outputs were compared to experimental data from literature in different conditions. The coefficients of determination for training and testing datasets are 0.9989 and 0.9988. The comparisons showed that the proposed model can be an applicable tool for predicting density of mixtures of bitumen and heavy n-alkane.     

Modeling the free convection heat transfer in a partitioned cavity using ANFIS

In this paper, an adaptive neuro-fuzzy inference system (ANFIS) is used to predict the free convection in a partitioned cavity consisting of an adiabatic partition. The main focus of the present paper is to consider the effects of partition angle and Rayleigh number variation on average heat transfer in the partitioned cavity. The training data for optimizing the ANFIS structure is obtained experimentally. For the best ANFIS structure obtained in this study, the mean relative errors of the train and test data were found to be 0.055% and 1.735% respectively, which shows that ANFIS can predict the experimental results precisely.     

Fuzzy modeling of the forced convection heat transfer from a V‐shaped plate exposed to an air slot jet

This paper focuses on the application of fuzzy logic (FL) to predict the forced convection heat transfer from V‐shaped plate internal surfaces exposed to an air impingement slot jet. The aim of the present paper is to consider the effects of the angle of a V‐shaped plate (Φ), slot‐to‐plate spacing ratio (Z/W), and Reynolds number (Re) variation on average heat transfer from the V‐shaped plate internal surfaces. The data used for developing the FL structure was obtained experimentally by a Mach‐Zehnder interferometer. The proposed FL was developed using MATLAB functions. It was observed that the average Nusselt number will be decreased with an increase in jet spacing and be increased with an increase in Reynolds number and angle of V‐shaped plate. Moreover, it is also shown that fuzzy logic is a powerful technique to use for predicting heat transfer due to its low error rate. The average error of the fuzzy predictions compared with experimental data was found to be 0.33% for this study. © 2012 Wiley Periodicals, Inc. Heat Trans Asian Res; Published online in Wiley Online Library ( wileyonlinelibrary.com/journal/htj ). DOI 10.1002/htj.21009     

The evaluation of autothermal methane reforming for hydrogen production over Ni/CeO2 catalysts

Nanocrystalline Ni/CeO₂ catalysts with various loadings of Ni (10, 15, 20, and 25%) were synthesised by a facile solvent deficient precipitation method for methane autothermal reforming process. The characterisation techniques such as XRD, BET, TPH, H₂-TPR were carried out on fresh and spent samples to investigate the catalytic properties of the Ni/CeO₂. On the basis of characterisation results, the 20% Ni/CeO₂ performs the best activity among the catalysts with different Ni contents. The optimal reaction conditions for autothermal methane reforming has been investigated by evaluating the effect of reaction parameters including the reactivity temperature, the gas hourly space velocity (GHSV) and H₂O/CH₄ (S/C) and O₂/CH₄ (O/C) molar ratios. The stability of 20 wt% Ni/CeO₂ catalyst at 700 °C is examined for 20 h on-stream reaction. It reveals that the methane conversion starts a graduate decrease trend from the second 10 h, which is found to be because of the sintering of Ni nanoparticles by TPH and BET analysis.