Preparation,characterization, viscosity,and thermal conductivity of nitrogen-doped graphene aqueous nanofluids

Nanofluids perform a crucial role in the development of newer technologies ideal for industrial purposes. In this study, Nitrogen-doped graphene (NDG) nanofluids, with varying concentrations of nanoparticles (0.01, 0.02, 0.04, and 0.06 wt%) were prepared using the two-step method in a 0.025 wt% Triton X-100 (as a surfactant) aqueous solution as a base. Stability, zeta potential, thermal conductivity, viscosity, specific heat, and electrical conductivity of nanofluids containing NDG particles were studied. The stability of the nanofluids was investigated by UV–vis over a time span of 6 months and concentrations remain relatively constant while the maximum relative concentration reduction was 20 %. The thermal conductivity of nanofluids was increased with the particle concentration and temperature, while the maximum enhancement was about 36.78 % for a nanoparticle loading of 0.06 wt%. These experimental results compared with some theoretical models including Maxwell and Nan’s models and observed a good agreement between Nan’s model and the experimental results. Study of the rheological properties of NDG nanofluids reveals that it followed the Newtonian behaviors, where viscosity decreased linearly with the rise of temperature. It has been observed that the specific heat of NDG nanofluid reduced gradually with the increase of concentration of nanoparticles and temperature. The electrical conductivity of the NDG nanofluids enhanced significantly due to the dispersion of NDG in the base fluid. This novel type of fluids demonstrates an outstanding potential for use as innovative heat transfer fluids in medium-temperature systems such as solar collectors.     

Combined Computational and Experimental Study on the Adsorption and Inhibition Effects of N2O2 Schiff Base on the Corrosion of API 5L Grade B Steel in 1 mol/L HCI

The electrochemical behavior of low carbon steel （API 5L grade B） in 1 mol/L HCI solution with different concentrations of N,Nr-bis（4-formylphenol）-trimethylenediamine Schiff base was studied by electrochemical techniques and density functional theory analysis. The inhibition efficiency was found to increase with increasing inhibitor concentration and decreased with increasing temperature. The high inhibition efficiency was attributed to the blocking of active sites by adsorption of inhibitor molecules on the steel surface. Thermodynamic parameters for the adsorption and activation processes were determined. Galvanostatic polarization data indicated that Schiff base act as a mixed-type inhibitor and the adsorption isotherm obeyed the Langmuir adsorption isotherm. Results obtained from quantum chemical studies show excellent correlations between the quantum chemical parameters and the experimental inhibition efficiencies using density functional theory at the B3LYP/6-31G（d,p） and B3LYP/3-21G basis set levels and ab initio calculations using HF/6-31G（d,p） and HF/3-21G methods.     

An Integrated Approach for Enhancing the Quality of the Product by Combining Robust Design and Customer Requirements

Enhancing the quality of the product has always been one considerable concern of production process management, and this subject gave way to implementing so many methods including robust design. In this paper, robust design utilizes response surface methodology (RSM) considering the mean and variance of the response variable regarding system design, parameter design, and tolerance design. In this paper, customer requirements and robust design are regarded simultaneously to achieve enriched quality. Subsequently, with a non‐linear programming, a novel method for integrating RSM and quality function deployment has been proposed to achieve robustness in design. The customer requirements are regarded in every stage of product development process meaning system design, parameter design and tolerance design. To validate the applicability of the proposed approach, it has been implemented in a real case of chemical industry. Research findings show that the proposed method is much better than other existing methods including MSE and dual response methods. According to this method, the resulted mean is better than MSE method, and more importantly, the variance of the process is approximately 14% and 10% lesser than dual response and MSE method. Copyright © 2013 John Wiley & Sons, Ltd.     

Minimizing torque ripple in a brushless DC motor with fuzzy logic: applied to control rod driving mechanism of MNSR

A permanent magnet BLDC(brushless direct current) motor is used to move the control rod of a miniature neutron source reactor(MNSR). The BLDC motor drive is modeled using MATLAB/SIMULINK. Two main parts of the modeling are the inverter switching and the current control. Current control with chopping used to minimize the torque ripple of the MNSR control rod drive. Fuzzy logic current control together with soft chopping control shows the best response of all the three strategies. The prototype drive mechanism has an ATmega32 controller and power MOSFET switches. The simulation results are compared with experimental drive mechanism.     

Classification of acoustic emission signals collected during tensile tests on unidirectional ultra high molecular weight polypropylene fiber reinforced epoxy composites using principal component analysis

The objective of this study is to utilize a mathematical procedure for the evaluation of damage mechanism in ultra high molecular weight polypropylene/epoxy composite (UHMWPP/epoxy) specimen with different configuration based on the analysis of the AE signals of presented. Principal component analysis (PCA) is powerful tool, which utilized for the classification of the monitored AE transients. We worked on epoxy L160 resin, UHMWPP fiber bundle and UHMWPP/epoxy unidirectional specimens, subjected to tensile loading. Using model specimens exhibiting a predominant damage mechanism, correlations were established between the observed damage growth mechanisms and the AE parameter variances result in PCA. Outputs from this study revealed that the PCA is an effective tool for identifying damage modes such as matrix cracking, fibre/matrix debonding, fibre breakage and fibre pull-out in the UHMWPP/epoxy composites. The presence of damage modes in UHMWPP/epoxy composites was proven with scanning electron microscopy (SEM) images.     

Analysis of nonpremixed multiregion laminar flames through biofuel porous particles considering the effect of heat recirculation

In this study, a comprehensive analysis is conducted to evaluate the effects of heat recirculation and particle porosity on combustion characteristics of multizone counterflow nonpremixed flames fed with porous biofuel particles. For this purpose, the structure of flame contains preheat, postvaporization, and oxidizer zones. Additionally, Lycopodium is considered as the volatile biofuel, especially due to its appreciable flammability and dispensability. Dimensionalized and nondimensionalized forms of mass and energy conservation equations are scrutinized in each zone. To explore of the thermal recirculation effect, a specific term is included in the energy conservation equation. The variation of several parameters, including flame temperature, particle radius, mass fraction of the gaseous fuel and oxidizer, mass particle content, equivalence ratio, and particle porosity, is studied in this work considering and ignoring the thermal recirculation impact. As a result, increasing heat recirculation coefficient from $k=0$ to 1 will rise the flame temperature and shift the flame position to the left side (fuel nozzle). Furthermore, consideration of the thermal heat recirculation will improve the gaseous fuel production in the preheat and postvaporization zones. Additionally, an increase in mass concentration and reduction of particles radius and porosity would lead to a rise in the flame temperature.     

Natural production, storage, and utilization of ice in deep ponds for summer air conditioning

A design is proposed to improve the performance of wind towers (or Baud-Geers) for natural ventilation and passive cooling. Under similar climatological and design conditions, the new design is capable of delivering air to the building at higher flow rates. It can also cool the air evaporatively to lower temperatures. Higher airflow rates and the evaporative cooling capability of the new Baud-Geer design can be fully utilized at nigh in summer to cool the building mass to lower temperatures.Momentum, mass and energy analyses are carried out for the proposed design. The results are presented in graphical forms which may be used as guidelines for employing the design for specific applications in the hot, arid areas of the world. An example is worked out to show the use of the results.     

Oil pricing policies and macroeconomy for an oil-based economy

This paper analyses the oil pricing policies for an oil-based economy within a national planning framework. It contains a total asset maximization problem in the non-oil sector and a macroeconomic model. The main conclusion is that Hotelling's r-percent rule fails to apply for an oil-based nation if the minimum-import constraint becomes binding. Therefore, the difference between the marginal revenue growth rate and the yield on domestic investment turns down when the import constraint is binding and then it goes through several cycles before it turns up as the constraint is non-binding over the planning horizon.     

Dipyridamole recognition and controlled release by uniformly sized molecularly imprinted nanospheres

We used novel synthetic conditions of precipitation polymerization to obtain uniformly sized molecularly imprinted nanospheres of dipyridamole for application in the design of new drug delivery systems. In addition, the morphology, drug release, and binding properties of molecularly imprinted polymers (MIPs) were studied, and the effects of morphology on other properties were investigated. The MIPs prepared by acetonitrile/chloroform (19:1, v/v) were uniformly sized nanospheres with an average mean diameter of approximately 88 nm at a wetted state, 50 nm at a dry state, and a polydispersity index of 0.062. The imprinted nanospheres showed excellent binding properties and had 62.7% of template binding compared with 17.1% of its blank polymer. The imprinted nanospheres with 67.5 (mg template/of polymer) of binding capacity had better imprinting efficiency than the 50.5% of binding capacity shown by irregularly shaped MIP particles that were prepared by chloroform. The molecular binding abilities of imprinted nanospheres in human serum were evaluated by HPLC analysis (binding about 77% of dipyridamole). Results from release experiments of MIPs showed a very slow, controlled, and satisfactory release of dipyridamole. The loaded drug was released up to 99% in 17 days for nanospheres and 22 days for irregularly shaped particles.     

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.