Study of Adsorption/Desorption Effect of 2-Mercaptobenzothiazole as Sweet Corrosion Inhibitor on API-5L X60 Steel

Protection of Metals and Physical Chemistry of Surfaces - In this study, the inhibitive performance of 2-mercaptobenzothiazole (2MBT) and 2-aminobenzothiazole (2ABT) were investigated on API-5L X60...     

Improved formic acid oxidation using electrodeposited Pd–Cd electrocatalysts in sulfuric acid solution

In the present research, nanostructured Pd–Cd alloy electrocatalysts with different compositions were produced using the electrodeposition process. The morphology of the samples was studied by scanning electron microscopy analysis. Also, the elemental composition of the samples was determined by energy-dispersive X-ray spectroscopy and elemental mapping tests. Tafel polarization and electrochemical impedance spectroscopy methods were employed to determine the electrochemical corrosion properties of the synthesized samples in a solution containing 0.5 M sulfuric acid and 0.1 M formic acid. The linear sweep voltammetry, cyclic voltammetry, and chronoamperometry techniques were also employed to evaluate the electrocatalytic activity of prepared samples toward the oxidation of formic acid. In this respect, the influence of some factors such as formic acid and sulfuric acid concentrations and also potential scan rate was investigated. Compared to the pure Pd sample, the Pd–Cd samples were more reactive for the oxidation of formic acid. Besides, the sample with a lower amount of Pd (Pd_1·3Cd) demonstrated much higher electrocatalytic activity than the Pd_7·1Cd and Pd_2·1Cd samples. The observed high mass activity of 15.06 A mg^?1_Pd for the Pd_1·3Cd sample which is 21.1 times higher than Pd/C is an interesting result of this study.     

Learning nonlinear dynamics with behavior ordinary/partial/system of the differential equations: looking through the lens of orthogonal neural networks

In this paper, size-dependent dynamic stability of axially loaded functionally graded (FG) composite truncated conical microshells with magnetostrictive facesheets surrounded by nonlinear viscoelastic foundations including a two-parameter Winkler–Pasternak medium augmented via a Kelvin–Voigt viscoelastic approach is analyzed considering nonlinear cubic stiffness. To this purpose, von Karman-type kinematic nonlinearity along with modified couple stress theory of elasticity was applied to third-order shear deformation conical shell theory in the presence of magnetic permeability tensor and magnetic fluxes. The numerical technique of generalized differential quadrature (GDQ) was used for the solution of microstructural-dependent dynamic stability responses of FG composite truncated conical microshells. It was seen that moving from prebuckling to postbuckling domain somehow increased the significance of couple stress type of size dependency on frequency. In addition, within both prebuckling and postbuckling regimes, an increase of material gradient index decreased the importance of couple stress type of size dependency on the frequency of an axially loaded FG composite truncated conical microshell. Furthermore, it was revealed that by applying a positive magnetic field to an axially loaded truncated conical microshell with magnetostrictive facesheets, its frequency at a specific axial load value was increased in prebuckling domain and decreased in postbuckling domain. However, this pattern was reversed by applying a negative magnetic field.

     

Fuzzy logic controller and cascade inverter for direct torque control of IM

In this paper, a five-level cascaded H-bridge multilevel inverters topology is applied on induction motor control known as direct torque control (DTC) strategy. More inverter states can be generated by a five-level inverter which improves voltage selection capability. This paper also introduces two different control methods to select the appropriate output voltage vector for reducing the torque and flux error to zero. The first is based on the conventional DTC scheme using a pair of hysteresis comparators and look up table to select the output voltage vector for controlling the torque and flux. The second is based on a new fuzzy logic controller using Sugeno as the inference method to select the output voltage vector by replacing the hysteresis comparators and lookup table in the conventional DTC, to which the results show more reduction in torque ripple and feasibility of smooth stator current. By using Matlab/Simulink, it is verified that using five-level inverter in DTC drive can reduce the torque ripple in comparison with conventional DTC, and further torque ripple reduction is obtained by applying fuzzy logic controller. The simulation results have also verified that using a fuzzy controller instead of a hysteresis controller has resulted in reduction in the flux ripples significantly as well as reduces the total harmonic distortion of the stator current to below 4 %.     

Preparation and characterization of poly(vinyl alcohol)/gum tragacanth/cellulose nanocomposite film

The effects of gum tragacanth obtained from two species of Astragalus Gossypinus (GT-G) and A. Parrowianus (GT-P) at two levels of 10% and 30% combined with cellulose nanofibers (CNF; 5%) on the physico-mechanical and structural properties of polyvinyl alcohol (PVA) nanocomposite film were investigated in this study. The water solubility and water vapor permeability of the films decreased with increasing the content of both gums, especially in the film containing 30% GT-P. The highest values of the tensile strength (39.3 MPa) and elongation at break (445%) belonged to the treatment containing 10% GT-P (90/10P/0). The FTIR and DSC analyses confirmed good interactions between GT and PVA in the 90/10P/0 treatment. SEM images indicated the dense structure of this film as the optimum treatment. Although the presence of CNF in the films containing GT-G improved some properties, especially the Young modulus, it impaired all the functional properties of nanocomposite GT-P film.     

A pseudo-spectral scheme for the approximate solution of a time-fractional diffusion equation

We consider an initial-boundary-value problem for a time-fractional diffusion equation with initial condition u₀(x) and homogeneous Dirichlet boundary conditions in a bounded interval [0, L]. We study a semidiscrete approximation scheme based on the pseudo-spectral method on Chebyshev–Gauss–Lobatto nodes. In order to preserve the high accuracy of the spectral approximation we use an approach based on the evaluation of the Mittag-Leffler function on matrix arguments for the integration along the time variable. Some examples are presented and numerical experiments illustrate the effectiveness of the proposed approach.     

A C5 parallel robot identification and control

The paper proposes a controller scheme based on a priori identification for a C5 parallel robot. First we realize the identification of dynamic parameters of the robot using the Least Squares technique. Different data are used for this step of identification. The cross validation permitted to select and confirm the identified parameters. After, a control scheme (computed torque) is applied to control the C5 parallel robot. The functions of this control scheme are based on precedent identified parameters. In order to reduce the effect of the identification error, we have added a robustness term based on sliding mode technique. The stability of the system in closed loop is presented using the Lyapunov principle. Experimental results of identification and control are presented and show the effectiveness of our methodology.     

Analysis and forecasting of IPO underpricing

Probability of withdrawal is a feature of initial public offering (IPOs), which can be an important parameter in decisions of investors and issuers. Considering the probability of offering withdrawal facilitates more precise estimation of underpricing. In this paper, the effective factors on probability of IPO withdrawal and underpricing in Tehran Stock Exchange have been characterized using regression, and then neural network is applied to estimate the probability of IPO withdrawal and underpricing. To evaluate the performance of our applied method, fuzzy regression is employed and compared with neural network. According to the obtained empirical results, neural network demonstrates better accuracy than fuzzy regression. The results indicate that there is a meaningful relationship between underpricing and probability of withdrawal, and the probability of IPO withdrawal plays an important role in precise evaluation of underpricing.