Prediction of hydrate equilibrium conditions using k-nearest neighbor algorithm to CO2 capture

Gas or clathrate hydrates are an important issue when they form in the oil and gas pipelines. Since the determination of the hydrate formation temperature and pressure is very difficult experimentally for every gas system and it is impossible in terms of cost and time approximately, mathematical models can be useful tools to overcome these difficulties. In this study, k-nearest neighbor model was used to predict the equilibrium conditions of hydrate formation in absorption and separation of carbon dioxide from flue gas mixture, containing carbon dioxide and nitrogen. At the training phase, temperature and composition data of nitrogen and carbon dioxide in the flue gas mixture at equilibrium conditions and the equilibrium pressures of hydrate formation were used as input and output, respectively. The error percentage less than 0.38% indicates the high accuracy of the proposed model. In this study, 80%, 85%, and 90% of the training data are examined for three numbers of nearest. For three numbers of used nearest (k = 1, k = 2 and k = 3), the value of k = 1 leads to the lowest error; so, it is selected as the best nearest in the presented model.     

3D FEM analysis,dynamic modeling,and performance assessment of transverse flux PMSG for small‐scale gearless wind energy conversion systems

The transverse flux permanent magnet synchronous generator has a great potential for use in direct‐drive wind energy conversion systems due to its large pole numbers, high torque, and power density. This research work develops dynamic model of a single‐side transverse flux permanent magnet synchronous generator for use in a small‐scale gearless wind energy conversion system. For acquiring the parameters of the considered generator, required for dynamic modeling, 3D finite element model of the machine is developed and analyzed in both magneto‐static and transient modes. Field‐oriented control approach is employed for tracking maximum power point from the variable wind speed. The simulation results illustrate an accurate response of the system to the wind speed variation and proper performance of the developed dynamic model and control approach of the system. Copyright © 2015 John Wiley & Sons, Ltd.     

A Novel Evolutionary-Based Cooperative Spectrum Sensing Mechanism for Cognitive Radio Networks

Cognitive radio (CR) is considered as a feasible intelligent technology for 4G wireless networks or self-organization networks and envisioned as a promising paradigm of exploiting intelligence for enhancing efficiency of underutilized spectrum bands. In CR, one of the main concerns is to reliably sense the presence of primary users, to attain protection against harmful interference caused by the potential spectrum access of secondary users (SUs). In this paper, evolutionary algorithms, namely, genetic algorithm (GA) and particle swarm optimization (PSO) are investigated. An imperialistic competitive algorithm (ICA) is proposed to minimize error detection at the common soft data fusion (SDF) center for structurally centralized cognitive radio network (CRN). By using these techniques, evolutionary operations are invoked to optimize the weighting coefficients applied on the sensing measurement components received from multiple cooperative SUs. The proposed method is compared with other evolutionary algorithms, as well as other conventional deterministic, such as maximal ratio combining- (MRC-), modified deflection coefficient- (MDC-), normal deflection coefficient- (NDC-) based SDF schemes and OR-rule HDF based. MATLAB simulations confirm the superiority of the ICA-based scheme over the PSO-, GA-based and other conventional schemes in terms of detection performance. In addition, the ICA-based scheme also shows promising convergence and time running performance as compared to other iterative-based schemes. This makes ICA an adequate solution to meet real-time requirements.     

Chatter instability analysis of spinning micro-end mill with process damping effect via semi-discretization approach

In this paper, the stability of delay differential equations (DDEs), describing self-excited vibrations in a micro-milling process, is investigated based on semi-discretization (SD) method. Due to the stubby geometry of micro-tools, the shear deformation and rotary inertia effects are considered for modeling the structure. The extended Hamilton’s principle is used to derive a detailed dynamical model of the spinning micro-tool with the support of misalignment in which the gyroscopic effects cause coupling of equations. Considering the actual geometry of the micro-end mill, exact dynamic stiffness (DS) formulations are developed to investigate the tool’s free vibration characteristics. The extracted mode shapes obtained from DS method are utilized as base functions in a Galerkin approach. Having considered regenerative cutting force, imposing the Galerkin method reduces the governing PDEs of the system to a set of DDEs. The resulting equations are discretized by means of SD procedure. Finally, numerical Floquet theory is utilized to investigate the stability of the system. Also, the effects of process damping on the stability diagrams are explored. The results show the efficiency of the proposed model and delineate the considerable influence of process damping on the stability borders of the system especially at low spindle speed.     

Probabilistic assessment of torsion in concrete beams externally strengthened with CFRP composites

This paper illustrates an analytical probabilistic study of concrete beams subjected to torsion that are strengthened with carbon fiber reinforced polymer (CFRP). Hii and Al-Mahaidi’s method is one of the best analytical models for evaluating the torsional capacity of CFRP strengthened reinforced concrete beams. The first-order reliability method is carried out to probabilistically assess the capacity of CFRP-strengthened beams. For this aim, the statistical characteristics of design variables and model errors have been considered, followed by the determination of the average reliability indexes of the strengthened beams. The effect of each design variable on the average reliability is also determined. The assessment shows that the Hii and Al-Mahaidi’s analytical model is unconservative. In order to correct the situation, a more relaxed set of resistance factors for use in a load and resistance factor design format are needed. These are then determined for two target reliability levels of $ \beta_{\text T} $  = 3.0 and $ \beta_{\text T} $  = 3.5. It is found that factors of 0.9200 and 0.8225 are needed for target reliability levels, $ \beta_{\text T} $  = 3.0 and $ \beta_{\text T} $  = 3.5, respectively. Values of 0.9 and 0.8 are suggested for use in real practice depending on the target reliability sought.     

Numerical investigation of the mechanism behind the deflagration to detonation transition in homogeneous and inhomogeneous mixtures of H2-air in an obstructed channel

The accidental release of hydrogen into enclosures can result in a flammable mixture with concentration gradients and possible deflagration-to-detonation transition (DDT). This numerical study aims to investigate the effect of obstacle spacing and mixture concentration on the DDT in a homogeneous and inhomogeneous hydrogen-air mixture. The paper focuses on the mechanisms behind the DDT in two mixtures with an average hydrogen concentration of 15% and 30%. Unlike the near-stoichiometric mixture, in the lean mixture, DDT only occurs in the inhomogeneous mixture. Depending on obstacle spacing, three different regimes of DDT were observed in the near-stoichiometric inhomogeneous mixture: i) Detonation was ignited when a strong Mach stem formed and propagated between the obstacles; ii) two explosion centers appeared when incident shock and Mach stem reflected from upper and lower obstacles, respectively; iii) Mach stem did not form but DDT occurred behind the flame front at the top of the obstacle.     

Torsion of strain gradient bars

The governing differential equation and both classical and non-classical boundary conditions of strain gradient bars are derived using variational approach. A closed-form analytical solution is obtained for static torsion and the characteristic equation, which gives the natural frequencies, is derived and analytically solved for the free torsional vibrations of the strain gradient microbars. A fixed-fixed microbar is considered as a specific case to investigate the torsional size-dependent static and free-vibration behavior of strain gradient microbars. The results of the current model are compared to those of the modified couple stress and classical theories.     

Acidic sulphate leaching of chalcopyrite concentrates in presence of pyrite

Copper concentrates with mineralogy dominated by chalcopyrite have slow leaching kinetics at atmospheric pressure in sulphate media because of the formation of passivation layer on its surface during the leaching. To enhance the leaching rate of the copper concentrate, pyrite was added to act as a catalyst. Pyrite and copper sulphide minerals then form a galvanic cell which increases both the copper leaching rate and yield. Effect of parameters such as solution redox potential, temperature, initial acid concentration, solids content, total initial iron concentration and pyrite to copper sulphide minerals mass ratio were investigated. Mineralogical analyses by XRD were performed on selected leach residues and the feed materials. A copper recovery higher than 80% in 24 h was achieved at a redox potential of 410 mV vs Ag, AgCl, a temperature of 85 °C, 15 g/L of initial acid concentration, a solid content of 7.8% (w/v), a total initial iron concentration 5 g/L and pyrite to copper sulphide minerals mass ratio 2:1. XRD patterns on leach residues showed that candidates for surface passivation, i.e. jarosite and elemental sulphur, were formed at high total initial iron concentrations.     

The S-transform using a new window to improve frequency and time resolutions

The S-transform presents arbitrary time series as localized invertible time–frequency spectra. This transformation improves the short-time Fourier transform and the wavelet transform by merging the multiresolution and frequency-dependent analysis properties of wavelet transform with the absolute phase retaining of Fourier transform. The generalized S-transform utilizes a combination of a Fourier transform kernel and a scalable-sliding window. The common S-transform applies a Gaussian window to provide appropriate time and frequency resolution and minimizes the product of these resolutions. However, the Gaussian S-transform is unable to obtain uniform time and frequency resolution for all frequency components. In this paper, a novel window based on the $t$ student distribution is proposed for the S-transform to achieve a more uniform resolution. Simulation results show that the S-transform with the proposed window provides in comparison with the Gaussian window a more uniform resolution for the entire time and frequency range. The result is suitable for applications such as spectrum sensing.