A Computational Study on the Reduction Behavior of Iron Ore/Carbon Composite Pellets in Both Single and Multi-layer Bed Rotary Hearth Furnace

Metallurgical and Materials Transactions B - A phenomenological model for the reduction of iron ore/carbon composite pellets in a multi-layer bed rotary hearth furnace has been developed. A single...     

Analysis of Relay Based D2D System with Fluctuating Beckmann Fading

Wireless Personal Communications - In this paper, performance of a relay-based device-to-device (D2D) communication system over a Fluctuating Beckmann (FB) fading channel is analysed. FB fading...     

Performance analysis of M‐APSK generalised spatial modulation with constellation reassignment

Generalised spatial modulation (GSM) is a recently developed multiple‐input multiple‐output (MIMO) technique aimed at improving data rates over conventional spatial modulation (SM) systems. However, for identical antenna array size and configurations (AASC), the bit error rate (BER) of GSM systems in comparison with SM systems is degraded. Recently, a GSM system with constellation reassignment (GSM‐CR) was proposed in order to improve the BER of traditional GSM systems. However, this study focused on M‐ary quadrature amplitude modulation (M‐QAM) schemes. The focus of this paper is the application of a circular constellations scheme, in particular, amplitude phase shift keying (APSK) modulation, to GSM and GSM‐CR systems. An analytical bound for the average BER of the proposed M‐APSK GSM and M‐APSK GSM‐CR systems over fading channels is derived. The accuracy of this bound is verified using Monte Carlo simulation results. A 4 × 4 16‐APSK GSM‐CR system achieves a gain of 2.5 dB at BER of 10^?5 over the traditional 16‐APSK GSM system with similar AASC. Similarly, a 6 × 4 32‐APSK GSM‐CR system achieves a gain of 2 dB at BER of 10^?5 over equivalent 32‐APSK GSM system.     

New multicriteria group decision support systems for small hydropower plant locations selection based on intuitionistic cubic fuzzy aggregation information

There has been a quick development in construction activities during the last couple of decades attributable to a general improvement in all features of humankind. Because of innovative progressions and regularly expanding human progress, there is a diligent requirement of power. Close by the ordinary energy sources, renewable energy sources have likewise lead significantly to the rising power requirement. All over the world in the past, a number of small hydropower plants (SHPPs) have been developed, as a renewable energy source. Generally, these SHPPs are being manufactured and worked by the private designers consenting to the administration rules. So as to help a designer in choosing the most productive and doable SHPP for development and consequent activity, the concept of the intuitionistic cubic fuzzy set (ICFS) theory is established and a few important operations for ICFSs are characterized, and also a strategy dependent on intuitionistic cubic fuzzy Hamacher hybrid averaging (ICFHHA) operator, intuitionistic cubic fuzzy Hamacher order weighted averaging (ICFHOWA) operator, and intuitionistic cubic fuzzy Hamacher weighted averaging (ICFHWA) operators is utilized in the present paper. The financial criteria and technobusiness, as assumed for examining the practicality of the candidate SHPPs, are presented qualitatively utilizing intuitionistic cubic fuzzy numbers (ICFNs). Further study their fundamental properties and the relationship among these aggregation operators. Developed group decision-making (DM) algorithm under intuitionistic cubic fuzzy (ICF) environment. An interpretative case for the analysis of SHPP for construction is given to demonstrate the feasibility and practicality of the mentioned new techniques. Further validate its effectiveness and benefits via a comparative analysis with pre-existing aggregation operators, and the outcomes demonstrate that the proposed SHPP determination model has some special favorable circumstances, which is progressively practical and adaptable for SHPP choice under a complex and uncertain environment.     

Unsteady nonlinear convection on Eyring–Powell radiated flow with suspended graphene and dust particles

This research contemplates the flow and heat transport of MHD rheological Eyring–Powell fluid embedded with dust and graphene nanoparticles (GP) in an ethylene–glycol (EG) mixture in the presence of nonlinear convection, Cattaneo–Christov heat flux, and thermal radiation. Primarily existing PDEs (fluid and dust phase) are transferred to non-dimensional form by invoking similarity transformations then solved numerically through RKF-45 method. The graphene particles are significantly used in energy transmission in aerospace, power and propulsion generation etc. Through graphical illustrations, velocity and temperature profiles (fluid and dust phases) converse for various prominent parameters. The results of friction factor and heat transfer rate are presented and analyzed. Validation of the present result is made with the existing data. Results demonstrate that increasing nonlinear convection parameter has an inverse relationship with the Nusselt number and the velocity in the dust and fluid phases. This may happen due to the domination of unsteadiness in the flow.

     

Development of a hybrid PSO–ANN model for estimating glucose and xylose yields for microwave-assisted pretreatment and the enzymatic hydrolysis of lignocellulosic biomass

In this paper, two artificial intelligent systems, the artificial neural network (ANN) and particle swarm optimization (PSO), were combined to form a hybrid PSO–ANN model that was used to improve estimates of glucose and xylose yields from the microwave–acid pretreatment and enzymatic hydrolysis of lignocellulosic biomass based on pretreatment parameters. ANN is a powerful tool capable of determining the relationship between the desired input and output data while PSO was used as a robust population-based search algorithm to optimize the performance of the ANN model. Specifically, it was used to determine the optimum number of neurons in the hidden layer and the best value of the learning rate of the ANN model. The optimization method includes minimizing the fitness function mean absolute error that was found to be 0.0176. The PSO algorithm suggested an optimum number of neurons in the hidden layer as 15 and a learning rate of 0.761 these consequently used to construct the ANN model. After constructing the hybrid PSO–ANN model, the performance of the intelligent system was examined by determining the regression coefficient (R ²) for estimating the experimental values of glucose and xylose and compared to the results from a response surface methodology (RSM) model. The results of R ² of the hybrid PSO–ANN model for glucose and xylose were 0.9939 and 0.9479, respectively, while the RSM model results for the same sugars were 0.8901 and 0.8439. This analysis reveals that the hybrid PSO–ANN model offers a higher degree of accuracy in comparison with the more commonly used RSM model.

     

Role of Ni<Superscript>2+</Superscript> Ions in Magnetite Nano-particles Synthesized by Co-precipitation Method

In the present work, nickel-doped iron oxide (Ni_xFe_3?x O ₄) nanoparticles with different concentration of nickel (x = 0, 0.05, 0.1, and 0.15) have been prepared by co-precipitation method. These prepared nanoparticles have been characterized by using x-ray diffractometer, thermo gravimetric analysis and differential scanning calorimetry, Fourier transform infrared spectroscopy, scanning electron microscopy, vibrating sample magnetometer, and UV-Visible spectroscopy to study their structural, thermal, morphological, magnetic, and optical properties, respectively. The x-ray diffraction confirms the formation of single-phase inverse spinel cubic structure of NiFe₃ O ₄ nanoparticles. Crystallite size has been estimated by the full width at half maximum of the most intense x-ray diffraction peak where vibrational and stretching modes of metal-oxygen bonds in 872 cm are shown in Fourier transform infrared spectra which confirms the formation of nanoparticles. The thermal analysis revealed that the transition temperature and stability increases with increasing Ni concentration. The surface morphology indicated that the particles are spherical in shape with some agglomeration. The magnetic measurement revealed that the coercivity and anisotropy increases with nickel doping in magnetite nanoparticles. The optical analysis revealed that direct and indirect both types of band gap increases when the particle size decreases because the absorption spectra shift toward smaller wavelength. The blue shift confirms the formation of nanoparticles.     

Structural,elastic, optoelectronic and magnetic properties of $$\mathbf{CdHo }_\mathbf{2}{} \mathbf{S}_\mathbf{4}$$ spinel: a first-principle study

We report the results of the full-potential linearized augmented plane wave (FP-LAPW) calculations on the structural, elastic, optoelectronic and magnetic properties of \(\hbox {CdHo}_{2}\hbox {S}_{4}\) spinel. Both the generalized gradient approximation (GGA) and Trans-Blaha modified Becke-Johnson potential (TB-mBJ) are used to model the exchange-correlation effects. The computed lattice parameter, internal coordinate and bulk modulus are in good agreement with the existing experimental data. According to the calculated elastic moduli, \(\hbox {CdHo}_{2}\hbox {S}_{4}\) is mechanically stable with a ductile nature and a noticeable elastic anisotropy. The ferromagnetic phase of \(\hbox {CdHo}_{2}\hbox {S}_{4}\) is energetically favourable compared to non-magnetic one, with a high magnetic moment of about 8.15 \(\upmu _{\mathrm{B}}\). The calculated band structure demonstrates that the title compound is a direct band gap semiconductor. The TB-mBJ yields a band gap of \(\sim \)1.86 and \(\sim \)2.17 eV for the minority and majority spins, respectively. The calculated optical spectra reveal a strong response in the energy range between the visible light and the extreme UV regions.     

Cubic fuzzy Einstein aggregation operators and its application to decision-making

In this paper, we define some Einstein operations on cubic fuzzy set (CFS) and develop three arithmetic averaging operators, which are cubic fuzzy Einstein weighted averaging (CFEWA) operator, cubic fuzzy Einstein ordered weighted averaging (CFEOWA) operator and cubic fuzzy Einstein hybrid weighted averaging (CFEHWA) operator, for aggregating cubic fuzzy data. The CFEHWA operator generalises both the CFEWA and CFEOWA operators. Furthermore, we develop various properties of these operators and derive the relationship between the proposed operators and the exiting aggregation operators. We apply CFEHWA operator to multiple attribute decision-making with cubic fuzzy data. Finally, a numerical example is constructed to demonstrate the established approach.     

Switched beam dielectric resonator antenna array with six reconfigurable radiation patterns

A single feed, four element rectangular Dielectric Resonator Antenna (DRA) array, with beam switching capability is proposed. A wide impedance bandwidth of more than 25% at the center frequency of 1.95 GHz is achieved. Each DRA has two excitation strips and four parasitic patches. The six cases are discussed; each case corresponds to a diverse radiation pattern. The antenna beam is switched in azimuth (θ = 45°) at Φ = 0°, 60°, 120°, 180°, 240°, and 300°. The antenna gain is found to be more than 7 dB in most of the frequency band of interest. A passive prototype is developed and tested to validate simulation results. The comparison between the simulated and measured reflection coefficients and the radiation patterns for the six cases is presented. A good agreement between the measured and simulated results is observed. © 2016 Wiley Periodicals, Inc. Int J RF and Microwave CAE 26:519–530, 2016.