Application of Metaheuristic Algorithms for Optimizing Longitudinal Square Porous Fins

The objectives of this study involve the optimization of longitudinal porous fins of square cross-section using metaheuristic algorithms. A generalized nonlinear ordinary differential equation is derived using Darcy and Fourier’s laws in the energy balance around a control volume and is solved numerically using RFK 45 method. The temperature of the base surface is higher than the fin surface, and the fin tip is kept adiabatic or cooled by convection heat transfer. The other pertinent parameters include Rayleigh number (100 ≤ Ra ≤ 10⁴), Darcy number, (10⁻⁴ ≤ Da ≤ 10⁻²), relative thermal conductivity ratio of solid phase to fluid (1000 ≤ k_r ≤ 8000), Nusselt number (10 ≤ Nu ≤ 100), porosity (0.1 ≤ φ ≤ 0.9). The impacts of these parameters on the entropy generation rate are investigated and optimized using metaheuristic algorithms. In computer science, metaheuristic algorithms are one of the most widely used techniques for optimization problems. In this research, three metaheuristic algorithms, including the firefly algorithm (FFA), particle swarm algorithm (PSO), and hybrid algorithm (FFA-PSO) are employed to examine the performance of square fins. It is demonstrated that FFA-PSO takes fewer iterations and less computational time to converge compared to other algorithms.     

Feasibility-Guided Constraint-Handling Techniques for Engineering Optimization Problems

The particle swarm optimization (PSO) algorithm is an established nature-inspired population-based meta-heuristic that replicates the synchronizing movements of birds and fish. PSO is essentially an unconstrained algorithm and requires constraint handling techniques (CHTs) to solve constrained optimization problems (COPs). For this purpose, we integrate two CHTs, the superiority of feasibility (SF) and the violation constraint-handling (VCH), with a PSO. These CHTs distinguish feasible solutions from infeasible ones. Moreover, in SF, the selection of infeasible solutions is based on their degree of constraint violations, whereas in VCH, the number of constraint violations by an infeasible solution is of more importance. Therefore, a PSO is adapted for constrained optimization, yielding two constrained variants, denoted SF-PSO and VCH-PSO. Both SF-PSO and VCH-PSO are evaluated with respect to five engineering problems: the Himmelblau’s nonlinear optimization, the welded beam design, the spring design, the pressure vessel design, and the three-bar truss design. The simulation results show that both algorithms are consistent in terms of their solutions to these problems, including their different available versions. Comparison of the SF-PSO and the VCH-PSO with other existing algorithms on the tested problems shows that the proposed algorithms have lower computational cost in terms of the number of function evaluations used. We also report our disagreement with some unjust comparisons made by other researchers regarding the tested problems and their different variants.     

Energy-Efficient Low-Complexity Algorithm in 5G Massive MIMO Systems

Energy efficiency (EE) is a critical design when taking into account circuit power consumption (CPC) in fifth-generation cellular networks. These problems arise because of the increasing number of antennas in massive multiple-input multiple-output (MIMO) systems, attributable to inter-cell interference for channel state information. Apart from that, a higher number of radio frequency (RF) chains at the base station and active users consume more power due to the processing activities in digital-to-analogue converters and power amplifiers. Therefore, antenna selection, user selection, optimal transmission power, and pilot reuse power are important aspects in improving energy efficiency in massive MIMO systems. This work aims to investigate joint antenna selection, optimal transmit power and joint user selection based on deriving the closed-form of the maximal EE, with complete knowledge of large-scale fading with maximum ratio transmission. It also accounts for channel estimation and eliminating pilot contamination as antennas M → ∞. This formulates the optimization problem of joint optimal antenna selection, transmits power allocation and joint user selection to mitigate inter-cell-interference in downlink multi-cell massive MIMO systems under minimized reuse of pilot sequences based on a novel iterative low-complexity algorithm (LCA) for Newton’s methods and Lagrange multipliers. To analyze the precise power consumption, a novel power consumption scheme is proposed for each individual antenna, based on the transmit power amplifier and CPC. Simulation results demonstrate that the maximal EE was achieved using the iterative LCA based on reasonable maximum transmit power, in the case the noise power is less than the received power pilot. The maximum EE was achieved with the desired maximum transmit power threshold by minimizing pilot reuse, in the case the transmit power allocation ρ_d = 40 dBm, and the optimal EE = 71.232 Mb/j.     

Using remotely sensed and ancillary data to predict spatial variability of rainfed crop yield

Rainfed agriculture is dominant in Sudan. The current methods for crop yield estimation are based on taking random cutting samples during harvesting time. This is ineffective in terms of cost of information and time. The general objective of this study is to highlight the potential role of remote-sensing techniques in upgrading methods of monitoring rainfed agricultural performance. The specific objective is to develop a relationship between satellite-derived crop data and yield of rainfed sorghum. The normalized difference vegetation index (NDVI), rainfall, air temperature (AT) and soil moisture (SM) are used as independent variables and yield as a dependent variable. To determine the uncertainty associated with the independent variables, a sensitivity analysis (SA) is conducted. Multiple models are developed using different combinations of data sets. The temporal images taken during sorghum’s mid-season growth stage give a better prediction than those taken during its development growth stage. Among predictor variables, SM is associated with the highest uncertainty.     

A novel technique for separating glycerine from palm oil-based biodiesel using ionic liquids

Biodiesel production from abundant bio-sources has drawn the attention of the academic as well as the industrial communities in recent years. However, one of the most serious obstacles for using biodiesel as an alternative fuel is the complicated and costly purification processes involved in its production. The difficulties involved in the separation of glycerine and other un-reacted reactants and by-products necessitate the development of new competent low cost separation processes for this purpose. In this work, a low cost quaternary ammonium salt-glycerine-based ionic liquid is proposed as a solvent for extracting glycerine from the transesterification biodiesel product. The separation technique was tested on palm oil-based produced biodiesel with KOH as a reaction catalyst. The study investigated the effect of DES:biodiesel ratio and the DES composition on the efficiency of the extraction process. The lab scale purification experiments proved the viability of the separation technique with a best DES:biodiesel molar ratio of 1:1 and a DES molar composition of 1:1 (salt:glycerine). The purified biodiesel fulfilled the EN 14214 and ASTM D 6751 standard specifications for biodiesel fuel in terms of glycerine content. A continuous separation process is suggested for industrial scale application.     

Mitigating Pilot Contamination for Channel Estimation in Multi-cell Massive MIMO Systems

Massive multiple-input multiple-output (MIMO) is a crucial technology platform for the fifth-generation of cellular systems (5G). However, massive MIMO systems are affected by pilot contamination, which influences the data rate of the system. This contamination is caused by the non-orthogonality of the pilot sequences transmitted by users in a cell similar to the neighboring cells. The current study proposes a channel-estimation scheme that employs comprehensive knowledge of large-scale gained by applying an orthogonal pilot reuse sequence to eliminate pilot contamination in edge users with reduced channel quality based on the approximation of large-scale fading, and the performance of this scheme is evaluated using the maximum ratio transmission and zero-forcing precoding techniques. Largely interfering users in neighboring cells are established based on an estimation of large-scale fading, and these users are included in the joint channel processing. The channel quality of users is enhanced by allocating orthogonal pilot reuse sequences to the center user and the edge users based on their levels of pilot contamination estimated from the large-scale fading to mitigate this problem when the number of antenna elements M is infinite. The findings of the simulation indicate that improved channel approximation and reduced performance loss could lead to a high data rate.

     

Energy-Efficient Power Allocation with Hybrid Beamforming for Millimetre-Wave 5G Massive MIMO System

Wireless Personal Communications - Massive multiple-input and multiple-output systems combined with hybrid beamforming technique is a key approach to achieve high data rate and extended cell...     

Graft Copolymerization onto Starch–I. Synthesis and Optimization of Starch Grafted with N-tert-Butylacrylamide Copolymer and its Hydrogels

Grafting of N-tert-butylacrylamide (BAM) onto starch in aqueous medium initiated by ceric ammonium nitrate ion has been studied under N₂ atmosphere. The optimum conditions with respect to monomer concentration, initiator concentration, polymerization temperature, polymerization time and material to liquor ratio were studied in terms of percent of grafting efficiency (%GE) and percent of grafting yield (%GY). The optimum conditions obtained for the grafting of BAM on 1.0 g starch were: [BAM]=0.020 mol/L, [CAN]=0.91×10^–3 mol/L, Temperature=30C, and Time=240 min. Starch-g-BAM copolymer was characterized by FTIR, TGA for thermal stability, X-ray diffraction (XRD) for the crystallinity and scanning electron microscope (SEM) for surface morphology of the copolymer. Acid hydrolysis and viscosity average molecular weight (M _v) of copolymer were evaluated for the copolymer. Hydrogels prepared by grafting of BAM onto gelatinized starch showed maximum water uptake and moisture retain of 162% and 63% respectively.