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Go to Editorial ManagerIn this paper, a compact ultra-wide band (UWB) printed patch antenna is designed and optimized using four biologically and plant inspired optimization algorithms. These algorithms are the newly adopted Moss Rose Optimization Algorithm (MROA), Runner Root Algorithm (RRA), Sunflower Optimization Algorithm (SFOA) and Particle Swarm Optimization (PSO). These algorithms are modified in an optimizer software, which merges the attributes of the design of electromagnetic environment of CST Microwave Studio with those of the technical programming environment of MATLAB. A compact (12 × 21.5) mm 2 printed patch antenna has been proposed and simulated over the whole UWB frequency range using these four optimization algorithms. The simulation results show the superiority of the antenna design using MROA, which has the widest covered frequency range, the lowest reflection coefficient and the lowest standing wave ratio.
In this article, a hybrid optimization method has been proposed consisting of Adaptive Genetic Algorithms (AGAs) and Constrained Nonlinear Programming (NLP) to solve the problems of performance optimization of circular array antenna consisting paraOel center feeding short dipoles elements with two complex nonlinear optimization problems. In the first problem. the hybrid optimization algorithm is used to reduce the value of sidelobe level in the circular array radiation pattern by finding the oPtlmal values of the excitation coefficients of each element in the clrcular array. In the second problem, a synthesis of circular array with different forms of the desired radiation pattern is considered. Several examples are considered here to verify the validlty of this method. Comparisons were made between the results of this method and the results obtained by {SGA) Standard Genetic Algorithm, and it is clearly shown that this method is more efficient and flexible in solving the problems of performance optimization of circular array antenna .
Crow Search Algorithm is an innovative meta- heuristic optimization algorithm. In this paper, chaotic maps are combined into Crow Search Algorithm to increase its global optimization. Ten variant chaotic maps are used and the Tent map is found as the best choices for high dimensional problems. The novel Chaotic Crow Search Algorithm is relied on the substitution of a random location of search space and the awareness parameter of crow with chaotic sequences. The results show that the chaotic maps are able to enhance the performance of the Crow Search Algorithm. Also the novel Chaotic Crow Search Algorithm outperforms the conventional Crow Search Algorithm, first version of Chaotic Crow Search Algorithm, Genetic Algorithm, and Particle Swarm Optimization Algorithm from the point view of speed convergence and the function dimensions.
This study presents an attempt for establishment of sustainable development and management policies for utilization of Basrah coastal aquifer. The simulation/optimization approach is used with application to Um-Qasr aquifer in Basrah. In this research, 5 management schemes for sustainable use of a coastal aquifer exposed to seawater intrusion were developed and solved. The objective of the management models is to maximize the total amount of water pumped from the aquifer for beneficial use, and optimum location, numbers and redistribution of wells. Salt concentration of the pumped water from each of the pumping well was considered as a main constraint together with the minimum water head which is considered to control saltwater intrusion by heads balances with time. Solutions of the management schemes are based on a linkage between a simulation module SEAWAT and Simulated Annealing (SA) algorithm optimization module. The heads and concentrations, calculated by the simulation model based on pumping rates, are used in a SA optimization procedure to achieve an optimum solution. The five multi-objective management schemes were applied on Um-Qasr coastal aquifer. The results show that using simulation / optimization approach in Um- Qasr region can improve planning and management policies and can give better decision for aquifer utilization. The results show that the aquifer can safely increase its pumping rate by (175%) greater than its current abstraction according to the results of schemes 1.
Mathematical programming techniques have been used to minimize the cost of reinforced concrete counterfort retaining wall.The study presents a formulation based on elastic analysis and the ultimate strength method of design as per ACI-M318code. A computer program is generated to handle the considered problem. The formulation of optimization problem has been made by utilizing the interior penalty function method as an optimization method with the purpose of minimizing the objective function representing the cost of one-meter length of the counterfort retaining wall. This includes cost of concrete, reinforcement, and formwork. The design variables considered in this study are the dimensions and the amounts of reinforcement. It is found that the optimal spacing of counterforts equals about (0.214 to 0.366) of total height of wall. The optimum width of the base is found in the range (0.50 to 0.78) of the total height of the wall. Also the thickness of the stem is in the range(0.0284 to 0.0377) of the total height and it is less than half thickness of the base.
In this paper friction stir welding process has been studied whereby utilized FEM method (Ansys software ver. 20). The main effective parameter in this process were rotational speed, linear speed, tool shoulder radius, heat transfer coefficient and clamping percentage to study their influence on represent temperature, von misses stress and frictional stress distribution. Because of the difficulty to obtained the number of the simulation cases in order to get the most important results, Taguchi L27 orthogonal array was apply to reduce the total number of the simulation cases. Pure copper (t = 3.18 mm) material type was applied as work plate material. ANOVA statistical tool was utilized to achieved the optimization process after the simulation cases done. Percentage of contribution of each parameter can be obtained by ANOVA table and mean of S/N ratio plot. Validation process was achieved between the Current study and experiment work in the temperature distribution field with percentage of error 2.7 %. From optimization result It is found that the optimum condition in order to obtained good results for temperature was rotational speed of (450 rpm), linear speed (2.75 mm/s), tool shoulder radius (7 mm), heat transfer coefficient (300 w/m 2 K), clamping distance percentage (40 %). And for von misses stress was rotational speed of (550 rpm), linear speed (3 mm/s), tool shoulder radius (7 mm), heat transfer coefficient (300 w/m 2 K), clamping distance percentage (20 %). While for frictional stress was rotational speed of (450 rpm), linear speed (2.5 mm/s), tool shoulder radius (7 mm), heat transfer coefficient (300 w/m 2 K), clamping distance percentage (30 %).
A significant quantity of pollutants are contained within domestic wastewater which creates a substantial environmental issue with a large quantity of effluent that contains high amounts of contaminants. Turbidity is a major indicator of water quality and a measure of suspended solids. The purpose of this investigation was to study the use of electrocoagulation (EC) as a method of removing turbidity from municipal wastewater using aluminum electrodes. Using a Design of Experiments (DOE) approach, specifically Response Surface Methodology (RSM), the effect of three important operating variables was studied. These were: the initial pH of the wastewater in the range from 3 to 9; the current (or amperage, ranged from 0.1 A to 1.1 A); and the time for which the wastewater was treated by the EC process (ranged from 10 minutes to 20 minutes). The initial turbidity of each of the municipal wastewaters used in the testing remained constant at 336 NTU (nephelometric turbidity units) throughout the entire investigation. The effect of a number of different experiments was made in order to evaluate the effectiveness of the EC process for removing turbidity from the municipal wastewaters, and in addition take a measure of a predictive model of turbidity removal efficiency. The main conclusion drawn from the investigation was that the EC process will be very effective for removing turbidity from municipal wastewaters, which can vary from 5% removal to total removal (as high as 97%). There appeared to be a statistical correlation between the removal efficiency and the three experimental variables: pH (r=0.4316); amperage (r=0.3714); and time of treatment (r=0.3965). The removal efficiency was highest using the variables of Run 8 whereby the pH was equal to 9, the current was held constant at 0.6 A and the treatment time was 10 minutes, resulting in a turbidity removal efficiency of 97%. The various data showed that both slightly acid (pH=6) and alkaline (pH=9) gave a markedly superior removal than acid (pH=3) for obtaining constant, high removal efficiencies (average of 90.00% and 90.33%, respectively). Also, it was determined that a current of 0.6 A provided the most optimum amperage, giving an average removal efficiency of 95.33%. In addition, it was shown that long treatment times resulted in high removal efficiency, with the most averages of removal efficiencies recorded when the time of treatment was set.
Nowadays, it is crucial to assess power system contingencies resulting from line outages or generator failures, as they might cause breaches of system constraints. This is a vital part of ensuring the security of modern power supplies. Another hindrance to providing electricity to consumers is the increased system losses and voltage fluctuations resulting from increased demand and diminished power generation capacity. The DG connection is a crucial subject regarding these harmful consequences. This study is focused on clarifying the effect of distribution generators (DG) on mitigating congestion in electrical power transmission lines, minimizing power losses, and enhancing the voltage profile of the Iraqi national grid system. An optimization method is used to identify the optimal size and position based on fitness indicators such as voltage, power losses, and line congestion. The PSO algorithm is executed as proposed. The outcomes illustrate the effectiveness of the proposed technique for estimating the optimal size and placement of distributed generators (DG). At the same time, it reduces congestion and improves the voltage level of the bus. The proposed technique was implemented using the MATLAB/R2018a programming language.
Mathematical programming techniques have been used to minimize the cost of reinforced concrete T-beam floor. The floor system consists of one way continuous slab and simply supported T-beams. The study presents a formulation based on elastic analysis followed by the ultimate strength method of design with the consideration of serviceability constraints as per ACI Code. The formulation of optimization problem has been made by utilizing the interior penalty function method as an optimization method with the purpose of minimizing the objective function representing the cost of one-meter length of the floor system. The cost includes cost of concrete, reinforcement, and formwork. The design variables considered in this study are the dimensions and the amounts of reinforcement for the slab and beams, in addition to the spacing of the beams. Many examples are solved to show the effect of these design variables on the optimum solution of the floor system. The effect on the optimum design of the compressive strength of concrete, yield strength of steel, concrete cost ratios, and formwork cost ratios has also been studied.
A linked simulation-optimization model for obtaining the optimum management of groundwater flow is presented in this research. (MODFLOW, 98) packages are used to simulate the flow of the groundwater system. This model is integrated with an optimization model which is based on the genetic algorithm (GA). Three management cases were undertaken by running the model with adopted calibrated parameters. In the first case found the optimum value of the objective function is (0.32947E+08 m3/year), in other words, the pumping rates could be raised to nine times the current pumping rates, with a highest decline in the hydraulic heads of groundwater compared with initial hydraulic heads reached to 6 cm. In a second case twenty six wells out of thirty five can be operated with "on/off" status associated with each well to obtain the maximum value of pumping rate. In third case is allowed to move a location of well anywhere within a user defined region of the model grid until the optimal location is reached. The optimum value of objective function in third case is (0.35539E+08 m3/year) with 8% increasing of the pumping rates compared with the first case. This is due to the random distribution of existing well locations.
The present work includes a study on the effect of loading rubber waste into cement mortar on the thermal and mechanical properties of a thermal insulator.The experimental work of the study included the preparation of ten models of 35 mm diameter and 5 mm thickness. Portland cement and natural sand were used as a matrix and rubber waste (extracted from the consumed tires) as a filler was added in weight percentages ( 5% ,10% ,15% ,20% ,25% ,30% ,35% ,40%,45% and 50%). Water was also used as a binder.Also, the experimental work included conducting a thermal conductivity test using Lee’s Disk method, and a hardness test using the Shore scale. The theoretical side included extraction of empirical equations, depending on the experimental results. The thermal conductivity equation was for two variables, temperature and mass fraction. While the hardness equation was for one variable, mass fraction. Theoretically determined heat capacity was extracted using the equations of the composites. Based on the empirical equations of thermal conductivity and hardness and using the technique of multi- objectives genetic algorithm, the optimum values of temperature and mass fraction were extracted, which achieve the best thermal insulation of the mortar. The results showed a significant decrease in thermal conductivity. The reduction in thermal conductivity was (90.3%) at 5% and reduced to (95.73%) at 50%. The specific heat capacity was increasing as the percentage of rubber waste increase. The results also indicated a decrease in hardness. The optimal value of thermal insulation was (0.02658 W/m 2 .ºC ) as a thermal conductivity and (58.07 N/m 2 ) as a hardness, at temperature (50°C) and mass fraction (27.764%) of rubber waste.
Tn this paper, a hierarchical phoneme recognition system is proposed. The hierarchical approach is applied here to recursively partition the recognition problem into smaller and smaller sub-problems those are independently handled at the di~tinct nodes of the hierarchy. The nodes are individually set to chara~erize different properties of the input phoneme, or more precisely to make separate d~isioos on its pertinence to the different reference subgroups of phonemes. The full characteri:zation of the input phoneme is achieved by traversing some root-to-leaf path through the hierarchy. The relationships between the different features of phonemes and their pertinence to the different reference subgroups. are to be objectively characteriz.ed ttnd optimized here. This involves specifying the decisive subset of features for each pertinence decision and neglecting the remaining features those are irrelevam to (or probably have negative effect on) that decision, at each node of the hierarchy. The optimization applied through the feature election process here, is not aimed at reducing the amount of feamres to be used in the recognition process, for the purpose of decreasing the time-complexity of the systcn1, but, is interested in enhancing the decision making accuracy of the system by avoiding the misleading features.
In this paper, a second order Sliding Mode Controller (SMC), based on Super – Twisting algorithm, Fuzzy estimator and PID controller is presented for quarter vehicle active suspensions. Because of the chattering that appeared at the output of the system when using first order SMC, second order SMC is preferred. The proposed controller has been derived in order to achieve the convergence and the stability of the system that can improve the comfortable driving and vehicles safety against different road disturbances. The Artificial Bee Colony optimization method has been utilized to find the optimal values of the proposed controller parameters. The obtained results of the simulations have been verified the efficiency and the ability of the proposed control scheme to suppress the oscillations and give the stability of the suspension system in the presence of uncertainty and different road disturbances.
Solar desalination uses solar radiation to convert saline or seawater into clean water and is increasingly crucial due to growing pollution from industrial and automotive sources. Although solar stills offer a sustainable solution, they face challenges in terms of production efficiency. This study presents a new structural design for solar stills, which incorporates advanced insulation materials, a well-designed distillate channel, and an inclined base to enhance productivity. The research explores how different climatic conditions such as wind speed, solar radiation, and atmospheric humidity affect solar still performance. Seven experimental setups were evaluated, comparing traditional inclined stills with advanced closed-loop systems. The results demonstrated that closed-loop systems improved productivity by 28.6% compared to open-loop systems. Additionally, moderate wind speeds increased productivity by 20.82%, while partial cloud cover and light rain decreased productivity by 52.15% and 12.9%, respectively. However, light rain also enhanced condensation efficiency by cooling the glass surface. This study highlights the importance of incorporating environmental factors into the design and optimization of solar still systems for improved performance.
The LCL Series Resonant Converter (LCL-SRC) type offer nearly load- independent output voltage under some operating conditions. By this way the output voltage can be regulated against a wide load and line variations with a small variation of switching frequency. In this paper a simple method for optimization of LCL-SRC is presented. This method takes the stored energy as a theoretical index to obtain the minimal size of the converter inductors L1 and L2 which contribute significantly to the converter size and weight. The Rac method for the analysis of resonant converter is discussed. This method was found fairly accurate for operation above resonant frequency.
The objective function is to satisfy certain constraints and achieve minimum capital, maintenance, and operation costs. Ion exchange unit was used in this study. This study includes development of computer program for advanced wastewater treatment plants design adopting genetic algorithm. The program was developed using Matlab software. The output of the genetic algorithm includes the finding of optimum design criteria for advanced wastewater treatment plants. The obtained design criteria are satisfying the required effluent quality with minimum treatment cost. Based on results of applying GA on ion exchange treatment plant, it was found that the optimum values of bed depth, service flowrate, regenerate flowrate, and back wash rate are 0.71m, 25m3/m3.hr, 8 m3/m3.hr, and 55 m/hr respectively.