genetic algorithm (ga)

This study investigates using composite patch connections to repair cracked composite sheets under tensile stress. Finite element analysis was employed to model and analyze the behavior of the cracked composite sheet in three scenarios: without a patch, with a one-sided patch, and with a two-sided (symmetric) patch. The primary objective was to examine the influence of the composite patch material on the stress distribution, crack growth strain, and overall performance of the repaired sheet. An optimization approach was also developed to design the multilayer composite patch connection with the lowest weight and cost while withstanding the highest possible load. Two optimization algorithms, the Genetic Algorithm and the Colonial Competitive Algorithm, were implemented and compared in this regard. The results demonstrate that using a symmetric, two-sided composite patch connection effectively reduces crack growth and enhances the strength of the repaired sheet. Furthermore, the optimization analysis revealed that the Colonial Competitive Algorithm provided superior performance to the Genetic Algorithm in identifying the optimal design parameters for the composite patch connection. This study contributes to understanding crack behavior in composite sheets and developing cost-effective, weight-efficient repair solutions using composite patch connections. The findings can inform the design and implementation of composite repair techniques in various engineering applications.

In this article, the optimal robust H2 / H∞ control of self-driving car platoons (SDCPs) under external disturbance is investigated. By considering the engine dynamics and the effects of external disturbance, a linear dynamical model is presented to define the motion of each self-driving car (SDC). Each following SDC is in direct communication with the leader. By utilizing the relative position of following SDCs and the leader, the error dynamics of each SDC is calculated. The particle swarm optimization (PSO) method is utilized to find the optimal control gains. To this aim, a cost function which is a linear combination of H2 and H∞ norms of the transfer function between disturbance and target variables is constructed. By employing the PSO method, the cost function will be minimized and therefore, the robustness of the controller against external disturbance is guaranteed. It will be proved that under the presented robust control method, the negative effects of disturbance on system performance will significantly reduce. Therefore, the SDCP is internally stable and subsequently, each SDC tracks the motion of the leader. In order to validate the proposed method, simulation examples will be presented and analyzed.

Acoustic scaling is one of the efficient techniques for measuring acousticparameters of large and luxury places. Due to the range of acousticscaling frequency, an airborne ultrasonic transducer has been used fortransporting the power to the air. One major problem of ultrasonictransducers, radiating acoustic energy into the air, is to find the properacoustic impedance of one or more matching layers. This work aims atdeveloping an original solution to the acoustic impedance mismatchbetween transducer and air. Therefore we consider three piezoelectrics,PZT, PVDF, and EMFi transducers and air that have high acousticimpedance deference. We proposed the use of a genetic algorithm (GA) toselect the best acoustic impedances for matching layers from the materialdatabase for a narrow band ultrasonic transducer that works at afrequency below the 1MHz by considering attenuation. This yields ahighly more efficient transmission coefficient. Also, the results showedthat by using the increasing number of layers we can increase our chanceto find the best sets of materials with valuable both in acoustic impedanceand low attenuation. Precisely, the transmission coefficient is almosthigher than 80% for the more studied cases.

Controlling of the quadrotor has been noted for its trouble as the consequence of exceeds nonlinear system, strong coupled multivariable and external disturbances. Quadrotor position and attitude is controlled by several methodologies using feedback linearization, but when quadrotor works with unstructured inputs (e.g. wind disturbance), some limitations of this technique appear which influence flight work. Design control system with fast response, disturbance rejection, small error, and stability is the main objective of this work. So in this paper we can make use of new methods of control to design a controller of nonlinear robust with a reasonable performance to test the impact of wind disturbance in quadrotor control such as Fuzzy-PID controller and compared its results with the others four controllers which are PID tuned using GA, FOPID tuned using GA, ANN and ANFIS then discus which controller give the best results in the presence and absence of wind disturbance. The main objective of this paper is that performance of the designed control structure is computed by the fast response without overshoot and minim error of the position and attitude. Simulation results, shows that position and attitude control using FOPID has fast response and better steady state error and RMS error than Fuzzy-PID, ANFIS, ANN and PID tuned using GA without impact of wind disturbance but after impact of wind disturbance it was observed using Fuzzy-PID has fast response with minimum overshoot and better steady state error and RMS error than the other four controllers used in the paper and compared with most of literature reviews which didn't give the adequate results contrasted with the required position and attitude. The all controllers are tested by simulation under the same conditions using SIMULINK under MATLAB2015a.

In this paper, a new optimization method coupling genetic algorithm (GA) and computational fluid dynamics (CFD) based on Windows Socket was found to optimize the configurations of porous insert in a tube for heat transfer enhancement. The region in the enhanced tube was divided into several layers in the radial direction. The porosity of porous media filled in each layer was the design variable, which varies from 0.5 to 1.0. The results show that the thermo-hydraulic performance of the enhanced tube can be improved effectively by using the optimized porous insert, particularly using the optimized multiple layers of porous insert. However, there is an appropriate layer number of porous insert to ensure the optimal performance of the enhanced tube for a given set of parameters.

This paper deals with the problem of the instability regions of a free-free uniform Bernoulli beam consisting of two concentrated masses at the two free ends under the follower and transversal forces as a model for a space structure. The follower force is the model for the propulsion force and the transversal force is the controller force. The main aim of this study is to analyze the effects of the concentrated masses on the beam instability. It is determined that the transverse and rotary inertia of the concentrated masses cause a change in the critical follower force. This paper also offers an approximation method as a design tool to find the optimal masses at the two tips using an artificial neural network (ANN) and genetic algorithm (GA). The results show that an increase in the follower and transversal forces leads to an increase of the vibrational motion of the beam which is not desirable for any control system and hence it must be removed by proper approaches.

The purpose of this paper is multi-objective optimization of refrigeration cycle by optimization of all components of the cycle contains heat exchangers, air condenser, evaporator and super-heater. Studied refrigeration cycle is compression refrigeration cycle of unit 132 Third refineries in south pars that provide chilled water for cooling refinery equipments. Cycle will be performed by the genetic algorithm optimization. Thermodynamic purpose of the cycle Expressed by minimization of Exergy destruction or maximization or coefficient of performance (C.O.P), economic purpose of the cycle Expressed by minimization of cold water production cost by TRR method and environmental purpose of the cycle Expressed by minimization of NOx, CO2 and CO Which is produced by power consumption. Combination of objectives and decision variables with suitable engineering and physical constraints makes a set of the MINLP optimization problem. In EES software. Optimization programming is performed using NSGA-II algorithm. Four optimization scenarios including the thermodynamic single-objective, the economic single-objective, environmental single-objective by power electricity consumption and multi-objective optimizations are performed. The output of the multi-objective optimization is a Pareto frontier that yields a set of optimal points that the final optimal solution has been selected using two decision-making approaches including the LINMAP and TOPSIS methods.. It was shown that the best results in comparison to the simple cycle reduction in Exergy destruction from 264.8 kW to 127.6 kW(Increased coefficient of performance from 3.872 to 7.088), reduction in cold water production cost from 117.5 dollar/hour to 87.19 dollar/hour and reduction in NOx emission from 4958 kg/year to 2645 kg/year.

Wind power has been widely considered in recent years as an available and a clean renewable energy source. The cost of wind energy production is currently the main issue, and increasing the size of wind turbines can reduce wind energy production costs. Hence, megawatt wind turbines are being rapidly developed in recent years. In this paper, an aerodynamic analysis of the NREL 5MW turbine is carried out using the modified blade element momentum theory (BEM). The genetic algorithm (GA) as an optimization method and the Bezier curve as a geometry parameterization technique are used to optimize the original design. The modified BEM results are compared with the NREL published results for verification. Cost of energy (COE) is considered an objective function, which is one of the most important and common choices of objective function for a megawatt wind turbine. Besides, the optimization variables involve chord and twist distributions variation along the blade span. The optimal blade shape is investigated for the minimum cost of energy with considered constant rotor diameter and airfoil profiles. Then the objective function is improved and a new optimum geometry is compared with the original geometry. Although the Annual Energy Production and rated power are reduced by 2% and 3% respectively, the net cost of wind energy production is decreased by 15%, showing the importance of such optimization studies.