afshin ghanbarzadeh

A common method utilized in wind turbines is pitch angle control whereby via varying the angle of wind turbine blades around their own axis, power generated at high speeds of wind is held around maximum amount and is kept away from the severe mechanical stress on wind turbine. In current study, in order to control pitch angle, a control method based on using PI controller is suggested. Therefore, gains of the PI controller are regulated through combining the Firefly evolutionary algorithm and MLP neural network in such a way that the controller at its output sends a suitable controlling signal to the pitch actuator to set the pitch angle and so by varying the blades pitch angle suitably at high speeds of wind, the produced generator power remains around its nominal value. A wind turbine 5MW made by NREL (National Renewable Energy Laboratory) has been utilized based on FAST software code to simulate and analyze the results. The simulation results show that proposed method has a good performance.

Several studies have been conducted to accurately control the deformation of Shape Memory Alloys (SMAs) as an actuator, however, due to the non-linear relationship between the change of mechanical structure, including stress and strain, they have often been associated with a challenge. In the current study, a wire made of intelligent memory alloy (Nitinol) is used as an actuator of one degree-of-freedom mechanism. In order to observe the operation of the wire under electrical stimuli, a laboratory set-up is implemented. Our main goal is to accurately control the position of this nonlinear system with high precision by using optimal control. So, the nonlinear system equations are extracted and sorted into state-dependent matrices and the State-Dependent Riccati Equation (SDRE) is used to find the optimal control value. To verify the experiment three inputs including multiple steps, a low-frequency sine wave and a high-frequency sine wave, are applied to the system. The results, show the good performance of the controller in sustainability, fast response, and tracking of the desired position with low overshoot.

The use of multilayer pipes has increased recently thanks to their superior mechanical and chemical properties as a replacement of homogeneous single-layer pipes. Therefore, applicable inspections and non-destructive tests for multilayer pipes should be investigated. In this study, the governing equations of torsional wave propagation in the multilayer pipe were initially developed, and the relations between the displacement fields and dynamic stresses in the multilayer pipe were calculated. Then, the dispersion curves and group velocity for the multilayer pipe are plotted according to the boundary conditions. The torsional wave propagation in the multilayer pipe was also simulated using the finite element method via ABAQUS software. By comparing the analytical results and the numerical simulations, a complete agreement was observed between the results. Finally, the influence of effective parameters on torsional wave propagation in two- and three-layer pipes was investigated. The obtained results showed how the thickness, lay-up, and mechanical properties of the layers could affect the velocity of torsional wave propagation in the multilayer pipes.

In this research, Hunt type 6-DOF parallel robot is optimized based on kinetostatic performance indices and the effect of geometrical parameters on these indices is investigated. For this purpose, structural and geometrical parameters of Hunt type parallel robot are introduced. in order to determine the relationship between joint angle values and end effector coordinates, inverse kinematic is obtained. Jacobian matrix is developed to map velocity from joint space to Cartesian space. Manipulability, force manipulability and condition number are considered as indices to evaluate the robot performance. By defining the fitness functions, constraints and boundaries of geometric parameters, the optimized parallel robot structure is obtained using the multi-objective bees algorithm. A set of robot geometric parameters is presented, each of which has the best performance based on one of the indices. Also, a robot with specific geometric parameters is selected, which is suitable based on almost all performance indices. Finally, the effect of end effector movement on robot performance is investigated.

This paper presents a new Fast Kurtogram Method in the time-frequency domain using novel types of statistical features instead of the kurtosis. For this study, the problem of four classes for Bearing Fault Detection is investigated using various statistical features. This research is conducted in four stages. At first, the stability of each feature for each fault mode is investigated. Then, resistance to load changes as well as failure growth is studied. In the end, the resolution and fault detection for each feature using comparison with a determined pattern and the coherence rate is calculated. From the above results, the best feature that is both resistant and repeatable to different variations, as well as having suitable accuracy of detection and resolution, is selected. It is found that kurtosis feature is not in a good condition in comparison with other statistical features such as harmmean and median. This approach increases the fault identification accuracy significantly.

A primary objective in many human upright state movements is control of balance and monitoring, analysis, and intervention to improve it, has become a part of human biomechanics research.In studies with a quantitative approach to human balance, it is necessary to know the numerical quantity of balance in a body state or at any moment during a path.This study proposes a new quantitative Criterion to express stable state during walking cycle.The basis of this quantitative criterion is the Probability of dynamic success in completing the swing phase without losing balance and the initiation of a fall. The probability of motion realization has been calculated and simulated on a seven-link model with a distributed mass.In this study by taking into consideration the kinematic constraints, energy consumption, muscle stimulation level and changes in stimulation beside maximizing balance, the movement in stance phase is calculated as an optimal movement.The optimal step length has been calculated considering a weight for probability of motion realization and energy consumption. In this method both the maximum balance and minimum energy consumption have been considered.For instance, the optimal step length considering the maximum balance constraint in the specific path for an individual with the height of 187 cm and mass of 92 kg was calculated about 27 cm with this probabilistic approach.One of the factors in maintaining balance is cadence rate. By increasing the of center of mass average velocity, the probability of balance maintenance decreases, thus also with considering center of mass average velocity beside maximum balance constraint , the optimal step length is calculated 46 cm.

In this paper, the mechanical vibration analysis of functionally graded (FG) nanoplate embedded in visco Pasternak foundation incorporating magnet and thermal effects is investigated. It is supposed that a uniform radial magnetic field acts on the top surface of the plate and the magnetic permeability coefficient of the plate along its thickness are assumed to vary according to the volume distribution function. The effect of in-plane pre-load, viscoelastic foundation, magnetic field and temperature change is studied on the vibration frequencies of functionally graded annular and circular nanoplate. Two different size dependent theories also are employed to obtain the vibration frequencies of the FG circular and annular nanoplate. It is assumed that a power-law model is adopted to describe the variation of functionally graded (FG) material properties. The FG circular and annular nanoplate is coupled by an enclosing viscoelastic medium which is simulated as a visco Pasternak foundation. The governing equation is derived for FG circular and annular nanoplate using the modified strain gradient theory (MSGT) and the modified couple stress theory (MCST). The differential quadrature method (DQM) and the Galerkin method (GM) are utilized to solve the governing equation to obtain the frequency vibration of FG circular and annular nanoplate. Subsequently, the results are compared with valid results reported in the literature. The effects of the size dependent, the in-plane pre-load, the temperature change, the magnetic field, the power index parameter, the elastic medium and the boundary conditions on the natural frequencies are scrutinized. According to the results, the application of radial magnetic field to the top surface of plate gives rise to change the state of stresses in both tangential and radial direction as well as the natural frequency. Also, The temperature changes play significant role in the mechanical analysis of FG annular and circular nanoplate. This study can be useful to product the sensors and devices at the nanoscale with considering the thermally and magnetically vibration properties of the nanoplate.

Nowadays, piezoelectric transducers are widely applied because of their capability to convert environmental energies (e.g. mechanical vibrations) into the electrical energy. In an energy harvester structure, not only piezoelectric characteristics but also properties of the non-piezoelectric part of the energy harvesting structure are highly important. Therefore, in the present research, electrical energy generation from forced vibrations of a composite beam with the piezoelectric layer is considered. For this purpose, firstly, the governing equations of the system are obtained using Euler-Bernoulli beam theory. Then, Kantorovich method was used to calculate the output voltage for a composite beam with the piezoelectric layer. To verify the analytical method, the results were compared to the finite-element modeling results. Furthermore, the effects of fiber orientation angle and layup arrangement in the composite beam with piezoelectric layer on the amount of harvested energy were investigated. According to the obtained results, by increasing the elastic modulus of the composite beam and its effect on the damping ratio of the structure, considerably higher energy is harvested. Then, the effects of composite beam dimensions, the ratio of composite beam thickness to the piezoelectric layer thickness, the concentrated mass, and the damping ratio on the amount of harvested energy were studied. The results show that using the composite materials and by proper design of layup and fiber orientation angle in each layer, it is possible to get different equivalent elastic modulus in the composite beam, and consequently alter natural frequency of the system and output voltage amplitude of the circuit

Optimization of continuous synthesis of high purity carbon nanotubes (CNTs) using chemical vapour deposition (CVD) method was studied experimentally and theoretically. Iron pentacarbonyl (Fe(CO)5), acetylene (C2H2) and Ar were used as the catalyst source, carbon source and carrier gas respectively. The synthesis temperature and flow rates of Ar and acetylene were optimized to produce CNTs at a large scale. A flow rate of 30-120 sccm of acetylene and 500-3000 sccm of Ar at temperatures between 650-950 °C were examined. Using the fundamental trial and error method it was found that the maximum yield of pure CNTs can be produced at 750 °C with flow rates of 40-45 sccm of acetylene and 1500 sccm of Ar. In theoretical part, an artificial neural network (ANN) and the Bees Algorithm (BA) were used to model and optimize the CNTs production, based on the experimental data. The Bees Algorithm used the ANN as the fitness function and the optimum variables found as 60 sccm for acetylene, 555 sccm for argon and 759 °C for temperature. The computational results have relatively good agreement with the experimental results.

Any industry needs an efficient predictive plan in order to optimize the management of resources and improve the economy of the plant by reducing unnecessary costs and increasing the level of safety. Rotating machinery is the most common machinery in industry and the root of the faults in rotatingmachinery is often faulty rolling element bearings. Because of a transitory characteristic vibration of bearing faults, combining Continuous wavelet transforms with envelope analysis is applied for signal proseccing. This paper studies the application of independent component analysis and support vector machines to for automated diagnosis of localized faults in rolling element bearings. The independent component analysis is used for feature extraction and data reduction from original features. The principal components analysis is also applied in feature extraction process for comparison with independent component analysis does. In this paper, support vector machines-based multi-class classification is applied to do faults classification process and utilized a cross-validation technique in order to choose the optimal values of kernel parameters.

In this study, the effects of geometrical parameters of 6-DOF Hexa parallel robot on kinematic, and dynamic performance indices are investigated and its structure is optimized using the intelligent multi-objective Bees Algorithm. In this way, after describing the structure and specifying the geometrical parameters of the robot, inverse kinematic relations of the robot are obtained. Jacobian matrix that maps velocity from joint space to Cartesian space is developed. Mass matrix is obtained from calculating the total kinetic energy of the manipulator in terms of the actuated joints vector. Inverse of the homogen jacobian based condition number is considered as a index to evaluate the kinematic dexterity. based on mass matrix as relation between acceleration vector of the end effecter and torque vector of actuated joints, dynamic dexterity index is presented. Using the multi-objective Bees Algorithm and considering dynamic and kinematic performance indices in a pre-determined workspace as the objective functions, structure of Hexa parallel robot is optimized. In this way, the proper geometrical constraints such as limitation of universal and spherical joins, and the constraints to singularity avoidance are considered. Pareto front of the multi objective optimization of the robot is drawn. Diagrams of the kinematic and dynamic performance indices variation in the workspace and the effects of geometrical parameters variation on them are presented.

The equations of Lamb wave propagation in an infinite isotropic micro plate with finite thickness on the basis of consistent coupled stress theory is presented in this study. By employing the characteristic length scale parameter, the effect of micro-plate size is considered, and thereby the effects of different plate dimensions on the dispersion of Lamb waves is illustrated. Lamb wave propagation velocity in aluminum nitride micro-plates has received many interests due to its applications in surface acoustic resonators. In the current work, at first, the dimensionless relations are developed through the definition of dimensionless parameters where the extracted curves can be applied to all thicknesses, propagation wavelengths and characteristic length scale parameters of a micro-plate. In addition, using the quasi-static approximation, the Lamb wave dispersion curves in both symmetric and asymmetric modes for an aluminum nitride micro plate are plotted and compared with the results from the classical theory. The integrity of the present formulation is verified by comparing the obtained results with the experimental data in the literature. Finally, by employing the dispersion curves and the reported experimental data, a novel method has been proposed to determine the size of characteristic length parameter in the consistent coupled stress theory.

Rotating machinery is the most common machinery in industry. The root of the faults in rotating machinery is often faulty rolling element bearings. This paper presents a technique using optimized artificial neural network by the Bees Algorithm for automated diagnosis of localized faults in rolling element bearings. The inputs of this technique are a number of features (maximum likelihood estimation values), which are derived from the vibration signals of test data. The results show that the performance of the proposed optimized system is better than most previous studies, even though it uses only two features. Effectiveness of the above method is illustrated using obtained bearing vibration data.

The dogleg severity is one of the most important parameters in directional drilling. Improvement of these indicators actually means choosing the best conditions for the directional drilling in order to reach the target point. Selection of high levels of the dogleg severity actually means minimizing well trajectory, but on the other hand, increases fatigue in drill string, increases torque and drag, particularly in the rotation mode. Therefore the aim is to define the index in an optimal range which meets both requirements. Particle swarm algorithm was used for optimization the dogleg severity. The final measured depth and directional well pattern were considered as an objective function and Build & Hold, respectively. Then the fatigue caused by the stresses exerted on the drill string, evaluated by modified Goodman equation simultaneously. The relationship between path parameters and the obligation to reach a target point in directional wells, converts the problem into a constrained optimization problem. Comparing the proposed directional drilling path in a drilled well in the Ahwaz oilfield with the responses obtained from the particle swarm algorithm indicated that the particle swarm algorithm is converged in finding the shortest path, and on the other hand, it decreases the time of using directional drilling equipment due to the selection of the proper dogleg severity. Note that it is likely to add other constraints to the optimization process which indicates the particle swarm algorithm efficiency in solving these problems.

In the present paper, the flow and heat transfer of two types of nanofluids, namely, silver-water and silicon dioxide-water, were theoretically analyzed over an isothermal continues stretching sheet. To this purpose, the governing partial differential equations were converted to a set of nonlinear differential equations using similarity transforms and were then analytically solved. It was found that the magnitude of velocity profiles in the case of SiO2-water nanofluid was higher than that of Ag-water nanofluid. The results showed that the increase of nanoparticle volume fraction increased the non-dimensional temperature and thickness of thermal boundary layer. In both cases of silver and silicon dioxide, increase of nanoparticle volume fraction increased the reduced Nusselt number and shear stress. It was also demonstrated that the increase of the reduced Nusselt number was higher for silicon dioxide nanoparticles than silver nanoparticles. However, the thermal conductivity of silver was much higher than that of silicon dioxide.

Designing synchronic recovery cycle was very complex due to existence two different recovery cycle power which was related to retrievers boiler. And any change in designing directly was eclipsed power, efficiency, and costs, and many other variables. Researchers always was tied to indicating a way for optimizing properties and different sections (parts) of synchronic recovery cycles, but complete reviewing cycle was less considered due to unique complexities. In this article, we are considered to complete modeling synchronic recovery cycle, indicating the results of energy and exergy analysis, defining appropriate fitness function and then optimizing the model which was indicated by powerful instruments, genetic and PSO algorithms. Also, the accuracy of calculated results was proved by comparing with practical cycle results of BILKENT University. It was necessary to say that in this research, for the first time, has been optimized complete cycle synchronic recovery by genetic algorithm.

In this project guidance and control of underwater robot, including three engines and propeller attached to it, by Fuzzy control has been investigated. Fuzzy control is done based on human experience and requiered laws. The robot can also be controlled and guided by the user. This robot may be used in sea or swimming pool environment for finding goal point and locate in desired direction. In addition, this robot is able to follow a definite path and to do searching operation in that path. This robot is also able to overtake barriers on the surface or under the surface and forward toward target and path the barriers using fuzzy rules. In other words, while facing any barriers using fuzzy rules. In other words, while facing any barrier, robot decides necessary decision in such a way not to collide with it and path it. For simulation of the required system, webot's software which is strong software for mobile robot simulation and Maple's material software is used. This robot is capable to distance any obstacle in 3D and move towards the goal. Obstacle avoidance is done by fuzzy rules. Means when face any obstacle, the underwater robot decide for not collision and passes it. For the simulation system, Webots that is strong software for mobile robot simulation and mathematical software Maple is used.

Designing synchronic recovery cycle was very complex due to existence two different recovery cycle power which was related to retrievers boiler. And any changes in designing directly were eclipsed power, efficiency, and costs, and many other variables.Researchers always was tied to indicating a way for optimizing properties and different sections (parts) of synchronic recovery cycles, but complete reviewing cycle was less considered due to unique complexities.In this article, we are considered to complete modeling synchronic recovery cycle, indicating the results of energy analysis, exergy of defining appropriate fitness function and then optimizing the model which was indicated by powerful instruments of genetic algorithm.Also, the accuracy of calculated results was proved by comparing with practical cycle results of biklent university. It was necessary to say that in this research, for the first time, has been optimized complete cycle synchronic recovery by genetic algorithm.

The aim of this work is to analysis parameters variation effect on PEM static model output voltage .Fuel cells designing parameters play an important role in their operation improvement .This paper has been shown the effects of several numerically simulated parameters such as temperature, pressure, cross section and Membrane thickness on PEM fuel cell operation. In this study we have been abbreviated anode and cathode pressures by fuel cell pressure. Simulation has been done under following conditions: temperature cell 298-353 , pressure 1.2-10 atm, cross section 0.016-0.05 m2 . Voltage current curves have been shown in different cases of parameters variation. MATLAB software has been applied for PEM static model simulation.