نشریه مهندسی مکانیک و ارتعاشات
سال یازدهم شماره 1 (پیاپی 38، بهار 1399)

The linear aeroelastic equation of motion of a wind turbine blade considering the length increase and rotation terms of the blade is derived. The blade is a composite cantilever beam. The Euler-Bernoulli theory is the fundamental theory in developing the equations. Because of the compatibility of the finite element and BEM, the blade is modeled with the finite element method. Applying Hamiltonian leads to the aeroelastic equations of motion. The finite element matrices are derived by considering linear and Hermitian shape function in axial and transverse deflection, respectively. We consider the linear equation of motion with length increase term. Simulation and analyzing the natural frequency and mode shapes validate the equations of motion. Besides, the effects of the length increase of the blade and rotation of blade on both short and long composite blades are investigated. Analysis of natural frequencies implies that the first and second frequencies of long blade ore affected by length increase and rotation of the blade. However, higher modes are affected by less than one percent.

In this paper, the experimental, numerical, and analytical investigation ‎of a blunt rigid projectile to the steel targets is discussed, Therefore, in ‎the first part, the experimental tests are carried out to find the depth of ‎penetration and the projectiles are cylindrical in diameter 10 mm and 20 ‎mm in length with AISI 52100 and steel plates with dimensions of 120 × ‎‎100×10 are selected from AISI 1045. In the second part, the numerical ‎simulation of the impact model in the Abacus software is carried out ‎and the accuracy of the numerical model is verified with 8% error rate ‎of the numerical solution with the experimental results. In the third ‎section, presents an‏ ‏analytical model derived‏ ‏from the Chen analytical‏ ‏model and obtain the depth of projectile penetration. Finally, a ‎comparison between experimental, numerical and analytical results is ‎performed, the results obtained in three solutions (experimental, ‎Numerical and analytical) have acceptable agreement.‎

The speed of drilling operations has a direct effect on drilling costs and various parameters such as drilling fluid properties and hydraulic drilling affect it. Therefore, it is very important to use models with different parameters that have high accuracy. Because the relationship between these parameters is complex, a computational method is needed. Artificial neural network is a new computational method for learning that is used to predict the output responses of complex systems. In this paper, the neural network is used to predict the drill penetration rate by considering the parameters of drilling fluid and multilayer artificial intelligence models and radial base are used to detect and predict drilling speed as output parameters.

In this article, the magnetic field effect on the natural convection heat transfer is simulated via LBM. The vertical wall of the left side of the cavity is at a constant hot temperature, while the vertical wall of the right side of the cavity has three different temperature boundary conditions, 1) constant cold temperature, 2) linear temperature and 3) constant hot temperature. A lozenge-shaped obstacle located in the center of the cavity is examined in four different modes, 1) cold, 2) conducting, 3) adiabatic, and 4) hot. The bottom wall of the cavity is also evaluated in three different slopes. The results show that increasing the slope of the wall and the Rayleigh number by unchanged all the parameters leads to an increase in heat transfer. Also, changing the boundary temperature of the walls and the obstacle can affect the amount of heat transfer. In addition, increasing the strength of the magnetic field reduces the average Nusselt number, which differs in different conditions.

The multi-rotor is a Without driver Aircraft with six degrees of freedom. The main shape of this bird is similar to a cross, which with six BLDC motors is capable of performing complex movements and maneuvers. At present, the control of this group of birds is done by the ground pilot, which is manually controlled or through the GPS system. The adaptive fuzzy method is an indirect controller to control the two modes of torsion and rotation in the flight system, which determines the desired output by taking the input. The advantage of this method is that if there is noise, it updates itself and synchronizes itself with the system. The result creates stability. In this paper, first the multi-rotor flying robot is dynamically modeled and then the adaptive fuzzy control structure is modeled with the help of a fuzzy detector for the multi-rotor flying robot autopilot. As a result, the amelioration and navigation control and stability In autopilot, the multi-rotor flying robot can be obtained with the help of adaptive fuzzy.

Todays, there are using hybrid methods in order to reach high level degree of accuracy and reliability for engineering systems. According to more reality modelling of system, it was mixed three strategies such as fuzzy, artificial neural networks and adaptive method. This mixed methods is presenting and analyzing each of engineering problem. Adaptive-Neural-Fuzzy (ANF) can be showed in which a robustness and reliable model by designer who assess that in order to make decision as well. In this paper, main aim is experimental condition and health monitoring of rotary system is including shaft, bearings, electromotor which are main components of system and using piezoelectric as sensor by ANF method. Firstly, by using LabVIEW software, experimental data of flexural vibration was recorded with piezoelectric sensor where were fixed on top of bearings, and secondly we used MATLAB software for analyzing experimentation for presentation of ANF model in order to curve fitting of data.