مجله مهندسی مکانیک امیرکبیر
سال پنجاه و چهارم شماره 2 (اردیبهشت 1401)

Lane Change at high speeds is a strategic maneuver to avoid the collision. In this situation, The time of an accident possibility is mainly less than two seconds. therefore, finding the proper trajectory and control of the vehicle is crucial at the lowest cost. In this paper, based on a skilled driver’s performance in a similar situation, a proper path and corresponding appropriate control system was designed aiming at vehicle stability preserving and collision avoidance. To this purpose, possible paths were simulated and identified using the vehicle's seven degrees of freedom model and applying the driver’s behavior. A neural network system was trained; then, the trajectory was chosen. A hybrid controller was hired for the vehicle navigation, consisting of the driver's performance pattern with a covering neural network and two proportional derivative controllers. The Novelties of this method are the simultaneous design of a stable path while maintaining geometric constraints and the low computational burden of the path planning and control system. The results show that the highest neural network error is about 11%. Also, the control system has been able to steer the vehicle and follow the trajectory with 40cm maximum lateral displacement error in the speed and road friction different conditions.

Concerns about aircraft gust disturbance have increased not only because of the design cases that are not primarily structural but also because of gust influence on aircraft handling qualities and flight controllability. Load alleviation system duty is reducing loads caused by a gust on aircraft. Using active control when crossing gust causes alleviation of loads on aircraft and improves ride quality. In this paper gust response of a flexible aircraft has been simulated by using the Lagrange equation and quasi-steady aerodynamics. Wing has been considered as flexible and other parts have been considered rigid. Two degrees of freedom in pitch and plunge of rigid mode have been considered and the elastic wing has been modeled as a beam with torsion and bending. Gust responses with different profiles have been analyzed. Then by using elevators and aileron gust loads have been reduced. Feedback control has been used to decrease the pitch and heave acceleration of the aircraft. Closed and open-loop response to gust has been compared and it has been shown that pitch oscillations have been damped very well by elevator. Then by using elevators and flaperon gust loads have been reduced by using neural networks adaptive controller and classic controller. Comparison has been made between closed-loop and open loop response to gust.

In this paper, a four-wheeled omnidirectional robot of the mecanum type is investigated. In this study, the kinematics and dynamics of the robot have been analyzed, emphasizing the influence of parameters and models on equations. The robot-based behavior control is carried out by applying kinematic equations. This method of control will enable the robot to reach its desired position despite obstacles. This method of control will enable the robot to reach its desired position despite obstacles. The work done in the robot control method is the main contribution of this study. This control method uses a behavior-based algorithm to guide a robot toward a target point by bypassing obstacles and selecting appropriate behaviors. We are interested in investigating the rotational motion of this robot, independent of its linear motion since it has three degrees of freedom on the plane. Therefore, during the movement of the robot and reaching the goal, the robot should always be oriented towards a moving point separate from the target point. The results show that this method gives a good estimate of the robot speed and the speed of the robot wheels and their torque.

Tire online normal force has effects on vehicle safety and performance and dynamic control systems. It is influenced by too many parameters such as vehicle mass and center of gravity position and vehicle instantaneous dynamics states. In this paper, a new estimation algorithm is developed to estimate tires’ online normal forces during a maneuver. The proposed algorithm uses a dynamic measure module to make a hardware-software coupled model which is validated by real test data. The algorithm uses artificial neural networks advantages to estimate the vehicle mass distributions. A combination of real and model-generated data is used to train, test, and validate the artificial neural network structure. By applying two roll and pitch artificial neural network blocks, it estimates tires’ static normal forces. In this respect, the validated vehicle model instantaneously monitors the estimated values. The results show that the proposed algorithm estimates the vehicle total mass with less than 5 percent. In addition, the coupled model uses the estimated static values to estimate the tire's online normal forces with considering the measured vehicle dynamics states by dynamic module. Comparing the obtained results from the proposed method with the outputs from Carsim indicates the acceptable accuracy of this method.

Recently, it has been substantiated that besides initially curved micro-structures, pressurized flat micro-plates can also experience snap-through instability. Given the potential applications of these micro-plates in designing high-sensitive sensors, the present work aims to investigate the bi-stable behavior of such structures when they are integrated with a piezoelectric layer. To this end, the modified couple stress theory together with the geometric nonlinear Kirchhoff plate model are employed. Hiring Galerkin’s method, the reduced governing equilibrium, and stability equations are then achieved. The limit points associated with the micro-plate equilibrium path are then determined through the simultaneous solution of these equations. The present findings are compared and validated by available results in the literature. The influence of the piezoelectric actuation on the bi-stable response of the system is then investigated. The results reveal that the shape of the micro-plate equilibrium path and the number and the position of its limit points can seriously be affected by applying the piezoelectric voltage. Despite the previous studies, the present paper shows that applying positive piezoelectric voltage does not decrease the pull-in threshold of the system all the time and can sometimes increase it when the micro-plate undergoes large differential pressures. Furthermore, the results reveal that applying positive piezoelectric voltages expands the snapping zone while negative ones downsize this region. The present results can be very useful for micro-electromechanical system engineers.

Defects in adhesive joints are an important issue in the construction of space structures. In this paper, using lamp waves, suitable properties have been obtained to identify the size and position of the defects of the adhesive joints. Using finite element simulations, the effect of the defect on the propagation of the lamp waves has been investigated. Simulations have been performed for three different adhesive thicknesses, three different sizes of circular defects in 9 different positions, and the effect of each of them on the wave passing through the joint has been investigated. The signals obtained from the faulty connections were compared with the signal obtained from the healthy connection and the desired area was isolated from the total received signal for further analysis. The proper and correct separation of defects requires finding suitable characteristics for it. Therefore, 34 features were examined to differentiate and separate defects. Then, the neural network was used to provide the basis for creating appropriate patterns for the separation of defects. The percentage of correct detection of neural network for adhesive thickness separation was 93.8%, for defect area separation in terms of size 100% and for defect position separation in X and Y axes were 96.1 and 95.1%, respectively. The obtained results show the efficiency of the improved distance evolution method and the features selected to distinguish the defects of such connections.

In this study, the free vibrations of functionally graded graphene platelet-reinforced porous nanocomposite plates with various shapes such as rectangular, elliptical, and triangular ones embedded on an elastic foundation are analyzed. To mathematically model the considered plate and elastic foundation, the first-order shear deformation plate theory, and Pasternak model are used, respectively. Three types of graphene nanoplatelet distribution patterns and porous dispersion types through the thickness are considered for the nanocomposite plate. To obtain the effective material properties of the considered nanocomposite, a micromechanical model is employed. Then, the energy functional of considered functionally graded graphene platelet-reinforced porous nanocomposite plates are expressed, and the analytical P-Ritz method is used to solve the vibration problem corresponding to different shapes and boundary conditions, the influences of porosity coefficient, the weight fraction of graphene nanoplatelets, elastic foundation coefficients and also the lengths-to-width and -thickness ratios on the natural frequency are analyzed. It is illustrated that the plate with non-uniform and symmetric of first type porosity distribution pattern and the first type graphene nanoplatelets has a higher natural frequency. Also, by increasing the porosity coefficient, the natural frequency of the plate associated with all patterns of graphene nanoplatelets is reduced.

In this study, delamination of the corrugated composite plates made of unidirectional glass fibers and polyester resin has been investigated. The samples are fabricated by hand lay-up process based on the ASTM-D5528 standard. Using experimental tests, the strain energy release rate in mode I has been calculated for composite corrugated specimens by the prevalent method of interlaminar failure. Also, the samples were simulated as a double cantilever beam by Abaqus software, and the mechanical properties of unidirectional glass/polyester composite and the results of the numerical solution are also obtained. Fracture surfaces of experimental samples were analyzed by scanning electron microscope. Force-displacement curves obtained from experimental and numerical methods have been compared to find the material behavior and calculate the strain energy release rate for different samples with three pre-crack lengths. The results show that the corrugated composite plates have a higher interlaminar fracture toughness rather than flat samples and the four-wave sample with a crack length of 60 and 65 mm has the highest values of the strain energy rate released, equal to 963.77  J/m2 and 705.95  J/m2, respectively.

In this paper, using the coupled Lord-Shulman generalized thermoelasticity theory and considering the nonlinear thermal effects, the thermoelastic behavior of annular disks made of functionally graded materials under internal thermal shock is investigated. To this end, the governing equations of the problem are first derived within the framework of the polar coordinates system. It should be noted that the energy equation is kept in its original nonlinear form in this derivation process. The solution procedure is then presented based on the generalized differential quadrature method. In the numerical results, the effects of important parameters such as functionally graded index and magnitude of applied thermal shock on the propagation of thermomechanical waves in the disks are studied. The results show that with increasing the functionally graded index, displacement and stress decrease as time evolves. Also, with presenting results for various magnitudes of thermal shock it is shown that conducting a nonlinear thermal analysis is necessary when the thermal shock magnitude is considerable. In addition, it is revealed that the fluctuations in the temperature are reduced as the relaxation time decreases. Moreover, increasing this parameter leads to temperature variations, whereas the frequency of the system decreases.

Magnesium-based nanocomposites are widely used in the aerospace, automotive, and medical industries. Due to the special properties of boron nitride nanotubes, these nanotubes play an important role in strengthening nanocomposites. In this research, magnesium nanocomposites are reinforced by boron nitride nanotubes and the mechanical properties of these nanocomposites under uniaxial tensile loading in the axial direction of the nanotubes have been investigated by the molecular dynamics method by Lammps software. Also, the coefficients of the atomic potential function of magnesium atoms have been calculated using the law of composition and the data extracted by Gaussian software. The results of molecular dynamics simulations show the improvement of mechanical properties of magnesium-based metal nanocomposites due to the addition of boron nitride nanotubes. The presence of boron nitride (0,12), (0,14), (0,16) and (0,18) nanotube reinforcers as magnesium field reinforcers increased the elastic modulus by 13, 14.9, 16.2 and 17 percent. Other results of this study indicate that the elastic behavior of nanocomposites is independent of strain rate changes. Also, by performing this simulation over a wide range of temperatures, obvious changes in the mechanical properties of the nanocomposite at different temperatures have been obtained.

In recent years, with the advent of the Fourth Industrial Revolution concepts and the development of artificial intelligence technologies, new approaches such as the digital twin have been introduced. In a digital twin, a virtual counterpart of the physical system during its whole life is created, with abilities such as analyzing, evaluating, optimizing, and predicting. The first step in creating a digital twin model is to construct a (multi) digital health indicator that describes different aspects of the physical component state during the whole life of the component. In this research, a new method for constructing health indicators based on vibration measurement and a deep learning model has been introduced. For this purpose, the Continuous Wavelet Transform was used to convert the raw vibration signals into two-dimension images; Then, the deep learning model was used to extract features from the images and the health indicator is constructed based on the differences of the images in normal and failure stages. In this article, various Autoencoder architectures are discussed, and it is demonstrated that the Convolutional Autoencoder has better performance in terms of detecting incipient faults. The performance of the proposed model is evaluated by the vibration data of the bearing, and the constructed health indicator exhibited a monotonically increasing degradation trend and had good performance in terms of detecting incipient faults.

Today, the usage of composite materials in various industries such as aerospace, transportation, construction, etc. has increased. Therefore, an adequate understanding of the production processes and assembly of these materials is inevitable. Machining is one of the common processes in assembling composite parts. This process includes two categories of traditional and non-traditional machining processes and grinding is one of the traditional methods. Grinding is one of the applicable machining processes for the finishing of composite parts. Many parameters such as feed rate, depth of cut, tool geometry, fiber direction, and abrasive particles material and size are effective on the machined surface. In this study, the effect of grinding parameters including feed rate, depth of cut, abrasive particles size, and fiber orientation on the surface quality of Carbon Fiber Reinforced Polymer has been evaluated. The experiments were designed by Response Surface Method in Minitab software V.19. The results showed that abrasive particles' size and depth of cut are the most effective parameters on the machined surface roughness. The feed rate and fiber direction are of secondary importance, respectively. Also, the scanning electron microscopy images confirm these results. Finally, it was suggested to use 50µm of the depth of cut, 200mm/min of feed rate, perpendicular to fiber direction and course abrasive particle to achieve a roughness of less than 5µm.