amir hossein rabiee

The vortex shedding from a bluff body can provoke structural vibrations known as flow-induced vibrations (FIV), which characterize an intrinsic phenomenon in the design of cylindrical structures. There are numerous passive and active methods to suppress FIV, among which suction and/or blowing on a cylinder surface is one of the most common approaches. In this work, different configurations of simultaneous suction and blowing are considered at two different Reynolds numbers corresponding to the galloping and frequency synchronization ranges. The parameters studied include the number of slots for suction and blowing, their length, and the velocity of the sucked and blown flow. The design of experiments method (DOE) is used to find the required simulation elements. The simulation results show that the dominant parameter in the reduction of galloping and vortex-induced oscillations and mass flow rate is the flow velocity in the areas of blowing and sucking. In addition, regression analysis is used to derive a relationship between various influencing parameters and performance parameters.

Leveraging artificial intelligence to forecast heat transfer characteristics across diverse industries holds significant potential for improving thermal equipment design, increasing heat transfer efficiency, optimizing cooling systems, and reducing energy consumption. The main contribution and purpose of the current study is predicting the Nusselt number in the context of turbulent flow-induced vibration around a heated cylinder experiencing unconfined oscillations along both streamwise and transverse axes. The anticipation of the Nusselt number relies on transverse and streamwise displacements of the oscillating cylinder and encompasses three distinct scenarios: displacement input in the x-direction, displacement input in the y-direction, and comprehensive amalgamation of both x and y inputs. This prediction is achieved through a sophisticated deep long short-term memory network, meticulously crafted and fine-tuned using a particle swarm optimization algorithm. The results highlight the effectiveness of the optimized networks across various inputs, with the highest predictive precision observed when employing combined x and y inputs. The correlation coefficients within the test segment are as follows: 0.967 for x input, 0.961 for y input, and 0.975 for combined x and y inputs. By applying the methodology elucidated in this study, the forecasting of heat transfer characteristics for structures subjected to fluid flow emerges as a feasible possibility.

Bone micromilling is widely used in orthopedic, spine, skull, knee joint replacement, and orthopedic surgeries to cut bone and make holes in tissue. The application of tools with a smaller diameter in the bone micromilling compared to conventional milling causes a significant reduction in force and also the length of the treatment period. In this article, in the form of an experimental study, an intelligent model for predicting bone micromilling force has been obtained based on the fuzzy inference system. For this purpose, first, an experiment design method has been used to extract a group of practical experiments. Then, based on the obtained results and approximation capability of fuzzy systems, an accurate model for predicting the cutting force has been established founded on the input values of tool rotation speed, feed rate, tool diameter, cutting depth and cutting direction. By examining the obtained results, it can be seen that the fuzzy model has been able to accurately approximate the resulting force of the bone micromilling process based on the considered inputs; The mean absolute percentage error and coefficient of determination for the data of the test section were calculated as 11.22% and 0.93%, respectively. Using the data of this research, surgeons with full knowledge can set the best values of the input variables of the micromilling process without worrying about causing damage and cracks in the bone tissue with the maximum possible operating speed.

The present study numerically evaluates vortex-induced vibration (VIV) for an electrically conductive fluid around a cylinder on an elastic support. The flow is subjected to a uniform magnetic field in the z-direction to evaluate the VIV attenuation performance of this open-loop active control method. To analyze this fluid-structure interaction (FSI) problem, the finite volume method (FVM) was employed based on the SIMPLE algorithm to solve the governing continuity and momentum equations of the fluid flow and an explicit integration method to solve the motion equations of the rigid structure. Simulations were carried out at reduced velocities of 2-9 and different Stuart numbers. The simulation results demonstrated that the magnetic field was significantly effective and wholly (100%) suppressed transverse and longitudinal VIVs. A rise in the magnetic field magnitude eliminated vortex shedding for all the reduced velocities, leading to a symmetric wake. The symmetric vortex even disappeared above the critical Stuart number.

In this paper, by considering the processing parameters, including blank holder force, blank holder gap, and cavity pressure as the most important input factors in the hydroforming process, an experimental design is performed, and an adaptive neural-fuzzy inference system (ANFIS) is applied to model and predict the behavior of aluminum thinning rate (upper layer and lower layer), the height of wrinkles and achieved depths that are extracted in hydroforming process. Also, the optimal constraints of the network structure are obtained by the gray wolf optimization algorithm. Accordingly, the results of experimental tests are utilized for training and testing of the ANFIS. The accurateness of the attained network is examined using graphs and also based on the statistical criteria of root mean square error, mean absolute error, and correlation coefficient. The results show that the attained model is very effective in approximating the aluminum thinning rate (upper layer and lower layer), the height of wrinkles, and achieved depth in the hydroforming process. Finally, the results also show that the root means of the square error of aluminum thinning rate (upper layer and lower layer), the height of wrinkles, and achieved depth of the test section are 1.67, 2.25, 0.05, and 2.67, respectively. It is also observed that the correlation coefficient for the test data is very close to 1, which demonstrates the high precision of the ANFIS in predicting the outputs of the hydroforming procedure.

Flow-induced instabilities are one of the major challenges in the design of aerospace structures. Numerous passive and active control methods have been used to reduce the flow-induced oscillations of square cross-section cylinder as the basic geometry for structures with sharp corners. The suction and blowing flow control method are one of the most effective approaches for controlling the flow and consequently reducing the vibrations resulting from the aerodynamic forces, which so far are not considered for an elastically-mounted square cylinder which fluctuates freely in the transverse direction. Therefore, in this paper, suction and blowing flow control methods have been used separately to suppress flow-induced oscillations. In the suction-based method, a slut is placed on the front surface of the cylinder and in the blowing-based method another slot is inserted on the back surface of the cylinder. In the present study, the effect of suction and blowing velocities as well as the effect of suction and blowing slut lengths on the efficiency of the flow control approach was evaluated. According to the flow-structure interaction simulations, it is observed that the applied flow control method has been able to reduce flow-induced vibrations appropriately.

In this paper, the active flow control of flow-induced vibration of a circular cylinder placed in the isothermal channel affected by jet injection is studied. The effect of flow injection on heat transfer inside the channel has also been examined. For this purpose, three slots are placed symmetrically in the upper and lower walls of the channel at distances 0, D, and 4D where D is the diameter of the cylinder from the side surface. The main innovation of the present study is to evaluate the effectiveness of the proposed flow control method in terms of channel height. For this purpose, 6 channels with heights of 5.5D, 6D, 7D, 8D, 9D, and 10D are considered to perform fluid-solid interaction simulations. The finite element method has been used to solve the flow and energy equations. For coupling the movement of the cylinder with the flow field, the dynamic mesh method is used. Numerical results show that for all channels with different heights, jet injection, either unilaterally or bilaterally, from slot 3, has no effect on displacement because the distance of the jet from the cylinder is large. By increasing the height of the channel, the injection velocity must be increased to completely reduce the oscillations of the cylinder.

The forming of tailor machined blanks due to the different thicknesses is more complex than the monolithic sheets. The presence of two sections with different thicknesses leads to different formability behaviors and consequently their different spring-backs. Therefore, it is important to examine the spring-back in the thin and thick sections of tailor machined blanks in order to minimize the spring-back value. In this paper, an adaptive neural-fuzzy inference system is used to model the effect of important parameters to predict the percent of spring-back corresponding to the thin and thick sections on the creep age formed tailor machined blanks. In addition, the obtained model is used to optimize the creep forming process using particle swarm optimization algorithm. In order to model the process behavior, some experiments have been performed on the creep forming of tailor machined blanks. The accuracy of the obtained model is investigated using different figures as well as by the specific criteria , , , and .

This paper covers the application of the Fuzzy-PID controller to stabilize the three-axis gimbal payload orientation with respect to the inertial frame in the presence of platform motion. In this way, the effect of external disturbances induced by the operating environment is greatly reduced, thereby increasing the accuracy of ultimate operation. Three independent controllers are employed to maintain the triple angles of the three-axis gimbal payload at a desired orientation. The Fuzzy-PID controller benefits the typical PID control structure in which the control gains are adaptively computed by a fuzzy inference system. The particle swarm optimization algorithm is also used to calculate the optimal values of input-output scale factors. A co-simulation platform is considered by coupling the PSO-optimized Fuzzy-PID controllers modeled in Matlab/Simulink to the mechanical gimbal model designed in Solidworks and exported to Simulink by using Simscape toolbox, aiming at the calculation of control torque needed for stabilization of gimbal payload. The effectiveness of the proposed controller is examined by simulation of the designed system for various commanded angles in the presence of different disturbances, including sinusoidal disturbances with diverse frequencies and random vibrations. According to the adopted collaborative simulations, it is shown that the utilized control system performs very well in the tracking of the desired angles and also the rejection of the applied perturbations.

In this paper, by considering the temperature, time, and process pressure, as the most important factors in producing the thermoplastic composites, an experimental design was performed. An adaptive neuro-fuzzy inference system (ANFIS) was utilized to estimate the important characteristics containing flexural strength, porosity volume ratio, fiber volume ratio, and flexural modulus. Then, the parameters of the ANFIS network were optimized by the teaching-learning-based optimization (TLBO) algorithm. For the purpose of modeling material behavior in the process, the experimental results were utilized for the training and validation of the adaptive inference system. The accuracy of the obtained model has been investigated by using different graphs, based on the statistical criteria of the mean absolute error, correlation coefficient, mean square error, and the percentage of mean absolute error. Based on the obtained results, the TLBO-ANFIS approach has been very effective in estimating the above-mentioned properties in the production process. The network error for estimating flexural strength, porosity volume ratio, fiber volume ratio, and flexural modulus in the teaching section was equal to 0.159%, 0.0003%, 1.074%, and 0.0001%, and the corresponding values were equal to 0.852%, 42.413%, 33.95%, and 4.894% in the testing section.

Resistance spot welding process of AISI 1060 steel has been experimentally investigated by studying the effects of welding current, electrode force, welding cycle and cooling cycle on tensile-shear strength. Using the response surface methodology, experimental tests are performed. An adaptive neural-fuzzy inference system is applied to model and predict the behavior of tensile-shear strength. Additionally, the optimal parameters of adaptive neural-fuzzy inference systems are obtained by the gray wolf optimization algorithm. For modeling the process behavior, the results of experiments have been employed for training (70% of data) and testing (30% of data) of the inference system. The results show that the applied network has been very successful in predicting the tensile-shear strength and the coefficient of determination and mean absolute percentage error for the test section data are 0.96 and 6.02%, respectively. This indicates the considerable accuracy of the employed model in the approximation of the desired outputs. After that, the effect of each input parameter on tensile-shear strength is quantitatively evaluated with the Sobol sensitivity analysis method. The results show that the tensile-shear strength of the joint rises by increasing the welding current and welding cycle and also decreasing the electrode force and cooling cycle.

Resistance Spot Welding (RSW) is one of the effective manufacturing processes used widely for joining sheet metals. Prediction of weld strength of welded samples has great importance in manufacturing and different methods are used by researchers to find the fracture force. In this article, the Adaptive Neuro-Fuzzy Inference System (ANFIS) is utilized for prediction of joint strength in welded samples by RSW. A design of experiments (DOE) is prepared according to effective process parameters includes welding current, welding cycle, cooling cycle and electrode force. The sheet metal samples prepared from AISI 1075 carbon steel. Tensile test specimens are prepared and the tensile-shear strength of welded samples are measured. A model is developed according to ANFIS and trained according to teaching-learning based optimization algorithm. 70 % of test data used for network train and the remained 30 % used for access the accuracy of trained network. The accuracy of the trained network was assessed and the results show that the trained network can predict the joint strength with high accuracy. The determination factor (R2) and mean absolute percentage error (MAPE) are 0.99 and 0.48 % for trained data and 0.95 and 6.2% for test data.

In this paper, passive and active vortex-induced vibration control of a circular cylinder that oscillates freely in longitudinal and transverse directions is investigated by utilization of nonlinear energy sink. The nonlinear energy sink is composed of a mass, a damping and a nonlinear spring that attaches inside of vibrating cylinder. The vibrational energy of the main cylinder is transferred to the adsorbent mass, thereby reducing the cylinder oscillations. The effectiveness of the proposed control method, numerical results are presented for four Reynolds numbers located in the lock-in region, Re = 85, 90, 95, 100. According to the numerical simulations, the optimized parameters for the passive nonlinear energy sink are considered equal to ... . It can be seen that at all Reynolds numbers, active nonlinear energy sink perform better than passive energy absorbers in reducing vortex-induced vibrations.

In this article, an adaptive neuro-fuzzy inference system is utilized to model the effect of important parameters in the cortical bone milling process including the rotational speed, feed rate, depth of cut and tool diameter to predict the cutting forces. To model the process force behavior, experimental tests are conducted on the fresh cow femur. Next, the results of performed experiments are used to train and test the inference system. In this model, the most influential parameters of automatic cortical bone milling process including the rotational speed, feed rate, tool diameter and depth of cut are taken as the input parameters, while the cutting forces in the feed direction, normal to the feed direction and normal to the bone surface as well as the resultant force are considered as the output. To this aim, the adaptive neuro-fuzzy inference system relies on 75% of the trained laboratory data and the remaining 25% to test the model validation. The accuracy of the obtained model is investigated using different diagrams and numerous statistical criteria. The results indicate that the adaptive neuro-fuzzy network has shown a successful performance in predicting the cutting forces of cortical bone milling process.

This paper dealing with a novel algorithm based on features of Fuzzy-PID controllers to estimate heat flux on the inverse heat conduction problems. The main structure of Fuzzy-PID is a PID controller in which the proportionalو integrator and the derivative gains are obtained online by fuzzy system. The input of the algorithm is the measured temperatures within the model. In each time-step, the smart controller calculates the proper heat flux in order to adjust the measured temperature with desired input temperature. The model studied a flat plate with an insulated surface and an active level that affects the variable heat flux at the time. The variation of heat flux with time can be considered to be constant, step, and triangular. The measured temperatures are obtained at the active and inactive surface with numerical simulation. The effect of noise level at the measurement temperatures on the accuracy of the proposed method is investigated. The estimations and error analysis indicate that this algorithm is very successful in estimating the different forms of heat flux with different amounts of noise and the different thermocouple positions in the wall.

Vortex induced vibration is a well-known phenomenon in the engineering applications involving the fluid/structure interaction. Especially, it has been observed in various ocean engineering applications such as offshore risers, deep water bridge piers and oil pipelines. In the flow around bluff bodies such as marine risers, in a specific range of Reynolds numbers, the asymmetric vortex shedding at the bluff body wake results in periodic hydrodynamic forces on the riser and consequently the vortex-induced- vibration. When the vortex shedding frequency is close to the natural frequency of the structure, the cylinder tends to dramatically vibrates in transverse direction which is commonly termed as the "lock-in" phenomenon. Since vortex induced vibration is one of the most important causes of fatigue damage and structural instability in marine risers, exploring efficient ways to reduce or suppress vortex induced vibrations, has attracted the attention of many ocean engineering researchers. In the present study, two-way fluid/structure interaction simulation of vortex induced vibration of the circular and truncated cylinders are conducted. For this purpose, laminar flow around an elastically supported two degree of freedom cylinder (circular or truncated), which can freely vibrate in stream-wise and transverse directions, is considered.

To solve the governing equations of two-dimensional, unsteady and incompressible flow over circular and truncated cylinders, a finite volume technique is employed. Moreover, the rigid body motion equations in stream-wise and transverse directions are incorporated into the computational fluid dynamics solver to treat the coupling which exists between the fluid flow and cylinder movement. To calculate the rigid body motion of cylinder and treat the fluid-cylinder interaction, a User-Defined Function is used. In every time step, the temporal variation of hydrodynamic forces (lift and drag) determined by solving the mass and momentum equations are employed as the source terms in rigid body motion equations to compute the velocity and displacement of cylinders. Fluid-structure interaction is handled using the Fluent's moving deforming mesh feature which deforms and remeshes cells during transverse and streamwise motions of the cylinders. The pressure-based solver with first-order implicit unsteady formulation is employed to solve the discretized continuity and momentum equations. The coupling between pressure and velocity fields are handled by using computationally efficient fractional step method along with the non-iterative time-advancement algorithm for time matching strategy in computational fluid dynamics solver. To solve the governing equation for the velocity fields, one needs suitable boundary conditions at the inlet, outlet, lower and upper boundaries, and on the surface of cylinders. A uniform profile of free-stream velocity is used at the inlet. At the outlet, the downstream boundary is located far from the cylinders such that the streamwise gradients for the velocity vectors could safely be set equal to zero. Along the upper and lower boundaries, the y-component velocity is considered to be zero while for the x-component velocity, the gradient in the y-direction is set equal to zero. At the cylinder’ walls, the no-slip condition is imposed on both velocity components.

In order to validate the numerical method used in the study of fluid-structure interaction, the results for the transverse oscillations of the circular cylinder and truncated one (with truncation angle of 45 degrees) at different Reynolds numbers are compared with the results of Kumar et al. (2018). It is noteworthy that the obtained results in the present study are in good agreement with those of Kumar et al. (2018) and the numerical model accurately predicts the maximum amplitude of transverse vibration and the width of the lock-in region. Moreover, the influence of the truncation angle (behind the cylinder) on the vibration suppression of truncated cylinders is evaluated. The results show that as the Reynolds number increases from 80 to 85, the vibration of the truncated cylinders enters the lock-in region and experiences a sharp jump in their transverse displacement. Also, in this region, the truncation angle does not have a significant effect on the transverse vibrations of the cylinders and merely reduces their in-line vibration. However, changing the structural design of the cylinder (making a truncation at the back of the cylinder) has a substantial effect on the vibration reduction in the right half of the synchronization region. At Re = 100 (Reynolds number corresponding to the lock-out region), when the truncation angle increases from zero to 60 degrees, the transverse vibration of the cylinder is reduced by about 66%.

In summary, it is concluded that the significant difference in the oscillation amplitude of the circular and truncated cylinders is in the right half of the lock-in region. When the truncation angle increases, the width of the lock-in region decreases.

An adaptive fuzzy sliding mode controller (AFSMC) is adopted to reduce the 2D flow-induced vibration of an elastically supported square-section cylinder, free to oscillate in stream-wise andtransverse directions in both lock-in and galloping regions. The AFSMC strategy consists of a fuzzy logic inference system intended to follow a sliding-mode controller (SMC), and a robust control system designed to retrieve the variance between the sliding mode and fuzzy controllers.  The sprung square cylinder first experiences vortex-induced vibrations with increasing Reynolds number, and then, after passing the critical flow velocity, it confronts high-amplitude and low-frequencyvibrations of galloping owning to its sharp corners. A co-simulation platform is considered by linking the AFSMC system modeled in Matlab/Simulink to the plant model implemented in Fluent, aiming at the calculation of opposite control force needed for comprehensive annihilation of the cylinder motions. Based on the performed numerical simulations, it becomes clear that the utilized active control system has successfully mitigated the two-degree-of-freedom vibrations of a square cylinder in both the lock-in region and galloping zone. Here, the vibration amplitudes in the transverse andstreamwise directions have decreased by 93% and 94%, for the lock-in region and 93% and 99%, for the galloping zone, respectively.

In this paper a collaborative simulation between Matlab/Simulink and Fluent softwares is done to active control of an elastically mounted circular cylinder, free to move in in-line and cross-flow directions. The control goal is reduction of the two-dimensional vortex-induced vibrations (VIV) of cylinder. The natural oscillator frequency is complemented with the vortex shedding frequency of a stationary cylinder. A parallel simulation scheme is realized by linking the PID controller employed in Matlab/Simulink to the plant model constructed in Fluent, aiming at calculation of the control force necessary for total annihilation of the transverse cylinder vibrations. The simulation results reveal the high performance and effectiveness of the adopted control algorithm in diminishing the VIV of elastic cylinder. Once the control algorithm is turned on, there is a extreme reduction in the transverse and in-line cylinder oscillation amplitudes as well as lift and drag coefficients values. In particular, it is observed that the coalesced vortices in the far wake region of the uncontrolled cylinder are seprated and displaying wake vortices of weaker strengths.