The application of friction stir welding(FSW) is growing owing to the omission of difficulties in traditional welding processes. In the current investigation, artificial neural network(ANN) technique was employed to p...The application of friction stir welding(FSW) is growing owing to the omission of difficulties in traditional welding processes. In the current investigation, artificial neural network(ANN) technique was employed to predict the microhardness of AA6061 friction stir welded plates. Specimens were welded employing triangular and tapered cylindrical pins. The effects of thread and conical shoulder of each pin profile on the microhardness of welded zone were studied using tow ANNs through the different distances from weld centerline. It is observed that using conical shoulder tools enhances the quality of welded area. Besides, in both pin profiles threaded pins and conical shoulders increase yield strength and ultimate tensile strength. Mean absolute percentage error(MAPE) for train and test data sets did not exceed 5.4% and 7.48%, respectively. Considering the accurate results and acceptable errors in the models' responses, the ANN method can be used to economize material and time.展开更多
A two-dimensional computational fluid dynamics model was established to simulate the friction stir butt-welding of 6061 aluminum alloy. The dynamic mesh method was applied in this model to make the tool move forward a...A two-dimensional computational fluid dynamics model was established to simulate the friction stir butt-welding of 6061 aluminum alloy. The dynamic mesh method was applied in this model to make the tool move forward and rotate in a manner similar to a real tool, and the calculated volumetric source of energy was loaded to establish a similar thermal environment to that used in the experiment. Besides, a small piece of zinc stock was embedded into the workpiece as a trace element. Temperature fields and vector plots were determined using a finite volume method, which was indirectly verified by traditional metallography. The simulation result indicated that the temperature distribution was asymmetric but had a similar tendency on the two sides of the welding line. The maximum temperature on the advancing side was approximately 10 K higher than that on the retreating side. Furthermore, the precise process of material flow behavior in combination with streamtraces was demonstrated by contour maps of the phases. Under the shearing force and forward extrusion pressure, material located in front of the tool tended to move along the tangent direction of the rotating tool. Notably, three whirlpools formed under a special pressure environment around the tool, resulting in a uniform composition distribution.展开更多
This paper presents a method of determining the friction coefficient in metal forming using multilayer artificial neural networks based on experimental data obtained from strip drawing test. The number of input variab...This paper presents a method of determining the friction coefficient in metal forming using multilayer artificial neural networks based on experimental data obtained from strip drawing test. The number of input variables of the artificial neural network has been optimized using genetic algorithm. This process is based on surface parameters of the sheet and dies, sheet material parameters and clamping force as input parameters to train the neural network. In addition to demonstrating the fact that regression statistics model using genetic selection and intelligent problem solver are better than models without preprocessing of input data, the sensitivity analysis of the input variables has been conducted. This avoids the time-consuming testing of neurons in finding the best network architecture. The obtained results from this study have also pointed out that genetic algorithm can successfully be applied to optimize the training set and the outputs agree with experimental results. This allows reduction or elimination of expensive experimental tests to determine friction coefficient value.展开更多
A new method to recover packet losses using (2,1,m) convolutional codes is proposed. The erasure correcting decoding algorithm and the decoding determinant theorem is presented. It is also proved that the codes with o...A new method to recover packet losses using (2,1,m) convolutional codes is proposed. The erasure correcting decoding algorithm and the decoding determinant theorem is presented. It is also proved that the codes with optimal distance profile have also optimal delay characteristic. Simulation results show that the proposed method can recover the packet losses more elliciently than RS codes over different decoding delay conditions and thus suits for different packet network delav conditions.展开更多
To meet the authorization administration requirements in a distributedcomputer network environment, this paper extends the role-based access control model with multipleapplication dimensions and establishes a new acce...To meet the authorization administration requirements in a distributedcomputer network environment, this paper extends the role-based access control model with multipleapplication dimensions and establishes a new access control model ED-RBAC(Extended Role Based AccessControl Model) for the distributed environment. We propose an extendable hierarchical authorizationassignment framework and design effective role-registeringi role-applying and role-assigningprotocol with symmetric and asymmetric cryptographic systems. The model can be used to simplifyauthorization administration in a distributed environment with multiple applications.展开更多
In this paper,a method of reducing the tracking error in CNC machining is proposed.The structured neural network is used to approximate the discontinuous friction in CNC machining,which has jump points and uncertainti...In this paper,a method of reducing the tracking error in CNC machining is proposed.The structured neural network is used to approximate the discontinuous friction in CNC machining,which has jump points and uncertainties.With the estimated nonlinear friction function,the reshaped trajectory can be computed from the desired one by solving a second order ODE such that when the reshaped trajectory is fed into the CNC controller,the output is the desired trajectory and the tracking error is eliminated in certain sense.The proposed reshape method is also shown to be robust with respect to certain parameters of the dynamic system.展开更多
The ultra-low specific speed centrifugal blower is widely used in energy industries due to its features such as low flow rate,high pressure and low manufacturing cost. However,the width-to-diameter ratio of the above ...The ultra-low specific speed centrifugal blower is widely used in energy industries due to its features such as low flow rate,high pressure and low manufacturing cost. However,the width-to-diameter ratio of the above blower becomes relatively small to satisfy the needed operation condition and its performances are considerably degraded as a result of relatively high leakage,disc friction and passage friction loss consequently. The purpose of this paper is to improve its performance through the optimization design of the blade’s profile properly. Based on artificial neural networks (ANN) and hierarchical fair competition genetic algorithms with dynamic niche (HFCDN-GAs),the optimization design approach is established. By conjoining Bezier parameterization and FINE/TURBO solver,the optimized blade is designed by adjusting the profile gradually. An industrial ultra-low specific speed centrifugal blower with parallel hub and shroud has been selected as a reference case for optimization design. The performance investigations of the centrifugal blowers with different types of blades are conducted. The conclusions of the performance improvement of the optimized blade provide positive evidences in the application of the optimization design of the above blower blade.展开更多
文摘The application of friction stir welding(FSW) is growing owing to the omission of difficulties in traditional welding processes. In the current investigation, artificial neural network(ANN) technique was employed to predict the microhardness of AA6061 friction stir welded plates. Specimens were welded employing triangular and tapered cylindrical pins. The effects of thread and conical shoulder of each pin profile on the microhardness of welded zone were studied using tow ANNs through the different distances from weld centerline. It is observed that using conical shoulder tools enhances the quality of welded area. Besides, in both pin profiles threaded pins and conical shoulders increase yield strength and ultimate tensile strength. Mean absolute percentage error(MAPE) for train and test data sets did not exceed 5.4% and 7.48%, respectively. Considering the accurate results and acceptable errors in the models' responses, the ANN method can be used to economize material and time.
基金Project(51475232)supported by the National Natural Science Foundation of China
文摘A two-dimensional computational fluid dynamics model was established to simulate the friction stir butt-welding of 6061 aluminum alloy. The dynamic mesh method was applied in this model to make the tool move forward and rotate in a manner similar to a real tool, and the calculated volumetric source of energy was loaded to establish a similar thermal environment to that used in the experiment. Besides, a small piece of zinc stock was embedded into the workpiece as a trace element. Temperature fields and vector plots were determined using a finite volume method, which was indirectly verified by traditional metallography. The simulation result indicated that the temperature distribution was asymmetric but had a similar tendency on the two sides of the welding line. The maximum temperature on the advancing side was approximately 10 K higher than that on the retreating side. Furthermore, the precise process of material flow behavior in combination with streamtraces was demonstrated by contour maps of the phases. Under the shearing force and forward extrusion pressure, material located in front of the tool tended to move along the tangent direction of the rotating tool. Notably, three whirlpools formed under a special pressure environment around the tool, resulting in a uniform composition distribution.
文摘This paper presents a method of determining the friction coefficient in metal forming using multilayer artificial neural networks based on experimental data obtained from strip drawing test. The number of input variables of the artificial neural network has been optimized using genetic algorithm. This process is based on surface parameters of the sheet and dies, sheet material parameters and clamping force as input parameters to train the neural network. In addition to demonstrating the fact that regression statistics model using genetic selection and intelligent problem solver are better than models without preprocessing of input data, the sensitivity analysis of the input variables has been conducted. This avoids the time-consuming testing of neurons in finding the best network architecture. The obtained results from this study have also pointed out that genetic algorithm can successfully be applied to optimize the training set and the outputs agree with experimental results. This allows reduction or elimination of expensive experimental tests to determine friction coefficient value.
基金Supported by National Natural Science Foundation of China under Grant No.69896246
文摘A new method to recover packet losses using (2,1,m) convolutional codes is proposed. The erasure correcting decoding algorithm and the decoding determinant theorem is presented. It is also proved that the codes with optimal distance profile have also optimal delay characteristic. Simulation results show that the proposed method can recover the packet losses more elliciently than RS codes over different decoding delay conditions and thus suits for different packet network delav conditions.
文摘To meet the authorization administration requirements in a distributedcomputer network environment, this paper extends the role-based access control model with multipleapplication dimensions and establishes a new access control model ED-RBAC(Extended Role Based AccessControl Model) for the distributed environment. We propose an extendable hierarchical authorizationassignment framework and design effective role-registeringi role-applying and role-assigningprotocol with symmetric and asymmetric cryptographic systems. The model can be used to simplifyauthorization administration in a distributed environment with multiple applications.
基金partially supported by a National Key Basic Research Project of Chinaa USA NSF grant CCR-0201253the Foundation of UPC for the Author of National Excellent Doctoral Dissertation under Grant No.120501A
文摘In this paper,a method of reducing the tracking error in CNC machining is proposed.The structured neural network is used to approximate the discontinuous friction in CNC machining,which has jump points and uncertainties.With the estimated nonlinear friction function,the reshaped trajectory can be computed from the desired one by solving a second order ODE such that when the reshaped trajectory is fed into the CNC controller,the output is the desired trajectory and the tracking error is eliminated in certain sense.The proposed reshape method is also shown to be robust with respect to certain parameters of the dynamic system.
基金supported by the National Natural Science Foundation of China (Grant No.50776056)the National High Technology Research and Development Program of China ("863" Program) (Grant No.2009AA05Z201)
文摘The ultra-low specific speed centrifugal blower is widely used in energy industries due to its features such as low flow rate,high pressure and low manufacturing cost. However,the width-to-diameter ratio of the above blower becomes relatively small to satisfy the needed operation condition and its performances are considerably degraded as a result of relatively high leakage,disc friction and passage friction loss consequently. The purpose of this paper is to improve its performance through the optimization design of the blade’s profile properly. Based on artificial neural networks (ANN) and hierarchical fair competition genetic algorithms with dynamic niche (HFCDN-GAs),the optimization design approach is established. By conjoining Bezier parameterization and FINE/TURBO solver,the optimized blade is designed by adjusting the profile gradually. An industrial ultra-low specific speed centrifugal blower with parallel hub and shroud has been selected as a reference case for optimization design. The performance investigations of the centrifugal blowers with different types of blades are conducted. The conclusions of the performance improvement of the optimized blade provide positive evidences in the application of the optimization design of the above blower blade.
