Application of FEM and Abductive Network to Determine Forging Force and Billet Dimensions of Near Net-Shape Helical Bevel Gear Forging

2018 ◽  
Vol 920 ◽  
pp. 205-210
Author(s):  
Tung Sheng Yang ◽  
Yu Liang Chang
Keyword(s):  
Finite Element Method ◽  
Finite Element ◽  
Process Parameters ◽  
Prediction Models ◽  
Bevel Gear ◽  
Near Net Shape ◽  
Abductive Network ◽  
Forging Force ◽  
Forging Load ◽  
Element Method

In this paper, the use of the finite element method in conjunction with abductive network is presented to predict the maximum forging force and the volume of billet during near net-shape helical bevel gear forging. The maximum forging load and volume of billet are influenced by the process parameters such as modules, number of teeth, and die temperature. A finite element method is used to investigate the forging of helical bevel gear. In order to verify the prediction of FEM simulation for forging load, the experimental data are compared with the results of current simulation. A finite element analysis is also utilized to investigate the process parameters on forging load and volume of billet. Additionally, the abductive network was applied to synthesize the data sets obtained from the numerical simulation. The prediction models are then established for the maximum forging load and volume of billet of near net-shape helical bevel gear forging under a suitable range of process parameters. After the predictions of the maximum forging force and the volume of billet, the optimum of the power of forging machine and the dimensions of billet are determined.

Predictions of Maximum Forging Load and Effective Stress for Strain-Hardening Material of near Net-Shape Helical Gear Forging

2013 ◽  
Vol 284-287 ◽  
pp. 894-897
Author(s):  
Tung Sheng Yang ◽  
Tsung Hsien Yang
Keyword(s):  
Finite Element Method ◽  
Finite Element ◽  
Strain Hardening ◽  
Effective Stress ◽  
Material Properties ◽  
Helical Gear ◽  
Hardening Material ◽  
Near Net Shape ◽  
Abductive Network ◽  
Forging Load

In this paper, the use of the finite element method in conjunction with abductive network is presented to predict the maximum forging force and effective stress for strain-hardening material during near net-shape helical forging. The maximum forging load and effective stress are influenced by the material properties such as yielding stress, strength coefficient and strain hardening exponent. A finite element method is used to investigate the clamping-type forging of helical gear. In order to verify the prediction of FEM simulation for forging load, the experimental data are compared with the results of current simulation. A finite element analysis is also utilized to investigate the material properties on forging load and maximum effective stress. Additionally, the abductive network was applied to synthesize the data sets obtained from the numerical simulation. The prediction models are then established for the maximum forging load and maximum effective stress of near net-shape helical gear forging under a suitable range of material parameters.

Numerical Simulation of Riveting Process

2010 ◽  
Vol 34-35 ◽  
pp. 641-645
Author(s):  
Hong Shuang Zhang
Keyword(s):  
Numerical Simulation ◽  
Finite Element Method ◽  
Residual Stress ◽  
Finite Element ◽  
Process Parameters ◽  
Static Method ◽  
Riveting Process ◽  
Relationship Of ◽  
The Relationship ◽  
Element Method

In order to fully understanding the distribution of residual stress after riveting and the relationship between residual stress and riveting process parameters during riveting, Finite Element Method was used to establish a riveting model. Quasi-static method to solve the convergence difficulties was adopted in riveting process. The riveting process was divided into six stages according to the stress versus time curves. The relationship of residual stress with rivet length and rivet hole clearance were established. The results show numerical simulation is effective for riveting process and can make a construction for the practical riveting.

scholarly journals Computational Fluid Dynamics (CFD) Modeling and Simulation of Flow Regulatory Mechanism in Artificial Kidney Using Finite Element Method

Membranes ◽  
2020 ◽  
Vol 10 (7) ◽  
pp. 139
Author(s):  
Tuba Yaqoob ◽  
Muhammad Ahsan ◽  
Arshad Hussain ◽  
Iftikhar Ahmad
Keyword(s):  
Finite Element Method ◽  
Finite Element ◽  
Diffusion Model ◽  
Process Parameters ◽  
Clearance Rate ◽  
Pore Diffusion ◽  
Large Size ◽  
Depth Analysis ◽  
Pore Diffusion Model ◽  
Element Method

There is an enormous need in the health welfare sector to manufacture inexpensive dialyzer membranes with minimum dialysis duration. In order to optimize the dialysis cost and time, an in-depth analysis of the effect of dialyzer design and process parameters on toxins (ranging from tiny to large size molecules) clearance rate is required. Mathematical analysis and enhanced computational power of computers can translate the transport phenomena occurring inside the dialyzer while minimizing the development cost. In this paper, the steady-state mass transport in blood and dialysate compartment and across the membrane is investigated with convection-diffusion equations and tortuous pore diffusion model (TPDM), respectively. The two-dimensional, axisymmetric CFD model was simulated by using a solver based on the finite element method (COMSOL Multiphysics 5.4). The effect of design and process parameters is analyzed by solving model equations for varying values of design and process parameters. It is found that by introducing tortuosity in the pore diffusion model, the clearance rate of small size molecules increases, but the clearance rate of large size molecules is reduced. When the fiber aspect ratio (db/L) varies from 900 to 2300, the clearance rate increases 37.71% of its initial value. The results also show that when the pore diameter increases from 10 nm to 20 nm, the clearance rate of urea and glucose also increases by 2.09% and 7.93%, respectively, with tolerated transport of albumin molecules.

A FINITE ELEMENT ANALYSIS FOR THE EFFECTS OF PROCESS PARAMETERS AND MATERIAL ANISOTROPY IN THE CYLINDRICAL DEEP DRAWING

2008 ◽  
Vol 07 (01) ◽  
pp. 21-32
Author(s):  
T. S. YANG ◽  
N. C. HWANG ◽  
R. F. SHYU
Keyword(s):  
Finite Element Method ◽  
Finite Element ◽  
Process Parameters ◽  
Deep Drawing ◽  
Strain Hardening Exponent ◽  
Drawing Process ◽  
Material Anisotropy ◽  
Plastic Strain Ratio ◽  
Deep Drawing Process ◽  
Element Method

Deep drawing process, one of sheet metal forming methods, is very useful in industrial field because of its efficiency. The deep drawing process is affected by many material and process parameters, such as the strain-hardening exponent, plastic strain ratio, anisotropic property of blank, friction and lubrication, blank holder force, presence of drawbeads, the profile radius of die and punch, etc. In this paper, a finite element method is used to investigate the cylindrical deep drawing process. The thickness of product and the forming force predicted by current simulation are compared with the experimental data. A finite element method is also used to investigate the maximum forming load and the minimum thickness of products under various process parameter conditions, including the profile radius of die, the clearance between die cavity and punch and the blank holding force. Furthermore, the material anisotropy and process parameters effect on the earing are also investigated.

Die design for cold precision forging of bevel gear based on finite element method

2009 ◽  
Vol 16 (4) ◽  
pp. 546-551 ◽  
Author(s):  
Jun-song Jin ◽  
Ju-chen Xia ◽  
Xin-yun Wang ◽  
Guo-an Hu ◽  
Hua Liu
Keyword(s):  
Finite Element Method ◽  
Finite Element ◽  
Bevel Gear ◽  
Die Design ◽  
Precision Forging ◽  
Cold Precision Forging ◽  
Element Method

Robust Optimization for Tube Bending Process Based on Finite Element Method

2012 ◽  
Vol 531-532 ◽  
pp. 746-750
Author(s):  
Xue Wen Chen ◽  
Ze Hu Liu ◽  
Jing Li Zhang
Keyword(s):  
Finite Element Method ◽  
Finite Element ◽  
Robust Design ◽  
Process Parameters ◽  
Design Method ◽  
Design Parameters ◽  
Tube Bending ◽  
Performance Variation ◽  
Bending Process ◽  
Element Method

The main causes of performance variation in tube bending process are variations in the mechanical properties of material, initial tube thickness, coefficient of friction and other forming process parameters. In order to control this performance variation and to optimize the tube bending process parameters, a robust design method is proposed in this paper for the tube bending process, based on the finite element method and the Taguchi method. During the robust design process, the finite element analysis is incorporated to simulate the tube bending process and calculate the objective function value, the orthogonal design method is selected to arrange the simulation experiments and calculate the S/N ratio. Finally, a case study for the tube bending process is implemented. With the objective to control tube crack (reduce the maximum thinning ratio) and its variation, the robust design mathematical model is established. The optimal design parameters are obtained and the maximum thinning ratio has been reduced and its variation has been controlled.

scholarly journals Estimating the execution time of fully-online multiscale numerical simulations

2020 ◽  
Author(s):  
Juan Fabian ◽  
Antônio Gomes ◽  
Eduardo Ogasawara
Keyword(s):  
Finite Element Method ◽  
Finite Element ◽  
Numerical Methods ◽  
Numerical Simulations ◽  
Learning Process ◽  
Execution Time ◽  
Prediction Models ◽  
Computational Effort ◽  
Multiscale Numerical Methods ◽  
Element Method

In this paper, we propose a methodology for estimating the execution time of simulations driven by multiscale numerical methods. The methodology explores the idiosyncrasies of multiscale simulators to reduce the uncertainty of predictions. We use the multiscale hybrid-mixed (MHM) finite element method to validate our methodology. We compare our proposed technique with prediction models automatically selected and calibrated by Auto-WEKA. We show that the models obtained with our technique are competitive when compared with the models coming from Auto-WEKA, being interpretable and with much less computational effort during the learning process.

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