Papers by Keyword: Abductive Network

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Authors: Chin Tarn Kwan, Jui Tsai Chang
Abstract: In this paper, the finite element method is employed in conjunction with the abductive network to predict the optimum blank contour of an inner elliptic flange with unevenness in the flanging process. Different flange heights combined with various aspect ratios of the inner elliptic flange are taken into account as the process parameters in this study. A finite element-based code is utilized to investigate the material flow characteristics under different process parameters, and the abductive network is then employed to synthesize the data sets obtained from numerical simulations, thus establishing a predictive model. From this model, an optimal blank contour for producing an elliptic inner flange with unevenness can be found.
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Authors: Chin Tarn Kwan, Jui Tsai Chang, Ching Tien Lin
Abstract: In this paper, the finite element method is employed in conjunction with the abductive network to predict the optimum blank contour of an inner elliptic flange with unevenness in the flanging process. Different flange heights combined with various aspect ratios of the inner elliptic flange are taken into account as the process parameters in this study. A finite element-based code is utilized to investigate the material flow characteristics under different process parameters, and the abductive network is then employed to synthesize the data sets obtained from numerical simulations, thus establishing a predictive model. From this model, an optimal blank contour for producing an elliptic inner flange with unevenness can be found.
253
Authors: Tung Sheng Yang, Jen Chuan Yeh, Sheng Yi Chang
Abstract: This study applies the finite element method (FEM) in con-junction with an abductive network to predict springback’s angle during the U-shaped bending process with counter force. To verify the prediction of FEM simulation for springback, the experimental data are compared with the results of current simulation. Bending force, effective stress distribution and springback are investigated for different process parameters, such as profile radius of die, blank holder force and counter force of U-shaped bending process, by finite element analysis. The abductive network is then utilized to synthesize the data sets obtained from numerical simulations. Finally, prediction model is established for predicting springback’s angle under a suitable range of process parameters.
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Authors: Tung Sheng Yang, S.Q. Lee, J.Y. Li, C. Y. Liu
Abstract: This study applies the finite element method (FEM) in conjunction with an abductive network to predict the surface parameters for strain hardening material of asperity flattening in metal forming process. To verify the prediction of FEM simulation for surface parameters, the experimental data are compared with the results of current simulation. Contact area ratio, surface roughness, skewness and kurtosis are investigated for different process and material parameters, such as normal pressure, bulk strain rate, yielding stress, strength coefficient and strain hardening exponent of surface asperity flattening in metal forming, by finite element analysis. The abductive network is then utilized to synthesize the data sets obtained from numerical simulations, and the prediction model is established for predicting surface parameters. The predicted results of the surface parameters from the prediction model are in good agreement with the results obtained from the FEM simulation.
470
Authors: Tung Sheng Yang, Te Hua Fang, C.T. Kawn, G.L. Ke, S.Y. Chang
Abstract: Instrumented indentation is widely used to probe the elastic and plastic properties of engineering materials. Finite Element Method (FEM) has been widely used for numerical simulation of indentation tests on bulk and film material in order to analyze its deformation response. This study proposed an improved technique to determine the stress-strain curve of bulk material. FEM in conjunction with an abductive network is used to predict the stress-strain relationship of bilinear elastic-plastic material from the nanoindentation test’s force-displacement curve.
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Authors: Tung Sheng Yang, Sheng Yi Chang, Jian Chang Chou
Abstract: Scratch test is mainly used to study mechanical properties of materials near their surface. This study applies the finite element method (FEM) in conjunction with an abductive network to predict the scratch character such as rear contact angle, shape ratio and hardness for strain hardening bulk material of scratch process. To verify the prediction of FEM simulation of scratch process, the experimental data are compared with the results of current simulation. A finite element analysis is also utilized to investigate the material properties on side view contour, rear contact angle, hardness and shape ratio. Additionally, the abductive network was applied to synthesize the data sets obtained from the numerical simulation. The prediction models are then established for the rear contact angle, hardness and shape ratio of nanoscratch process under a suitable range of material parameters.
659
Authors: Tung Sheng Yang, Shuai Qiang Li, Sheng Yi Chang
Abstract: This study applies the finite element method (FEM) in conjunction with an abductive network to predict the workpiece surface parameters, including contact area ratio, surface roughness, skewness and kurtosis, of asperity flattening in sliding contact for metallic thin film on die material during the metal forming process. Contact area ratio, surface roughness, skewness and kurtosis are investigated for different process and material parameters, such as sliding distance, elastic modulus of film, normal pressure and bulk strain rate by finite element analysis. The abductive network is then utilized to synthesize the data sets obtained from numerical simulations, and the prediction model is established for predicting surface parameters. The predicted results of the surface parameters from the prediction model are in good agreement with the results obtained from the FEM simulation of workpiece asperity flattening in sliding contact for metallic thin film on die material.
896
Authors: Jui Chang Lin, Shen Yung Lin, K.S. Lee, Ming Fang Lu, Chia Ming Yen
Abstract: This paper presents a methodology for obtaining an optimal parting line of an injection mould based on FEM analysis and managements. This research utilizes Taguchi’s method to design a DATABASE for the gate position and warping of parts. Firstly, it sets up an injection model via a CAD system, and secondly, utilizes FEM to analyze the warp of the injection mould in different gate positions. Because of different gate positions, the parts experienced extreme differences in the amount of warping. This paper applies the neural network (abductive network) to build the relationship (database) between the gate position and amount of warp. Engineers can use this database without recourse to a CAD model and FEM solution to predict the amount of warping at different gate positions. This procedure saves time in building CAD models and on carrying out FEM analysis. The optimal parting line parameters can then be reached through a Simulated Annealing (SA) optimization algorithm. The methodology uses multi-objective function criteria, with a performance index to obtain perfect parts. This method of database management can offer various design fields of injection mould (e.g., design of gating and runner, and design of cooling system). It already achieves real optimization of design for injection moulding.
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