scholarly journals Prediction of Springback in the Air Bending Process Using a Kriging Metamodel

2016 ◽  
Vol 6 (5) ◽  
pp. 1200-1206 ◽  
Author(s):  
F. A. Khadra ◽  
A. W. El-Morsy
Keyword(s):  
Finite Element ◽  
Response Surface Methodology ◽  
Response Surface ◽  
Element Model ◽  
Training Data ◽  
Geometrical Parameters ◽  
Air Bending ◽  
Bending Process ◽  
Training Examples ◽  
Exponential Correlation Function

This paper addresses the use of the kriging‏ approach to predict the springback in the air bending process. The materials and the geometrical parameters, which significantly affect the springback, were considered as inputs, and the springback angle was considered as the response. A verified nonlinear finite element model was used to generate the training data required to create the kriging‏ metamodel. The training examples were selected based on computer-generated D-optimal designs. A comparison between the kriging approaches and the response surface methodology is conducted and discussed. The results showed that kriging accurately predicts the finite element springback results. Comparing the accuracy of kriging with a response surface methodology shows that kriging with a 2nd degree polynomial and exponential correlation function predicts the springback more accurately than the response surface methodology.

Effects of Air Bending Parameters on Spingback Using Finite Element Analysis

2013 ◽  
Vol 423-426 ◽  
pp. 978-983
Author(s):  
Xie Li
Keyword(s):  
Finite Element Analysis ◽  
Finite Element ◽  
Finite Element Model ◽  
Element Model ◽  
Internal Stresses ◽  
Element Analysis ◽  
Air Bending ◽  
Bending Process ◽  
Punch Radius ◽  
The Finite Element Model

Springback is a common phenomenon in air bending of sheet metal forming, caused by the elastic redistribution of the internal stresses during unloading. It has been recognized that springback is essential for the design of the air bending. Traditionally, the values of springback is obtained for air bending parameters from handbook tables or springback graphs. However, the handbook tables or springback graphs are obtained using experiments and it is a time consuming processes. In this paper, a finite element model has been used to analyze the air bending process. Some experiments are carried out on ST12 materials, and the finite element model is validated comparing with experiments. In the present research the influence of process variables such as punch radius, die radius and die on springback are discussed using finite element analysis. Thus, the presented results of this research provide a basis of design to improve forming quality.

Prediction the Springback in Air-Bending Process Using Neural Network Metamodel

2014 ◽  
Vol 619 ◽  
pp. 3-7 ◽  
Author(s):  
Fayiz Y. Abu Khadra ◽  
Jaber E. Abu Qudiri ◽  
H.M.A. Hussein
Keyword(s):  
Neural Network ◽  
Sheet Metal ◽  
Back Propagation ◽  
Element Model ◽  
Training Data ◽  
Back Propagation Algorithm ◽  
Air Bending ◽  
Bending Process ◽  
Geometric Deviations ◽  
Nonlinear Finite Element Model

To eliminate geometric deviations of sheet metal subjected to an air-bending process from the geometry required by the designer, it is necessary to predict the accurate value of the springback. Springback is the elastic deformation observed upon removal of the load during a bending process. In order to predict the springback amount, a multidimensional function should be approximated. In this paper, a neural network metamodel (NNM) based on the back propagation algorithm is introduced to predict the springback value. A verified nonlinear finite element model is developed to generate NNM training data. To select the training data for the NNM, computer generated D-optimal designs are utilized. The NNM developed model in this research can be used in determination of the springback value in sheet metal bending.

The Effect of Tool Geometrical Parameters on Cutting Temperature Based on Deform-3D

2013 ◽  
Vol 690-693 ◽  
pp. 2554-2558
Author(s):  
Hua Jing Zhang ◽  
Zhi Tao Tang
Keyword(s):  
Finite Element ◽  
Imaging System ◽  
Cutting Temperature ◽  
Element Model ◽  
Friction Model ◽  
Geometrical Parameters ◽  
Infrared Thermal Imaging ◽  
Temperature Filed ◽  
Thermal Imaging System ◽  
Key Techniques

The finite element method was adopted to predict the cutting temperature filed of workpiece surface when machining aerospace aluminum alloy 7050-T7451. Some key techniques such as the materials flow stress behavior, the separation of the chips with the workpiece, failure and fracture criterion, the tool-chip friction model were discussed in details. To validate the finite element model, the cutting temperature field of the chip was obtained by infrared thermal imaging system. The result revealed that the prediction model is credible. Based on the model, the effects of tool geometrical parameters such as flank wear, cutting edge inclination and corner radius on cutting temperature were analyzed.

Optimization Design of Pressure Shell in Underwater Vehicle Based on Response Surface Model

2009 ◽  
Vol 419-420 ◽  
pp. 89-92
Author(s):  
Zhuo Yi Yang ◽  
Yong Jie Pang ◽  
Zai Bai Qin
Keyword(s):  
Finite Element ◽  
Response Surface ◽  
Optimization Design ◽  
Engineering Application ◽  
Element Model ◽  
Response Surface Model ◽  
Design Stage ◽  
Surface Model ◽  
Design Variables ◽  
Structure Strength

Cylinder shell stiffened by rings is used commonly in submersibles, and structure strength should be verified in the initial design stage considering the thickness of the shell, the number of rings, the shape of ring section and so on. Based on the statistical techniques, a strategy for optimization design of pressure hull is proposed in this paper. Its central idea is that: firstly the design variables are chosen by referring criterion for structure strength, then the samples for analysis are created in the design space; secondly finite element models corresponding to the samples are built and analyzed; thirdly the approximations of these analysis are constructed using these samples and responses obtained by finite element model; finally optimization design result is obtained using response surface model. The result shows that this method that can improve the efficiency and achieve optimal intention has valuable reference information for engineering application.

Sign in / Sign up

Export Citation Format

Share Document