Springback Analysis In Air Bending Process Through Experiment Based Artificial Neural Networks ICTP 2014

Şenol, Özgü
Esat, Volkan
Darendeliler, Haluk


Springback analysis in air bending process through experiment based artificial neural networks
Senol, Ozgu; Esat, Volkan; Darendeliler, Haluk (2014-10-24)
Sheet metal bending is one of the most frequently used sheet metal forming processes in manufacturing industry. This study investigates bending parameters and springback phenomenon of a stainless-steel sheet in air bending process. In most of the applications, springback is determined either by trial and error procedures or by using numerical methods. Artificial Neural Network (ANN) approach has proved to be a helpful tool for the engineers. ANN is used in this study to predict the springback amounts of sta...
Springback Analysis in Wipe Bending Process through Neural Networks
Şenol, Özgü; Esat, Volkan; Darendeliler, Haluk (null; 2014-06-20)
Springback analysis in bending through finite element method based artificial neural networks
Şenol, Özgü; Darendeliler, Haluk; Esat, Volkan; Department of Mechanical Engineering (2013)
Springback prediction is vital in order to obtain the desired part shape in metal forming processes. In most of the applications, springback amount is determined by trial and error procedures, and recently by using numerical methods or through handbook tables. Artificial Neural Network (ANN) is a helpful tool for the engineers and applied in this study to determine the springback amounts in air, V-die and wipe bending processes. For this purpose, bending processes are analyzed by commercial finite element (...
Akman, T.; Karasözen, Bülent; Kanar-Seymen, Z. (2017-01-01)
The streamline upwind/Petrov Galerkin (SUPG) finite element method is studied for distributed optimal control problems governed by unsteady diffusion-convection-reaction equations with control constraints. We derive stability and convergence estimates for fully-discrete state, adjoint and control and discuss the choice of the stabilization parameter by applying backward Euler method in time. We show that by balancing the error terms in the convection dominated regime, optimal convergence rates can be obtain...
Slippage Estimation of Two Wheeled Mobile Robot Using Recurrent Deep Neural Network
Özçil, Osmail; Koku, Ahmet Buğra; Konukseven, Erhan İlhan (2019-12-14)
Position, velocity and acceleration information are important for mobile robots. Due to the wheel slippages, encoder data may not be reliable and IMU data also contains a cumulative error. Errors of inertial measurements are accumulated over velocity and position estimates and as time increases, these errors grow higher. Due to robot hardware and the operating surface, ground truth may not be available. In this work recurrent deep neural network is proposed in order to reduce the error in speed and yaw angl...
Citation Formats
Ö. Şenol, V. Esat, and H. Darendeliler, “Springback Analysis In Air Bending Process Through Experiment Based Artificial Neural Networks ICTP 2014,” 2014, vol. 81, Accessed: 00, 2021. [Online]. Available: https://hdl.handle.net/11511/72195.