Separation of temperature and strain in a single fiber BOTDA system by pseudo-inverse approach

2017 ◽  
Author(s):  
Felipe Lima dos Reis Marques ◽  
Claudio Floridia ◽  
Thayane Alves Almeida ◽  
Ariovaldo Antonio Leonardi ◽  
Fabiano Fruett
Keyword(s):  
Single Fiber ◽  
Inverse Approach ◽  
Pseudo Inverse

A Pseudo Inverse Approach with Kinematically Admissible Intermediate Configurations for the Axi-Symmetrical Cold Forging Modelling

2011 ◽  
Vol 399-401 ◽  
pp. 1832-1837 ◽  
Author(s):  
Ali Halouani ◽  
Yu Ming Li ◽  
Boussad Abbès ◽  
Ying Qiao Guo
Keyword(s):  
Equivalent Stress ◽  
Cold Forging ◽  
Loading History ◽  
Proportional Loading ◽  
Inverse Approach ◽  
Simplified Method ◽  
Tensile Curve ◽  
Stress Estimation ◽  
Good Strain ◽  
Pseudo Inverse

A simplified method called “Pseudo Inverse Approach” (PIA) has been developed for the axi-symmetrical cold forging modeling in this paper. The traditional “Inverse Approach” (IA) based on the assumptions of the proportional loading and simplified tool actions may quickly give a fairly good strain distribution, but poor stress estimation. Meanwhile the PIA proposed in this paper not only keeps the advantages of the Inverse Approach but also gives good stress estimation by taking into account the loading history. To fulfill this aim, some kinematically admissible intermediate configurations represented by the free surface are used to consider the deformation paths without classical contact treatment. A new direct algorithm of plasticity integration has been used by using the notion of equivalent stress and the tensile curve, leading to a very fast and robust plastic integration procedure. An axi-symmetrical forging has been taken as an example to validate the PIA.

Efficient pseudo-inverse approach for damage prediction in cold forging process simulation

2014 ◽  
Vol 23 (8) ◽  
pp. 1168-1188 ◽  
Author(s):  
Ali Halouani ◽  
Yuming Li ◽  
Boussad Abbès ◽  
Ying-Qiao Guo
Keyword(s):  
Process Simulation ◽  
Large Strain ◽  
Damage Model ◽  
Cold Forging ◽  
Integration Algorithm ◽  
Damage Prediction ◽  
Forging Process ◽  
Inverse Approach ◽  
Pseudo Inverse ◽  
Flow Theory Of Plasticity

This article presents an efficient pseudo-inverse approach for the damage prediction in cold forging process simulation. Pseudo-inverse approach combines the advantages of the fast inverse approach and accurate incremental approaches. Some intermediate configurations are created geometrically and corrected mechanically to well describe the deformation path. The formulation of an axi-symmetrical element based on pseudo-inverse approach is presented. A strain-based damage model is introduced in the flow theory of plasticity. A direct scalar integration algorithm of plasticity-damage is developed, leading to a fast and robust algorithm for large strain increments. The cold forging processes of two axi-symmetrical parts are simulated to validate pseudo-inverse approach by the incremental approach ABAQUS/Explicit. Pseudo-inverse approach gives very good results, but uses much less CPU time.

Optimization of Forging Preforms by Using Pseudo Inverse Approach

2012 ◽  
Vol 504-506 ◽  
pp. 613-618 ◽  
Author(s):  
Ali Halouani ◽  
Y.M. Li ◽  
Boussad Abbès ◽  
Y.Q. Guo ◽  
F.J. Meng ◽  
...  
Keyword(s):  
Effective Strain ◽  
Equivalent Stress ◽  
Optimization Method ◽  
Final Part ◽  
Cold Forging ◽  
Inverse Approach ◽  
Multi Stage ◽  
Optimization Loop ◽  
Forging Force ◽  
Pseudo Inverse

A simplified method called “Pseudo Inverse Approach” (PIA) has been developed for axi-symmetrical cold forging modelling. The approach is based on the knowledge of the final part shape. Some intermediate configurations are introduced and corrected by using a free surface method to consider the deformation paths without classical contact treatment. A new direct algorithm of plasticity is developed using the notion of equivalent stress and the tensile curve, which leads to a very fast and robust plastic integration procedure. Numerical tests have shown that the Pseudo Inverse Approach is very fast compared to the incremental approach. In this paper, the PIA will be used in an optimization loop for the preliminary preform design in multi-stage forging processes. The optimization problem is to minimize the effective strain variation in the final part and the maximum forging force during the forging process. The numerical results of the optimization method using the PIA are compared to those using the classical incremental approaches to show the efficiency and limitations of the PIA.

scholarly journals Thermo-viscoplastic numerical modeling of metal forging process by Pseudo Inverse Approach

2020 ◽  
Vol 21 (2) ◽  
pp. 202
Author(s):  
Anoop Ebey Thomas ◽  
Boussad Abbès ◽  
Yu Ming Li ◽  
Fazilay Abbès ◽  
Jean-Louis Duval
Keyword(s):  
Hot Forging ◽  
Weight Ratio ◽  
Accurate Estimate ◽  
Initial Shape ◽  
Cold Forming ◽  
Forging Process ◽  
Inverse Approach ◽  
Light Weighting ◽  
Pseudo Inverse ◽  
Hot Forging Process

Constant demands of light-weighting have forced many industries to resort to manufacturing practices that promise a component with a higher strength-to-weight ratio. Hot forging is one such method used to produce parts using difficult-to-form materials as well as to achieve complex geometries. Although numerical methods provide an efficient means to predict the material yield and the stress/strain states of the product at different stages of forming and classical methods are accurate enough to provide a suitable representation of the process, they tend to be computationally expensive. This limits their use in process optimization studies. The Pseudo Inverse Approach (PIA) developed in the context of 2D axisymmetric cold forming, provides a quick and fairly accurate estimate of the stress and strain fields in the final product for a given initial shape. In this work, the PIA is extended to include the thermal and viscoplastic effects associated with the hot forging process. The results are compared with commercially available software based on the classical approaches to show the efficiency and the limitations of PIA.

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