Heat source model for laser beam welding of steel-aluminum lap joints

2017 ◽  
Vol 93 (1-4) ◽  
pp. 709-716 ◽  
Author(s):  
Anton Evdokimov ◽  
Katrin Springer ◽  
Nikolay Doynov ◽  
Ralf Ossenbrink ◽  
Vesselin Michailov
2018 ◽  
Vol 7 (4.10) ◽  
pp. 85 ◽  
Author(s):  
Harinadh Vemanaboina ◽  
G. Edison ◽  
Suresh Akella ◽  
Ramesh Kumar Buddu

Laser welding process is employed in the manufacturing of critical components where the final assembly units necessitate strict tolerances like low distortions and residual stresses. Laser beam welding offers several advantages like low heat input, very narrow heat affected zone, low residual stresses, low distortions and good mechanical joint properties in the weld joints when compared to the conventional techniques like Tungsten Inert Gas Arc welding processes. However, the implementation of laser beam welding holds certain challenges like process parameters optimization, experimental set-up and handling and expensive costs. In order to minimize the complex experimental process, simulation techniques using Finite Element Methods (FEM) are employed in order to estimate the heat input and weld process optimization prior to the experiments. This greatly helps in the optimization and estimation of the incurred stresses and distortions with the adapted weld process with known input weld process parameters. The present work reports the Gaussian heat source model for the laser welding of Inconel 625 Alloy plates. The developed moving heat source model is presented and demonstrated with the thermal profiles in terms of the thermal histogram, temperature profiles in the joint cross sections through welded region, interface across the joints.  


2016 ◽  
Vol 879 ◽  
pp. 2008-2013
Author(s):  
Udo Hartel ◽  
Alexander Ilin ◽  
Steffen Sonntag ◽  
Vesselin Michailov

In this paper the technique of parameter identification is investigated to reconstruct the 3D transient temperature field for the simulation of laser beam welding. The reconstruction bases on volume heat source models and makes use of experimental data. The parameter identification leads to an inverse heat conduction problem which cannot be solved exactly but in terms of an optimal alignment of the simulation and experimental data. To solve the inverse problem, methods of nonlinear optimization are applied to minimize a problem dependent objective function.In particular the objective function is generated based on the Response Surface Model (RSM) technique. Sampling points on the RSM are determined by means of Finite-Element-Analysis (FEA). The scope of this research paper is the evaluation and comparison of gradient based and stochastic optimization algorithms. The proposed parameter identification makes it possible to determine the heat source model parameters in an automated way. The methodology is applied on welds of dissimilar material joints.


2009 ◽  
Vol 83-86 ◽  
pp. 858-865
Author(s):  
Abul Fazal M. Arif

Laser processing of sheet metals (such as cutting or welding) involves heating of the substrate material by laser beam with temperature in the substrate materials reaching the melting temperature. Therefore, such laser processes consist of heating, melting and solidification of the substrate metal. An important topic in laser processing simulation is the modeling of the heat source (distribution of heat input). The interaction of laser beam with a molten metal pool is a complex physical phenomenon that still cannot be modeled rigorously. Laser beam as a heat source causes highly non-linear temperature distribution across the cut or weld and various heat source modeling approaches have been reported in the literature. In general, the distribution of heat input can be classified as superficial and volumetric. In this paper, a moving volumetric heat source model is presented. Using the proposed heat source model, laser cutting process is simulated and residual stresses generated in the cutting region are predicted.


2020 ◽  
Vol 106 (7-8) ◽  
pp. 3367-3379 ◽  
Author(s):  
Shahriar Imani Shahabad ◽  
Zhidong Zhang ◽  
Ali Keshavarzkermani ◽  
Usman Ali ◽  
Yahya Mahmoodkhani ◽  
...  

2016 ◽  
Vol 87 (5-8) ◽  
pp. 1985-1997 ◽  
Author(s):  
Junqiang Wang ◽  
Jianmin Han ◽  
Joseph P. Domblesky ◽  
Zhiyong Yang ◽  
Yingxin Zhao ◽  
...  

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