- Tytuł:
- Investigating the FSW parameter’s role on microstructure and mechanical properties of welding AZ31B–AA8110 alloy
- Autorzy:
-
Dharmalingam, S.
Lenin, K.
Srinivasan, D. - Powiązania:
- https://bibliotekanauki.pl/articles/2173552.pdf
- Data publikacji:
- 2022
- Wydawca:
- Polska Akademia Nauk. Czytelnia Czasopism PAN
- Tematy:
-
AA8011–AZ31B alloy
FSW
friction stir welding
ANN-GA
artificial neural network based genetic algorithm
mechanical properties
stop AA8011–AZ31B
właściwości mechaniczne
zgrzewanie tarciowe z mieszaniem materiału zgorzeliny
algorytm genetyczny
sztuczna sieć neuronowa - Opis:
- The influence of friction stir welding (FSW) in automotive applications is significantly high in recent days as it can boast beneficial factors such as less distortion, minimized residual stresses and enhanced mechanical properties. Since there is no emission of harmful gases, it is regarded as a green technology, which has an energy efficient clean environmental solid-state welding process. In this research work, the FSW technique is employed to weld the AA8011–AZ31B alloy. In addition, the L16 orthogonal array is employed to conduct the experiments. The influences of parameters on the factors such as microstructure, hardness and tensile strength are determined. Microstructure images have shown tunnel formation at low rotational speed and vortex occurrence at high rotational speed. To attain high quality welding, the process parameters are optimized by using a hybrid method called an artificial neural network based genetic algorithm (ANN-GA). The confirmation tests are carried out under optimal welding conditions. The results obtained are highly reliable, which exhibits the optimal features of the hybrid method.
- Źródło:
-
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2022, 70, 1; e140098, 1--7
0239-7528 - Pojawia się w:
- Bulletin of the Polish Academy of Sciences. Technical Sciences
- Dostawca treści:
- Biblioteka Nauki
Artykuł