E3S Web Conf.
Volume 132, 2019XXII International Scientific Conference POLSITA 2019 “Progress of mechanical engineering supported by information technology”
|Number of page(s)||10|
|Section||Engineering and Technology|
|Published online||22 November 2019|
A genetic algorithm modelling of temperature distributions in the AZ31B magnesium alloys with 7075 aluminium alloy friction welded joints
1 Faculty of Production Engineering, Warsaw University of Life Sciences, Nowoursynowska 166, 02-787, Warsaw, Poland
2 Faculty of Mechanical Engineering, University of Science and Technology, Al. prof. S. Kaliskiego 7, 85-796, Bydgoszcz, Poland
3 Faculty of Production Engineering, Warsaw University of Technology, Narbutta 85, 02-524, Warsaw, Poland
* Corresponding author: email@example.com
This paper presents a genetic algorithm modelling of temperature distribution during heating and cooling of AZ31B magnesium alloys with 7075 aluminium alloy friction welded joints. The temperature distributions estimated in the joints using K-type thermocouples with the accuracy of ±⚟0.1°C. The thermocouples were installed in 1.2 mm holes at the periphery joint - 5, 10, and 15 mm from the weld interface. Temperature reading was performed with a digital thermometer with the requisition frequency of 1000Hz during friction welding. Maximum temperature measurements in the half-radius of the analysed joints were equal to 305°C and 324°C, for the AZ31B magnesium alloy and 7075 aluminium alloy specimens, respectively. Both temperature and increasing temperature gradient at the axial specimens were higher than those at the half-radius and periphery of the joints. The empirical models for heating T=a/b+exp(ct) and cooling phases T=a-btc were formulated by the authors of this study. These models used to describe the temperature curves of welding process. The goodness of fit of tested mathematical models to the experimental data was evaluated with the coefficient of determination R2. A nonlinear regression analysis was conducted to fit the models by genetic algorithm (GA) using computer program MATLAB.
© The Authors, published by EDP Sciences, 2019
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