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: firstname.lastname@example.org
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
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.