نویسنده
دانشکده مهندسی مواد، دانشگاه صنعتی اصفهان، اصفهان
چکیده
جوشکاری اصطکاکی اغتشاشی از روشهای بسیار کاربردی در اتصال فلزات غیرمشابه است. در این پژوهش به شبیه‌سازی توزیع حرارت در جوشکاری اصطکاکی اغتشاشی اتصال غیرمشابه فولاد زنگ‌نزن 304 به آلیاژ آلومینیوم 5083 با استفاده از روش المان محدود پرداخته شده است. حل حرارتی برای این مسئله از دو روش حل حالت پایدار و نیز حل حالت گذرا استفاده شده و دو روش با یکدیگر مقایسه شده‌اند. قابل ذکر است که، به‌منظور اعتبارسنجی مدل، ورق‌های فولاد زنگ‌نزن و آلومینیوم آماده‌سازی شده و جوشکاری اصطکاکی اغتشاشی صورت گرفته است. به‌علاوه با به‌کار بردن ترموکوپل بر قطعات، تاریخچه دمایی نقاط حین جوشکاری برای دو فلز به‌دست آمد. پس از آن، نتایج حاصل از شبیه‌سازی حرارتی با نتایج آزمایشگاهی حاصل از جوشکاری اصطکاکی اغتشاشی این اتصال مقایسه و اعتبارسنجی شد. در پایان با ساخت یک مدل شبکه عصبی، تأثیر پارامترهای ورودی فرایند جوشکاری بر حداکثر دمای زیر ابزار بررسی شد.
کلیدواژه‌ها
عنوان مقاله [English]
Thermal Simulation of Friction Stir Welding in 304 Stainless Steel to 5083 Aluminum Dissimilar Joint
نویسنده [English]
- B. Sadeghian
چکیده [English]
Friction stir welding is of the most applicable methods to join dissimilar metals. In this study, the thermal distribution during the joining of 304 stainless steel and 5083 aluminum alloy by friction stir welding method was simulated by the finite element method. Both, transient and stationary thermal solutions were used in the simulations and the two methods were compared correspondingly. To verify the model, two sheets of stainless steel and aluminum were prepared and the friction stir welding was applied. Additionally, by using thermocouples temperature, the history of points on the sheets was obtained during welding. Then, the simulation and the experimental results were compared to validate the model. Finally, an artificial neural network model was created and the effect of different input parameters on the maximum temperature under the tool was investigated.
کلیدواژه‌ها [English]
- Friction stir welding
- finite element method
- Dissimilar joint
- Transient solution
- Stationary solution
- Artificial Neural Network
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