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تغییرشکل پلاستیک ورق‌های آلومینیومی تقویت‌شده با روکش پلی‌اوره تحت بار دفعی: بررسی تجربی و مدل‌سازی با شبکه‌ی عصبی | ||
| نشریه مهندسی مکانیک امیرکبیر | ||
| مقاله 14، دوره 53، شماره 2 (Special Issue)، اردیبهشت 1400، صفحه 1251-1268 اصل مقاله (1.36 M) | ||
| نوع مقاله: مقاله پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22060/mej.2020.17127.6515 | ||
| نویسندگان | ||
| توحید میرزابابای مستوفی1؛ مصطفی سیاح بادخور2؛ مهساسادات میر علینقی3؛ هاشم بابایی* 4 | ||
| 1استادیار، دانشکده مهندسی مکانیک، دانشگاه ایوان کی، گرمسار، ایران | ||
| 2گروه مهندسی مکانیک، دانشگاه ایوانکی | ||
| 3استادیار گروه شیمی، دانشکده‌ی علوم پایه، دانشگاه آزاد اسلامی، واحد ورامین- پیشوا، ورامین، ایران | ||
| 4گیلان*مهندسی مکانیک | ||
| چکیده | ||
| از سامانه تک‌مرحله‌ای انفجار مخلوط گاز برای شکل‌دهی آزاد ساختارهای فلز - پلیمر استفاده شده است. در بخش تجربی، به منظور بهبود عملکرد ورق‌های آلومینیومی در برابر بار ضربه‌ای حاصل از انفجار مخلوط گاز، لایه‌ای از ماده پلی‌اوره به پشت ورق فلزی پاشیده شد. به منظور بررسی اثر ضخامت لایه‌های فلزی و پلیمری بر پاسخ دینامیکی سازه، از ورق آلومینیومی در ضخامت‌های 1، 5/1، 2 و 5/2 میلی‌متر و همچنین روکش پلی‌اوره در ضخامت‌های 3، 4، 5 و 6 میلی‌متر استفاده شده است. نتایج تجربی نشان داد که پاشش ماده پلی‌اوره به پشت ورق آلومینیومی می‌تواند بیشترین خیز دائمی سازه را تا میزان بسیار چشم‌گیری کاهش داده و از پارگی نمونه‌های آلومینیومی جلوگیری کند. در بخش مدل‌سازی عددی، از شبکه عصبی از نوع دسته‌بندی گروهی داده‌ها برای ارائه یک مدل ریاضی بر مبنای اعداد بی‌بعد جهت پیش‌بینی بیشترین خیز دائمی ساختارهای فلز - پلیمر تحت بار دفعی استفاده شد. به منظور افزایش قابلیت پیش‌بینی شبکه عصبی پیشنهادی برای این فرآیند، داده‌ها به دو دسته آموزش و پیش‌بینی تقسیم شدند نتایج بدست‌آمده نشان داد که توافق خوبی بین مدل ارائه‌شده با مقادیر تجربی برقرار است به‌طوری‌که تمامی نقاط در محدوده خطای کمتر از10% قرار گرفتند. | ||
| کلیدواژه‌ها | ||
| آلومینیوم؛ پلی‌اوره؛ انفجار مخلوط گاز؛ شبکه عصبی؛ مدل‌سازی | ||
| عنوان مقاله [English] | ||
| Plastic Deformation of Reinforced Aluminum Plates with Polyurea Coating under Impulsive Loading | ||
| نویسندگان [English] | ||
| Tohid Mirzababaie Mostofi1؛ Mostafa Sayah Badkhor2؛ ئشاسشسشیشف Miralinaghi3؛ Hashem Babaei4 | ||
| 1Assistant Professor, Faculty of Mechanical Engineering, University of Eyvanekey, Garmsar, Iran | ||
| 2Department of Mechanical Engineering, University of Eyvanekey | ||
| 3Department of Chemistry, Faculty of Science, Islamic Azad University, Varamin-Pishva Branch ,Varamin, Iran | ||
| چکیده [English] | ||
| A single-stage gas detonation apparatus was used for the free forming of metallic-polymeric structures. In the experimental section, to improve the performance of aluminum plates under gas mixture detonation loading, a layer of polyurea material was sprayed onto the back surface of the metallic plate. To investigate the effect of the thickness of the metallic and polymeric layers on the dynamic response of the structure, aluminum plates with different thicknesses of 1, 1.5, 2, and 2.5 mm, as well as polyurea coatings with different thicknesses of 3, 4, 5 and 6 mm, were used. Experimental results showed that spraying the polyurea coating onto the back surface of aluminum plates can significantly reduce the maximum permanent deflection of the structure and also prevent the rupture of the aluminum specimens. In the numerical modeling section, the group method of data handling neural network was used to present a mathematical model based on dimensionless numbers to predict the maximum permanent deflection of metallic-polymeric structures under impulsive loading. To increase the prediction capability of the proposed neural network for this process, the experimental data were divided into two training and prediction sets. The results showed that good agreement between the proposed model and the corresponding experimental results is obtained and all data points are within the ±10% error range. | ||
| کلیدواژه‌ها [English] | ||
| Aluminum, Polyurea, Gas detonation forming method, Neural network, Modelling | ||
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