پیوندهای مفید
آمار
| تعداد نشریات | 9 |
| تعداد شمارهها | 447 |
| تعداد مقالات | 5,734 |
| تعداد مشاهده مقاله | 8,047,196 |
| تعداد دریافت فایل اصل مقاله | 6,547,393 |
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 (2.31 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 | ||
| مراجع | ||
|
[1] T.M. Mostofi, H. Babaei, M. Alitavoli, Theoretical analysis on the effect of uniform and localized impulsive loading on the dynamic plastic behaviour of fully clamped thin quadrangular plates, Thin-Walled Structures, 109 (2016) 367-376. [2] T.M. Mostofi, A. Golbaf, A. Mahmoudi, M. Alitavoli, H. Babaei, Closed-form analytical analysis on the effect of coupled membrane and bending strains on the dynamic plastic behaviour of fully clamped thin quadrangular plates due to uniform and localized impulsive loading, Thin-Walled Structures, 123 (2018) 48-56. [3] M. Yasar, Gas detonation forming process and modeling for efficient spring-back prediction, Journal of materials processing technology, 150(3) (2004) 270-279. [4] M. Yaşar, H.I. Demirci, I. Kadi, Detonation forming of aluminium cylindrical cups experimental and theoretical modelling, Materials & design, 27(5) (2006) 397-404. [5] M. Kleiner, M. Hermes, M. Weber, H. Olivier, G. Gershteyn, F.-W. Bach, A. Brosius, Tube expansion by gas detonation, Production Engineering, 1(1) (2007) 9-17. [6] M.K. Meybodi, H. Bisadi, Gas Detonation Forming by a mixture of H2+ O2 Detonation, World Academy of Science, Engineering and Technology, 33 (2009) 55-58. [7] M. Khaleghi, B.S. Aghazadeh, H. Bisadi, Efficient oxyhydrogen mixture determination in gas Detonation forming, Int. J. Mech. Mechatron. Eng, 7 (2013) 1748-1754. [8] H. Babaei, T.M. Mostofi, S.H. Sadraei, Effect of gas detonation on response of circular plate-experimental and theoretical, Structural Engineering and Mechanics, 56(4) (2015) 535-548. [9] H. Babaei, T. Mirzababaie Mostofi, M. Alitavoli, Experimental investigation and analytical modelling for forming of circular-clamped plates by using gases mixture detonation, Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, (2015) 0954406215614336. [10] H. Babaei, T.M. Mostofi, M. Alitavoli, A. Darvizeh, Empirical modelling for prediction of large deformation of clamped circular plates in gas detonation forming process, Experimental Techniques, 40(6) (2016) 1485-1494. [11] H. Babaei, T.M. Mostofi, M. Namdari-Khalilabad, M. Alitavoli, K. Mohammadi, Gas mixture detonation method, a novel processing technique for metal powder compaction: Experimental investigation and empirical modeling, Powder technology, 315 (2017) 171-181. [12] S.P. Patil, M. Popli, V. Jenkouk, B. Markert, Numerical modelling of the gas detonation process of sheet metal forming, in: Journal of Physics: Conference Series, IOP Publishing, 2016, pp. 032099. [13] V. Jenkouk, S. Patil, B. Markert, Joining of tubes by gas detonation forming, in: Journal of Physics: Conference Series, IOP Publishing, 2016, pp. 032101. [14] S. Patil, K. Prajapati, V. Jenkouk, H. Olivier, B. Markert, Experimental and numerical studies of sheet metal forming with damage using gas detonation process, Metals, 7(12) (2017) 556. [15] T.M. Mostofi, H. Babaei, M. Alitavoli, The influence of gas mixture detonation loads on large plastic deformation of thin quadrangular plates: Experimental investigation and empirical modelling, Thin-Walled Structures, 118 (2017) 1-11. [16] T. Mirzababaie Mostofi, H. Babaei, M. Alitavoli, Experimental and theoretical study on large ductile transverse deformations of rectangular plates subjected to shock load due to gas mixture detonation, Strain, 53(4) (2017) e12235. [17] T.M. Mostofi, H. Babaei, M. Alitavoli, G. Lu, D. Ruan, Large transverse deformation of double-layered rectangular plates subjected to gas mixture detonation load, International Journal of Impact Engineering, 125 (2019) 93-106. [18] M. Amini, J. Isaacs, S. Nemat-Nasser, Experimental investigation of response of monolithic and bilayer plates to impulsive loads, International Journal of Impact Engineering, 37(1) (2010) 82-89. [19] M. Amini, A. Amirkhizi, S. Nemat-Nasser, Numerical modeling of response of monolithic and bilayer plates to impulsive loads, International Journal of Impact Engineering, 37(1) (2010) 90-102. [20] M. Amini, J. Isaacs, S. Nemat-Nasser, Investigation of effect of polyurea on response of steel plates to impulsive loads in direct pressure-pulse experiments, Mechanics of Materials, 42(6) (2010) 628-639. [21] M. Amini, J. Simon, S. Nemat-Nasser, Numerical modeling of effect of polyurea on response of steel plates to impulsive loads in direct pressure-pulse experiments, Mechanics of Materials, 42(6) (2010) 615-627. [22] K. Ackland, C. Anderson, T.D. Ngo, Deformation of polyurea-coated steel plates under localised blast loading, International Journal of Impact Engineering, 51 (2013) 13-22. [23] P. Tran, T.D. Ngo, A. Ghazlan, Numerical modelling of hybrid elastomeric composite panels subjected to blast loadings, Composite Structures, 153 (2016) 108-122. [24] A. Remennikov, T. Ngo, D. Mohotti, B. Uy, M. Netherton, Experimental investigation and simplified modeling of response of steel plates subjected to close-in blast loading from spherical liquid explosive charges, International journal of impact engineering, 101 (2017) 78-89. [25] Y. Li, Z. Chen, T. Zhao, X. Cao, Y. Jiang, D. Xiao, D. Fang. An experimental study on dynamic response of polyurea coated metal plates under intense underwater impulsive loading. International Journal of Impact Engineering. 133 (2019) 103361. [26] L. H. Dai, C. Wu, F. J. An, S. S. Liao. Experimental Investigation of Polyurea-Coated Steel Plates at Underwater Explosive Loading. Advances in Materials Science and Engineering (2018). [27] E. Sanchez, T. Shibata, L.A. Zadeh, Genetic algorithms and fuzzy logic systems: Soft computing perspectives, World Scientific, 1997. [28] K. Kristinsson, G.A. Dumont, System identification and control using genetic algorithms, IEEE Transactions on Systems, Man, and Cybernetics, 22(5) (1992) 1033-1046. [29] A.G. Ivakhnenko, Polynomial theory of complex systems, IEEE transactions on Systems, Man, and Cybernetics, (4) (1971) 364-378. [30] K.J. Åström, P. Eykhoff, System identification—a survey, Automatica, 7(2) (1971) 123-162. [31] Z. Xue, J.W. Hutchinson, Neck retardation and enhanced energy absorption in metal–elastomer bilayers, Mechanics of Materials, 39(5) (2007) 473-487. [32] O. Izadi, M. Silani, P. Mosaddegh, M. Farzin. Warpage and bending behavior of polymer–metal hybrids: experimental and numerical simulations. The International Journal of Advanced Manufacturing Technology, 98(1-4) (2018) 873-885. [33] O. Izadi, P. Mosaddegh, M. Silani, M. Dinari. An experimental study on mechanical properties of a novel hybrid metal–polymer joining technology based on a reaction between isocyanate and hydroxyl groups. Journal of Manufacturing Processes, 30 (2017) 217-225. [34] D.-W. Lee, S.-W. Seo, K.-B. Sim, Online evolution for cooperative behavior in group robot systems, International Journal of Control, Automation, and Systems, 6(2) (2008) 282-287. [35] S.J. Farlow, Self-organizing methods in modeling: GMDH type algorithms, CrC Press, 1984. [36] N. Nariman-Zadeh, A. Darvizeh, A. Jamali, A. Moeini, Evolutionary design of generalized polynomial neural networks for modelling and prediction of explosive forming process, Journal of Materials Processing Technology, 164 (2005) 1561-1571. [37] N. Nariman-Zadeh, K. Atashkari, A. Jamali, A. Pilechi, X. Yao, Inverse modelling of multi-objective thermodynamically optimized turbojet engines using GMDH-type neural networks and evolutionary algorithms, Engineering Optimization, 37(5) (2005) 437-462. [38] A. Jamali, A. Hajiloo, N. Nariman-Zadeh, Reliability-based robust Pareto design of linear state feedback controllers using a multi-objective uniform-diversity genetic algorithm (MUGA), Expert systems with Applications, 37(1) (2010) 401-413. [39] M. Ahmadi, M.-A. Ahmadi, M. Mehrpooya, M. Rosen, Using GMDH neural networks to model the power and torque of a stirling engine, Sustainability, 7(2) (2015) 2243-2255. [40] N. Nariman-Zadeh, A. Darvizeh, M. Felezi, H. Gharababaei, Polynomial modelling of explosive compaction process of metallic powders using GMDH-type neural networks and singular value decomposition, Modelling and Simulation in Materials Science and Engineering, 10(6) (2002) 727. [41] H. Gharababaei, N. Nariman-Zadeh, A. Darvizeh, A simple modelling method for deflection of circular plates under impulsive loading using dimensionless analysis and singular value decomposition, Journal of Mechanics, 26(3) (2010) 355-361. [42] M.A. Ahmadi, M. Golshadi, Neural network based swarm concept for prediction asphaltene precipitation due to natural depletion, Journal of Petroleum Science and Engineering, 98 (2012) 40-49.
| ||
|
آمار تعداد مشاهده مقاله: 951 تعداد دریافت فایل اصل مقاله: 1,066 |
||