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УДК 621.77, 539.89
Применение физического моделирования с использованием мягких модельных материалов для анализа и оптимизации процессов экструзии металла
M. Hawryluk1, M. Suliga2, M. Wi^claw1
1 Вроцлавский технологический университет, Вроцлав, 50-371, Польша 2 Ченстоховский политехнический университет, Ченстохова, 42-200, Польша
В статье рассмотрена концепция физического моделирования на основе описания модельных материалов и ее применение для анализа, проектирования и оптимизации процессов промышленной обработки металлов давлением. Предлагаемая методика позволяет оценить распределение напряжений и деформаций, силовые параметры процесса, а также определить мертвые зоны и нетипичного течения материала. Метод может служить альтернативой или дополнением к конечно-элементному моделированию. Рассмотрены необходимые условия сходства между физической моделью и реальным процессом, которые позволяют внедрить результаты моделирования в производственные процессы. Представлена развитая база данных мягких модельных материалов, применимая практически для любых металлических материалов. Также предложено новое описание условия пластического подобия на примере двух полупромышленных процессов (прямой и обратной экструзии). При сопоставлении модельных материалов с тремя металлическими материалами выявлены три основных типа обработки металлов давлением при температуре окружающей среды: горячая (свинец), теплая (упрочненный алюминий) и холодная обработка (отожженный алюминий). Применение условия пластического подобия дает хорошие результаты, поскольку при низком значении коэффициента подобия (близком к нулю) метод расчета течения, а также прочностные параметры, полученные при физическом моделировании, очень близки к таковым для промышленного процесса. Предполагается, что оптимальный выбор модельного материала для реального металлического материала позволит быстро и легко оптимизировать производственный процесс с низкими финансовыми затратами.
Ключевые слова: физическое моделирование, экструзия, условие пластического подобия, мягкий модельный материал, мертвая зона
DOI 10.24412/1683-805X-2021-3-51-54
Application of physical modeling with the use of soft model materials for the analysis and optimization of metal extrusion processes
M. Hawryluk1, M. Suliga2, and M. Wi^claw1
1 Wroclaw University of Science and Technology, Wroclaw, 50-371, Poland 2 Czestochowa University of Technology, Cz^stochowa, 42-200, Poland
The study presents the concept of physical modeling together with the characterization of the modeling materials as well as the possibilities of applying this type of physical simulation methods for the analysis, design and optimization of industrial metal forming processes. The method provides the possibility to define the stress and deformation distribution, estimate the force parameters of the given process as well as localize the dead zones and material flow errors. It can also be an alternative or supplementation the finite element modeling. The paper discusses the crucial similarity conditions between the physical model and the real process necessary to transform the results into industrial processes. A developed database of soft model materials was also presented, on the basis of which a model material can be selected for almost any metallic materials. The paper also proposes a new description of the plastic similarity condition, which was verified on an example of a two semi-industrial processes (backward and forward extrusion). The study demonstrates the attempt and the results of the influence of the matching the model materials for three metallic materials which at ambient temperature represent three main types of metal forming processes: hot (lead), warm (reinforced aluminum) and cold working (annealed aluminum). The obtained results showed great usefulness of the proposed condition of plastic similarity, because in the case of a low value of the similarity coefficient (close to zero), both the flow method and the strength parameters obtained in physical modeling are very similar to the industrial process. On this basis, it can be assumed that by selecting the appropriate model material for the actual metallic material, you can quickly and easily optimize the industrial process with low financial outlays.
Keywords: physical modeling, extrusion, plastic similarity condition, soft model material, dead zone
© Hawryluk M., Suliga M., Wi^claw M., 2021
1. Introduction
During the designing of an industrial plastic forming process, it is often necessary to perform many tests and trials, which is connected with a large amount of time and costs, while the most important stage of design is the final verification of the developed process performed on a real material and under industrial conditions. There is still a search of methods and techniques serving as verifying tools which would facilitate the designing and optimization of plastic forming processes as well as make it possible to partially or completely eliminate the experiment stage, at least on the real material [1, 2]. There are two main lines of such searches, one of which is currently based on mathematical methods, i.e. constantly developed numerical computational techniques [35], and the other uses modeling and physical simulation methods [6, 7]. The line of broadly understood numerical methods includes e.g.: the finite element method (FEM) and the finite volume method (FVM), as well as a whole spectrum of computer science tools (IT), which make it possible to develop mathematical models of various plastic forming processes as well as phenomena occurring in the deformed material [8-10]. Despite the undoubted usefulness of mathematical methods for process analysis, optimization and design, we should also mind their restrictions. The main curtailment in the application of methods based on mathematical techniques (FEM, FVM, IT) in a designing process is the lack of certainty of the correctness of the results due to certain assumed modeling simplifications, calculation errors, insufficient application experience and others. This causes the obtained results to be more or less in agreement with the reality, and it is assumed that the maximal error equals approximately 10%. Despite the fact that mathematical methods firmly change the meaning and range of the experiment on the real material, they remain the most expensive and time-consuming stage of the design and optimization process [11]. That is why an alternative as well as a certain kind of verification of such methods can be provided by physical modeling methods, e.g. with the use of another material or by way of performing an experiment in a scale [12]. Among them, a quite popular one is physical modeling with the use of soft modeling materials (based on synthetic or natural waxes and plasticines with the so-called modifiers, owing to which it is possible to obtain similarity of the modeling materials to the real metallic ones) [6, 13]. This method is much cheaper and faster, and it constitutes, next to physical simulations, another main line in the deve-
lopment of methods supporting the analysis, design and optimization of plastic forming processes. Physical modeling with the use of soft modeling materials can be a separate tool in the design and analysis of the processes, with the consideration of the shape as well as the force, quality and quantity parameters, or it can cooperate with numerical modeling, thus providing the computer simulation with the necessary information on the behavior of the deformed material as well as the boundary conditions, and it can also serve as a verifying tool [3, 9]. Physical modeling methods shorten the designing time as well as reduce the costs of the real experiment by using non-metallic soft modeling materials, which, through the application of various modifiers (chalk, kaolin, petrolatum, lanolin, etc.), make it possible to obtain the characteristics for almost all metallic materials. In the literature, we can find a vast amount of physical modeling applications for the analysis of industrial, mainly bulk metal, processes, in which compressive stresses dominate. Soft modeling materials, because of their unique construction, have found their application in the simulation of forging, extrusion, pressing and upsetting processes [3, 9, 14-16]. For example, to analyze extrusion processes, the authors have used physical modeling [17, 18]. There are also some studies in the literature which apply a soft metallic material (usually Pb at ambient temperature for the simulation of another material), which very well simulates e.g. hot deformation of steels [7, 19]. The choosing of a suitable material is closely dependent on the simulated case and, to a lesser degree, on the measurement method. For example, in turn, when the experiment needs large plastic deformations, a more ductile soft material should be used [20], e.g. plasticine with petrolatum and lanolin additions [13]. In order to simulate cracking, hard paraffin wax is used, which highlights the micro surface cracks as well as macrocracks [14, 21, 22]. In turn, in paper [23] the authors analyzed the behavior of soft materials in the aspect of fracture and adhesion phenomena. The biggest changes in the properties and application of modeling materials can be obtained through modification of their composition by way of introducing modifying additions in various amounts, in a loose, solid or semi-solid form, such as: kaolin, lanolin, paraffin, chalk, petrolatum, sugar, salt, etc. Other changes in the properties of modeling materials can be obtained by way of changing the strain rate and temperature of the process, which makes it possible to obtain any model of yield stress-deformation curves for different real metallic materials [24].
References
1. Behrens B.-A., Doegea E. et al. Precision forging processes for high-duty automotive components // J. Mater. Process Technol. - 2007. - V. 185. - V. 1-3. -P. 139-146. - https://doi.org/10.1016/j.jmatprotec. 2006.03.132
2. Milutinovic M., Vilotic D., Movrin D. Precision forging—tool concepts and process design // J. Technol. Plast. - 2008. - V. 33. - No. 1-2. - P. 73-89. -https://doi.org/10.1007/s12289-009-0577-7
3. Gouveia B.P.P.A., Rodrigues J.M.C., Martins P.A.F., Bay T. Physical and numerical simulation of the round-to-square forward extrusion // J. Mech. Work. Tech. - 2001. - V. 112. - P. 244-251. - https:// doi.org/10.1016/S0924-0136(01)00725-7
4. Hawryluk M., Jakubik J. Analysis of forging defects for selected industrial die forging processes // Eng. Failure Analys. - 2016. - V. 59. - P. 396-409. -https://doi.org/10.1016/j.engfailanal.2015.11.008
5. Hawryluk M., Mrzyglod B., Gronostajski Z. et al. Application of artificial neural networks in the analysis of mechanisms destroying forging tools // Archiv. Metall. Mater. - 2020. - V. 65. - No. 1. - P. 193-200. -https://doi.org/10.24425/amm.2019.131114
6. Wanheim T. Physical Modeling of Metal Processing. -Danmark: Procestechnics Institut, Danmarks Teknisk Hojkole, 1988.
7. Hawryluk M., Polak S., Gronostajski Z. Jaskiewicz K. Application of physical similarity utilizing soft modeling materials and numerical simulations to analyse the plastic flow of UC1 steel and the evolution of forces in a specific multi-operational industrial precision forging process with a constant-velocity joint housing // Experimental Tech. - 2019. - V. 43. - No. 2. - P. 225235. - https://doi.org/10.1007/s40799-018-0288-4
8. Hawryluk M., Mrzyglod B.A. Durability analysis of forging tools for different operating conditions with application of a decision support system based on artificial neural networks (ANN) // Eksploatac. Nieza-wodnosc. Maintenance Reliability. - 2017. - V. 19. -No. 3. - P. 338-348. - https://doi.org/10.17531/ein. 2017.3.4
9. Hawryluk M. The influence of the condition of plastic similarity on the accuracy of physical modeling of extrusion processes. PhD thesis. - Wroclaw: Wroclaw University of Science and Technology, 2006.
10. Gangopadhyay T., Kumar D., Pratihar D.I. Expert system to predict forging load and axial stress // Appl. Soft Comput. - 2014. - V. 11. - No. 1. - P. 744753. - https://doi.org/10.1016Zj.asoc.2009.12.036
11. Mrzyglod B., Hawryluk M., Janik M. et al. Sensitivity analysis of the artificial neural networks in a system for durability prediction of forging tools to forgings made of C45 steel // Int. J. Adv. Manufact. Technol. -2020. - V. 109. - No. 5-6. - P. 1385-1395. - https:// doi.org/0.1007/s00170-020-05641-y
12. Vazquez V., Altan T. New concepts in die design— Physical and computer modeling application // J. Mater. Proc. Technol. - 2000. - V. 98. - P. 212-223. -https://doi.org/10.1016/S0924-0136(99)00202-2
13. Wojcik L., Lis K., Pater Z. Plastometric tests for plasticine as physical modeling material // Open Eng. -2016. - V. 6. - No. 1. - P. 653-659. - https://doi.org/ 10.1515/eng-2016-0093
14. Gingher G.C., Padjen G. Hot strip mill edging practices and plasticine modeling // ISS-AIME: 34th MWSP Conf. Proc. - 1993. - V. 30. - P. 3-12.
15. Shin. H.W. et al. A study on the rolling of I-section beams // Int. J. Mach. Tools Manufact. - 1994. -V. 34. - No. 2. - P. 147-160. - https://doi.org/10. 1016/0890-6955(94)90097-3
16. Mohammadi M.M., Sadeghi M.H. Simulation and physical modeling of forging sequence of Bj type outer race international // Adv. Mater. Res. - 2010. - V. 8386. - P. 150-156. - https://doi.org/10.4028/www. scientific.net/AMR.83-86.150
17. Sharma M., Singh A.K., Singh P. et al. Experimental investigation of the effect of die angle on extrusion process using plasticine // Exp. Tech. - 2010. -V. 35. - P. 38-44. - https://doi.org/10.1111/j. 1747-1567.2010.00655.x
18. Sofuoglu H., Gedikli H. Physical and numerical analysis of three dimensional extrusion process // Comput. Mater. Sci. - 2004. - V. 31. - No. 1-2. - P. 113-124. -https://doi.org/10.1016/j.commatsci.2004.02.001
19. Gronostajski Z. et al. Analysis of forging process of constant velocity joint body // Steel Res. Int. - 2008. -V. 1. - P. 547-554.
20. Pertence A.E.M., Cetlin P. Similarity of ductility between model and real materials // J. Mater. Proc. Technol. - 2000. - V. 103. - P. 434-438. - https://doi. org/10.1016/S0924-0136(00)00513-6
21. Arentoft M. Prevention of Defects in Forging by Numerical and Physical Simulation. - Tech. Univer. Denmark Inst. Manufact. Eng., 1996.
22. Arentoft M., Henningsen P., Bay N., Wanheim T. Simulations of defects in metal forming // J. Mech. Working Technol. - 1994. - V. 45. - P. 527-532. -https://doi.org/10.1016/0924-0136(94)90393-X
23. Creton C., Ciccotti M. Fracture and adhesion of soft materials: A review // Rep. Progr. Phys. - 2016. -V. 79. - No. 4. - P. 046601. - https://doi.org/10.1088/ 0034-4885/79/4/046601
24. Buchely M.F., Maranon A., Silberschmidt V.V. Material model for modeling clay at high strain rates // Int. J. Impact Eng. - 2016. - V. 90. - P. 1-11. - https:// doi.org/10.1016/j.ijimpeng.2015.11.005
25. Eckerson K., Liechty B., Sorensen C. Thermome-chanical similarity between Van Akenplasticine and metals in hot-forming processes // J. Strain Anal. Eng. Des. - 2008. - V. 43. - No. 5. - P. 383-394. - https:// doi.org/10.1243/03093247JSA364
26. Xiang Y., Zhong D., Rudykh S. et al. A review of physically based and thermodynamically based constitutive models for soft materials // J. Appl. Mech. Transact. ASME. - 2020. - V. 87. - No. 11. -P. 110801. - https://doi.org/10.1115/1.4047776
27. Gronostajski Z., HawrylukM. Analysis of metal forming processes by using physical modeling and new plastic similarity condition // AIP Conf. Proc. -2007. - V. 907. - P. 608-613. - https://doi.org/10. 1063/1.2729580
Received 03.03.2021, revised 09.04.2021, accepted 10.04.2021
This is an excerpt of the article "Application of Physical Modeling with the Use of Soft Model Materials for the Analysis and Optimization of Metal Extrusion Processes". Full text of the paper is published in Physical Me-somechanics Journal. DOI: 10.1134/S1029959922010076
Сведения об авторах
Marek Hawryluk, Prof., Wroclaw University of Science and Technology, Poland, marek.hawryluk@pwr.edu.pl Maciej Suliga, Prof., Czestochowa University of Technology, Poland, maciej.suliga@pcz.pl
Mateusz Wi^claw, Msc Eng., PhD study, Wroclaw University of Science and Technology, Poland, mateusz.wieclaw@pwr.edu.pl
