Published January 10, 2022
| Version v1
Journal article
Open
Increasing the mechanical properties of structural cast iron for machine-building parts by combined Mn – Al alloying
Creators
- 1. Poltava State Agrarian University
- 2. PC Technology Center; National Technical University "Kharkiv Polytechnic Institute"
- 3. National Technical University "Kharkiv Polytechnic Institute"
- 4. Odessа Polytechnic National University
- 5. National University of Civil Defence of Ukraine
- 6. Sumy National Agrarian University
Description
The object of research in this work was cast iron for machine-building parts, alloyed with Al. The possibility of improving the mechanical properties of cast iron by choosing the optimal Mn – Al combinations, depending on the carbon content in the cast iron, was determined. The study was carried out on the basis of available retrospective data of serial industrial melts by constructing the regression equation for the ultimate strength of cast iron in the three-factor space of the input variables C – Mn – Al. The optimization problem was solved by the ridge analysis method after reducing the dimension of the factor space by fixing the carbon content at three levels: C = 3 %, C = 3.3 %, and C = 3.6 %.
It was found that the maximum values of the ultimate strength are achieved at the minimum level of carbon content (C = 3%) and are in the range of values close to 300 MPa. In this case, the Al content is in the range (2.4–2.6) %, and the Mn content is about 0.82 %. With an increase in the carbon content, there is a tendency to a decrease in the content of Mn and Al in the alloy, which is necessary to ensure the ultimate strength close to 300 MPa. The results of the ridge analysis of the response surface also showed that at the upper limit of the carbon content (C = 3.6%), it is not possible to reach the ultimate strength of 300 MPa in the existing range of Mn and Al variation.
All solutions are verified for the following ranges of input variables C = (2.94–3.66) %, Mn = (0.5–1.1) %, Al = (1.7–2.9) %.
Graphical-analytical descriptions of the optimal Mn – Al ratios are obtained, depending on the actual content of carbon in the alloy, which make it possible to purposefully select the optimal melting modes by controlling the tensile strength of the alloy
Files
Increasing the mechanical properties of structural cast iron for machine-building parts by combined Mn – Al alloying_zenodo.pdf
Files
(1.0 MB)
Name | Size | Download all |
---|---|---|
md5:9e2ff19908e40ece9de93d9233160af4
|
1.0 MB | Preview Download |
Additional details
References
- Dymko, I., Muradian, A., Leheza, Y., Manzhula, A., Rudkovskyi, O. (2017). Integrated approach to the development of the effectiveness function of quality control of metal products. Eastern-European Journal of Enterprise Technologies, 6 (3 (90)), 26–34. doi: https://doi.org/10.15587/1729-4061.2017.119500
- Akimov, O. V., Koval', O. S., Pulyaev, A. A., Dymko, E. P., Egorenko, T. A., Vysotskiy, S. V. (2015). Quality improvement of cast parts of ice: accounting technological aspects of the automated foundry. Eastern-European Journal of Enterprise Technologies, 6 (1 (78)), 56–62. doi: https://doi.org/10.15587/1729-4061.2015.56039
- Dymko, I. (2018). Choice of the optimal control strategy for the duplex-process of induction melting of constructional iron. EUREKA: Physics and Engineering, 4, 3–13. doi: https://doi.org/10.21303/2461-4262.2018.00669
- Demin, D. (2020). Constructing the parametric failure function of the temperature control system of induction crucible furnaces. EUREKA: Physics and Engineering, 6, 19–32. doi: https://doi.org/10.21303/2461-4262.2020.001489
- Domin, D. (2013). Artificial orthogonalization in searching of optimal control of technological processes under uncertainty conditions. Eastern-European Journal of Enterprise Technologies, 5 (9 (65)), 45–53. doi: https://doi.org/10.15587/1729-4061.2013.18452
- Dotsenko, Y., Dotsenko, N., Tkachyna, Y., Fedorenko, V., Tsybulskyi, Y. (2018). Operation optimization of holding furnaces in special casting shops. Technology Audit and Production Reserves, 6 (1 (44)), 18–22. doi: https://doi.org/10.15587/2312-8372.2018.150585
- Cheng, Y., Huang, F., Li, W., Liu, R., Li, G., Wei, J. (2016). Test research on the effects of mechanochemically activated iron tailings on the compressive strength of concrete. Construction and Building Materials, 118, 164–170. doi: https://doi.org/10.1016/j.conbuildmat.2016.05.020
- Borsato, T., Berto, F., Ferro, P., Carollo, C. (2016). Effect of in-mould inoculant composition on microstructure and fatigue behaviour of heavy section ductile iron castings. Procedia Structural Integrity, 2, 3150–3157. doi: https://doi.org/10.1016/j.prostr.2016.06.393
- Demin, D. A., Pelikh, V. F., Ponomarenko, O. I. (1998). Complex alloying of grey cast iron. Litejnoe Proizvodstvo, 10, 18–19.
- Demin, D. A. (1998). Change in cast iron's chemical composition in inoculation with a Si-V-Mn master alloy. Litejnoe Proizvodstvo, 6, 35.
- Bai, Y., Luan, Y., Song, N., Kang, X., Li, D., Li, Y. (2012). Chemical Compositions, Microstructure and Mechanical Properties of Roll Core used Ductile Iron in Centrifugal Casting Composite Rolls. Journal of Materials Science & Technology, 28 (9), 853–858. doi: https://doi.org/10.1016/s1005-0302(12)60142-x
- Endo, M., Yanase, K. (2014). Effects of small defects, matrix structures and loading conditions on the fatigue strength of ductile cast irons. Theoretical and Applied Fracture Mechanics, 69, 34–43. doi: https://doi.org/10.1016/j.tafmec.2013.12.005
- Fourlakidis, V., Diószegi, A. (2014). A generic model to predict the ultimate tensile strength in pearlitic lamellar graphite iron. Materials Science and Engineering: A, 618, 161–167. doi: https://doi.org/10.1016/j.msea.2014.08.061
- Chibichik, O., Sil'chenko, K., Zemliachenko, D., Korchaka, I., Makarenko, D. (2017). Investigation of the response surface describing the mathematical model of the effects of the Al/Mg rate and temperature on the Al-Mg alloy castability. ScienceRise, 5 (2), 42–45. doi: https://doi.org/10.15587/2313-8416.2017.101923
- Makarenko, D. (2017). Investigation of the response surfaces describing the mathematical model of the influence of temperature and BeO content in the composite materials on the yield and ultimate strength. Technology Audit and Production Reserves, 3 (3 (35)), 13–17. doi: https://doi.org/10.15587/2312-8372.2017.104895
- Demin, D. A., Pelikh, V. F., Ponomarenko, O. I. (1995). Optimization of the method of adjustment of chemical composition of flake graphite iron. Litejnoe Proizvodstvo, 7-8, 42–43.
- Domina, O. (2020). Selection of alternative solutions in the optimization problem of network diagrams of project implementation. Technology Audit and Production Reserves, 4 (4 (54)), 9–22. doi: https://doi.org/10.15587/2706-5448.2020.210848
- Akimov, O., Penzev, P., Marynenko, D., Saltykov, L. (2018). Identification of the behavior of properties of a cold-hardening glass-liquid mixture with propylene-carbonate different in dosing components. Technology Audit and Production Reserves, 2 (3 (46)), 4–9. doi: https://doi.org/10.15587/2312-8372.2019.169748
- Demin, D. (2017). Synthesis of nomogram for the calculation of suboptimal chemical composition of the structural cast iron on the basis of the parametric description of the ultimate strength response surface. ScienceRise, 8 (37), 36–45. doi: https://doi.org/10.15587/2313-8416.2017.109175
- Demin, D. (2017). Strength analysis of lamellar graphite cast iron in the «carbon (C) – carbon equivalent (Ceq)» factor space in the range of C = (3,425-3,563) % and Ceq = (4,214-4,372) %. Technology Audit and Production Reserves, 1 (1 (33)), 24–32. doi: https://doi.org/10.15587/2312-8372.2017.93178
- Zinchenko, P. S., Aksenenko, M. P., Yovbak, A. V., Orendarchuk, Yu. V. (2016). Application of liquid glass mixtures with reduced content of liquide glass as a factor in improving the quality of machine-building castings. ScienceRise, 5 (2 (22)), 6–9. doi: https://doi.org/10.15587/2313-8416.2016.69836
- Domina, O., Lunin, D., Barabash, O., Balynska, O., Paida, Y., Mikhailova, L., Niskhodovska, O. (2018). Algorithm for selecting the winning strategies in the processes of managing the state of the system "supplier – consumer" in the presence of aggressive competitor. Eastern-European Journal of Enterprise Technologies, 6 (3 (96)), 48–61. doi: https://doi.org/10.15587/1729-4061.2018.152793
- Domina, O. (2020). Features of finding optimal solutions in network planning. EUREKA: Physics and Engineering, 6, 82–96. doi: https://doi.org/10.21303/2461-4262.2020.001471
- Demin, D. (2018). Investigation of structural cast iron hardness for castings of automobile industry on the basis of construction and analysis of regression equation in the factor space «carbon (C) - carbon equivalent (Ceq)». Technology Audit and Production Reserves, 3 (1 (41)), 29–36. doi: https://doi.org/10.15587/2312-8372.2018.109097
- Mohanad, M. K., Kostyk, V., Domin, D., Kostyk, K. (2016). Modeling of the case depth and surface hardness of steel during ion nitriding. Eastern-European Journal of Enterprise Technologies, 2 (5 (80)), 45–49. doi: https://doi.org/10.15587/1729-4061.2016.65454
- Demin, D. (2017). Synthesis of optimal control of technological processes based on a multialternative parametric description of the final state. Eastern-European Journal of Enterprise Technologies, 3 (4 (87)), 51–63. doi: https://doi.org/10.15587/1729-4061.2017.105294
- Frolova, L., Shevchenko, R., Shpyh, A., Khoroshailo, V Antonenko, Y. (2021). Selection of optimal Al–Si combinations in cast iron for castings for engineering purposes. EUREKA: Physics and Engineering, 2, 99–107. doi: https://doi.org/10.21303/2461-4262.2021.001694
- Zatolokin, E. A., Skiba, V. P., Mis'kevich, V. I., Saltykova, I. A., Mityagin, L. Ya. (1976). Issledovanie svoystv i razrabotka tekhnologii proizvodstva otlivok iz vysokokachestvennogo alyuminievogo chuguna. Otchet o NIR, tema No. 19142, 104.
- Demin, D. (2019). Development of «whole» evaluation algorithm of the control quality of «cupola – mixer» melting duplex process. Technology Audit and Production Reserves, 3 (1 (47)), 4–24. doi: https://doi.org/10.15587/2312-8372.2019.174449