RESEARCH PAPER
THE DYNAMIC PERFORMANCE ANALYSIS OF THE FOIL BEARING STRUCTURE
1
Institute of Fluid-Flow Machinery, Polish Academy of Sciences, ul. Fiszera 14, 80-231 Gdańsk
Online publication date: 2014-01-22
Publication date: 2013-03-01
Acta Mechanica et Automatica 2013;7(1):58-62
KEYWORDS
ABSTRACT
Foil bearings are a variety of slide bearings in which an additional set of foils is applied between journal and bush, in order to improve the selected static and dynamic properties. Engineers and researchers from all over the world investigate bearings of this type since many years - both from numerical as well as experimental point of view. Due to the complexity of construction, the reliable simulation models are all the time being searched for. This paper discusses the important stages of elaboration of the structural supporting layer numerical model of the foil bearing as well as results of verification tests. The main goal of the conducted study was assessment of reliability of the elaborated numerical model, in scope of dynamic properties. In the near future it will be used for elaboration of the numerical model of the entire foil bearing, which will take into account also phenomena in fluid-film layer. Those models will be used together to describe bearing system in operation.
REFERENCES (35)
1.
Portevin A, Le Chatelier F. (1923). Sur un phénomène observé lors de l’essai de traction d’alliages en cours de transformation. Compt Rend Acad Sci Paris. 176: 507-510.
2.
Bergstrom Y, Roberts W. (1971). The application of dislocation model to dynamic strain ageing in α-iron containing interstitial atoms. Acta Metall. 19: 815-823. doi:10.1016/0001-6160(71)90138-6.
3.
Yilmaz A. (2011). The Portevin-Le Chatelier effect: a review of experimental findings. Sci Technol Adv Mater. doi:10.1088/1468-6996/12/6/063001.
4.
Reyne B, Manach PY, Moës N. (2019). Macroscopic consequences of Piobert–Lüders and Portevin–Le Chatelier bands during tensile deformation in Al-Mg alloys. Mater Sci Eng A. 746: 187-196. doi:10.1016/j.msea.2019.01.009.
5.
Sarkar A, Maloy SA, Murty KL. (2015). Investigation of Portevin-Le Chatelier effect in HT-9 steel. Mater Sci Eng A. 631: 120-125. doi:10.1016/j.msea.2015.02.022.
6.
Cui C, Zhang R, Zhou Y, Sun X. (2020). Portevin-Le Châtelier effect in wrought Ni-based superalloys: Experiments and mechanisms. J Mater Sci Technol. 51: 16-31. doi:10.1016/j.jmst.2020.03.023.
7.
Graff S, Dierke H, Forest S, Neuhäuser H, Strudel JL. (2008). Finite element simulations of the Portevin–Le Chatelier effect in metal–matrix composites. Philos Mag. 88: 3389-3414. doi:10.1080/14786430802108472.
8.
Lipski A, Mroziński S. (2012). The effects of temperature on the strength properties of aluminium alloy 2024-T3. Acta Mech Autom. 6 (3): 62-66.
9.
Coër J, Manach PY, Laurent H, Oliveira MC, Menezes LF. (2013). Piobert– Lüders plateau and Portevin–Le Chatelier effect in an Al–Mg alloy in simple shear. Mech Res Commun. 48: 1-7. doi:10.1016/j.mechrescom.2012.11.008.
10.
Manach PY, Thuillier S, Yoon JW, Coër J, Laurent H. (2014). Kinematics of Portevin-Le Chatelier bands in simple shear. Int J Plast. 58: 66-83. doi:10.1016/j.ijplas.2014.02.005.
11.
Cottrell AH, Bilby BA. (1949). Dislocation theory of yielding and strain ageing of iron. Proc Phys Soc A. 62 (1): 49-62. doi:10.1088/0370-1298/62/1/308.
12.
Kozłowska A, Grzegorczyk B, Morawiec M, Grajcar A. (2019). Explanation of the PLC Effect in Advanced High-Strength Medium-Mn Steels. A Review. Materials. 12 (24): 1-14. doi:10.3390/ma12244175.
13.
Jiang H, Zhang Q, Chen X, Chen Z, Jiang Z, Wu X, Fan J. (2007). Three types of Portevin–Le Chatelier effects: Experiment and modelling. Acta Mater. 55 (7): 2219-2228. doi:10.1016/j.actamat.2006.10.029.
14.
Hu Q, Zhang Q, Cao P, Fu S. (2012). Thermal analyses and simulations of the type A and type B Portevin–Le Chatelier effects in an Al–Mg alloy. Acta Mater. 60 (4): 1647-1657. doi:10.1016/j.actamat.2011.12.003.
15.
Schwink CH, Nortmann A. (1997). The present experimental knowledge of dynamic strain ageing in binary f.c.c. solid solutions. Mater Sci Eng A. 234: 1-7. doi:10.1016/S0921-5093(97)00139-1.
16.
Sarkar A, Barat P, Mukherjee P. (2010). Multiscale entropy analysis of the Portevin-Le Chatelier Effect in an Al-2.5%Mg alloy. Fractals. 18: 319-325. doi:10.1142/S0218348X10004944.
17.
Xu J, Chen G, Fu S. (2021). Complexity analysis of the Portevin-Le Chatelier in an Al alloy at different temperatures. Theor Appl Mech Lett. 11 (2): 100233. doi:10.1016/j.taml.2021.100233.
18.
Brechtl J, Xie X, Wang Z, Qiao J, Liaw PK. (2020). Complexity analysis of serrated flows in a bulk metallic glass under constrained and unconstrained conditions. Mater Sci Eng A. 771: 138585. doi:10.1016/j.msea.2019.138585.
19.
Brechtl J, Chen B, Xie X, Ren Y, Venable JD, Liaw PK, Zinkle SJ. (2019). Entropy modeling on serrated flows in carburized steels. Mater Sci Eng A. 753: 135-145. doi:10.1016/j.msea.2019.02.096.
20.
Shannon CE. (1948). A mathematical theory of communication. Bell Syst Tech J. 27 (3): 379-423. doi:10.1002/j.1538-7305.1948.tb01338.x.
21.
Namdari A, Li Z. (2019). A review of entropy measures for uncertainty quantification of stochastic processes. Adv Mech Eng. 11: 1-14. doi:10.1177/1687814019857.
22.
Richman JS, Moorman JR. (2000). Physiological time-series analysis using approximate entropy and sample entropy. Am J Physiol Heart Circ Physiol. 278: H2039. doi:10.1152/ajpheart.2000.278.6.H203.
23.
Wu H, Zhou J, Xie C, Zhang J, Huang Y. (2021). Two-Dimensional Time Series Sample Entropy Algorithm: Applications to Rotor Axis Orbit Feature Identification. Mech Syst Signal Process. 147: 107123. doi:10.1016/j.ymssp.2020.107123.
24.
Pincus SM. (1991). Approximate entropy as a measure of system complexity. Proc Natl Acad Sci U S A. 88: 2297-2301. doi:10.1073/pnas.88.6.229.
25.
Mayer CC, Bachler M, Hörtenhuber M, Stocker C, Holzinger A, Wassertheurer S. (2014). Selection of entropy-measure parameters for knowledge discovery in heart rate variability data. BMC Bioinformatics. 15 (6): S2. doi:10.1186/1471-2105-15-S6-S2.
26.
Trybek P, Nowakowski M, Salowka J, Spiechowicz J, Machura L. (2018). Sample Entropy of sEMG Signals at Different Stages of Rectal Cancer Treatment. Entropy. 20: 863. doi:10.3390/e20110863.
27.
Azami H, da Silva LEV, Omoto ACM, Humeau-Heurtier A. (2019). Two-dimensional dispersion entropy: An information-theoretic method for irregularity analysis of images. Signal Process Image Commun. 75: 178-187. doi:10.1016/j.image.2019.04.013.
28.
Olbryś J, Majewska E. (2022). Regularity in Stock Market Indices within Turbulence Periods: The Sample Entropy Approach. Entropy. 24: 921. doi:10.3390/e24070921.
29.
Costa M, Goldberger AL, Peng CK. (2002). Multiscale Entropy Analysis of Complex Physiologic Time Series. Phys Rev Lett. 89: 068102. doi:10.1103/PhysRevLett.89.068102.
30.
McCormick PG. (1988). Theory of flow localization due to dynamic strain aging. Acta Metall. 36 (12): 3061-3067. doi:10.1016/0001-6160(88)90043-0.
31.
Zhang S, McCormick PG, Estrin Y. (2001). The morphology of Portevin-Le Chatelier bands: Finite element simulation for Al-Mg-Si. Acta Mater. 49 (6): 1087-1094. doi:10.1016/S1359-6454(00)00380-3.
32.
Böhlke T, Bondár G, Estrin Y, Lebyodkin MA. (2009). Geometrically non-linear modeling of the Portevin-Le Chatelier effect. Comput Mater Sci. 44 (4): 1076-1088. doi:10.1016/j.commatsci.2008.07.036.
33.
Wang WM. (1997). Stationary and propagative instabilities in metals: a computational point of view [dissertation]. Delft: Delft University of Technology.
34.
Hähner P, Rizzi E. (2003). On the kinematics of Portevin–Le Chatelier bands: theoretical and numerical modelling. Acta Mater. 51 (12): 3385-3397. doi:10.1016/S1359-6454(03)00122-8.
35.
Mucha M, Rose L, Wcisło B, Menzel A, Pamin J. (2023). Experiments and numerical simulations of Lueders bands and Portevin-Le Chatelier effect in aluminium alloy AW5083. Arch Mech. 75 (3): 301-336. doi:10.24423/aom.4204.
| eISSN: | 2300-5319 |
| ISSN: | 1898-4088 |
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