Application of Modern and Classical Optimization Techniques in Abrasion of Al-Cu-SiCp and Al-Cu-B4Cp Composites

Year 2018, Volume: 1 Issue: 1, 23 - 32, 01.08.2018

Ahmet Sahiner , Nurullah Yilmaz , Fevzi Bedir

Abstract

In
this study, we introduce the abrasion resistance of Al-Cu-SiC_p and Al-Cu-B₄C_p.
Based on Fuzzy Logic Modeling (FLM) and surface fitting techniques, we propose
the abrasion model of Al-Cu-SiC_p and Al-Cu-B₄C_p
which is decided by the rate of SiC_p and B₄C_p,
and the amount of applied pressure to the specimens. The model can lead to the
best rate of SiC_p and B₄C_p and the amount of
applied pressure to obtain the minimum abrasion.

Keywords

abrasive strength, fuzzy logic modeling, interdisciplinary modeling

References

• [1] B. D. O. Anderson and J. B. Moore, Linear optimal control, Prentice-Hall, Englewood Cliffs, N J, (1971).
• [2] L. Qi and P. Tseng, On Almost Smooth Functions and Piecewise Smooth Functions, Nonlinear Anal. 67 (2007), 773 -794.
• [3] R.T. Rockafellar, A property of piecewise smooth functions, Comput. Optim. Appl. 25 (2003), 247-250.
• [1] F. Bedir, Characteristic properties of Al-Cu-SiCp and Al-Cu-B4Cp composites produced by hot pressing method under nitrogen atmosphere, Mater. Design 28, (2007), 1238-1244.
• [2] C. Gode, Mechanical properties of hot pressed SiCp and B4Cp/Alumix 123 composites alloyed with minor Zr, Composites Part: B, 54 (2013), 34-40.
• [3] R.P. Ge, A filled function method for finding global minimizer of a function of several variables, Math. Program. 46, (1990), 191-204.
• [4] R.P. Ge, The theory of filled function method for finding global minimizer of a nonlinearly constrained minimization problem, J. Comput. Math. 5, (1987), 1-9.
• [5] P. Ma, C. Zou, H. Wang, J. Jie, Y. Jia, B. Fu, Z. Wei, Microstructure evolution and precipitation of SiC particle reinforced Al-20Si composite solidified under high pressures, Mater. Lett., 79 (2012), 232-234.
• [6] E.H. Mamdani, Application of fuzzy algorithms for control of simple dynamic plant, Proc. IEEE 121 (1974), 1585-1588.
• [7] A. Sahiner, N. Yilmaz, O. Demirozer, Mathematical modeling and application of filled function method in entomology, Int. Journal Pest Manage 60 (2014), 232-237.
• [8] A. Sahiner, N. Ucar, N., N. Yilmaz, New optimisation techniques in mechanical characterization for beta-Sn single crystals, Oxidation Comm., 38 (2015), 166-174.
• [9] M. Sakawa, Fuzzy sets and interactive multi objective optimization, Plenum Press, New York, (1993).
• [10] M. Saltan, S. Saltan, A. Sahiner, Fuzzy logic modeling of deflection behavior against dynamic loading in flexible pavements, Constr. Build. Mater. 21 (2007), 1406-1414.
• [11] M. Sugeno, T. Takagi, Multi-dimensional fuzzy reasoning, Fuzzy Sets Syst. 9 (1983).
• [12] T. Takagi, M. Sugeno, Fuzzy identification of systems and its applications to modeling and control, IEEE Trans. Syst., Man and Cybernetics 15 (1985), 116-132.
• [13] F. Toptan, A. Kilicarslan, I. Kerti, The effect of Ti addition on the properties of Al-B4C interface: a microstructural study, Materials Science Forum, (2010), 636-637.
• [14] Z.Y. Wu, F.S. Bai, H.W.J. Lee, Y.J. Yang, A filled function method for constrained global optimization, J. Glob. Opt., 39 (2007), 495-507.
• [15] Y.T. Xu, Y. Zhang, S.G. Wang, A modified tunneling function method for non-smooth global optimization and its application in artificial neural network, Appl. Math. Model., 39 (2015), 6438-6450.
• [16] Y. Yang, Y. Shang, A new filled function method for unconstrained global optimization, Appl. Math. Comput., 173 (2006), 501-512.
• [17] L.A. Zadeh, Fuzzy sets, lnform. Control. 8 (1965), 338-352.
• [18] H. J. Zimmermann, Fuzzy set theory, Wiley Interdisciplinary Reviews: Computational Statistics, 2 317–332 (2010).