- Volume 19 Issue 4
DOI QR Code
Identification of Cross-WLF Viscosity Model Parameters Using Optimization Technique
최적화기법을 이용한 Cross-WLF점도 모델 계수 추정
- Kim, Sun-Yong (School of Mechanical Engineering, Ulsan College) ;
- Park, Si-Hwan (School of Mechanical Engineering, Ulsan College)
- Received : 2018.01.03
- Accepted : 2018.04.06
- Published : 2018.04.30
Predicting the behavior of rheological polymers is highly shear rate- and temperature-dependent. The Cross-WLF viscosity model has become a powerful solution that describes the shear rate- and temperature-dependent characteristics. To estimate the behavior of polymers in computational simulations, the coefficients of the Cross-WLF model should be well identified. An identification technique was proposed to determine the Cross-WLF viscosity model coefficient. The assumption is that the Cross-WLF viscosity model well describes the real characteristics of polymers when the calculated viscosity with the parameters is identical to the reference data. In this study, Auto-desk Moldflow data were used as a reference. The numerical examples showed that the proposed method accurately identifies the Cross-WLF viscosity model coefficients.
Cross-WLF viscosity model coefficients;Identification;Optimization procedure;Sensitivity analysis;Injection molding
Supported by : Ministry of Trade, industry & Energy (MI)
- C.A.Hieber and H.H. Chiang, "Shear-rate-dependence modeling of polymer melt viscosity," Polymer Engineering and Science, vol. 32, no. 14, pp. 931-938, 1992. DOI: https://doi.org/10.1002/pen.760321404 https://doi.org/10.1002/pen.760321404
- W.A. Rahman, LT. Sin and A.R. Rahmat, "Injection moulding simulation analysis of natural fiber composite window frame," Journal of Materials Processing Technology, vol. 197, no. 1-3, pp. 22-30, 2008. DOI: https://doi.org/10.1016/j.jmatprotec.2007.06.014 https://doi.org/10.1016/j.jmatprotec.2007.06.014
- X. Shi, M. Huang, Z. Zaho and C. Shen, "Nonlinear Fitting Technology of 7-Parameters Cross-WLF Viscosity Model," Advanced Materials Research, Vols. 189-193, pp. 2103-2106, 2011. DOI: https://doi.org/10.4028/www.scientific.net/AMR.189-193.2103 https://doi.org/10.4028/www.scientific.net/AMR.189-193.2103
- R. Deng, P. Davis and A.K. Bajaj, "Flexible polyurethane foam modeling and identification of viscoelastic parameters for automotive seating applications," Journal of Vibration and Acoustics, vol. 262, no. 3, pp. 391-417, 2003. DOI: https://doi.org/10.1016/S0022-460X(03)00104-4
- D.H. Lee and W.S. Hwang, "Identification of dynamic joint characteristics using multi-domain FRF-based substructing method," Transactions of Korean Society for Noise and Vibration Engineering, vol. 14, no. 6, pp. 536-545, 2004. DOI: https://doi.org/10.5050/KSNVN.2004.14.6.536 https://doi.org/10.5050/KSNVN.2004.14.6.536
- S.Y. Kim and D.H. Lee, "Identification of fractional-derivative-model parameters of viscoelastic materials using an optimization technique," Transactions of Korean Society for Noise and Vibration Engineering, vol. 16, no. 12, pp. 1192-1200, 2006. DOI: https://doi.org/10.5050/KSNVN.2006.16.12.1192 https://doi.org/10.5050/KSNVN.2006.16.12.1192
- S.Y. Kim and D.H. Lee, "Identification of fractional-derivative-model parameters of viscoelastic materials from measured FRFs," Journal of Sound and Vibration, vol. 324, no. 3-5, pp. 570-586, 2009. DOI: https://doi.org/10.1016/j.jsv.2009.02.040 https://doi.org/10.1016/j.jsv.2009.02.040
- Moldflow, Autodesk Moldflow Insight 2016, 2016 Autodesk Inc., 2016.
- Matlab, Matlab R2017a, MathWorks Inc., 2017.
- Moldflow Plastics Labs, Moldflow Material Testing Report, 2007.