Estimation of the thermal conductivity of a material is a typical inverse heat conduction problem (IHCP). The temperature-dependant thermal conductivity estimation method of genetic algorithms (GA) is presented. A physical practical constraint that the value of thermal conductivity of a typical thermal protection material should not decrease with the temperature increasing
and a engineering practical constraint that the predicted temperature should be greater than the measurement values when the temperature is high
are taken into account in the algorithms. Then
the constrained estimation algorithm of thermal conductivity is developed by two methods
i.e.
the increments estimation method and the penalty function method. After applying these constrained estimation methods to a typical case
it is found that
these estimation methods are feasible and they can overcome the shortcoming of the original unconstrained estimation method that some unphysical oscillations may appear in the estimation result when the measurement noise is significant. The estimated results are of more engineering meanings in practical applications.
关键词
Keywords
references
BECK J V, BLACKWELL B, Jr CLAIR C R S. Inverse heat conduction-ill-posed problems[M]. John WileySons. New York, 1985.
OZISIK M N, ORLANDE H R B. Inverse heat transfer-fundamentals and applications[M]. TaylorFrancis, New York, 2000.
YANG C, ULRICH G. Estimation of thermal properties based on inverse heat conduction method[J]. Journal of Chemical Industry and Engineering, 2005, 56(12):2415-2420. (in Chinese)
WANG D G, LIU Y X, LI S J, et al. Inverse heat conduction problem for identifying thermal conductivity and thermal diffusivity simultaneously[J]. J University of Shanghai for Science and Technology, 2001, 23 (3):233-237. (in Chinese)
XUE Q W, YANG H T, DU X Y. An inverse heat conduction problem with multi-variables in a transient state with a homotopic regularization method[J]. Chinese Journal of Computational Physics, 2006, 23(2):151-157. (in Chinese)
XUE Q W, WEI W, YANG H T. Parameters identification of inverse heat conduction problems in transient state with multi-variables[J]. Chinese Journal of Solid Mechanics, 2009, 30(1):65-69. (in Chinese)
JIANG G Q, MA S Y. The prediction of thermal protection performance for coating material[J]. Acta Aerodynamica Sinica, 2004, 22(1):24-28. (in Chinese)
QIAN W Q, CAI J S. Parameter estimation of heat conduction coefficient and heat flux by sensitivity method[J]. Acta Aerodynamica Sinica, 1998, 16(2):226-231. (in Chinese)
ZHAO X L. The research of effective conductivity in porous media[D]. Liaoning: Dalian University of Technology (in Chinese)
ZHOU H L, XU X S, LI X L, et al. Identification of temperature-dependent thermal conductivity for 2-D transient heat conduction problems[J]. Applied Mathematics and Mechanics, 2014, 35(12):1341-1351. (in Chinese)
TANG Z H, QIAN G H, QIAN W Q. Estimation of temperature-dependent function thermal conductivity for a material[J]. Chinese Journal of Computational Mechanics, 2011, 28(3):377-382. (in Chinese)
ZHOU Y, QIAN W Q, HE K F, et al. Estimating temperature-dependent thermal conductivity and specific heat simultaneously[J]. Chinese Journal of Computational Physics, 2011, 28(5):719-724. (in Chinese)
ISHIHARA, A. Burning surface temperature measured with a thermocouple[C]//39th AIAA/ASME/SAE/ASEE Joint Propulsion Conference and Exhibit, AIAA 2003-5086, 2003.
ZHOU M, SUN S D. Principle and application of genetic algorithms[M]. Beijing:National Defense Industry Press, 1999. (in chinese)
KRAMER O, SCHLACHTER U, SPRECKELS V. An adaptive penalty function with meta-modeling for constrained problems[C]//Proceedings of 2013 IEEE Congress on Evolutionary Computation, June20-23, Cancun, Mexico. pp. 1350-1354, 2013.