This paper presents a joint state and input estimation algorithm for the one-dimensional heat-conduction problem. A computationally efficient method is proposed in this work to solve the inverse heat-conduction problem (IHCP) using orthogonal collocation method (OCM). A Kalman filter (KF) algorithm is used in conjunction with a recursive-weighted least-square (RWLS)-based method to simultaneously estimate the input boundary condition and the temperature field over the heat-conducting element. A comparison study of the algorithm is shown with explicit finite-difference method (FDM) of approximation and analytical solution of the forward problem, which clearly reveals the high accuracy with lower-dimensional modeling. The estimation results show that the performance of the estimator is robust to noise sensitivity up to a certain level, which is practically acceptable.
Joint State and Input Estimation for One-Dimensional Heat Conduction
Contributed by the Heat Transfer Division of ASME for publication in the JOURNAL OF HEAT TRANSFER. Manuscript received May 31, 2014; final manuscript received June 16, 2015; published online August 11, 2015. Assoc. Editor: P. K. Das.
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Nundy, S., Mukhopadhyay, S., and Kanti Deb, A. (August 11, 2015). "Joint State and Input Estimation for One-Dimensional Heat Conduction." ASME. J. Heat Transfer. December 2015; 137(12): 121014. https://doi.org/10.1115/1.4030962
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