Near real-time prediction of thermophysical parameters and time-dependent boundary heat flux of participating medium

The scattering coefficient ( Ks ), absorption coefficient ( Ka ), thermal conductivity ( A) and time-varying boundary heat flux (q(t)) of 1D participating medium are simultaneously determined in near real time. The forward problem of coupled conductive and radiative heat transfer is solved by finite volume method (FVM). The unscented Kalman filter (UKF) and corresponding smoothing technique (UKS) are employed to estimate the q(t), lambda, Ka and Ks . To achieve non-intrusive detection, the measured signals on bound-aries of the medium (such as radiative intensity on right boundary and temperatures on boundaries) are employed as inputs in the inverse problem. The effects of measurement error covariance, process error covariance, future measured signals, sampling interval and thermophysical properties on estimation re-sults are thoroughly investigated. The UKS algorithm, when compared to the UKF algorithm, can improve the stability and accuracy of estimated q(t), lambda, Ka and Ks . It is found that the UKS algorithm is efficient and accurate to solve the near real-time prediction of thermophysical parameters and boundary heat flux of participating medium even with measurement errors.(c) 2023 Elsevier Ltd. All rights reserved.