Abstract

A hybrid optimization method, which combines unscented Kalman smoothing (UKS) technique and sequential quadratic programming (SQP) algorithm, is proposed to estimate the time-dependent boundary heat flux and temperature-dependent optical and thermophysical parameters (such as absorption coefficient, refractive index and thermal conductivity) of grey translucent medium simultaneously. The transient coupled radiative and conductive problem in grey translucent medium is solved by finite volume method (FVM) in forward model. In inverse problem, the measured signals consist of the temperature and radiative intensity on the boundaries of the medium. The effects of model parameters (such as the number of future time step and process noise covariance) and different incident heat fluxes on the reconstructed results are studied by the UKS-SQP technique. The results indicate that the proposed hybrid optimization technique is accurate and effective for determining the time-varying boundary heat flux, temperature-dependent optical and thermophysical parameters of grey translucent medium even with the measurement error.

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