A physics-informed calibration method for transient surface heat flux prediction under complex radiative heating

Monitoring surface heat fluxes of materials is crucial in engineering and is a prerequisite for thermal system design. However, the thermophysical properties of most engineering materials are temperature-dependent, which undoubtedly increases the difficulty of surface heat flux estimation. In this paper, a data-driven calibration integral equation method was proposed to solve these problems. Additionally, an experimental heating system was designed based on quartz lamps, and the system was used to test this calibration-based inverse prediction method. Due to the complexity of the quartz lamp heating system, the difference between the incident surface heat flux and net surface heat flux are considered. In addition, the time delay caused by the heating system was also discussed based on mathematic analysis. Then, a new equation was derived for surface heat flux estimation without the impact of the delay time. Subsequently, stainless steel 304 and Inconel 600 were selected as test samples to validate the accuracy of surface heat flux predictions. In this process, the thermal conductivities of the materials were no need to be provided. The results show that the predictions of the calibration integral equation are accurate, with a relative root mean square error of less than 12%. By comparing the prediction accuracy with space marching method, the integral equation is weakly parameter-dependent, which decreases the system uncertainty. This outcome indicates that the involved inverse method can provide guidance for thermal system design.