Simultaneous Reconstruction of Multiple Time-Varying Thermal Properties Based on Translucent Materials

Area of Science:

• Materials Science
• Heat Transfer
• Computational Physics

Background:

• Accurate measurement of transient heat flow and thermal conductivity in harsh environments is challenging.
• Conventional direct methods are insufficient for translucent media and complex heat exchange scenarios.
• Existing photothermal reconstruction methods often focus on single or time-invariant properties.

Purpose of the Study:

• To develop a computational model for simultaneous reconstruction of time-varying thermal flow fields and internal thermal conductivity.
• To address the limitations of current methods in reconstructing dynamic thermal properties.
• To validate the model's effectiveness in reconstructing multiple thermal parameters.

Main Methods:

• Utilized numerical simulation of internal heat transfer in participating media.
• Employed stochastic particle swarm optimization algorithms.
• Integrated Kalman filter technology for parameter estimation.

Main Results:

• The model successfully enabled simultaneous reconstruction of various thermal parameters.
• Inversion results showed slight oscillations around true values under measurement noise, indicating reduced accuracy.
• The model demonstrated robustness and accuracy under ideal conditions.

Conclusions:

• The developed computational model is effective for simultaneous reconstruction of dynamic thermal parameters in participating media.
• The approach offers a valuable tool for applications in high-tech materials and energy.
• Further refinement may be needed to mitigate accuracy reduction caused by measurement noise.