A roadmap for decoding the sound of boiling
摘要
Bubble acoustics offers a powerful window into the complex physics of liquid-vapor phase-change phenomena such as boiling. Advancing this field requires a synergistic convergence of improved physical understanding, rigorous experimental standardization with optimized acoustic sensing, and integration of interpretable data-driven modeling. This perspective outlines a unified roadmap emphasizing experimental fidelity, open standardized datasets, and explainable machine learning for intelligent, real-time diagnostics in next-generation multiphase thermal systems.