The field of acoustic research is moving towards the development of more accurate and efficient methods for sound speed profile inversion, source depth estimation, and sound radiation simulation. Researchers are exploring new approaches to address the challenges posed by complex object boundaries and horizontally varying sound speed profiles. The use of hybrid numerical solutions, finite element models, and machine learning techniques is becoming increasingly popular. These advancements have significant implications for various applications, including underwater acoustics, medical imaging, and digital media production. Noteworthy papers include:

• A method for inverting dual-channel sound speed profiles using refracted normal modes, which has advantages such as fewer inversion parameters and faster inversion speed.
• A sound source depth estimation method based on the upper limit of modal frequency, which has been verified using experimental data.
• A hybrid numerical solution for sound radiation simulation, which can handle complex and dynamic object boundaries without relying on ghost cells.