• T J Prasanna Kumar
• K Sivajibabu
• B Durga Prasad

Aircraft engine noise reduction remains a critical challenge due to increasingly stringent environmental regulations and the limitations of conventional passive acoustic liners. Recent advances in nanotechnology and computational intelligence have enabled the development of nanoresonator-based acoustic liners that exhibit enhanced low-frequency attenuation and tunable vibrational characteristics. This review presents a comprehensive and critical assessment of analytical, numerical, experimental, and data-driven approaches used in the design and optimization of acoustic liners, with a particular focus on nanoresonator–nanotube systems. Comparative analysis highlights the role of nonlocal elasticity, wave propagation theory, and polynomial eigenvalue formulations in capturing nanoscale effects that are neglected in classical continuum models. Furthermore, emerging hybrid machine learning optimization techniques are examined for their ability to improve predictive accuracy and design efficiency. The review identifies key research gaps and outlines future directions toward intelligent, adaptive acoustic liners for next-generation aero-engine applications.

Acoustic liners; Nanoresonators; Carbon nanotubes; Graphene nanoparticles; Nonlocal elasticity; Machine learning optimization; Aero-engine noise

"Nanoresonator-Based Acoustic Liners for Aircraft Engine Noise Control: A Comprehensive Review of Analytical Modeling, Nanoscale Effects, and Data-Driven Optimization Strategies", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 12, page no.c581-c586, December-2025, Available :http://www.jetir.org/papers/JETIR2512265.pdf

"Nanoresonator-Based Acoustic Liners for Aircraft Engine Noise Control: A Comprehensive Review of Analytical Modeling, Nanoscale Effects, and Data-Driven Optimization Strategies", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 12, page no. ppc581-c586, December-2025, Available at : http://www.jetir.org/papers/JETIR2512265.pdf