Skip to main content
Springer Nature Link
Log in

Multi-objective Optimized Design for Intermediate-Frequency Noise Reduction in Aircraft Cabins

  • Published:
Wireless Personal Communications Aims and scope Submit manuscript

Abstract

A multi-objective optimized noise reduction design strategy for aircraft cabins was formulated and a mathematical model of multi-objective structural optimization was established based on the dynamic response and acoustic radiation equations of the structure. Later, the finite element and statistical energy analysis of the simplified hybrid simulation model of the aircraft cabin section was conducted to identify noise sources in aircraft cabin under different excitation conditions. A multistage optimization task was set up using the collaborative optimization algorithm, and an overall optimization process was designed for multi-objective optimization calculation and analysis. Results were compared with non-optimized results to verify the validity of the proposed optimization algorithm. Calculated results demonstrated that the proposed multi-objective optimized design can reduce sound pressure in aircraft cabin effectively, with an average reduction of 3–4 dB in the intermediate-frequency band.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

References

  1. Aloufi, B., Behdinan, K., & Zu, J. (2016). Theoretical vibro-acoustic modeling of acoustic noise transmission through aircraft windows. Journal of Sound and Vibration, 371, 344–369.

    Article  Google Scholar 

  2. Zverev, A. Y. (2016). Noise control mechanisms of inside aircraft. Acoustical Physics, 62(4), 478–482.

    Article  Google Scholar 

  3. Efimtsov, B. M., & Lazarev, A. (2012). A complex of analytical models for predicting noise in an aircraft cabin. Acoustical Physics, 58(4), 404–410.

    Article  Google Scholar 

  4. Baklanov, V. S. (2016). Role of structural noise in aircraft pressure cockpit from vibration action of new-generation engines. Acoustical Physics, 62(4), 456–461.

    Article  Google Scholar 

  5. MacMartin, Douglas G. (1996). Collocated structural control for reduction of aircraft cabin noise. Journal of Sound and Vibration, 190(1), 105–119.

    Article  Google Scholar 

  6. Yan, Y. J., Li, P. B., & Lin, H. G. (2016). Analysis and experimental validation of the middle-frequency vibro-acoustic coupling property for aircraft structural model based on the wave coupling hybrid FE-SEA method. Journal of Sound and Vibration, 371, 227–236.

    Article  Google Scholar 

  7. Hall, A., Mayer, T., Wuggetzer, I., & Childs, P. R. N. (2013). Future aircraft cabins and design thinking: optimisation vs. win-win scenarios. Propulsion and Power Research, 2(2), 85–95.

    Article  Google Scholar 

  8. Gardi, A., Sabatini, R., & Ramasamy, S. (2016). Multi-objective optimization of aircraft flight trajectories in the ATM and avionics context. Progress in Aerospace Sciences, 83, 1–36.

    Article  Google Scholar 

  9. Bravo, T., Maury, C., & Pinhède, C. (2014). Optimising the absorption and transmission properties of aircraft microperforated panels. Applied Acoustics, 79, 47–57.

    Article  Google Scholar 

  10. Paz, J., Díaz, J., Romera, L., et al. (2015). Size and shape optimization of aluminum tubes with GFRP honeycomb reinforcements for crashworthy aircraft structures. Composite Structures, 133, 499–507.

    Article  Google Scholar 

  11. Stanef, D. A., Hansen, C. H., & Morgans, R. C. (2004). Active control analysis of mining vehicle cabin noise using finite element modelling. Journal of Sound and Vibration, 277(1–2), 277–297.

    Article  Google Scholar 

  12. Haase, T., Unruh, O., Algermissen, S., et al. (2016). Active control of counter-rotating open rotor interior noise in a Dornier 728 experimental aircraft. Journal of Sound and Vibration, 376, 18–32.

    Article  Google Scholar 

  13. Mallardo, V., Aliabadi, M. H., Brancati, A., et al. (2012). An accelerated BEM for simulation of noise control in the aircraft cabin. Aerospace Science and Technology, 23(1), 418–428.

    Article  MATH  Google Scholar 

  14. Isakari, H., Kondo, T., Takahashi, T., et al. (2017). A level-set-based topology optimisation for acoustic–elastic coupled problems with a fast BEM-FEM solver. Computer Methods in Applied Mechanics and Engineering, 315, 501–521.

    Article  MathSciNet  Google Scholar 

  15. D’Amico, R., Neher, J., Wender, B., et al. (2012). On the improvement of the solution accuracy for exterior acoustic problems with BEM and FMBEM. Engineering Analysis with Boundary Elements, 36(7), 1104–1115.

    Article  MathSciNet  MATH  Google Scholar 

  16. Shorter, P. J., & Langley, R. S. (2005). On the reciprocity relationship between direct field radiation and diffuse reverberant loading. Journal of the Acoustical Society of America, 117(1), 85–95.

    Article  Google Scholar 

  17. Reynders, E., Langley, R. S., & Dijckmans, A. (2014). A hybrid finite element-statistical energy analysis approach to robust sound transmission modeling. Journal of Sound and Vibration, 333(19), 4621–4636.

    Article  Google Scholar 

  18. Cicirello, A., & Langley, R. S. (2014). Efficient parametric uncertainty analysis within the hybrid finite element/statistical energy analysis method. Journal of Sound and Vibration, 333(6), 1698–1717.

    Article  Google Scholar 

  19. Muller, G., & Buchschmid, M. (2014). Hybrid approaches for vibroacoustical problems based on the finite element method and statistical energy analysis. Wave Motion, 51(4), 622–634.

    Article  MathSciNet  Google Scholar 

  20. Wang, Y. L., Qin, X. P., Huang, S., et al. (2017). Structural-borne acoustics analysis and multi-objective optimization by using panel acoustic participation and response surface methodology. Applied Acoustics, 116, 139–151.

    Article  Google Scholar 

  21. Beigmoradi, S., Hajabdollahi, H., & Ramezani, A. (2014). Multi-objective aero acoustic optimization of rear end in a simplified car model by using hybrid robust parameter design, artificial neural networks and genetic algorithm methods. Computers & Fluids, 90, 123–132.

    Article  Google Scholar 

  22. Li, W., Jia, Y. J., Wen, Y., et al. (2016). An improved collaborative optimization for multidisciplinary problems with coupled design variables. Advances in Engineering Software, 102, 134–141.

    Article  Google Scholar 

  23. Yang, L. X., Qi, J. G., Li, S. K., et al. (2016). Collaborative optimization for train scheduling and train stop planning on high-speed railways. Omega, 64, 57–76.

    Article  Google Scholar 

Download references

Acknowledgements

This work was financially supported by the National Natural Science Foundation of China (Grant No. 11404205) and the Fundamental Research Funds for the Central Universities of Ministry of Education of China (Grant No. GK201703015).

Author information

Authors and Affiliations

  1. School of Physics and Information Technology, Shaanxi Normal University, Xi’an, China

    Jie Gao & Ning Qiang

Authors
  1. Jie Gao
    View author publications

    You can also search for this author inPubMed Google Scholar

  2. Ning Qiang
    View author publications

    You can also search for this author inPubMed Google Scholar

Corresponding author

Correspondence to Ning Qiang.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Gao, J., Qiang, N. Multi-objective Optimized Design for Intermediate-Frequency Noise Reduction in Aircraft Cabins. Wireless Pers Commun 102, 3737–3747 (2018). https://doi.org/10.1007/s11277-018-5405-2

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11277-018-5405-2

Keywords