Analyzing vibration transmission through cantilever systems using biomechanical and impact-responsive metamaterial structures
Abstract
Vibration control in cantilever systems is a critical challenge in various engineering applications, where unwanted vibrations can lead to structural fatigue, reduced performance, and potential failure. This study investigates the effects of integrating biomechanical and impact-responsive metamaterials into cantilever systems to mitigate vibration transmission. The metamaterials, characterized by their adaptive stiffness and energy-absorbing properties, are strategically embedded in key structural components such as the arms, joints, and base. Through experimental analysis, this work assesses the reduction in vibration amplitude, shifts in natural frequency, enhanced damping capacity, energy absorption during impact, and strain reduction at critical points. The results show that the metamaterial-enhanced system achieves significant reductions in vibration amplitude, up to 40%, and increases in natural frequency by over 30%, minimizing the risk of resonance. Additionally, the damping ratio is improved by as much as 53%, while the energy absorption during impact is increased by up to 26%. Strain reduction at critical points reaches 24%, contributing to improved mechanical resilience. These findings demonstrate the potential of biomechanical and impact-responsive metamaterials in enhancing the dynamic performance of cantilever systems, offering a new approach to vibration mitigation in engineering applications.
References
1. Mishra, M., Lourenço, P. B., & Ramana, G. V. (2022). Structural health monitoring of civil engineering structures using the internet of things: A review. Journal of Building Engineering, 48, 103954.
2. Wang, T. (2023). Pendulum-based vibration energy harvesting: Mechanisms, transducer integration, and applications. Energy Conversion and Management, 276, 116469.
3. Jiang, J., Liu, S., Feng, L., & Zhao, D. (2021). A review of piezoelectric vibration energy harvesting with magnetic coupling based on different structural characteristics. Micromachines, 12(4), 436.
4. Balaji, P. S., & Karthik SelvaKumar, K. (2021). Applications of nonlinearity in passive vibration control: a review. Journal of Vibration Engineering & Technologies, 9, 183-213.
5. Ngo, H., Orton, S., Rajakaruna, M., & Revision, B. Management of Long-lever Cantilever Sign Structures.
6. Wani, Z. R., Tantray, M., Farsangi, E. N., Nikitas, N., Noori, M., Samali, B., & Yang, T. Y. (2022). A critical review on control strategies for structural vibration control. Annual Reviews in Control, 54, 103-124.
7. Valipour, A., Kargozarfard, M. H., Rakhshi, M., Yaghootian, A., & Sedighi, H. M. (2022). Metamaterials and their applications: an overview. Proceedings of the Institution of Mechanical Engineers, Part L: Journal of Materials: Design and Applications, 236(11), 2171-2210.
8. Qi, J., Chen, Z., Jiang, P., Hu, W., Wang, Y., Zhao, Z., ... & Fang, D. (2022). Recent progress in active mechanical metamaterials and construction principles. Advanced Science, 9(1), 2102662.
9. Al Rifaie, M., Abdulhadi, H., & Mian, A. (2022). Advances in mechanical metamaterials for vibration isolation: A review. Advances in Mechanical Engineering, 14(3), 16878132221082872.
10. Wu, L., Wang, Y., Chuang, K., Wu, F., Wang, Q., Lin, W., & Jiang, H. (2021). A brief review of dynamic mechanical metamaterials for mechanical energy manipulation. Materials Today, 44, 168-193.
11. Indumathi N et al., Impact of Fireworks Industry Safety Measures and Prevention Management System on Human Error Mitigation Using a Machine Learning Approach, Sensors, 2023, 23 (9), 4365; DOI:10.3390/s23094365.
12. Parkavi K et al., Effective Scheduling of Multi-Load Automated Guided Vehicle in Spinning Mill: A Case Study, IEEE Access, 2023, DOI:10.1109/ACCESS.2023.3236843.
13. Ran Q et al., English language teaching based on big data analytics in augmentative and alternative communication system, Springer-International Journal of Speech Technology, 2022, DOI:10.1007/s10772-022-09960-1.
14. Ngangbam PS et al., Investigation on characteristics of Monte Carlo model of single electron transistor using Orthodox Theory, Elsevier, Sustainable Energy Technologies and Assessments, Vol. 48, 2021, 101601, DOI:10.1016/j.seta.2021.101601.
15. Huidan Huang et al., Emotional intelligence for board capital on technological innovation performance of high-tech enterprises, Elsevier, Aggression and Violent Behavior, 2021, 101633, DOI:10.1016/j.avb.2021.101633.
16. Sudhakar S, et al., Cost-effective and efficient 3D human model creation and re-identification application for human digital twins, Multimedia Tools and Applications, 2021. DOI:10.1007/s11042-021-10842-y.
17. Prabhakaran N et al., Novel Collision Detection and Avoidance System for Mid-vehicle Using Offset-Based Curvilinear Motion. Wireless Personal Communication, 2021. DOI:10.1007/s11277-021-08333-2.
18. Balajee A et al., Modeling and multi-class classification of vibroarthographic signals via time domain curvilinear divergence random forest, J Ambient Intell Human Comput, 2021, DOI:10.1007/s12652-020-02869-0.
19. Omnia SN et al., An educational tool for enhanced mobile e-Learning for technical higher education using mobile devices for augmented reality, Microprocessors and Microsystems, 83, 2021, 104030, DOI:10.1016/j.micpro.2021.104030 .
20. Firas TA et al., Strategizing Low-Carbon Urban Planning through Environmental Impact Assessment by Artificial Intelligence-Driven Carbon Foot Print Forecasting, Journal of Machine and Computing, 4(4), 2024, doi: 10.53759/7669/jmc202404105.
21. Shaymaa HN, et al., Genetic Algorithms for Optimized Selection of Biodegradable Polymers in Sustainable Manufacturing Processes, Journal of Machine and Computing, 4(3), 563-574, https://doi.org/10.53759/7669/jmc202404054.
22. Hayder MAG et al., An open-source MP + CNN + BiLSTM model-based hybrid model for recognizing sign language on smartphones. Int J Syst Assur Eng Manag (2024). https://doi.org/10.1007/s13198-024-02376-x
23. Bhavana Raj K et al., Equipment Planning for an Automated Production Line Using a Cloud System, Innovations in Computer Science and Engineering. ICICSE 2022. Lecture Notes in Networks and Systems, 565, 707–717, Springer, Singapore. DOI:10.1007/978-981-19-7455-7_57.
24. Kalogeropoulou, M., Kracher, A., Fucile, P., Mihăilă, S. M., & Moroni, L. (2024). Blueprints of Architected Materials: A Guide to Metamaterial Design for Tissue Engineering. Advanced Materials, 2408082.
25. Saunders, R. (2020). Metamaterials using additive manufacturing technologies. Naval Research Laboratory, Washington [Online]. Available at.
26. Krushynska, A. O., Torrent, D., Aragón, A. M., Ardito, R., Bilal, O. R., Bonello, B., ... & Wright, O. B. (2023). Emerging topics in nanophononics and elastic, acoustic, and mechanical metamaterials: an overview. Nanophotonics, 12(4), 659-686.
27. Barri, K. (2022). Self-sensing and Self-powering Multifunctional Mechanical Metamaterials (Doctoral dissertation, University of Pittsburgh).
28. Park, Y. (2023). The Design of Mechanical Metamaterials for Nonlinear-Elastic Functional Structures and Surface Morphing (Doctoral dissertation, UC San Diego).
29. Liang, K., Wang, Y., Luo, Y., Takezawa, A., Zhang, X., & Kang, Z. (2023). Programmable and multistable metamaterials made of precisely tailored bistable cells. Materials & Design, 227, 111810.
30. Yang, D., Guo, X., Zhang, W., & Cao, D. (2024). Non-linear dynamics and bandgap control in magneto-rheological elastomers metamaterials with inertial amplification. Thin-Walled Structures, 204, 112237.
31. He, Y., Bi, Z., Wang, T., Wang, L., Lu, G., Cui, Y., & Tse, K. M. (2024). Design and mechanical properties analysis of hexagonal perforated honeycomb metamaterial. International Journal of Mechanical Sciences, 270, 109091.
32. Ji, J. C., Luo, Q., & Ye, K. (2021). Vibration control based metamaterials and origami structures: A state-of-the-art review. Mechanical Systems and Signal Processing, 161, 107945.
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