Open Access
Issue
Mechanics & Industry
Volume 21, Number 6, 2020
Article Number 603
Number of page(s) 15
DOI https://doi.org/10.1051/meca/2020075
Published online 25 September 2020
  1. A. Benyoucef, M. Leblouba, A. Zerzour, Stiffness and energy dissipation of oval leaf spring mounts under unidirectional line loading, Mech. Ind. 18, 414 (2017) [CrossRef] [Google Scholar]
  2. C. Grenat, S. Baguet, C.-H. Lamarque, R. Dufour, A multi-parametric recursive continuation method for nonlinear dynamical systems, Mech. Syst. Signal Process. 127, 276–289 (2019) [Google Scholar]
  3. G. Kouroussis, H.P. Mouzakis, K.E. Vogiatzis, Structural impact response for assessing railway vibration induced on Buildings, Mech. Ind. 18, 803 (2017) [Google Scholar]
  4. A. Malher, C. Touzé, O. Doaré, G. Habib, G. Kerschen, Flutter control of a two-degrees-of-freedom airfoil using a nonlinear tuned vibration absorber, J. Computat. Nonlinear Dyn. 12 (2017) [Google Scholar]
  5. Q. Yu, D. Xu, Y. Zhu, G. Guan, An efficient method for estimating the damping ratio of a vibration isolation system, Mech. Ind. 21, 103 (2020) [CrossRef] [Google Scholar]
  6. H. Moeenfard, S. Awtar, Modeling geometric nonlinearities in the free vibration of a planar beam flexure with a tip mass, J. Mech. Des. 136, 044502 (2014) [CrossRef] [Google Scholar]
  7. C.E. Okwudire, Reduction of torque-induced bending vibrations in ball screw-driven machines via optimal design of the nut, J. Mech. Des. 134, 1–9 (2012) [CrossRef] [Google Scholar]
  8. A.Z. Trimble, J.H. Lang, J. Pabon, A. Slocum, A device for harvesting energy from rotational vibrations, J. Mech. Des. 132, 091001 (2010) [CrossRef] [Google Scholar]
  9. H. Frahm, Device for damping vibrations of bodies, 18 April 1911, US Patent 989, 958. [Google Scholar]
  10. F. Weber, Semi-active vibration absorber based on real-time controlled MR damper, Mech. Syst. Signal Process. 46, 272–288 (2014) [Google Scholar]
  11. A.F. Vakakis, O. Gendelman, Energy pumping in nonlinear mechanical oscillators: part II—resonance capture. J. Appl. Mech. 68, 42–48 (2001) [Google Scholar]
  12. D. Younesian, A. Nankali, M.E. Motieyan, Application of the nonlinear energy sink systems in vibration suppression of railway bridges, in: ASME 2010 10th Biennial Conference on Engineering Systems Design and Analysis, American Society of Mechanical Engineers Digital Collection, 2010, pp. 227–231 [Google Scholar]
  13. Y.S. Lee, A.F. Vakakis, L.A. Bergman, D.M. McFarland, G. Kerschen, Suppression aeroelastic instability using broadband passive targeted energy transfers, part 1: theory, AIAA J. 45, 693–711 (2007) [Google Scholar]
  14. E. Gourc, S. Seguy, G. Michon, A. Berlioz, Delayed dynamical system strongly coupled to a nonlinear energy sink: application to machining chatter, in: MATEC Web of Conferences, EDP Sciences, 2012, Vol. 1, p. 05002 [Google Scholar]
  15. S. Goyal, T.M. Whalen, Design and application of a nonlinear energy sink to mitigate vibrations of an air spring supported slab, in: ASME 2005 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, American Society of Mechanical Engineers Digital Collection, 2005, pp. 2331–2339 [Google Scholar]
  16. D. Qiu, S. Seguy, M. Paredes, Tuned nonlinear energy sink with conical spring: design theory and sensitivity analysis, J. Mech. Des. 140, 011404 (2018) [CrossRef] [Google Scholar]
  17. A. Vakakis, O. Gendelman, L. Bergman, D. McFarland, G. Kerschen, Y. Lee, Nonlinear targeted energy transfer in discrete linear oscillators with single-dof nonlinear energy sinks, Nonlinear Target. Energy Transfer Mech. Struct. Syst. 93–302 (2009) [Google Scholar]
  18. S. Charlemagne, C.-H. Lamarque, A.T. Savadkoohi, Dynamics and energy exchanges between a linear oscillator and a nonlinear absorber with local and global potentials, J. Sound Vibr. 376, 33–47 (2016) [CrossRef] [Google Scholar]
  19. T.A. Nguyen, S. Pernot, Design criteria for optimally tuned nonlinear energy sinks—part 1: transient regime, Nonlinear Dyn. 69(1–2), 1–19 (2012) [Google Scholar]
  20. B. Vaurigaud, A.T. Savadkoohi, C.-H. Lamarque, Targeted energy transfer with parallel nonlinear energy sinks. Part I: design theory and numerical results, Nonlinear Dyn. 66, 763–780 (2011) [Google Scholar]
  21. E. Boroson, S. Missoum, P.-O. Mattei, C. Vergez, Optimization under uncertainty of parallel nonlinear energy sinks, J. Sound Vibr. 394, 451–464 (2017) [CrossRef] [Google Scholar]
  22. M. Paredes, E. Rodriguez, Optimal design of conical springs, Eng. Comput. 25, 147–154 (2009) [Google Scholar]
  23. M. Gobbi, G. Mastinu, On the optimal design of composite material tubular helical springs, Meccanica 36, 525–553 (2001) [Google Scholar]
  24. M.M. Shokrieh, D. Rezaei, Analysis and optimization of a composite leaf spring. Composite Struct. 60, 317–325 (2003) [CrossRef] [Google Scholar]
  25. H. Trabelsi, P.-A. Yvars, J. Louati, M. Haddar, Interval computation and constraint propagation for the optimal design of a compression spring for a linear vehicle suspension system, Mech. Mach. Theory 84, 67–89 (2015) [Google Scholar]
  26. X. Lu, Z. Liu, Z. Lu, Optimization design and experimental verification of track nonlinear energy sink for vibration control under seismic excitation, Struct. Control Health Monitor. 24, e2033 (2017) [Google Scholar]
  27. N.E. Wierschem, J. Luo, M. Al-Shudeifat, S. Hubbard, R. Ott, L.A. Fahnestock, D.D. Quinn, D.M. McFarland, B. Spencer Jr A. Vakakis et al., Experimental testing and numerical simulation of a six-story structure incorporating two-degree-of-freedom nonlinear energy sink, J. Struct. Eng. 140, 04014027 (2014) [CrossRef] [Google Scholar]
  28. K. Yang, Y.-W. Zhang, H. Ding, T.-Z. Yang, Y. Li, L.-Q. Chen, Nonlinear energy sink for whole-spacecraft vibration reduction. J. Vibr. Acoust. 139, 021011 (2017) [CrossRef] [Google Scholar]
  29. H. Zhao, G. Chen, J.Z. Zhou, The robust optimization design for cylindrical helical compression spring. in: Adv. Mater. Res., Trans. Tech. Publ., 2012, Vol. 433, pp. 2201–2205 [Google Scholar]
  30. V. Rathod, O.P. Yadav, A. Rathore, R. Jain, Reliability-based design optimization considering probabilistic degradation behavior, Qual. Reliabil. Eng. Int. 28, 911–923 (2012) [CrossRef] [Google Scholar]
  31. E. Boroson, S. Missoum, Stochastic optimization of nonlinear energy sinks, Struct. Multidiscipl. Optim. 55, 633–646 (2017) [Google Scholar]
  32. E.R. Boroson, S. Missoum, Optimization under uncertainty of parallel nonlinear energy sinks. in: 57th AIAA/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference, 2016, pp. 1421 [Google Scholar]
  33. B. Pidaparthi, S. Missoum, Stochastic optimization of nonlinear energy sinks for the mitigation of limit cycle oscillations, AIAA J. 57, 2134–2144 (2019) [Google Scholar]
  34. M. Weiss, B. Vaurigaud, A.T. Savadkoohi, C.-H. Lamarque, Control of vertical oscillations of a cable by a piecewise linear Absorber, J. Sound Vibr. 435, 281–300 (2018) [CrossRef] [Google Scholar]
  35. M.M. Opgenoord, D.L. Allaire, K.E. Willcox, Variance-based sensitivity analysis to support simulation-based design under uncertainty, J. Mech. Des. 138, 111410 (2016) [CrossRef] [Google Scholar]
  36. E. Rodriguez, M. Paredes, M. Sartor, Analytical behavior law for a constant pitch conical compression Spring, J. Mech. Des. 128, 1352–1356 (2006) [CrossRef] [Google Scholar]
  37. P. Edler, S. Freitag, K. Kremer, G. Meschke, Optimization approaches for the numerical design of structures under consideration of polymorphic uncertain data, ASCE-ASME J. Risk Uncert. Eng. Syst. B: Mech. Eng. (2019) [Google Scholar]
  38. S.M. Göhler, T. Eifler, T.J. Howard, Robustness metrics: consolidating the multiple approaches to quantify Robustness, J. Mech. Des. 138, 111407 (2016) [CrossRef] [Google Scholar]
  39. O. Braydi, P. Lafon, R. Younes, On the formulation of optimization problems under uncertainty in mechanical design, Int. J. Interact. Des. Manuf. (IJIDeM) 13, 75–87 (2019) [CrossRef] [Google Scholar]
  40. S. Yu, Z. Wang, Z. Wang, Time-dependent reliability-based robust design optimization using evolutionary algorithm, ASCE-ASME J. Risk Uncert. Eng. Syst. B: Mech. Eng. 5, 020911 (2019) [Google Scholar]
  41. J. Havinga, A.H. van den Boogaard, G. Klaseboer, Sequential improvement for robust optimization using an uncertainty measure for radial basis functions, Struct. Multidiscipl. Optim. 55, 1345–1363 (2017) [Google Scholar]
  42. N. Lelièvre, P. Beaurepaire, C. Mattrand, N. Gayton, A. Otsmane, On the consideration of uncertainty in design: optimization-reliability-robustness, Struct. Multidiscipl. Optim. 54, 1423–1437 (2016) [Google Scholar]
  43. R.E. Caflisch, Monte Carlo and quasi-Monte Carlo methods, Acta Numer. 7, 1–49 (1998) [Google Scholar]
  44. V. Baudoui, Optimisation robuste multiobjectifs par modèles de substitution, PhD thesis, Toulouse, ISAE, 2012 [Google Scholar]
  45. O. Braydi, P. Lafon, R. Younes, Study of uncertainties and objective function modeling effects on probabilistic optimization results, ASCE-ASME J. Risk Uncert. Eng. Syst. B: Mech. Eng. (2019) [Google Scholar]
  46. W.-N. Yang, B.L. Nelson, Using common random numbers and control variates in multiple-comparison procedures, Oper. Res. 39, 583–591 (1991) [Google Scholar]

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