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Reduced-order modeling with multiple scales of electromechanical systems for energy harvesting

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Abstract

New technologies that aim at powering wireless nodes by scavenging the energy from ambient vibrations can be a practical solution for some structural monitoring applications in the near future. In view of possible large-scale applications of piezoelectric energy harvesters, an accurate modeling of the interfaces in these devices is needed for more advanced and reliable simulations, since they might have large influence on functionality and performance of smart monitoring infrastructures. In this perspective, a novel multiscale and multiphysics hybrid approach is proposed to assess the dynamic response of piezoelectric energy harvesting devices. Within the framework of the presented approach, the FE2 method is employed to compute stress and strain levels at the microscale in the most critical interfaces. The displacement-load curve of the whole device (so-called capacity curve or pushover curve) is then obtained by means of the application of a suitable pattern of static forces. Finally, the parameters of a reduced-order model are calibrated on the basis of the nonlinear static analysis. This reduced-order model, in turn, is employed for the efficient dynamic analysis of the energy harvesting device.

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References

  1. R.E. Nickell, Comput. Methods Appl. Mech. Eng. 7, 107 (1976)

    Article  ADS  MathSciNet  Google Scholar 

  2. K.J. Bathe, S. Gracewski, Comput. Struct. 13, 699 (1981)

    Article  Google Scholar 

  3. S.R. Idelsohn, A. Cardona, Comput. Methods Appl. Mech. Eng. 49, 253 (1985)

    Article  ADS  Google Scholar 

  4. G. Kerschen, M. Peeters, J.C. Golinval, A.F. Vakakis, Mech. Syst. Signal Process. 23, 170 (2009)

    Article  ADS  Google Scholar 

  5. M. Peeters, R. Viguié, G. Sérandour, G. Kerschen, J.C. Golinval, Mech. Syst. Signal Process. 23, 195 (2009)

    Article  ADS  Google Scholar 

  6. L. Renson, G. Deliége, G. Kerschen, Meccanica 49, 1901 (2014)

    Article  MathSciNet  Google Scholar 

  7. J.P. Noel, L. Renson, C. Grappasonni, G. Kerschen, Mech. Syst. Signal Process. 74, 95 (2015)

    Article  ADS  Google Scholar 

  8. W. Lacarbonara, B. Carboni, G. Quaranta, Meccanica 51, 2629 (2016)

    Article  MathSciNet  Google Scholar 

  9. P. Tiso, E. Jansen, M. Abdalla, AIAA J. 49, 2295 (2011)

    Article  ADS  Google Scholar 

  10. A.K. Chopra, R.K. Goel, Earthquake Eng. Struct. Dyn. 31, 561 (2002)

    Article  Google Scholar 

  11. F. Otero, S. Oller, X. Martinez, Arch. Comput. Methods Eng. 25, 479 (2016)

    Article  Google Scholar 

  12. K. Matous, M.G.D. Geers, V.G. Kouznetsova, A. Gillman, J. Comput. Phys. 330, 192 (2016)

    Article  ADS  Google Scholar 

  13. F. Covezzi, S. de Miranda, F. Fritzen, S. Marfia, E. Sacco, Meccanica 53, 1291 (2018)

    Article  Google Scholar 

  14. A. Moyeda, J. Fish, Comput. Mech. 62, 685 (2017)

    Article  Google Scholar 

  15. J. Oliver, M. Caicedo, A.E. Huespe, J.A. Hernández, E. Roubin, Comput. MethodsAppl. Mech. Eng. 313, 560 (2017)

    Article  ADS  Google Scholar 

  16. M. Leuschner, F. Fritzen, Mech. Mater. 104, 121 (2016)

    Article  Google Scholar 

  17. S. Marfia, E. Sacco, Composites B 136, 241 (2017)

    Article  Google Scholar 

  18. S. Fillep, J. Mergheim, P. Steinmann, Comput. Mech. 59, 385 (2017)

    Article  MathSciNet  Google Scholar 

  19. M. Caicedo, J.L. Mroginski, S. Toro, M. Raschi, A. Huespe, J. Oliver, Arch. Comput. Methods Eng. 1 (2018)

  20. P.R. Budarapu, T. Rabczuk, J. Indian Inst. Sci. 97, 339 (2017)

    Article  Google Scholar 

  21. V. Lucas, J.C. de Golinval, R.C. Voicu, M. Danila, R. Gavrila, R. Müller, A. Dinescu, L. Noels, L. Wu, Int. J. Numer. Methods Eng. 111, 26 (2016)

    Article  Google Scholar 

  22. F. Feyel, Comput. Mater. Sci. 16, 344 (1999)

    Article  Google Scholar 

  23. F. Feyel, Comput. Methods Appl. Mech. Eng. 192, 3233 (2003)

    Article  ADS  Google Scholar 

  24. F. Feyel, J.L. Chaboche, Comput. Methods Appl. Mech. Eng. 183, 309 (2000)

    Article  ADS  Google Scholar 

  25. V. Kouznetsova, W. Brekelmans, F. Baaijens, Comput. Mech. 27, 37 (2001)

    Article  Google Scholar 

  26. K. Terada, N. Kikuchi, Comput. Methods Appl. Mech. Eng. 190, 5427 (2001)

    Article  ADS  Google Scholar 

  27. C. Liu, C. Reina, J. Mech. Phys. Solids 104, 187 (2017)

    Article  ADS  MathSciNet  Google Scholar 

  28. R. Alberdi, G. Zhang, K. Khandelwal, Int. J. Numer. Methods Eng. 114, 1018 (2018)

    Article  Google Scholar 

  29. U. Solinc, J. Korelc, Comput. Mech. 56, 905 (2015)

    Article  MathSciNet  Google Scholar 

  30. J. Schroder, M.A. Keip, Comput. Mech. 50, 229 (2012)

    Article  MathSciNet  Google Scholar 

  31. M.A. Keip, P. Steinmann, J. Schroder, Comput. Methods Appl. Mech. Eng. 278, 62 (2014)

    Article  ADS  Google Scholar 

  32. E. Polukhov, D. Vallicotti, M.A. Keip, Comput. Methods Appl. Mech. Eng. 337, 165 (2018)

    Article  ADS  Google Scholar 

  33. J. Schröder, M. Labusch, A 3D magnetostrictive Preisach model for the simulation of magneto-electric composites on multiple scales, in Lecture Notes in Applied and Computational Mechanics, Multiscale Modeling of Heterogeneous Structures (Springer, 2018), Vol. 86, Chap. 15, pp. 303–327

  34. M. Labusch, et al. An FE2 scheme for magneto-electro-mechanically coupled boundary value problems, in CISM International Centre for Mechanical Sciences, Ferroic Functional Materials, edited by J. Schröder, D.C. Lupascu (2018), Vol. 581, Chap. 5, pp. 227–262

  35. M.A. Keip, M. Rambausek, Int. J. Solids Struct. 121, 1 (2017)

    Article  Google Scholar 

  36. M.J. Zahr, P. Avery, C. Farhat, Int. J. Numer. Methods Eng. 112, 855 (2017)

    Article  Google Scholar 

  37. N.G. Elvin, N. Lajnef, A. Elvin, Smart Mater. Struct. 15, 977 (2006)

    Article  ADS  Google Scholar 

  38. M. Rhimi, N. Lajnef, J. Energy Eng. 138, 185 (2012)

    Article  Google Scholar 

  39. M. Peigney, D. Siegert, Smart Mater. Struct. 22, 095019 (2013)

    Article  ADS  Google Scholar 

  40. C. Maruccio, G. Quaranta, L. De Lorenzis, G. Monti, Smart Mater. Struct. 25, 085040 (2016)

    Article  ADS  Google Scholar 

  41. P. Cahill, A. Mathewson, V. Pakrashi, J. Bridge Eng. 23, 04018056 (2018)

    Article  Google Scholar 

  42. P. Cahill, B. Hazra, R. Karoumi, A. Mathewson, V. Pakrashi, Mech. Syst. Signal Process. 106, 265 (2018)

    Article  ADS  Google Scholar 

  43. J. Korelc, J. Eng. Comput. 18, 312 (2002)

    Article  Google Scholar 

  44. J. Korelc, Comput. Mech. 44, 631 (2009)

    Article  MathSciNet  Google Scholar 

  45. V. Kouznetsova, W.A.M. Brekelmans, F.P.T. Baaijens, Comput. Mech. 27, 37 (2001)

    Article  Google Scholar 

  46. M.G.D. Geers, V.G. Kouznetsova, W.A.M. Brekelmans, Comput. Methods Appl. Mech. Eng. 192, 559 (2003)

    Article  Google Scholar 

  47. A. Kefal, C. Maruccio, G. Quaranta, E. Oterkus, Mech. Syst. Signal Process. 121, 890 (2019)

    Article  ADS  Google Scholar 

  48. G. Quaranta, F. Trentadue, C. Maruccio, G.C. Marano, Mech. Syst. Signal Process. 104, 134 (2018)

    Article  ADS  Google Scholar 

  49. C. Maruccio, G. Quaranta, P. Montegiglio, F. Trentadue, G. Acciani, Shock Vib. 2018, 2054873 (2018)

    Google Scholar 

  50. C. Maruccio, L. De Lorenzis, L. Persano, D. Pisignano, Comput. Mech. 55, 983 (2015)

    Article  MathSciNet  Google Scholar 

  51. L. Persano, C. Dagdeviren, C. Maruccio, L. De Lorenzis D. Pisignano, Adv. Mater. 26, 7574 (2014)

    Article  Google Scholar 

  52. C. Maruccio, L. De Lorenzis, Fracture and Structural Integrity 8, 49 (2014)

    Google Scholar 

  53. S.C. Stanton, A. Erturk, B.P. Mann, D.J. Inman, J. Appl. Phys. 108, 074903 (2010)

    Article  ADS  Google Scholar 

  54. N.G. Elvin, A. Elvin, J. Intell. Mater. Syst. Struct. 23, 1475 (2012)

    Article  Google Scholar 

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Authors and Affiliations

  1. Department of Innovation Engineering, University of Salento, Lecce, Italy

    Claudio Maruccio & Giuseppe Grassi

  2. Department of Structural Engineering and Geotechnics, Sapienza University of Rome, Rome, Italy

    Giuseppe Quaranta

Authors
  1. Claudio Maruccio
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  2. Giuseppe Quaranta
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  3. Giuseppe Grassi
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Correspondence to Claudio Maruccio.

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Maruccio, C., Quaranta, G. & Grassi, G. Reduced-order modeling with multiple scales of electromechanical systems for energy harvesting. Eur. Phys. J. Spec. Top. 228, 1605–1624 (2019). https://doi.org/10.1140/epjst/e2019-800173-x

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  • DOI: https://doi.org/10.1140/epjst/e2019-800173-x

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