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Strategy for the maintenance and monitoring of electric road infrastructures based on recursive lifetime prediction

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Abstract

Wireless charging is an attractive technology that is expected to promote customer acceptance of electric vehicles since it can improve convenience and sustainability. The dynamic properties and the long-term structural behavior of these particular infrastructures call for in depth investigations, to define specific requirements for the installation of the system, as well as for its maintenance, lifecycle analysis and monitoring. Currently, several technologies exist that integrate dynamic inductive charging systems within the infrastructure, ranging from rails with box-section to buried solutions. A wide-range discussion is provided on how to assess the structural performance of electric roads (e-roads), including numerical strategies for the estimation of their lifetime. Structural health monitoring (SHM) strategies for e-roads will be then outlined. Indeed, a SHM strategy integrated with lifecycle management is essential to calibrate structural assessment and prediction, to optimize the maintenance of infrastructure and, possibly, to operate infrastructure systems beyond their original design life. Finally, results of simulations are presented for the e-road solution.

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References

  1. Ceravolo R, Miraglia G, Pinotti E, Surace C, Zanotti Fragonara L (2015) Modelling of a road infrastructure adapted for dynamic inductive recharging for maintenance and monitoring. 7th International Conference on Structural Health Monitoring on Intelligent Infrastructures, Turin, Italy

  2. Ceravolo R, Miraglia G, Surace C, Zanotti Fragonara L (2016)  A computational methodology for assessing the time-dependent structural performance of electric road infrastructures. Comput Aided Civ Infrastruct Eng 31(9):701–716

    Article  Google Scholar 

  3. Zopf C, Garcia MA, Kaliske M (2015) A continuum mechanical approach to model asphalt. Int J Pavement Eng 16(2):105–124

    Article  Google Scholar 

  4. Al-Khateeb LA, Saoud A, Al-Msouti MF (2010) Rutting prediction of flexible pavements using finite element modeling. Jordan J Civ Eng 5(2):173–190

    Google Scholar 

  5. Ahmed A, Erlingsson S (2013) Evaluation of permanent deformation models for unbound granular materials using accelerated pavement tests. Road Mater Pavement Des 14:178–195

    Article  Google Scholar 

  6. Darabi MK, Abu Al-Rub RK, Masad EA, Huang C-W, Little DN (2012) A modified viscoplastic model to predict the permanent deformation of asphaltic materials under cyclic-compression loading at high temperatures. Int J Plast 35:100–134

    Article  Google Scholar 

  7. Qiao Y, Dawson A, Huvstig A, Korkiala-Tanttu L (2015) Calculating rutting of some thin flexible pavements from repeated load triaxial test data. Int J Pavement Eng 16(6):467–476

    Article  Google Scholar 

  8. Rahman MS, Erlingsson S (2015) Predicting permanent deformation behaviour of unbound granular materials. Int J Pavement Eng 16(7):587–601

    Article  Google Scholar 

  9. Saevarsdottir T, Erlingsson S (2015) Modelling of responses and rutting profile of a flexible pavement structure in a heavy vehicle simulator test. Road Mater Pavement Des 16(1):1–18

    Article  Google Scholar 

  10. Gupta A, Kumar P, Rastogi R (2014) Critical review of flexible pavement performance models. KSCE J Civ Eng 18(1):142–148

    Article  Google Scholar 

  11. Baburamani P (1999) Asphalt fatigue life prediction models—a literature review. Research Report ARR 334, ARRB Transport Research Ltd., Vermont South, Victoria

  12. Hoki B, Soohyok I, Yong-Rak K (2013) Nonlinear viscoelastic approach to model damage-associated performance behavior of asphaltic mixture and pavement structure. Can J Civ Eng 40(4):313–323

    Article  Google Scholar 

  13. Čygas D, Laurinavičius A, Paliukaitė M, Motiejūnas A, Žiliūtė L, Vaitkus A (2015) Monitoring the mechanical and structural behavior of the pavement structure using electronic sensors. Comput Aided Civ Infrastruct Eng 30(4):317–328

    Article  Google Scholar 

  14. Qarib H, Adeli H (2014) Recent advances in health monitoring of civil structures. Sci Iran Trans A Civ Eng 21(6):1733–1742

    Google Scholar 

  15. Seo Y, Kim YR (2008) Using acoustic emission to monitor fatigue damage and healing in asphalt concrete. KSCE J Civ Eng 12(4):237–243

    Article  MathSciNet  Google Scholar 

  16. Jin C, Jang S, Sun X et al (2016) Damage detection of a highway bridge under severe temperature changes using extended Kalman filter trained neural network. J Civ Struct Health Monit 6:545. doi:10.1007/s13349-016-0173-8

    Article  Google Scholar 

  17. Spencer BF, Jo H, Mechitov KA et al (2016) Recent advances in wireless smart sensors for multi-scale monitoring and control of civil infrastructure. J Civ Struct Health Monit 6:17. doi:10.1007/s13349-015-0111-1

    Article  Google Scholar 

  18. Kalyankar R, Uddin N (2017) Axle detection on prestressed concrete bridge using bridge weigh-in-motion system. J Civ Struct Health Monit 7:191. doi:10.1007/s13349-017-0210-2

    Article  Google Scholar 

  19. Helmi K, Bakht B, Mufti A (2014) Accurate measurements of gross vehicle weight through bridge weigh-in-motion: a case study. J Civ Struct Health Monit 4:195. doi:10.1007/s13349-014-0076-5

    Article  Google Scholar 

  20. Fraser M, Elgamal A, Conte JP, Masri S, Fountain T, Gupta A, El Zarki M (2003) Elements of an integrated health-monitoring framework. In: SPIE 10th Annual International Symposium on Smart Structures and Materials, 5047, pp 231–242

  21. Adeli H, Jiang X (2009) Intelligent infrastructure—neural networks, wavelets, and chaos theory for intelligent transportation systems and smart structures. CRC Press, Taylor & Francis, Boca Raton

    Google Scholar 

  22. Frangopol DM, Messervey TB (2009) Maintenance principles for civil structures. In: Boller C, Chang FK, Fujino Y (eds) Encyclopedia of structural health monitoring. Wiley, Chichester

    Google Scholar 

  23. Chen F, Taylor N, Kringos N (2015) Electrification of roads: opportunities and challenges. Appl Energy 150:109–119

    Article  Google Scholar 

  24. Chuntaek R (2013) The development and deployment of on-line electric vehicles (OLEV). NE-conference papers, IEEE energy conversion congress and exposition (ECCE) 2013. Colorado Convention Center, Denver, CO, USA. http://hdl.handle.net/10203/192077. Accessed 1 Aug 2016

  25. Boys JT, Covic GA (2012) Basic concepts. IPT fact sheet series: no. 1. Qualcomm. https://www.qualcomm.com/media/documents/files/ipt-fact-sheet-1-uoa-2012.pdf. Accessed Aug 2016

  26. Ceravolo R, Pescatore M, De Stefano A (2009) Symptom based reliability and generalized repairing cost in monitored bridges. Reliab Eng Syst Saf 94(8):1331–1339

    Article  Google Scholar 

  27. El Hamra W, Attallah Y (2011) The role of vehicles’ identification techniques in transportation planning—modeling concept. Alex Eng J 50:391–398

    Article  Google Scholar 

  28. Cantisani G, Di Vitoa M, Luteria P (2012) VPL Project’09: an integrated station for vehicles’ operating conditions survey. In: SIIV, 5th International Congress, Sustainability of Road Infrastructures, Procedia, Social and Behavioral Sciences 53:777–788

  29. Wyman JH (1989) An evaluation of currently available WIM systems. In: Proceedings of 3rd National Conference on Weigh-In-Motion, March, pp 6–176

  30. Cottrell B Jr (1992) Evaluation of weigh-in-motion systems. Final Report. FHWA Report FHWA/VA-92-RB, VTRC 92-RB; National Technical Information Service, Springfield VA, p 100

  31. Papagiannakis AT, Phang WA, Woodrooffe JHF, Bergan AT, Haas RCG (1988) Accuracy of weigh-in-motion scales and piezoelectric cables. Transp Res Record 1215; TRB, Washington D.C., pp 189–196

  32. Glover M, Newton W (1991) Evaluation of a multi-sensor weigh-in-motion system. RR 307, Transport and Road Research Lab, Crawthorne, England

  33. Karpis O (2012) Sensor for vehicles classification. In: Proceedings of the federated conference on computer science and information systems. pp 785–789. ISBN 978-83-60810-51-4

  34. Gontarz S, Szulim P, Senko J, Dybała J (2015) Use of magnetic monitoring of vehicles for proactive strategy development. Transp Res Part C 52:102–115

    Article  Google Scholar 

  35. Cho HJ, Tseng MT (2013) A support vector machine approach to CMOS-based radar signal processing for vehicle classification and speed estimation. Math Comput Model 58:438–448

    Article  MathSciNet  MATH  Google Scholar 

  36. Levenberg E (2014) Estimating vehicle speed with embedded inertial sensors. Transp Res Part C 46:300–308

    Article  Google Scholar 

  37. Malla RB, Sen A, Garrick NW (2008) A special fiber optic sensor for measuring wheel loads of vehicles on highways. Sensors 8:2551–2568

    Article  Google Scholar 

  38. Tardy A, Jurczyszyn M, Caussignac J-M, Morel G, Briant G (1989) High sensitivity transducer for fibre-optic pressure sensing applied to dynamic mechanical testing and vehicle detection on roads. In: Arditty HJ, Dakin JP, Kersten RT (eds) Optical fiber sensors, Springer Proceedings in physics, vol 44. Springer, Berlin, pp 215–221

    Chapter  Google Scholar 

  39. Boby J, Teral S, Caussignac JM, Siffert M (1994) Weighing of vehicles in motion using fiber optic sensors. In: Electrical communication, 1st quarter. International Telephone and Telegraph Corporation, Alcatel Alsthom Publications, France, pp 74–77

  40. Teral SR, Larcher SJ, Caussignac JM, Barbachi M (1996) Fiber optic weigh-in-motion sensor: correlation between modeling and practical characterization. In: Proceeding SPIE, smart structures and materials 1996: smart sensing, processing, and instrumentation, vol 2713. San Diego, CA. doi:10.1117/12.240881

  41. Kunzler M, Edgar R, Udd E, Taylor T, Schulz WL, et al. (2002) Fiber grating traffic monitoring systems. In: Proceeding SPIE, smart structures and materials 2002: smart systems for bridges, structures, and highways, vol 4696. San Diego, CA. doi:10.1117/12.472559

  42. Casas JR, Cruz PJS (2003) Fiber optic sensors for bridge monitoring. J. Bridge Eng 8:362–373

    Article  Google Scholar 

  43. Moyo P, Brownjohn JMW, Suresh R, Tjin SC (2005) Development of fiber Bragg grating sensors for monitoring civil infrastructure. Eng Struct 27:1828–1834

    Article  Google Scholar 

  44. Kersey AD, Davis MA, Patrick HJ (1997) Fiber grating sensors. J Lightwave Technol 15(8):1442–1463

    Article  Google Scholar 

  45. Kleinerman M, Kelleher PW (1992) Distributed force-sensing optical fiber using forward time-division multiplexing. Proceedings of SPIE 1586, Distributed and Multiplexed Fiber Optic Sensors. 1 Jan 1992, p 67. doi:10.1117/12.56508

  46. Malla RB, Garrick N, Sen A, Dua P (1998) A dual core forward time division multiplexing optical fiber for weigh in motion system. Fiber optic sensors for construction materials and bridges. Technomic Publishing Co., Lancaster, pp 251–262

    Google Scholar 

  47. Roberts FL, Kandhal PS, Brown ER, Lee D, Kennedy TW (1996) Hot mix asphalt materials, mixture design and construction. National Asphalt Pavement Association Research and Education Foundation, Lanham

    Google Scholar 

  48. Yiqiu T, Haipeng W, Shaojun M, Huining X (2014) Quality control of asphalt pavement compaction using fibre Bragg grating sensing technology. Constr Build Mater 54:53–59

    Article  Google Scholar 

  49. Xu D-S et al (2013) A new flexible FBG sensing beam for measuring dynamic lateral displacements of soil in a shaking table test. Measurement 46:200–209

    Article  Google Scholar 

  50. Lee B (2003) Review of the present status of optical fiber sensors. Opt Fiber Technol 9(2):57–59

    Article  Google Scholar 

  51. Zhou A et al (2012) Optical fiber Bragg grating sensor assembly for 3D strain monitoring and its case study in highway pavement. Mech Syst Signal Process 28:36–49

    Article  Google Scholar 

  52. Burningham S, Stankevich N (2005) Why road maintenance is important and how to get it done. Transport Note No. TRN-4, The world bank, Washington, DC

  53. Transport Research Laboratory, and Department for International Development (1998) Overseas Road Note 15: Guidelines for the design and operation of road management systems. ISSN:0951-8797, Copyright Transport Research Laboratory

  54. Ceravolo R, De Stefano A, Pescatore M (2008) Change in dynamic parameters and safety assessment of civil structures. Mech Time Depend Mater 12(4):365–376

    Article  Google Scholar 

  55. Kong JS, Frangopol DM (2004) Cost-reliability interaction in life-cycle cost optimization of deteriorating structures. J Struct Eng 130(11):1704–1712

    Article  Google Scholar 

  56. "Nuovo codice della strada”, decreto legisl. 30 aprile 1992 n. 285 e successive modificazioni. TITOLO III—DEI VEICOLI, Capo I—DEI VEICOLI IN GENERALE, Art. 61. Sagoma limite, Art. 62. Massa limite (in Italian)

  57. Pinotti E (2013) Vibration in smart infrastructure systems for electric vehicles, Turin, Italy. http://opac.biblio.polito.it:80/F/func=direct&doc_number=000360040&local_base=TESW. Accessed Aug 2016

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Acknowledgements

This research has been supported by the European Commission within the FP7 projects UNPLUGGED (Grant No. 314126) and FABRIC (Grant No. 605405).

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Correspondence to Rosario Ceravolo.

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Ceravolo, R., Miraglia, G. & Surace, C. Strategy for the maintenance and monitoring of electric road infrastructures based on recursive lifetime prediction. J Civil Struct Health Monit 7, 303–314 (2017). https://doi.org/10.1007/s13349-017-0227-6

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  • DOI: https://doi.org/10.1007/s13349-017-0227-6

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