International Journal of Civil Engineering

, Volume 17, Issue 3, pp 347–359 | Cite as

Methodology to Develop Fragility Curves of Glass Façades Under Wind-Induced Pressure

  • Isaac Felipe Lima-Castillo
  • Roberto Gómez-Martínez
  • Adrián Pozos-EstradaEmail author
Research paper


High wind speeds produced by hurricanes or synoptic winds can cause considerable damage and the failure of structural and nonstructural elements. The use of glass façades in buildings has become very popular; in Mexico, a large number of buildings along the coast are designed with glass façades. Glass façades provide light, temperature control, and an esthetic view; however, this type of glass system is particularly vulnerable to high wind-induced pressures. A methodology to determine the fragility curves of glass façades under turbulent wind loading is proposed. This methodology could be used to select the appropriate glass thickness of a façade. The procedure employs an autoregressive and moving average model to simulate the wind field and Monte Carlo techniques to simulate the glass resistance of the windows. The methodology to construct the fragility curves is illustrated with a numerical example of a glass façade of a 96-m tall building. Three cases of glass resistance associated with coefficients of variation equal to 0, 10, and 20% were considered. The results of the numerical example show that the uncertainty in the glass resistance plays an important role in the development of the fragility curves of the glass façades for high mean wind speeds between 38 and 67 m/s at a height of 10 m.


Glass façade ARMA model Wind pressure Fragility curves Probability of damage 



The financial support received from the Institute of Engineering of the National Autonomous University of Mexico (UNAM), the National Council on Science and Technology of Mexico (CONACYT), and the Graduate School of Engineering at UNAM is gratefully acknowledged.


  1. 1.
    CENAPRED (2015) Características e impacto socioeconómico de los huracanes “Stan” y “Willma” en la República Mexicana en el 2005 (in Spanish), Centro Nacional de Prevención de Desastres, Comisión económica para américa latina y el caribe de las naciones unidas, (CEPAL). Accessed 9 Aug 2018
  2. 2.
    Murià-Vila D, Jaimes MA, Pozos-Estrada A, López A, Reinoso E, Chávez MM, Peña F, Sánchez-Sesma J, López O (2018) Effects of hurricane Odile on the infrastructure of Baja California Sur, Mexico. Nat Hazards 91(3):963–981CrossRefGoogle Scholar
  3. 3.
    Haase M, Wong F, Amato A (2007) Double-skin facades for Hong Kong. Surv Built Environ 18:17–32. Accessed 9 Aug 2018
  4. 4.
    Mosqueda G, Porter KA, O’Connor J, McAnany P (2007) Damage to engineered buildings and bridges in the wake of Hurricane Katrina. In: Proceedings SEI structures congressGoogle Scholar
  5. 5.
    Unanwa C, McDonald J, Mehta K, Smith D (2000) The development of wind damage bands for buildings. J Wind Eng Ind Aerodyn 84:119–149CrossRefGoogle Scholar
  6. 6.
    Unanwa C, McDonald J (2000) Building wind damage prediction and mitigation using damage bands. Nat Hazards Rev 1(4):197–203CrossRefGoogle Scholar
  7. 7.
    Vickery PJ, Skerlj PF, Lin J, Twisdale LA, Young MA, Lavelle FM (2006) HAZUS Hurricane model methodology. II: damage and loss estimation. Nat Hazards Rev 7(2):94–103CrossRefGoogle Scholar
  8. 8.
    Stewart MG, Rosowsky DV, Huang Z (2003) Hurricane risk and economic viability of strengthened construction. Nat Hazards Rev 4(1):12–19CrossRefGoogle Scholar
  9. 9.
    Pinelli JP, Simiu E, Gurley K, Subramanian C, Zhang L, Cope A, Filliben J, Hamid S (2004) Hurricane damage prediction model for residential structures. J Struct Eng 130(11):1685–1691CrossRefGoogle Scholar
  10. 10.
    Filliben J, Gurley K, Pinelli JP, Simiu E (2002) Fragility curves, damage matrices, and wind induced loss estimation. In: Proceedings of the third international conference on computer simulation in risk analysis and hazard mitigation, pp 119–126Google Scholar
  11. 11.
    Stubbs ND, Perry D, Lombard P (1995) Cost effectiveness of the new building code for windstorm resistant construction along| the Texas Coast, Report from Texas A&M University, Mechanics and Materials Center to the Texas Department of Insurance.,%20Perry%20Lombard.pdf. Accessed 10 Jan 2017
  12. 12.
    Vanmarcke E, Lin N, Yau SC (2013) Quantitative risk analysis of damage to structures during windstorms. Struct Infrastruct Eng 10(10):1311–1319CrossRefGoogle Scholar
  13. 13.
    Mahesh SS, Lokeswarappa RD, Jun W, Daniel SS (2014) Failure probability of laminated architectural glazing due to combined loading of wind and debris impact. Eng Fail Anal 36:226–242CrossRefGoogle Scholar
  14. 14.
    Minor JE, Beason WL, Harris PL (1978) Designing for windborne missiles in urban areas. J Struct Div l04:1749–1759Google Scholar
  15. 15.
    Wen YK, Kang YJ (2001) Minimum building life-cycle cost design criteria. I: methodology. J Struct Eng 127(3):330–337CrossRefGoogle Scholar
  16. 16.
    Wen YK, Kang YJ (2001) Minimum building life-cycle cost design criteria. II: applications. J Struct Eng 127(3):338–346CrossRefGoogle Scholar
  17. 17.
    Herbin AH, Barbato M (2012) Fragility curves for building envelope components subject to windborne debris impact. J Wind Eng Ind Aerodyn 107–108(1):285–298CrossRefGoogle Scholar
  18. 18.
    Rezaei SN, Chouinard L, Legeron F, Langlois S (2015) Vulnerability analysis of transmission towers subjected to unbalanced ice loads. In: Proceedings of the 12th international conference on applications of statistics and probability in civil engineering. Accessed 10 Jan 2017
  19. 19.
    Porter K, Kennedy R, Bachman R (2007) Creating fragility functions for performance-based earthquake engineering. Earthq Spectra 23(2):471–489CrossRefGoogle Scholar
  20. 20.
    Porter K (2018) A Beginner’s guide to fragility, vulnerability, and risk. University of Colorado Boulder. Accessed 9 Aug 2018
  21. 21.
    Petrini F (2009) A probabilistic approach to performance-based wind engineering (PBWE). Dissertation, Università degli Studi di Roma “La Sapienza”Google Scholar
  22. 22.
    Simiu E, Scanlan RH (1986) Wind effects on structures, 2nd edn. Wiley, New YorkGoogle Scholar
  23. 23.
    CFE (Comisión Federal de Electricidad) (2008) Manual de diseño de obras civiles. Diseño por viento (in Spanish). Comisión Federal de Electricidad, MexicoGoogle Scholar
  24. 24.
    Samaras E, Shinozuka M, Tsurui A (1985) ARMA representation of random processes. J Eng Mech 111(3):449–461CrossRefGoogle Scholar
  25. 25.
    Kaimal JC, Wyngaard JC, Izumi Y, Coté OR (1972) Spectral characteristics of surface-layer turbulence. J R Meteorol Soc 98:563–589CrossRefGoogle Scholar
  26. 26.
    Davenport AG (1967) Gust loading factors. J Struct Eng 93(3):11–34Google Scholar
  27. 27.
    Holmes JD (2015) Wind loading of structures. CR Press, Taylor & Francis, Boca RatonCrossRefGoogle Scholar
  28. 28.
    New York City Codes, Glass and Glazing, Chap. 24. Accessed 10 Jan 2017
  29. 29.
    Kanabolo DC (1984) The strength of new window glass plates using surface characteristics. Dissertation, Texas Tech. UniversityGoogle Scholar
  30. 30.
    Haldimann M (2006) Fracture strength of structural glass elements—analytical and numerical modelling, testing and design. Dissertation, École Polytechnique Fédérale de LausanneGoogle Scholar
  31. 31.
    Gavanski E, Kopp GA (2011) Glass breakage tests under fluctuating wind loads. J Arch Eng 17(1):34–41CrossRefGoogle Scholar
  32. 32.
    Lamela MJ, Ramos A, Fernández P, Fernández-Canteli A, Przybilla C, Huerta C, Pacios A (2014) Probabilistic characterization of glass under different type of testing. Proc Mater Sci 3:2111–2116CrossRefGoogle Scholar
  33. 33.
    Badalassi M, Biolsi L, Royer G, Salvatore W (2014) Safety factors for the structural design of glass. Constr Build Mater 55:114–127CrossRefGoogle Scholar
  34. 34.
    Pisano G, Royer G (2015) The statistical interpretation of the strength of float glass for structural applications. Constr Build Mater 98:741–756CrossRefGoogle Scholar
  35. 35.
    Rubinstein RY (2017) Simulation and the Monte Carlo method. Wiley, HobokenGoogle Scholar
  36. 36.
    Vann WP, McDonald JR (1978) An engineering analysis: mobile homes in windstorms. National Oceanic and Atmospheric Administration, Silver SpringGoogle Scholar
  37. 37.
    FEMA (Federal Emergency Management Agency) (2003) HAZUS-MH MR3 technical manual. Mitigation Division. Accessed 10 Jan 2017
  38. 38.
    Vyzantiadou MA, Avdelas AV (2004) Point fixed glazing systems: technological and morphological aspects. J Constr Steel Res 60:1227–1240CrossRefGoogle Scholar
  39. 39.
    Hong HP, Lind NC (1996) Approximate reliability analysis using normal polynomial and simulation results. Struct Saf 18(4):329–333CrossRefGoogle Scholar

Copyright information

© Iran University of Science and Technology 2018

Authors and Affiliations

  1. 1.Instituto de IngenieríaUniversidad Nacional Autónoma de MéxicoMexicoMexico

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