Hurricane Damage Prediction Model for Residential Structures
by Jean-Paul Pinelli, (Assoc. Prof., Dept. of Civ. Engrg., FLorida Inst. of Technol., 150 West Univ. Blvd., Melbourne, FL 32901-6975. E-mail: pinelli@fit.edu), Emil Simiu, (NIST Fellow, Bldg. and Fire Res. Lab., Bldg. 226, Room B264, Natl. Inst. of Standard and Technol., Gaithersburg, MD 20899), Kurt Gurley, (Assoc. Prof., Dept. of Civ. and Coastal Engrg., Univ. of Florida, P.O. Box 116580, Gainesville, FL 32611-6580. E-mail: kgurl@ce.ufl.edu), Chelakara Subramanian, (Assoc. Prof., Dept. of Mech. and Aerospace Engrg., Florida Inst. of Technol., 150 West Univ. Blvd., Melbourne, FL 32901. E-mail: subraman@fit.edu), Liang Zhang, (Grad. Res. Asst., Dept. of Civ. Engrg., Florida Inst. of Technol., 150 West Univ. Blvd., Melbourne, FL 32901-6975. E-mail: lzhang@fit.edu), Anne Cope, (Grad. Res. Asst., Dept. of Civ. and Coastal Engrg., Univ. of Florida, P.O. Box 116580, 124 Yon Hall, Gainesville, FL 32611-6580. E-mail: copead@ufl.edu), James J. Filliben, (Group Leader, Statistical Engrg. Div., Information Technol. Lab., NIST North, Room 353, Natl. Inst. of Standard and Technol., Gaithersburg, MD 20899-0001), and Shahid Hamid, (Assoc. Prof., Dept. of Finance, Florida Intl. Univ., Miami, FL 33199)
Journal of Structural Engineering, Vol. 130, No. 11, November 2004, pp. 1685-1691, (doi: http://dx.doi.org/10.1061/(ASCE)0733-9445(2004)130:11(1685))
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| Document type: |
Journal Paper |
| Abstract: |
The paper reports progress in the development of a practical probabilistic model for the estimation of expected annual damage induced by hurricane winds in residential structures. The estimation of the damage is accomplished in several steps. First, basic damage modes for components of specific building types are defined. Second, the damage modes are combined in possible damage states, whose probabilities of occurrence are calculated as functions of wind speeds from Monte Carlo simulations conducted on engineering numerical models of typical houses. The paper describes the conceptual framework for the proposed model, and illustrates its application for a specific building type with hypothetical probabilistic input. Actual probabilistic input must be based on laboratory studies, postdamage surveys, insurance claims data, engineering analyses and judgment, and Monte Carlo simulation methods. The proposed component-based model is flexible and transparent. It is therefore capable of being readily scrutinized. The model can be used in conjunction with historical loss data, to which it can readily be calibrated. |
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