RCOV.shingles - Shingles
The following models are available:
RCOV.shingles.001a | Roof Cover - Asphalt Shingles with standard construction and nail pattern
Suggested Block Size: 1 EA
Gurley, K., J. P. Pinelli, C. Subramanian, A. Cope, L. Zhang, J. Murphree, A. Artiles, P. Misra, S. Gulati, and E. Simiu. 2005. Florida Public Hurricane Loss Projection Model engineering team final report volume II: Predicting the vulnerability of typical residential buildings to hurricane damage. Technical report. Florida International University: International Hurricane Research Center.
Peng, J. 2013. Modeling natural disaster risk management: Integrating the roles of insurance and retrofit and multiple stakeholder perspectives. Ph.D. United States – Delaware: University of Delaware.
RCOV.shingles.001b | Roof Cover - Asphalt Shingles with standard construction and nail pattern
Suggested Block Size: 1 EA
Gurley, K., J. P. Pinelli, C. Subramanian, A. Cope, L. Zhang, J. Murphree, A. Artiles, P. Misra, S. Gulati, and E. Simiu. 2005. Florida Public Hurricane Loss Projection Model engineering team final report volume II: Predicting the vulnerability of typical residential buildings to hurricane damage. Technical report. Florida International University: International Hurricane Research Center.
Jain, A., A. A. Bhusar, D. B. Roueche, and D. O. Prevatt. 2020. Engineering-Based Tornado Damage Assessment: Numerical Tool for Assessing Tornado Vulnerability of Residential Structures. Front. Built Environ., 6. Frontiers. https://doi.org/10.3389/fbuil.2020.00089.
RCOV.shingles.002a | Roof Cover - Shingles with high-wind construction and nail pattern
Suggested Block Size: 1 EA
Gurley, K., J. P. Pinelli, C. Subramanian, A. Cope, L. Zhang, J. Murphree, A. Artiles, P. Misra, S. Gulati, and E. Simiu. 2005. Florida Public Hurricane Loss Projection Model engineering team final report volume II: Predicting the vulnerability of typical residential buildings to hurricane damage. Technical report. Florida International University: International Hurricane Research Center.
Grayson, J. M., W. Pang, and S. Schiff. 2013. Building envelope failure assessment framework for residential communities subjected to hurricanes. Engineering Structures, 51: 245–258. https://doi.org/10.1016/j.engstruct.2013.01.027.
RCOV.shingles.002b | Roof Cover - Shingles with high-wind construction and nail pattern
Suggested Block Size: 1 EA
Gurley, K., J. P. Pinelli, C. Subramanian, A. Cope, L. Zhang, J. Murphree, A. Artiles, P. Misra, S. Gulati, and E. Simiu. 2005. Florida Public Hurricane Loss Projection Model engineering team final report volume II: Predicting the vulnerability of typical residential buildings to hurricane damage. Technical report. Florida International University: International Hurricane Research Center.
Kakareko, G., S. Jung, S. Mishra, and O. A. Vanli. 2021. Bayesian capacity model for hurricane vulnerability estimation. Structure and Infrastructure Engineering, 17 (5): 638–648. Taylor & Francis. https://doi.org/10.1080/15732479.2020.1760318.
RCOV.shingles.002c | Roof Cover - Shingles with high-wind construction and nail pattern
Suggested Block Size: 1 EA
Gurley, K., J. P. Pinelli, C. Subramanian, A. Cope, L. Zhang, J. Murphree, A. Artiles, P. Misra, S. Gulati, and E. Simiu. 2005. Florida Public Hurricane Loss Projection Model engineering team final report volume II: Predicting the vulnerability of typical residential buildings to hurricane damage. Technical report. Florida International University: International Hurricane Research Center.
Peng, J. 2013. Modeling natural disaster risk management: Integrating the roles of insurance and retrofit and multiple stakeholder perspectives. Ph.D. United States – Delaware: University of Delaware.