Citation

Acosta TJS, Galisim JJ, Tan LR, Hernandez JY. Procedia Eng. 2018; 212: 395-402.

Copyright

(Copyright © 2018, Elsevier Publishing)

DOI

10.1016/j.proeng.2018.01.051

PMID

unavailable

Abstract

Last 2016, Typhoon Nina with the international name NOCK-TEN made landfall over Lubang Island. Damage to both infrastructure and agriculture reached ₱6.2 billion as reported by the National Disaster Risk Reduction and Management Council (NDRRMC). Among the infrastructure, an estimated damage of ₱1.1 billion was attributed to the education sector. Damage to non-structural components such as furniture, learning materials, and computer units were estimated to reach at least ₱34.8 million. Aside from functioning as educational facilities, school buildings also serve as evacuation shelters for post disaster recovery operations. Hence strengthening of these structures are of high importance. The Department of Education Bicol Region reported that around 625 schools were totally damaged, 1,082 schools were partially damaged and needed major repairs, and 988 schools needed minor repairs. Most of the damage were observed at the roof coverings, roof frames, wall openings and the walls. Hence these comprise the building components where the damage will be quantified. Field surveys were conducted through region IV and V of the southern part of Luzon, Philippines. From the field survey, damage of every building component are quantified as the percentage of damaged elements to the total number of units of the corresponding building component comprising one building. Each percent damage to building component is converted to an equivalent ratio of the repair cost to the total building construction cost, defined as the damage ratio. Each damage ratio is plotted against the corresponding maximum local wind speed, forming the empirical vulnerability curves. The wind speed data was retrieved from an open source wind speed data map provided by Professor Mark Saunders from the University College of London. Vulnerability curves were curve-fitted using a cumulative lognormal distribution for wind speeds ranging from 96 - 242kph (26 - 68mps).

RESULTS can then be used by the local government in the prioritization of retrofits and the cost-benefit analysis of repairs for different school building designs. The results can also serve as validation for computational vulnerability curves and as a basis for developing a damage prediction tool for school buildings. Applications such as these can be incorporated into pre-disaster mitigation strategies for typhoon prone areas.

Language: en

Keywords

2016 Typhoon Nina; building damage; empirical; field survey; resilience; school buildings; vulnerability curves; wind