The authors of this database are Reza Jafarzadeh (University of Auckland), Jason M. Ingham (University of Auckland) and Suzanne Wilkinson (University of Auckland). The database was published at NEEShub on December 09 2013 and has been reproduced here to preserve the data and ensure continued access.
Seismic retrofitting of existing structures is a key issue in any earthquake-prone region when considering the extensive damage and severe economic loss caused by previous strong ground motions (Nuti and Vanzi, 2003). Promoting and enhancing building owners' decisions to adopt earthquake risk preparedness measures are essential activities to reduce fatalities, damage to properties, and economic and social disruption in a seismic disaster (Egbelakin et al., 2011).
A report published by the California Seismic Safety Commission (1999) emphasized how seismic retrofit programs can greatly abate the potential devastating effects of earthquakes. Nevertheless, requiring improvements in a community's existing building stock is a difficult public policy decision, requiring careful engineering and economic analysis along with societal considerations (United States Government Accountability Office (GAO), 2007). People in geographic regions subject to seismic hazards are frequently faced with the decision of whether or not to retrofit existing structures in order to lower their potential losses due to earthquakes.
The cost of seismic retrofit is one of the key factors having a crucial role in making such a decision (FEMA 227, 1992). The database presented herein is a response to the need for a greater amount of reliable data when developing cost estimation models. Using a semi-structured questionnaire, a meticulous data collection effort in Iran led to the development of a large cost database comprised of information from 158 seismic retrofit projects. Each project pertained to a particular earthquake-prone public school building having a framed structure constructed of either reinforced concrete or structural steel. The comprehensive and reliability of the database is well described elsewhere that readers are encouraged to refer to for detailed information (e.g., Jafarzadeh, 2012).
Cost Data and its Determinants
The cost targeted in the database is the seismic retrofit net construction cost (RNCC) which is, by definition, the basic amount to be paid to a contractor(s) for executing seismic retrofit construction work. This amount was calculated by dividing the total seismic retrofit construction cost (SRCC) by cost coefficients considered for construction tender pricing. The RNCC is composed of two components, being the structural cost (SC) and the cover-up cost (CC). The SC arises from seismic retrofitting of elements which together constitute the seismic resisting system of a building (e.g., beams, columns, diaphragms, foundations), whereas the CC is associated with clean-up and construction finishing works. The database also includes the information for fourteen variables which are identified to have an impact on the prediction of the RNCC.
These variables are
- total plan area,
- number of stories,
- compliancy with minimum seismic provisions as prescribed in the first in-place Iranian seismic design code,
- seismicity in terms of the design base acceleration (DBA) of an earthquake with a 475-year return period,
- soil type as determined by the average value of the shear wave velocity (Vs) in the top 30 meters of the site soil profile,
- building plan configuration, (9) building elevation configuration,
- seismic retrofit technique designed to increase seismic resistance,
- structural type in terms of presence or absence of a lateral-force-resisting system in an existing building,
- foundation type,
- floor and roof diaphragm type, and finally
- whether the retrofit solution was extended to the case of non-structural components, particularly infill walls.
For a given school, the data on the RNCC and its constituents, together with the fourteen identified cost governing variables were carefully extracted from the final documents developed by engineering consultants and enacted by the State Organization of School Renovation, Development and Mobilization (SOSRDM) through the seismic retrofit study of that particular school. The cost values in the research database were normalized to the base year 2008 and were expressed in U.S. dollars, using an exchange rate of U.S$1=10,000 Rials.
The importance of the database posted here is more pronounced by recognizing that, in comparison to other construction disciplines, less effort has been devoted in the literature to develop trustworthy seismic retrofit construction cost models on the basis of real historical data. This database was used as the backbone of two recent studies performed by Jafarzadeh et al. (2013a and b) in which parametric and non-parametric seismic retrofit construction cost models were developed using multi-linear regression analysis and artificial neural network technique, respectively. The database will provide value to those attempting to determine key variables that influence seismic retrofit cost, or to those comparing seismic retrofit practices and costs in different areas of the world.
The authors acknowledge the participation of companies and organizations permitting access to the records of school seismic retrofit projects that they have been involved with. With great gratitude, the first author would additionally like to acknowledge the financial support provided by Farasaz Industrial Group Ltd during the full term of this study.
- California Seismic Safety Commission., 1999. >it>Earthquake Risk Management: Mitigation Success Stories.>/it> (SSC Report 99-05). Proposition 122 Seismic Retrofit Practices Improvement Program, Product 2.2 Earthquake Risk Management Tools for Decision-Makers, Prepared by EQE International, Inc. for the California Seismic Safety Commission, Oakland, California, United States.
- Egbelakin, T., Wilkinson, S., Potangaroa, R., Ingham, J. M., 2011. Enhancing Seismic Risk Mitigation Decisions: A Motivational Approach.
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A Benefit-Cost Model for the Seismic Rehabilitation of Hazardous Buildings, Volume I: A User Manual (FEMA 227).Prepared by the VSP Associates, Inc. for FEMA, Washington, D.C., United States.
- Jafarzadeh, R., 2012.
Seismic Retrofit Cost Modelling of Existing Structures.Ph.D. Dissertation, The University of Auckland, Auckland, New Zealand.
- Jafarzadeh, R., Ingham, J. M., Wilkinson, S., Gonzalez, V., and Aghakouchak, A. A., 2013a. Application of Artificial Neural Network Mrthodology for Predicting Seismic Retrofit Construction
Cost. Journal of Construction Engineering and Management,DOI: 10.1061/(ASCE)CO.1943-7862.0000725.
- Jafarzadeh, R., Wilkinson, S., Gonzalez, V., Ingham, J. M., and Ghodrati Amiri, G. R., 2013b. Predicting Seismic Retrofit Construction Cost for Buildings with Framed Structures Using Multi-Linear Regression Analysis.
Journal of Construction Engineering and Management,DOI: 10.1061/(ASCE)CO.1943-7862.0000750.
- Nuti, C., Vanzi, I., 2003. To Retrofit or Not to Retrofit? Engineering Structures, 25(6), 701-711.
United States Government Accountability Office., 2007. Natural Hazard Mitigation: Various Mitigation Efforts Exist, but Federal Efforts Do Not Provide a Comprehensive Strategic Framework. (Report GAO-07-403). Washington, D.C.: Government Accountability Office (GAO) (Available: http://www.gao.gov/new.items/d07403.pdf
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