Abstract
Natural
disasters, especially major earthquakes, cause widespread devastation in the
built environment. Hence, the major component of the recovery in its aftermath constitutes
a chain of projects starting at different times, having different costs and
durations. In this study, the post disaster recovery curve modelled through a
mathematical approach taking into account these properties of the projects. The
approach followed is based on the project S-curve concept that provides the
opportunity to simulate the progress by outlining the project spending. Well-known
mathematical functions are adapted to model the project spending and the
handover processes. Monte Carlo simulation is performed to evaluate the general
behavior of the recovery curve using the model developed. Weibull distribution
is used to generate the model’s parameters. Results of the Monte Carlo
simulation demonstrate that the recovery process exhibits an S-shape, the
duration of initial portion and the slope of the bulk portion being
significantly governed by the level of preparedness of the community.
References
- [1] Bruneau, M., Chang, S., Eguchi, R. Lee, G., O’Rourke, T., Reinhorn, A., Shinozuka,M., Tierney, K., Wallace, W., von Winterfelt, D., (2003). “A framework to Quantitatively Assess and Enhance the Seismic Resilience of Communities”, EERI Spectra Journal, 19, (4), 733-752
- [2] Cimellaro, G.P., Reinhorn, A.M., Bruneau, M. (2010a) “Seismic resilience of a hospital system” Structure and Infrastructure Engineering, Vol. 6, Nos. 1–2, February–April 2010, 127–144
- [3] Cimellaro, G.P., Reinhorn, A.M., Bruneau, M. (2010b) “Framework for analytical quantification of disaster resilience” Engineering Structures 32 (2010) 3639–3649
- [4] Cimellaro, G.P. (2016) “Urban Resilience for Emergency Response and Recovery Fundamental Concepts and Applications” Springer International Publishing Switzerland
- [5] Güler, H.G, Sözdinler, C.Ö., Arikawa, T., Yalçıner, A.C. (2018) “Tsunami AfetiSonrasıYapısalveYapısalOlmayanÖnlemlerveFarkındalıkÇalışmaları: JaponyaÖrneği”, TeknikDergi, 8605-8629
- [6] Şengöz, A., Sucuoğlu, H., (2009) “2007 Deprem Yönetmeliğinde Yer Alan “Mevcut Binaların Değerlendirilmesi” Yöntemlerinin Artıları ve Eksileri”, Teknik Dergi, 4609-4633
- [7] Yanmaz, Ö., Luş, H., (2005) “Yapı Güçlendirme Yöntemlerinin Fayda-Maliyet Analizi”, Teknik Dergi, 3497-3522
- [8] Cimellaro, G.P., Reinhorn, A.M., Bruneau, M. (2006) “Quantification of Seismic Resilience”, Proceedings of the 8th U.S. National Conference on Earthquake Engineering, April 18-22, San Francisco, California, USA
- [9] Kenley, R. (2005), Financing Construction – Cash Flows and Cash Farming, Taylor and Francis e-Library, ISBN 0-203-46739-6.
- [10] Hudson, K. W. and Maunick, J. (1974). Capital expenditure forecasting on health building schemes, or a proposed method of expenditure forecast. Research report, Surveying Division, Research Section, Department of Health and Social Security, UK.
- [11] Hudson, K. W. and Maunick, J. (1974). Capital expenditure forecasting on health building schemes, or a proposed method of expenditure forecast. Research report,
- [12] Peer, S. (1982). ‘Application of cost-flow forecasting models’. Journal of the Construction Division, ASCE, Proc. Paper 17128, 108(CO2): 226–32.
- [13] Kenley, R., and Wilson, O. D. (1986) “A construction project cash flow model-An idiographic approach.” Construction Management and Economics, 4(3), 213–232.
- [14] Miskawi, Z. (1989) “An S-curve equation for project control.” Construction Management and Economics, 7(2), 115–124.
- [15] Khosrowshahi, F. (1991) ‘Simulation of expenditure patterns of construction projects Construction Management and Economics 9(2): 113–132.
- [16] Boussabaine, A. H. and Elhag, T. (1999). ‘Applying fuzzy techniques to cash flow analysis’. Construction Management and Economics 17: 745–755.
- [17] Hudson, K. W. (1978). ‘DHSS expenditure forecasting method’. Chartered Surveyor—Building and Quantity Surveying Quarterly 5: 42–45.
- [18] Ouyang, M., Wang, Z. (2015) “Resilience assessment of interdependent infrastructure systems: With a focus on joint restoration modeling and analysis”, Reliability Engineering and System Safety, 141(2015)74–82, doi.org/10.1016/j.ress.2015.03.011
- [19] Zobel, C.W., (2013) “Analytically comparing disaster recovery following the 2012 derecho”, Proceedings of the 10th International ISCRAM Conference – Baden-Baden, Germany, May 2013 T. Comes, F. Fiedrich, S. Fortier, J. Geldermann and T. Müller, eds.
- [20] Porter, K. (2016) “Damage and Restoration of Water Supply Systems in an Earthquake Sequence”, Structural Engineering and Structural Mechanics Program, Department of Civil Environmental and Architectural Engineering, University of Colorado, SESM 16-02, July 2016.
Abstract
Natural
disasters, especially major earthquakes, cause widespread devastation in the
built environment. Hence, the major component of the recovery in its aftermath constitutes
a chain of projects starting at different times, having different costs and
durations. In this study, the post disaster recovery curve modelled through a
mathematical approach taking into account these properties of the projects. The
approach followed is based on the project S-curve concept that provides the
opportunity to simulate the progress by outlining the project spending. Well-known
mathematical functions are adapted to model the project spending and the
handover processes. Monte Carlo simulation is performed to evaluate the general
behavior of the recovery curve using the model developed. Weibull distribution
is used to generate the model’s parameters. Results of the Monte Carlo
simulation demonstrate that the recovery process exhibits an S-shape, the
duration of initial portion and the slope of the bulk portion being
significantly governed by the level of preparedness of the community.
References
- [1] Bruneau, M., Chang, S., Eguchi, R. Lee, G., O’Rourke, T., Reinhorn, A., Shinozuka,M., Tierney, K., Wallace, W., von Winterfelt, D., (2003). “A framework to Quantitatively Assess and Enhance the Seismic Resilience of Communities”, EERI Spectra Journal, 19, (4), 733-752
- [2] Cimellaro, G.P., Reinhorn, A.M., Bruneau, M. (2010a) “Seismic resilience of a hospital system” Structure and Infrastructure Engineering, Vol. 6, Nos. 1–2, February–April 2010, 127–144
- [3] Cimellaro, G.P., Reinhorn, A.M., Bruneau, M. (2010b) “Framework for analytical quantification of disaster resilience” Engineering Structures 32 (2010) 3639–3649
- [4] Cimellaro, G.P. (2016) “Urban Resilience for Emergency Response and Recovery Fundamental Concepts and Applications” Springer International Publishing Switzerland
- [5] Güler, H.G, Sözdinler, C.Ö., Arikawa, T., Yalçıner, A.C. (2018) “Tsunami AfetiSonrasıYapısalveYapısalOlmayanÖnlemlerveFarkındalıkÇalışmaları: JaponyaÖrneği”, TeknikDergi, 8605-8629
- [6] Şengöz, A., Sucuoğlu, H., (2009) “2007 Deprem Yönetmeliğinde Yer Alan “Mevcut Binaların Değerlendirilmesi” Yöntemlerinin Artıları ve Eksileri”, Teknik Dergi, 4609-4633
- [7] Yanmaz, Ö., Luş, H., (2005) “Yapı Güçlendirme Yöntemlerinin Fayda-Maliyet Analizi”, Teknik Dergi, 3497-3522
- [8] Cimellaro, G.P., Reinhorn, A.M., Bruneau, M. (2006) “Quantification of Seismic Resilience”, Proceedings of the 8th U.S. National Conference on Earthquake Engineering, April 18-22, San Francisco, California, USA
- [9] Kenley, R. (2005), Financing Construction – Cash Flows and Cash Farming, Taylor and Francis e-Library, ISBN 0-203-46739-6.
- [10] Hudson, K. W. and Maunick, J. (1974). Capital expenditure forecasting on health building schemes, or a proposed method of expenditure forecast. Research report, Surveying Division, Research Section, Department of Health and Social Security, UK.
- [11] Hudson, K. W. and Maunick, J. (1974). Capital expenditure forecasting on health building schemes, or a proposed method of expenditure forecast. Research report,
- [12] Peer, S. (1982). ‘Application of cost-flow forecasting models’. Journal of the Construction Division, ASCE, Proc. Paper 17128, 108(CO2): 226–32.
- [13] Kenley, R., and Wilson, O. D. (1986) “A construction project cash flow model-An idiographic approach.” Construction Management and Economics, 4(3), 213–232.
- [14] Miskawi, Z. (1989) “An S-curve equation for project control.” Construction Management and Economics, 7(2), 115–124.
- [15] Khosrowshahi, F. (1991) ‘Simulation of expenditure patterns of construction projects Construction Management and Economics 9(2): 113–132.
- [16] Boussabaine, A. H. and Elhag, T. (1999). ‘Applying fuzzy techniques to cash flow analysis’. Construction Management and Economics 17: 745–755.
- [17] Hudson, K. W. (1978). ‘DHSS expenditure forecasting method’. Chartered Surveyor—Building and Quantity Surveying Quarterly 5: 42–45.
- [18] Ouyang, M., Wang, Z. (2015) “Resilience assessment of interdependent infrastructure systems: With a focus on joint restoration modeling and analysis”, Reliability Engineering and System Safety, 141(2015)74–82, doi.org/10.1016/j.ress.2015.03.011
- [19] Zobel, C.W., (2013) “Analytically comparing disaster recovery following the 2012 derecho”, Proceedings of the 10th International ISCRAM Conference – Baden-Baden, Germany, May 2013 T. Comes, F. Fiedrich, S. Fortier, J. Geldermann and T. Müller, eds.
- [20] Porter, K. (2016) “Damage and Restoration of Water Supply Systems in an Earthquake Sequence”, Structural Engineering and Structural Mechanics Program, Department of Civil Environmental and Architectural Engineering, University of Colorado, SESM 16-02, July 2016.
Details
| Primary Language | English |
|---|---|
| Subjects | Civil Engineering |
| Journal Section | Articles |
| Authors | |
| Publication Date | July 1, 2020 |
| Submission Date | October 22, 2018 |
| Published in Issue | Year 2020 Volume: 31 Issue: 4 |
