Araştırma Makalesi
BibTex RIS Kaynak Göster

Assessment of the Disaster Recovery Progress through Mathematical Modelling

Yıl 2020, Cilt: 31 Sayı: 4, 10113 - 10126, 01.07.2020
https://doi.org/10.18400/tekderg.473099

Öz

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.

Kaynakça

  • [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.

Assessment of the Disaster Recovery Progress through Mathematical Modelling

Yıl 2020, Cilt: 31 Sayı: 4, 10113 - 10126, 01.07.2020
https://doi.org/10.18400/tekderg.473099

Öz

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.

Kaynakça

  • [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.
Toplam 20 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular İnşaat Mühendisliği
Bölüm Makale
Yazarlar

Seyyit Ümit Dikmen Bu kişi benim 0000-0002-4003-1368

Rıfat Akbıyıklı 0000-0003-1584-9384

Murat Sönmez Bu kişi benim 0000-0003-2328-6817

Yayımlanma Tarihi 1 Temmuz 2020
Gönderilme Tarihi 22 Ekim 2018
Yayımlandığı Sayı Yıl 2020 Cilt: 31 Sayı: 4

Kaynak Göster

APA Dikmen, S. . Ü., Akbıyıklı, R., & Sönmez, M. (2020). Assessment of the Disaster Recovery Progress through Mathematical Modelling. Teknik Dergi, 31(4), 10113-10126. https://doi.org/10.18400/tekderg.473099
AMA Dikmen SÜ, Akbıyıklı R, Sönmez M. Assessment of the Disaster Recovery Progress through Mathematical Modelling. Teknik Dergi. Temmuz 2020;31(4):10113-10126. doi:10.18400/tekderg.473099
Chicago Dikmen, Seyyit Ümit, Rıfat Akbıyıklı, ve Murat Sönmez. “Assessment of the Disaster Recovery Progress through Mathematical Modelling”. Teknik Dergi 31, sy. 4 (Temmuz 2020): 10113-26. https://doi.org/10.18400/tekderg.473099.
EndNote Dikmen SÜ, Akbıyıklı R, Sönmez M (01 Temmuz 2020) Assessment of the Disaster Recovery Progress through Mathematical Modelling. Teknik Dergi 31 4 10113–10126.
IEEE S. . Ü. Dikmen, R. Akbıyıklı, ve M. Sönmez, “Assessment of the Disaster Recovery Progress through Mathematical Modelling”, Teknik Dergi, c. 31, sy. 4, ss. 10113–10126, 2020, doi: 10.18400/tekderg.473099.
ISNAD Dikmen, Seyyit Ümit vd. “Assessment of the Disaster Recovery Progress through Mathematical Modelling”. Teknik Dergi 31/4 (Temmuz 2020), 10113-10126. https://doi.org/10.18400/tekderg.473099.
JAMA Dikmen SÜ, Akbıyıklı R, Sönmez M. Assessment of the Disaster Recovery Progress through Mathematical Modelling. Teknik Dergi. 2020;31:10113–10126.
MLA Dikmen, Seyyit Ümit vd. “Assessment of the Disaster Recovery Progress through Mathematical Modelling”. Teknik Dergi, c. 31, sy. 4, 2020, ss. 10113-26, doi:10.18400/tekderg.473099.
Vancouver Dikmen SÜ, Akbıyıklı R, Sönmez M. Assessment of the Disaster Recovery Progress through Mathematical Modelling. Teknik Dergi. 2020;31(4):10113-26.