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CEDLES: a framework for plugin-based applications for earthquake risk prediction and loss assessment

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Abstract

To evaluate the seismic risk and loss caused by an earthquake, many earthquake disaster loss assessment softwares have been developed. However, it is difficult to apply one earthquake disaster loss assessment software for all countries due to the different characteristics of seismic, architectural and economic of various countries. China is one of the high-seismicity regions in the world. Thus, it is imperative to develop an earthquake disaster loss assessment software suitable for China. In this paper, a novel framework for plugin-based applications named CEDLES is designed considering the scalability of the software. The features provided by CEDLES to ease the development of extensible applications are described. This framework includes a startup project, a common plugin framework base, a geographic information system plugin framework base, and a plugin manager project. These utilities allow rapid development and integration in which robustness and quality play a fundamental role. A first prototype, Earthquake Risk Prediction and Loss Assessment System (ERPLAS) is designed and implemented. It integrates the plugins of seismic hazard analysis, structural damage analysis, loss assessment, earthquake insurance rate estimation, and benefit–cost analysis of building retrofit, especially for China. ERPLAS is applied to Baqiao District in Xi’an and the estimation results are displayed and debated, which verify the practicality of ERPLAS and the feasibility and facility of CEDLES framework.

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References

  • Allen T, Earle P, Wald D, Jaiswal K, Hearne M, Marano K, Hotovec A (2009) Tools and datasets of the Prompt Assessment of Global Earthquakes for Response (PAGER) System. Commonw gov Aust, Canberra

    Google Scholar 

  • Apache log4net (2018) http://logging.apache.org/log4net/. Accessed 2 Jun 2018

  • ArcSDE (2018) https://en.wikipedia.org/wiki/ArcSDE. Accessed 2 Jun 2018

  • AvalonDock (2018) https://archive.codeplex.com/?p=avalondock. Accessed 2 Jun 2018

  • Brzev S, Scawthorn C, Charleson AW, Jaiswal K (2016) GEM Basic Building Taxonomy (Version 1.0). https://pubs.er.usgs.gov/publication/70045104. Accessed 16 Mar 2018

  • CAPRA (2019) https://ecapra.org/. Accessed 4 Jan 2019

  • Chatley R, Eisenbach S, Magee J (2003) Modelling a framework for plugins. In: Proceedings of the workshop on specification and verification of component-based systems, ser. Technical Report 03-11. Iowa State University, pp 49–57

  • Chen HF (2012) General development and design of HAZ-China earthquake disaster loss estimation system. Dissertation, Institute of engineering mechanics, China Earthquake Administration Harbin, China (in Chinese)

  • Chen XZ (2016) HAZChina Rapid earthquake loss assessment technical research and system development. Dissertation, Institute of engineering mechanics, China Earthquake Administration Harbin, China (in Chinese)

  • Chen DM, Duan R (2013) Amplification effects of site conditions on ground peak acceleration. J Earthq Eng Eng Vib 33(1):24–30 (in Chinese)

    Google Scholar 

  • Corbane C, Hancilar U, Ehrlich D, De Groeve T (2017) Pan-European seismic risk assessment: a proof of concept using the Earthquake Loss Estimation Routine (ELER). Bull Earthq Eng 15(3):1057–1083

    Article  Google Scholar 

  • Deniz A, Yucemen MS (2009) Assessment of earthquake rates for the Turkish Catastrophe Insurance Pool. Georisk 3(2):67–74

    Google Scholar 

  • DLL (2018) https://en.wikipedia.org/wiki/Dynamic-link_library. Accessed 9 Oct 2018

  • Durukal E, Erdik M, Sesetyan K, Demircioglu MB, Fahjan Y, Siyahi B (2005) Building loss estimation for earthquake insurance pricing. In: Proceedings of the 1906 earthquake conference, CD, paper no: 1311, EERI, Oakland

  • Eclipse (2018) https://en.wikipedia.org/wiki/Eclipse. Accessed 9 Oct 2018

  • Eclipse RCP (2019) https://wiki.eclipse.org/Rich_Client_Platform. Accessed 3 Jan 2019

  • ELER (2019) http://www.koeri.boun.edu.tr/news/neries%20eler%20v3.1_16_177.depmuh. Accessed 6 Jan 2019

  • Eren C, Luş H (2015) A risk based PML estimation method for single-storey reinforced concrete industrial buildings and its impact on earthquake insurance rates. Bull Earthq Eng 13(7):2169–2195

    Article  Google Scholar 

  • Federal Emergency Management Agency (FEMA) (2008) HAZUS-MH estimated annualized earthquake losses for the United States (FEMA 366). Technical report, Washington, DC

    Google Scholar 

  • Federal Emergency Management Agency (FEMA) (2012a) Multi-Hazard loss estimation methodology Hazus-MH 2.1, Advanced Engineering Building Module (AEBM) Technical and User’s Manual. Washington

  • Federal Emergency Management Agency (FEMA) (2012b) Seismic performance assessment of buildings volume 1—methodology, Technical report FEMA-P58. Washington

  • Federal Emergency Management Agency (FEMA) (2012c) Seismic performance assessment of buildings volume 2—implementation guide, Technical report FEMA-P58. Washington

  • Federal Emergency Management Agency (FEMA) (2013) Multi-hazard loss estimation methodology—earthquake model, Hazus-MH 2.1, Technical Manual. Washington

  • Hu YX (1990) Comprehensive probability method for the seismic risk analysis. Earthquake Press, Beijing (in Chinese)

    Google Scholar 

  • Incardona MF, Bourenkov GP, Levik K, Pieritz RA, Popov AN, Svensson O (2010) EDNA: a framework for plugin-based applications applied to X-ray experiment online data analysis. J Synchrotron Radiat 16(6):872–879

    Article  Google Scholar 

  • Kappos AJ, Dimitrakopoulos EG (2008) Feasibility of pre-earthquake strengthening of buildings based on cost–benefit and life-cycle cost analysis, with the aid of fragility curves. Nat Hazards 45(1):33–54

    Article  Google Scholar 

  • Karimzadeh S, Miyajima M, Hassanzadeh R, Amiraslanzadeh R, Kamel B (2014) A GIS-based seismic hazard, building vulnerability and human loss assessment for the earthquake scenario in Tabriz. Soil Dyn Earthq Eng 66:263–280

    Article  Google Scholar 

  • Kishor J, David W, Keith P (2010) A global building inventory for earthquake loss estimation and risk management. Earthq Spectra 26(3):731–748

    Article  Google Scholar 

  • Knox S, Meier P, Yoon J, Harou JJ (2018) A python framework for multi-agent simulation of networked resource systems. Environ Model Softw 103:16–28

    Article  Google Scholar 

  • Knublauch H, Fergerson RW, Noy NF, and Musen MA (2004) The Protégé OWL plugin: An open development environment for semantic web applications. In: Third international semantic web conference, Hiroshima, Japan

  • Liu JW, Wang ZM, Xie FR, Lv Y (2013) Seismic hazard assessment for greater North China from historical intensity observations. Eng Geol 164:117–130

    Article  Google Scholar 

  • Long L, Sun LF, Zheng SS et al (2016) Study on field collection system for urban building information based on Android. Technol Earthq Disaster Prev 11(3):682–691 (in Chinese)

    Google Scholar 

  • Maas SA, Labelle SA, Ateshian GA, Weiss JA (2018) A plugin framework for extending the simulation capabilities of FEBio. Biophys J 115(9):1630–1637

    Article  Google Scholar 

  • MAEviz (2018) http://rcp.ncsa.uiuc.edu/maeviz/about.html. Accessed 18 Jun 2018

  • Mazumder RK, Salman AM (2019) Seismic damage assessment using RADIUS and GIS: a case study of Sylhet City, Bangladesh. Int J Disaster Risk Reduct 34:243–254

    Article  Google Scholar 

  • Model View ViewModel (2018) http://en.wikipedia.org/wiki/Model_View_ViewModel. Accessed 5 Aug 2018

  • Molina S, Lang DH, Lindholm CD (2010) SELENA-An open-source tool for seismic risk and loss assessment using a logic tree computation procedure. Comput Geosci 36:257–269

    Article  Google Scholar 

  • National Standard of People’s Republic of China (NSPRC) (2010) Code for seismic design of buildings (GB 50011-2010). Architecture & Building Press, Beijing (in Chinese)

    Google Scholar 

  • National Standard of People’s Republic of China (NSPRC) (2015) Seismic ground motion parameter zonation map of China, GB 18306-2015. China Standard Publishing House, Beijing (in Chinese)

    Google Scholar 

  • Oracle Database (2018) https://en.wikipedia.org/wiki/Oracle_Database. Accessed 12 Aug 2018

  • OSRE (2019) https://sourceforge.net/projects/osre/. Accessed 1 Jan 2019

  • Pitilakis K, Argyroudis S (2014) Introduction to the applications of the SYNER-G methodology and tools. Springer, Enschede

    Book  Google Scholar 

  • Rao AS (2014) Structural deterioration and time-dependent seismic risk analysis. Dissertation, Stanford University

  • Reinoso E, Ordaz M, Cardona OD, Bernal G A (2018) After 10 years of CAPRA. In: Proceedings of the 16th European conference on earthquake engineering

  • SELENA (2019) https://www.norsar.no/search/?categoryID=294&q=selena. Accessed 4 Jan 2019

  • SharpDevelop (2018) http://www.icsharpcode.net/OpenSource/SD/Default.aspx. Accessed 12 Aug 2018

  • Strasser FO, Bommer JJ, Sesetyan K et al (2008) A Comparative study of European earthquake loss estimation tools for a scenario in Istanbul. J Earthq Eng 12(1):246–256

    Article  Google Scholar 

  • Sun BT, Chen HF (2009) Urban building loss assessment method considering the decoration damage due to earthquake. J Earthq Eng Eng Vib 29(5):164–169 (in Chinese)

    Google Scholar 

  • Valcárcel JA, Mora MG, Cardona OD, Pujades LG, Barbat AH (2013) Methodology and applications for the Benefit Cost Analysis of the seismic risk reduction of building portfolios at broad scale. Nat Hazards 69(1):845–868

    Article  Google Scholar 

  • Wang JP, Taheri H (2014) Seismic hazard assessment of the Tehran region. Nat Hazards Rev 15:121–127

    Article  Google Scholar 

  • Xu Z, Lu XZ, Law KH (2016) A computational framework for regional seismic simulation of buildings with multiple fidelity models. Adv Eng Softw 99:100–110

    Article  Google Scholar 

  • Xu Z, Lu XZ, Cheng QL et al (2018) A smart phone-based system for post-earthquake investigations of building damage. Int J Disaster Risk Reduct 27:214–222

    Article  Google Scholar 

  • Yeh CH, Loh CH, Tsai KC (2006) Overview of Taiwan earthquake loss estimation system. Nat Hazards 37(1–2):23–37

    Article  Google Scholar 

  • Yu YX, Wang SY (2003) Attenuation relations for horizontal peak ground acceleration and response spectrum in eastern and western China. Technol Earthq Disaster Prev 1(3):206–217 (in Chinese)

    Google Scholar 

  • Yucemen MS (2005) Probabilistic assessment of earthquake insurance rates for Turkey. Nat Hazards 35:291–313

    Article  Google Scholar 

  • Yucemen MS, Yilmaz C, Erdik M (2008) Probabilistic assessment of earthquake insurance rates for important structures: application to Gumusova-Gerede motorway. Struct Saf 30:420–435

    Article  Google Scholar 

Download references

Acknowledgements

The authors are grateful for the financial support received from the National Key R&D Program of China (Grant No. 2019YFC1509302), the Natural Science Foundation of China (Grant No. 51678475), the Science and Technology Plan Project in Xi'an, Shannxi, China (Grant No. 2019113813CXSF016SF026), and the Industrialization Projects of Education Department of Shaanxi Provincial Government of China (Grant No. 18JC020).

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Authors and Affiliations

  1. School of Civil Engineering, Xi’an University of Architecture and Technology, Xi’an, 710055, Shaanxi Province, China

    Li Long, Shansuo Zheng, Yixin Zhang, Longfei Sun, Yan Zhou & Liguo Dong

  2. Country Garden Company, Xi’an, 710055, Shaanxi Province, China

    Longfei Sun

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  1. Li Long
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  2. Shansuo Zheng
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  3. Yixin Zhang
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  4. Longfei Sun
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Correspondence to Shansuo Zheng.

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Long, L., Zheng, S., Zhang, Y. et al. CEDLES: a framework for plugin-based applications for earthquake risk prediction and loss assessment. Nat Hazards 103, 531–556 (2020). https://doi.org/10.1007/s11069-020-03999-6

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