IDEAS home Printed from https://ideas.repec.org/a/gam/jrisks/v9y2021i7p129-d589433.html
   My bibliography  Save this article

Reliability of Seismic Performance Assessments for Individual Buildings and Portfolios

Author

Listed:
  • Charles C. Thiel

    (Telesis Engineers, Inc., 80A Blake St., San Francisco, CA 94118, USA)

  • Theodore C. Zsutty

    (Consulting Engineer, 1579 Peregrino Way, San Jose, CA 95125, USA)

  • Yajie J. Lee

    (ImageCat, Inc., 400 Oceangate, Suite 1050, Long Beach, CA 90802, USA)

Abstract

Seismic performance and loss assessments are required in areas of Insurance, Finance and Public Policy. Providers are Structural Engineers and Risk Management Firms. There are no current procedures to evaluate the epistemic and aleatory uncertainties for such assessments. The essential issue is whether or not there is sufficient reliability in the result to use the result as the basis for risk management decisions and actions. For a single building this may be whether or not a prescribed earthquake performance level is met, life safety or if a portfolio’s vulnerability level is acceptable, whether the. loss for a given time period is less than a stated value. A method based in part on Federal Emergency Management Agency P-695, is developed for evaluating the reliability of performance and/or loss assessments for both individual and portfolios of buildings. Consideration is given to how well the building investigation and corresponding evaluation process have been performed, the qualifications of the person(s) doing the assessment, the thoroughness of the building evaluation, the technical validity of the assessment procedure or model and what computational reliabilities are presented. The method characterizes the uncertainty of each component of the assessment procedure for each building by qualitative determined assignments. The resulting reliability measure is likely to be most useful for determining whether/or not a building has acceptable life safety performance, or if a portfolio has an acceptably low loss risk over a given period of time. In both cases, the reliability must either be sufficient to warrant action, or serve to indicate need for improved assessment.

Suggested Citation

  • Charles C. Thiel & Theodore C. Zsutty & Yajie J. Lee, 2021. "Reliability of Seismic Performance Assessments for Individual Buildings and Portfolios," Risks, MDPI, vol. 9(7), pages 1-46, July.
  • Handle: RePEc:gam:jrisks:v:9:y:2021:i:7:p:129-:d:589433
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-9091/9/7/129/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2227-9091/9/7/129/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Enrico Zio, 2013. "Monte Carlo Simulation: The Method," Springer Series in Reliability Engineering, in: The Monte Carlo Simulation Method for System Reliability and Risk Analysis, edition 127, chapter 0, pages 19-58, Springer.
    2. Enrico Zio, 2013. "The Monte Carlo Simulation Method for System Reliability and Risk Analysis," Springer Series in Reliability Engineering, Springer, edition 127, number 978-1-4471-4588-2, April.
    3. Enrico Zio, 2013. "System Reliability and Risk Analysis by Monte Carlo Simulation," Springer Series in Reliability Engineering, in: The Monte Carlo Simulation Method for System Reliability and Risk Analysis, edition 127, chapter 0, pages 59-81, Springer.
    4. Enrico Zio, 2013. "System Reliability and Risk Analysis," Springer Series in Reliability Engineering, in: The Monte Carlo Simulation Method for System Reliability and Risk Analysis, edition 127, chapter 0, pages 7-17, Springer.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Michele Compare & Francesco Di Maio & Enrico Zio & Fausto Carlevaro & Sara Mattafirri, 2016. "Improving scheduled maintenance by missing data reconstruction: A double-loop Monte Carlo approach," Journal of Risk and Reliability, , vol. 230(5), pages 502-511, October.
    2. Di Maio, Francesco & Pettorossi, Chiara & Zio, Enrico, 2023. "Entropy-driven Monte Carlo simulation method for approximating the survival signature of complex infrastructures," Reliability Engineering and System Safety, Elsevier, vol. 231(C).
    3. Wang, Fan & Li, Heng, 2018. "System reliability under prescribed marginals and correlations: Are we correct about the effect of correlations?," Reliability Engineering and System Safety, Elsevier, vol. 173(C), pages 94-104.
    4. Tito G. Amaral & Vitor Fernão Pires & Armando Cordeiro & Daniel Foito & João F. Martins & Julia Yamnenko & Tetyana Tereschenko & Liudmyla Laikova & Ihor Fedin, 2023. "Incipient Fault Diagnosis of a Grid-Connected T-Type Multilevel Inverter Using Multilayer Perceptron and Walsh Transform," Energies, MDPI, vol. 16(6), pages 1-18, March.
    5. Penttinen, Jussi-Pekka & Niemi, Arto & Gutleber, Johannes & Koskinen, Kari T. & Coatanéa, Eric & Laitinen, Jouko, 2019. "An open modelling approach for availability and reliability of systems," Reliability Engineering and System Safety, Elsevier, vol. 183(C), pages 387-399.
    6. Rocco, Claudio M. & Moronta, José & Ramirez-Marquez, José E. & Barker, Kash, 2017. "Effects of multi-state links in network community detection," Reliability Engineering and System Safety, Elsevier, vol. 163(C), pages 46-56.
    7. Babykina, Génia & Brînzei, Nicolae & Aubry, Jean-François & Deleuze, Gilles, 2016. "Modeling and simulation of a controlled steam generator in the context of dynamic reliability using a Stochastic Hybrid Automaton," Reliability Engineering and System Safety, Elsevier, vol. 152(C), pages 115-136.
    8. Compare, Michele & Bellani, Luca & Zio, Enrico, 2017. "Reliability model of a component equipped with PHM capabilities," Reliability Engineering and System Safety, Elsevier, vol. 168(C), pages 4-11.
    9. Gascard, Eric & Simeu-Abazi, Zineb, 2018. "Quantitative Analysis of Dynamic Fault Trees by means of Monte Carlo Simulations: Event-Driven Simulation Approach," Reliability Engineering and System Safety, Elsevier, vol. 180(C), pages 487-504.
    10. Shiyu Chen & Wei Wang & Enrico Zio, 2021. "A Simulation-Based Multi-Objective Optimization Framework for the Production Planning in Energy Supply Chains," Energies, MDPI, vol. 14(9), pages 1-27, May.
    11. Kim, Hyeonmin & Kim, Jung Taek & Heo, Gyunyoung, 2018. "Failure rate updates using condition-based prognostics in probabilistic safety assessments," Reliability Engineering and System Safety, Elsevier, vol. 175(C), pages 225-233.
    12. Martin Folch-Calvo & Francisco Brocal-Fernández & Cristina González-Gaya & Miguel A. Sebastián, 2020. "Analysis and Characterization of Risk Methodologies Applied to Industrial Parks," Sustainability, MDPI, vol. 12(18), pages 1-35, September.
    13. Cadini, F. & Gioletta, A., 2016. "A Bayesian Monte Carlo-based algorithm for the estimation of small failure probabilities of systems affected by uncertainties," Reliability Engineering and System Safety, Elsevier, vol. 153(C), pages 15-27.
    14. Turati, Pietro & Pedroni, Nicola & Zio, Enrico, 2016. "Advanced RESTART method for the estimation of the probability of failure of highly reliable hybrid dynamic systems," Reliability Engineering and System Safety, Elsevier, vol. 154(C), pages 117-126.
    15. Sergio Copiello, 2020. "Business as Usual with Article Processing Charges in the Transition towards OA Publishing: A Case Study Based on Elsevier," Publications, MDPI, vol. 8(1), pages 1-14, January.
    16. Shafiee, Mahmood & Finkelstein, Maxim & Bérenguer, Christophe, 2015. "An opportunistic condition-based maintenance policy for offshore wind turbine blades subjected to degradation and environmental shocks," Reliability Engineering and System Safety, Elsevier, vol. 142(C), pages 463-471.
    17. Su, Huai & Zhang, Jinjun & Zio, Enrico & Yang, Nan & Li, Xueyi & Zhang, Zongjie, 2018. "An integrated systemic method for supply reliability assessment of natural gas pipeline networks," Applied Energy, Elsevier, vol. 209(C), pages 489-501.
    18. Naseri, Masoud & Baraldi, Piero & Compare, Michele & Zio, Enrico, 2016. "Availability assessment of oil and gas processing plants operating under dynamic Arctic weather conditions," Reliability Engineering and System Safety, Elsevier, vol. 152(C), pages 66-82.
    19. Michel Batteux & Tatiana Prosvirnova & Antoine Rauzy, 2017. "AltaRica 3.0 assertions: The whys and wherefores," Journal of Risk and Reliability, , vol. 231(6), pages 691-700, December.
    20. Mohammad Nadjafi & Mohammad Ali Farsi & Hossein Jabbari, 2017. "Reliability analysis of multi-state emergency detection system using simulation approach based on fuzzy failure rate," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 8(3), pages 532-541, September.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jrisks:v:9:y:2021:i:7:p:129-:d:589433. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.