The Role of Seismic Structural Health Monitoring (S2HM) in the Assessment of the Delay Time after Earthquakes
Abstract
:1. Introduction
2. Resilience
3. Seismic Resilience (SR)
- is the time of occurrence of the earthquake E;
- is the time at which the repair process starts;
- is the functionality just after the earthquake;
- L are the losses (calculated as L 1 ;
- RT is the repair time necessary to recover the original functionality (expressed in Crew Working Days, CWD);
- is the recovery function describing the recovery process.
- In this regard, the delay time is calculated as .
4. The Role of S2HM on SR
Case Study
5. Multidimensional Definition of SR
- (1)
- The loss model describes the reduction in functionality due to the initial impact of an event on a system. The quantification of the losses that are at the base of this model may be a challenging issue since several typologies of losses need to be considered, such as direct and indirect losses, as described in [20].
- (2)
- The recovery model aims to assess the ability of the system to recover from the impact by considering the process of recovery that is generally represented with an analytical formulation. Such formulation needs to describe several variables that are challenging to be defined and generally depend on the preparedness of a community, the level of technological know-how, and the distribution of economic funds for the recovery process.
6. Discussion
7. Conclusions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
- Cimellaro, G.P.; Reinhorn, A.M.; Bruneau, M. Seismic resilience of a hospital system. Struct. Infrastruct. Eng. 2010, 6, 127–144. [Google Scholar] [CrossRef]
- Bruneau, M.; Chang, S.E.; Eguchi, R.T.; Lee, G.C.; O’Rourke, T.D.; Reinhorn, A.M.; Shinozuka, M.; Tierney, K.; Wallace, W.A.; Von Winterfeldt, D. A Framework to Quantitatively Assess and Enhance the Seismic Resilience of Communities. Earthq. Spectra 2003, 19, 733–752. [Google Scholar] [CrossRef] [Green Version]
- Elms, D.G. Improving Community Resilience to Natural Events. Civ. Eng. Environ. Syst. 2015, 32, 77–89. [Google Scholar] [CrossRef]
- Almufti, I.; Willford, M. The REDiTM Rating System: Resilience-Based Earthquake Design Initiative for the Next Generation of Buildings; Arup Co.: London, UK, 2013. [Google Scholar] [CrossRef]
- Molina Hutt, C.; Almufti, I.; Willford, M.; Deierlein, G. Seismic loss and downtime assessment of existing tall steel-framed buildings and strategies for increased resilience. J. Struct. Eng. 2016, 142, C4015005. [Google Scholar] [CrossRef]
- Giordano, P.F.; Iacovino, C.; Quqa, S.; Limongelli, M.P. The value of seismic structural health monitoring for post-earthquake building evacuation. Bull. Earthq. Eng. 2022, 20, 4367–4393. [Google Scholar] [CrossRef]
- Cardone, D.; Flora, A.; De Luca, P.M.; Martoccia, A. Estimating direct and indirect losses due to earthquake damage in residential RC buildings. Soil Dyn. Earthq Eng. 2019, 126, 105801. [Google Scholar] [CrossRef]
- Comerio, M.C. Estimating downtime in loss modeling. Earthq. Spectra 2006, 22, 349–365. [Google Scholar] [CrossRef]
- Burton, H.V.; Deierlein, G.; Lallemant, D.; Lin, T. Framework for Incorporating Probabilistic Building Performance in the Assessment of Community Seismic Resilience. J. Struct. Eng. 2016, 142, C4015007. [Google Scholar] [CrossRef] [Green Version]
- Kolozvari, T. Methodology for developing practical recovery-based design requirements for buildings. Eng. Struct. 2023, 274, 115102. [Google Scholar] [CrossRef]
- Cook, D.T.; Liel, A.B.; Haselton, C.B.; Koliou, M. A framework for operationalizing the assessment of post-earthquake Functional recovery of buildings. Earthq. Spectra 2022, 38, 1972–2007. [Google Scholar] [CrossRef]
- Dahlhamer, J.M.; Tierney, K.J. Rebounding from disruptive events: Business recovery following the Northridge earthquake. Sociol. Spectr. 1998, 18, 121–141. [Google Scholar] [CrossRef] [Green Version]
- Aghababaei, M.; Koliou, M.; Pilkington, S.; Mahmoud, H.; Van de Lindt, J.W.; Curtis, A.; Smith, S.; Ajayakumar, J.; Watson, M. Validation of time-dependent repair recovery of the building stock following the 2011 Joplin Tornado. Nat. Hazards Rev. 2020, 21, 04020038. [Google Scholar] [CrossRef]
- Elms, D. The systems stance. Civ. Eng. Environ. Syst. 2020, 37, 166–182. [Google Scholar] [CrossRef]
- Marquis, F.; Kim, J.J.; Elwood, K.J.; Chang, S.E. Understanding post-earthquake decisions on multi-storey concrete buildings in Christchurch, New Zealand. Bull. Earthq. Eng. 2017, 15, 731–758. [Google Scholar] [CrossRef]
- Burton, H.V.; Kang, H.; Miles, S.B.; Nejat, A.; Yi, Z. A framework and case study for integrating household decision-making into post-earthquake recovery models. Int. J. Disaster Risk Reduct. 2019, 37, 101167. [Google Scholar] [CrossRef]
- Cremen, G.; Seville, E.; Baker, J.W. Modeling post-earthquake business recovery time: An analytical framework. Int. J. Disaster Risk Reduct. 2019, 42, 101328. [Google Scholar] [CrossRef]
- Han, R.; Li, Y.; van de Lindt, J. Seismic Loss Estimation with Consideration of Aftershock Hazard and Post-Quake Decisions. ASCE-ASME J. Risk Uncertain. Eng. Syst. Part A Civ. Eng. 2016, 2, 04016005. [Google Scholar] [CrossRef]
- Thöns, S.; Stewart, M.G. On the cost-efficiency, significance and effectiveness of terrorism risk reduction strategies for buildings. Struct. Saf. 2020, 85, 101957. [Google Scholar] [CrossRef]
- Forcellini, D. A new methodology to assess indirect losses in bridges subjected to multiple hazards. Innov. Infrastruct. Solut. 2019, 4, 1–9. [Google Scholar] [CrossRef]
- Forcellini, D. A resilience-based methodology to assess soil structure interaction on a benchmark bridge. Infrastructures 2020, 5, 90. [Google Scholar] [CrossRef]
- Forcellini, D. A Novel Methodology to Assess Seismic Resilience (SR) of Interconnected Infrastructures. Appl. Sci. 2022, 12, 12975. [Google Scholar] [CrossRef]
- Wildavsky, A. Searching for Safety; Technical report; Transaction Publishers: London, UK, 1988; Volume 10. [Google Scholar]
- Hoiling, C.; Schindler, D.; Walker, B.W. Roughgarden 1997, Biodiversity in the Functioning of Ecosystems: An Ecological Synthesis, Biodiversity Loss: Economic and Ecological Issues; Cambridge University Press: Cambridge, UK, 1997; p. 44. [Google Scholar]
- Horne, J.F.; Orr, J.E. Assessing behaviors that create resilient organizations. Employ. Relat. Today 1997, 24, 29–39. [Google Scholar]
- Mallak, L. Measuring resilience in health care provider organizations. Health Manpow. Manag. 1998, 24, 148–152. [Google Scholar] [CrossRef] [Green Version]
- Mileti, D.S. Disasters by Design: A Reassessment of Natural Hazards in the United States; National Academies Press: Wahington, DC, USA, 1999. [Google Scholar]
- Comfort, L. Shared Risk: Complex Systems in Seismic Response; Pergamom Press: Oxford, UK, 1999. [Google Scholar]
- Paton, D.; Smith, L.; Violanti, J. Disaster response: Risk, vulnerability and resilience. Disaster Prev. Manag. 2000, 9, 173–180. [Google Scholar] [CrossRef]
- Kendra, J.M.; Wachtendorf, T. Elements of resilience after the world trade center disaster: Reconstituting New York city’s emergency operations centre. Disasters 2003, 27, 37–53. [Google Scholar] [CrossRef]
- Cardona, D.O. The Notions of Disaster Risk: Conceptual Framework for Integrated Management; Technical report; Inter-American Development Bank, Universidad Nacional de Colombia, Istituto de Estudios Ambientales: Manizales, CO, USA, 2003. [Google Scholar]
- Pelling, M. The Vulnerability of Cities: Natural Disasters and Social Resilience; Earthscan LLC.: Sterling, VA, USA, 2003. [Google Scholar]
- UNISDR. Hyogo Framework for 2005–2015: Building the Resilience of Nations and Communities to Disasters. Technical Report. In Proceedings of the World Conference on Disaster Reduction, Kobe, Japan, 18–22 January 2005. [Google Scholar]
- Terzic, V.; Villanueva, P.K.; Saldana, D.; Yoo, D.Y. Framework for modelling post-earthquake functional recovery of buildings. Eng. Struct. 2021, 246, 113074. [Google Scholar] [CrossRef]
- Tian, Y.; Lu, X.; Lu, X.; Li, M.; Guan, H. Quantifying the seismic resilience of two tall buildings designed using Chinese and US Codes. Earthq. Struct. 2016, 11, 925–942. [Google Scholar] [CrossRef]
- Lu, X.; Xie, L.; Yu, C.; Lu, X. Development and application of a simplified model for the design of a super-tall mega-braced frame-core tube building. Eng. Struct. 2016, 110, 116–126. [Google Scholar] [CrossRef] [Green Version]
- Bruneau, M.; Reinhorn, A. Exploring the concept of seismic resilience for acute care facilities. Earthq. Spectra 2007, 23, 41–62. [Google Scholar] [CrossRef] [Green Version]
- Limongelli, M.P.; Çelebi, M. Seismic Structural Health Monitoring: From Theory to Successful Applications; Springer: Cham, Switzerland, 2019. [Google Scholar]
- Dolce, M.; Nicoletti, M.; De Sortis, A.; Marchesini, S.; Spina, D.; Talanas, F. Osservatorio sismico delle strutture: The Italian structural seismic monitoring network. Bull. Earthq. Eng. 2015, 15, 621–641. [Google Scholar] [CrossRef] [Green Version]
- Iacovino, C.; DiTommaso, R.; Ponzo, F.; Limongelli, M. The Interpolation Evolution Method for damage localization in structures under seismic excitation. Earthq. Eng. Struct. Dyn. 2018, 47, 2117–2136. [Google Scholar] [CrossRef]
- Quqa, S.; Landi, L.; Diotallevi, P.P. Seismic structural health monitoring using the modal assurance distribution. Earthq. Eng. Struct. Dyn. 2021, 50, 2379–2397. [Google Scholar] [CrossRef]
- Bursi, O.S.; Zonta, D.; Debiasi, E.; Trapani, D. Structural health monitoring for seismic protection of structure and infrastructure systems. In Proceedings of the Recent Advances in Earthquake Engineering in Europe—16th European Conference on Earthquake Engineering, Thessaloniki, Greece, 18–21 June 2018; pp. 339–358. [Google Scholar]
- Pozzi, M.; Der Kiureghian, A. Assessing the value of information for long-term structural health monitoring. In Health Monitoring of Structural and Biological Systems; Kundu, T., Ed.; SPIE Press: San Diego, CA, USA, 2011; p. 79842. [Google Scholar]
- Thöns, S. On the Value of Monitoring Information for the Structural Integrity and Risk Management. Comput. Civ. Infrastruct. Eng. 2017, 33, 79–94. [Google Scholar] [CrossRef]
- Yeo, G.L. Stochastic Characterization and Decision Bases under Time-Dependent Aftershock Risk in Performance-Based Earthquake Engineering; Stanford University: Stanford, CA, USA, 2005. [Google Scholar]
- Omenzetter, P.; Limongelli, M.P.; Yazgan, U. Quantifying the value of seismic structural health monitoring of buildings. In Proceedings of the 8th European Workshop on Structural Health Monitoring, EWSHM, Bilbao, Spain, 5–8 July 2016. [Google Scholar]
- Giordano, P.F.; Limongelli, M.P. The value of structural health monitoring in seismic emergency management of bridges. Struct. Infrastruct. Eng. 2020, 18, 537–553. [Google Scholar] [CrossRef]
- Iannacone, L.; Giordano, P.F.; Gardoni, P.; Limongelli, M.P. Quantifying the value of information from inspecting and monitoring engineering systems subject to gradual and shock deterioration. Struct Health Monit. 2021, 21, 72–89. [Google Scholar] [CrossRef]
- Holmes, W. Multi-Hazard Loss Estimation Methodology, Technical Manual; Federal Emergency Management Agency (FEMA): Washington, DC, USA, 2003.
Level | Accuracy | |
---|---|---|
L1 | Slight | 0.50 |
L2 | Moderate | 0.35 |
L3 | Extensive | 0.20 |
L4 | Complete | 0.05 |
Level | Accuracy | |
---|---|---|
L1 | Slight | 0.502 |
L2 | Moderate | 0.531 |
L3 | Extensive | 0.644 |
L4 | Complete | 0.951 |
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Forcellini, D. The Role of Seismic Structural Health Monitoring (S2HM) in the Assessment of the Delay Time after Earthquakes. Appl. Sci. 2023, 13, 3293. https://doi.org/10.3390/app13053293
Forcellini D. The Role of Seismic Structural Health Monitoring (S2HM) in the Assessment of the Delay Time after Earthquakes. Applied Sciences. 2023; 13(5):3293. https://doi.org/10.3390/app13053293
Chicago/Turabian StyleForcellini, Davide. 2023. "The Role of Seismic Structural Health Monitoring (S2HM) in the Assessment of the Delay Time after Earthquakes" Applied Sciences 13, no. 5: 3293. https://doi.org/10.3390/app13053293
APA StyleForcellini, D. (2023). The Role of Seismic Structural Health Monitoring (S2HM) in the Assessment of the Delay Time after Earthquakes. Applied Sciences, 13(5), 3293. https://doi.org/10.3390/app13053293