Estimation of seismic downtime for building retrofitting decision-making

Mucedero G , Couto R , Yükselen B , Monteiro R

Resilient Cities and Structures ›› 2025, Vol. 4 ›› Issue (3) : 15 -29.

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Resilient Cities and Structures ›› 2025, Vol. 4 ›› Issue (3) : 15 -29. DOI: 10.1016/j.rcns.2025.07.001
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Estimation of seismic downtime for building retrofitting decision-making

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Abstract

Recent research demonstrates the need for comprehensive frameworks to achieve an appropriate level of resilience (e.g., energy, seismic) of the European building stock, through integrated retrofitting interventions. Different frameworks have been proposed to identify optimal interventions when several feasible alternatives are available, considering multiple decision variables of different nature, such as social, economic, or technical. Within these efforts and frameworks, less attention has been paid to the post-earthquake recovery time of buildings and communities, thus ignoring the significance of reaching a desired recovery state (e.g., functional recovery) within a specified time frame. To overcome this limitation, this study estimates post-earthquake recovery times and uses them as one of the decision variables in multi-criteria identification of optimal retrofitting of an existing RC building. The case-study building is representative of the Italian school buildings constructed between the 1960s and 1970s and was analysed under two seismic hazard levels (moderate and high). Following the identification of the main structural deficiencies of the as-built structure through nonlinear static analyses, four seismic retrofit measures were selected. Then, the earthquake-induced downtime of each of the four retrofitted building configurations was assessed, analysing the different recovery times as a function of the seismic hazard level and the recovery state. A downtime-based metric, namely the expected annual downtime, was introduced as decision variable within an available multi-criteria decision-making framework to include the impact of downtime, rank the four retrofit measures and identify the preferable one.

Keywords

RC buildings / Optimal retrofit / Multi-criteria decision-making / Loss assessment / Downtime assessment

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Mucedero G, Couto R, Yükselen B, Monteiro R. Estimation of seismic downtime for building retrofitting decision-making. Resilient Cities and Structures, 2025, 4(3): 15-29 DOI:10.1016/j.rcns.2025.07.001

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Relevance to resilience

When seeking to identify optimal retrofitting strategies for existing buildings, conventional multi-criteria decision-making (MCDM) frameworks tend to consider various decision variables (DVs) of economic, technical, and social nature. However, they often overlook the crucial aspect of downtime and its impact on building functionality and community resilience. Mitigating the downtime impacts in future earthquakes means that research efforts should focus on allowing individuals to return to their homes while ensuring access to other vital services, such as education, healthcare, and commerce. To overcome this limitation and investigate the impact of downtime on the identification of optimal retrofitting strategies for RC buildings, post-earthquake recovery times were quantified, and the expected annual downtime was introduced as DV within an available MCDM framework. The results demonstrate the need to set multi-performance retrofitting objectives, of structural, economic, social and environmental nature, to assist cost-effective decisions, from a life-cycle perspective. This would guarantee that, following seismic events, building demolishment or high recovery times would not occur.

CRediT author statement

Gianrocco Mucedero: Conceptualization, Methodology, Software, Validation, Formal analysis, Writing-original draft preparation, Writing-review and editing. Rita Couto: Software, Validation, Formal analysis, Writing-original draft preparation. Besim Yükselen: Software, Validation, Formal analysis, Writing-original draft preparation. Ricardo Monteiro: Methodology, Validation, Writing-review and editing, Supervision, Project administration, Funding acquisition

All authors have read and agreed to the “Author Contributions”.

Declaration of competing interests

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgments

The work presented in this paper was developed within the framework of the projects “ReLUIS 2024-2026 (WP5 and WP13),” funded by the Italian Civil Protection Department and “PriorBuilt - Prioritisation of the Italian regions for seismic and energy performance upgrading of the existing buildings”, funded by ReLUIS. Additionally, it was developed as part of the activities of CONSTRUCT - Instituto de I&D em Estruturas e Construções (UID/04708), CERIS (UIDB/04625), and the project SERENE (2022.08138.PTDC), all funded by Fundação para a Ciência e a Tecnologia, I.P./MCTES (PIDDAC).

References

[1]

Bournas DA. Concurrent seismic and energy retrofitting of RC and masonry building envelopes using inorganic textile-based composites combined with insulation materials: a new concept. Compos Part B: Eng Sep 2018;148:166-79. doi: 10.1016/j.compositesb.2018.04.002.

[2]

Gkournelos PD, Bournas DA, Triantafillou TC. Combined seismic and energy upgrading of existing reinforced concrete buildings using TRM jacketing and thermal insulation. Earthq Struct 2019; 16(5):625-39. doi: 10.12989/eas.2019.16.5.625.

[3]

Calvi GM, Sousa L, Ruggeri C. Energy efficiency and seismic resilience:a common approach. In: Multi-hazard approaches to civil infrastructure engineering. Cham: Springer International Publishing; 2016. p. 165-208. July. doi: 10.1007/978-3-319-29713-2_9.

[4]

Manfredi V, Masi A. Seismic strengthening and energy efficiency: towards an integrated approach for the rehabilitation of existing RC buildings. Buildings Mar 2018; 8(3):36. doi: 10.3390/buildings8030036.

[5]

Marini A, et al. Combining seismic retrofit with energy refurbishment for the sustainable renovation of RC buildings: a proof of concept. Eur J Environ Civil Eng May 2022; 26(7):2475-95. doi: 10.1080/19648189.2017.1363665.

[6]

Pohoryles DA, Maduta C, Bournas DA, Kouris LA. Energy performance of existing residential buildings in Europe: a novel approach combining energy with seismic retrofitting. Energy Build 2020; 223. doi: 10.1016/j.enbuild.2020.110024.

[7]

Takeuchi T, Yasuda K, Iwata M.Studies on integrated building facade engineering with high-performance structural elements. In: IABSE symposium, budapest 2006: responding to tomorrow’s challenges in structural engineering. Zurich, Switzerland: International Association for Bridge and Structural Engineering (IABSE); 2006. p. 33-40. doi: 10.2749/222137806796185526.

[8]

Takeuchi T, Yasuda K, Iwata M. Seismic retrofitting using energy dissipation façades. In: Improving the seismic performance of existing buildings and other structures. Reston, VA: American Society of Civil Engineers; Dec 2009. p. 1000-9. doi: 10.1061/41084(364)91.

[9]

Caruso M, Pinho R, Bianchi F, Cavalieri F, Lemmo MT. Multi-criteria decisionmaking approach for optimal seismic/energy retrofitting of existing buildings. Earthq Spectra Feb 2023; 39(1):191-217. doi: 10.1177/87552930221141917.

[10]

Clemett N, Carofilis W, Gabbianelli G, O’Reilly GJ, Monteiro R. Optimal combined seismic and energy efficiency retrofitting for existing buildings in Italy. J Struct Eng 2023; 149(1):1-16. doi: 10.1061/(asce)st.1943-541x.0003500.

[11]

Caruso M, Pinho R, Bianchi F, Cavalieri F, Lemmo MT. Integrated economic and environmental building classification and optimal seismic vulnerability/ energy efficiency retrofitting. Bull Earthq Eng Jul 2021; 19(9):3627-70. doi: 10.1007/s10518-021-01101-4.

[12]

Menna C, Del Vecchio C, Di Ludovico M, Mauro GM, Ascione F, Prota A.Conceptual design of integrated seismic and energy retrofit interventions. J Build Eng 2021;38:102190 January, p. doi: 10.1016/j.jobe.2021.102190.

[13]

Cimellaro GGPG. Resilience-based design (RBD) modelling of civil infrastructure to assess seismic hazards. In: Seismic risk analysis and management of civil infrastructure systems. Elsevier; 2013. p. 268-303. Elsevier. doi: 10.1533/9780857098986.2.268.

[14]

M.V. Requena-García-Cruz, A. Morales-Esteban, P. Durand-Neyra, and J.M.C. Estêvão, “An index-based method for evaluating seismic retrofitting techniques. Application to a reinforced concrete primary school in Huelva, ” in Earth and its atmosphere, vol. 14, no. 4, Hyderabad, India, 2020. doi: 10.1371/journal.pone.0215120.

[15]

Sousa L, Monteiro R. Seismic retrofit options for non-structural building partition walls: impact on loss estimation and cost-benefit analysis. Eng Struct 2018;161:8- 27 no. January. doi: 10.1016/j.engstruct.2018.01.028.

[16]

Asadi E, Salman AM, Li Y. Multi-criteria decision-making for seismic resilience and sustainability assessment of diagrid buildings. Eng Struct Jul 2019;191:229-46. doi: 10.1016/j.engstruct.2019.04.049.

[17]

Caterino N, Iervolino I, Manfredi G, Cosenza E. Multi-criteria decision making for seismic retrofitting of RC structures. J Earthq Eng May 2008; 12(4):555-83. doi: 10.1080/13632460701572872.

[18]

Requena-Garcia-Cruz MV, Morales-Esteban A, Durand-Neyra P. Assessment of specific structural and ground-improvement seismic retrofitting techniques for a case study RC building by means of a multi-criteria evaluation. Structures Apr 2022;38:265-78. doi: 10.1016/j.istruc.2022.02.015.

[19]

Daniel S, Ghiaus C. Multi-criteria decision analysis for energy retrofit of residential buildings: methodology and feedback from real application. Energies (Basel) Jan 2023; 16(2):902. doi: 10.3390/en16020902.

[20]

Mosalam KM, Alibrandi U, Lee H, Armengou J. Performance-based engineering and multi-criteria decision analysis for sustainable and resilient building design. Struct Saf Sep 2018;74:1-13. doi: 10.1016/j.strusafe.2018.03.005.

[21]

Mohammadgholibeyki N, et al. A decision-making framework for life-cycle energy and seismic loss assessment of buildings. Struct Infrastruct Eng Jul 2023; 19(7):875-89. doi: 10.1080/15732479.2021.1983613.

[22]

Zareian F, Sampere C, Sandoval V, McCormick DL, Moehle J, Leon R. Reconnaissance of the Chilean wine industry affected by the 2010 Chile Offshore Maule earthquake. Earthq Spectra Jun 2012;28:503-12 no. 1_suppl1. doi: 10.1193/1.4000048.

[23]

Miranda E, Mosqueda G, Retamales R, Pekcan G.Performance of nonstructural components during the 27 February 2010 Chile earthquake. Earthq Spectra Jun 2012;28:453-71 no. 1_suppl1. doi: 10.1193/1.4000032.

[24]

Liel AB, Lynch KP.Vulnerability of reinforced-concrete-frame buildings and their occupants in the 2009 L’Aquila, Italy, earthquake. Nat Hazards Rev Feb 2012; 13(1):11-23. doi: 10.1061/(ASCE)NH.1527-6996.0000047.

[25]

Perrone D, Calvi PM, Nascimbene R, Fischer EC, Magliulo G.Seismic performance of non-structural elements during the 2016 Central Italy earthquake. Bull Earthq Eng Oct 2019; 17(10):5655-77. doi: 10.1007/s10518-018-0361-5.

[26]

Qu Z, Wang F, Chen X, Wang X, Zhou Z. Rapid report of seismic damage to hospitals in the 2023 Turkey earthquake sequences. Earthq Res Adv Oct 2023; 3(4):100234. doi: 10.1016/j.eqrea.2023.100234.

[27]

FEMA P- 2090, “Recommended options for improving the built environment for post-earthquake reoccupancy and functional recovery time, ” Gaithersburg, MD, Jan. 2021. doi: 10.6028/NIST.SP.1254.

[28]

FEMA,“Seismic Performance Assessment of Buildings, volume 3 - Supporting electronic materials and background documentation, ” Fema P-58, no.December 2018.

[29]

I. Almufti and M. Willford, “Resilience-based Earthquake Design Initiative for the next generation of buildings, ” REDiTM Rating System, no. October, pp. 1-133, 2013.

[30]

Burton H, Miles S, Kang H. Integrating performance-based engineering and urban simulation to model post-earthquake housing recovery. Earthq Spectra 2018; 34(4):1763-85.

[31]

Costa R, Haukaas T, Chang S. Agent-based model for post-earthquake housing recovery. Earthq Spectra 2021;37:46-72.

[32]

Cremen G, Seville E, Baker JW. Modeling post-earthquake business recovery time: an analytical framework. Int J Dis Risk Reduct Jan 2020;42:101328. doi: 10.1016/j.ijdrr.2019.101328.

[33]

Cook DT, Liel AB, Haselton CB, Koliou M. A framework for operationalizing the assessment of post-earthquake functional recovery of buildings. Earthq Spectra 2022; 38(3):1972-2007. doi: 10.1177/87552930221081538.

[34]

Molina C, Eeri HM, Vahanvaty T, Eeri M, Eeri PKM. An analytical framework to assess earthquake-induced downtime and model recovery of buildings. Earthq Spectra 2022. doi: 10.1177/87552930211060856.

[35]

SPUR, “Safe enough to stay. Report, ” San Francisco, C, 2012.

[36]

ANIA AllontAniamo i rischi, RimAniamo protetti. Edition (2024) https://www.ania.it/allontaniamo-i-rischi.

[37]

Couto R, Mucedero G, Bento R, Monteiro R. A practice-oriented approach for seismic and energy performance upgrading of existing buildings. J Earthq Eng Jul 2024:1- 28. doi: 10.1080/13632469.2024.2382474.

[38]

Couto R, Mucedero G, Bento R, Monteiro R. Understanding the Impact of Seismic Hazard and Climate Conditions on Multi Criteria-Based Retrofitting of Existing Buildings. Sustainability 2024; 16(10):4318. https://doi.org/10.3390/su16104318.

[39]

Carofilis W, Clemett N, Gabbianelli G, O’Reilly G, Monteiro R. Influence of parameter uncertainty in multi-criteria decision-making when identifying optimal retrofitting strategies for RC buildings. J Earthq Eng 2022. doi: 10.1080/13632469.2022.2087794.

[40]

Carofilis Gallo WW, Gabbianelli G, Monteiro R. Assessment of multi-criteria evaluation procedures for identification of optimal seismic retrofitting strategies for existing RC buildings. J Earthq Eng Aug 2022; 26(11):5539-72. doi: 10.1080/13632469.2021.1878074.

[41]

Gallina V, Torresan S, Critto A, Sperotto A, Glade T, Marcomini A. A review of multi-risk methodologies for natural hazards: consequences and challenges for a climate change impact assessment. J Environ Manag Mar 2016;168:123-32. doi: 10.1016/j.jenvman.2015.11.011.

[42]

Kappes MS, Keiler M, Von Elverfeldt K, Glade T. Challenges of analyzing multi-hazard risk: a review. Nat Hazards Nov 2012; 64(2):1925-58. doi: 10.1007/s11069-012-0294-2.

[43]

Argyroudis SA, Mitoulis SA, Hofer L, Zanini MA, Tubaldi E, Frangopol DM. Resilience assessment framework for critical infrastructure in a multi-hazard environment: case study on transport assets. Sci Total Environ Apr 2020;714:136854. doi: 10.1016/j.scitotenv.2020.136854.

[44]

Tilloy A, Malamud BD, Winter H, Joly-Laugel A. A review of quantification methodologies for multi-hazard interrelationships. Earth Sci Rev Sep 2019;196:102881. doi: 10.1016/j.earscirev.2019.102881.

[45]

Padgett JE, DesRoches R. Bridge functionality relationships for improved seismic risk assessment of transportation networks. Earthq Spectra 2007;23. doi: 10.1193/1.2431209.

[46]

A. Prota, M. Di Ludovico, C. Vecchio, and C. Menna, “Progetto DPC-ReLUIS 2019- 2021 WP5: interventi di rapida esecuzione a basso impatto ed integrati, ” vol. 72, 2020.

[47]

Mucedero G, Perrone D, Monteiro R. Infill variability and modelling uncertainty implications on the seismic loss assessment of an existing RC Italian School building. Appl Sci (Switzerland) 2022; 12(23). doi: 10.3390/app122312002.

[48]

McKenna F. OpenSees: a framework for earthquake engineering simulation. Comput Sci Eng 2011; 13(4):58-66. doi: 10.1109/MCSE.2011.66.

[49]

O’Reilly GJ, Sullivan TJ. Modeling techniques for the seismic assessment of the existing Italian RC frame structures. J Earthq Eng 2017; 23(8):1262-96. doi: 10.1080/13632469.2017.1360224.

[50]

Mucedero G, Perrone D, Brunesi E, Monteiro R. Numerical modelling and validation of the response of masonry infilled rc frames using experimental testing results. Buildings 2020; 10(10):1-30. doi: 10.3390/buildings10100182.

[51]

Merino RJ, Mucedero G, Perrone D, Filiatrault A, Monteiro R, Nascimbene R. Influence of acceleration-sensitive non-structural element classification on seismic loss estimation of a case-study building in Italy. J Build Eng Dec 2024;98:111399. doi: 10.1016/j.jobe.2024.111399.

[52]

MIT,“NTC 2018: D.M. del Ministero delle Infrastrutture e dei trasporti del 17/01/2018. Aggiorna- mento delle Norme Tecniche per le Costruzioni (in Italian), ” 2018.

[53]

Pagani M, et al. OpenQuake Engine: an open hazard (and Risk) software for the global earthquake model. Seismol Res Lett May 2014; 85(3):692-702. doi: 10.1785/0220130087.

[54]

Giardini D, Wössner J, Danciu L. Mapping Europe’s seismic hazard. Eos, Trans Am Geophys Union Jul 2014; 95(29):261-2. doi: 10.1002/2014EO290001.

[55]

J. Woessner et al., “The 2013 European seismic Hazard Model : key components and results, ” pp. 3553-96, 2015, doi: 10.1007/s10518-015-9795-1.

[56]

Cardone D. Fragility curves and loss functions for RC structural components with smooth rebars. Earthq Struct 2016; 10(5):1181-212. doi: 10.12989/eas.2016.10.5.1181.

[57]

Sassun K, Sullivan TJ, Morandi P, Cardone D. Characterising the in-plane seismic performance of infill masonry. Bull New Zealand Soc Earthq Eng 2016; 49(1):98-115. doi: 10.5459/bnzsee.49.1.98-115.

[58]

Cardone D, Flora A, De Luca Picione M, Martoccia A.Estimating direct and indirect losses due to earthquake damage in residential RC buildings. Soil Dyn Earthq Eng 2019;126:105801 June, p. doi: 10.1016/j.soildyn.2019.105801.

[59]

Mazzolani FM, Formisano A, Vaiano G. Adeguamento sismico di edifici in cemento aramato: BRB e FRP. Costruz Metall 2018;1:25-50 no. (Jun).

[60]

Fajfar P. A nonlinear analysis method for performance-based seismic design. Earthq Spectra Aug 2000; 16(3):573-92. doi: 10.1193/1.1586128.

[61]

Calvi GM. Choices and criteria for seismic strengthening. J Earthq Eng 2013; 17(6):769-802. doi: 10.1080/13632469.2013.781556.

[62]

Baltzopoulos G, Baraschino R, Iervolino I, Vamvatsikos D.SPO2FRAG: software for seismic fragility assessment based on static pushover. Bull Earthq Eng Oct 2017; 15(10):4399-425. doi: 10.1007/s10518-017-0145-3.

[63]

Nettis A, Gentile R, Raffaele D, Uva G, Galasso C. Cloud capacity spectrum method: accounting for record-to-record variability in fragility analysis using nonlinear static procedures. Soil Dyn Earthq Eng Nov 2021;150:106829. doi: 10.1016/j.soildyn.2021.106829.

[64]

Cosenza E, et al. The Italian guidelines for seismic risk classification of constructions: technical principles and validation. Bull Earthq Eng Dec 2018; 16(12):5905-35. doi: 10.1007/s10518-018-0431-8.

[65]

Chalarca B, Filiatrault A, Perrone D.Expected seismic response and annual seismic loss of viscously damped braced steel frames. Eng Struct 2024;303:117569 no. February. doi: 10.1016/j.engstruct.2024.117569.

[66]

J.W. Baker,“Introduction to probabilistic seismic hazard analysis, ”White Paper Version 2.1, p. 77, 2015.

[67]

O’Reilly GJ, Sullivan TJ. Quantification of modelling uncertainty in existing Italian RC frames. Earthq Eng Struct Dyn 2018; 47(4):1054-74. doi: 10.1002/eqe.3005.

[68]

Mucedero G, Perrone D, Monteiro R. Seismic risk assessment of masonry-infilled RC building portfolios: impact of variability in the infill properties, 21. Netherlands: Springer; 2023. doi: 10.1007/s10518-022-01563-0.

[69]

O’Reilly GJ, Perrone D, Fox M, Monteiro R, Filiatrault A. Seismic assessment and loss estimation of existing school buildings in Italy. Eng Struct 2018;168:142-62. doi: 10.1016/j.engstruct.2018.04.056.

[70]

Clemett N, Carofilis Gallo WW, Gabbianelli G, O’Reilly GJ, Monteiro R. Optimal combined seismic and energy efficiency retrofitting for existing buildings in Italy. J Struct Eng Jan 2023; 149(1):04022207. doi: 10.1061/(ASCE)ST.1943-541X.0003500.

[71]

N. Paul, J.S. Lee, M. Mieler, and I. Almufti, “Improving estimates of earthquakeinduced downtime in individual buildings using the REDi methodology, ” Structures Congress 2018: blast, impact loading, and response; and research and education - selected papers from the structures Congress 2018, vol. 2018-April, no. June, pp. 77-86, 2018, doi: 10.1061/9780784481349.008.

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