Abstract

Built vernacular heritage embraces buildings that are not designed by specialists, but are part of a process that involves many people over many generations and relies on empirical knowledge. Its value as a key-element for cultural identity is unquestionable. However, precisely due to its empirical and traditional nature, it is often seen as an obsolete and unsafe way of construction, which leads to its progressive abandonment. This lack of proper construction details and poor maintenance increases the seismic vulnerability of the vernacular heritage. There is an evident need for simplified easy-to-use seismic vulnerability assessment methods for vernacular architecture, given the generalized lack of resources that can be normally assigned to its study and preservation. Most of the times, visual inspection will be the only tool available to carry out the assessment. Nevertheless, simplified methods demand a deep understanding of the seismic behavior of vernacular architecture. This is a complex task given the great heterogeneity in the geometrical, structural, construction and material characteristics of vernacular buildings. The present works explores the development of a probabilistic method for the analytical derivation of seismic fragility functions of vernacular buildings considering uncertainty in material parameters and structural characteristics. The procedure followed to investigate the effect of uncertainty and to evaluate the influence of a set of key parameters on the seismic response of vernacular buildings is based on stochastic analysis. In the end, a simplified numerical tool is proposed which can be applied based on visual inspection. The process applied and shown here is considered as an example of application and can be replicated in other contexts. It ultimately intends to extend the applicability and reliability of current seismic vulnerability assessment methods.

Full document

The PDF file did not load properly or your web browser does not support viewing PDF files. Download directly to your device: Download PDF document

References

[1] Correia M. Experiences from past for today’s challenges. In: The road to sustainable development. Chapter 6 – Traditional and generational change, La Fábrica, Fundación Contemporánea (2017), pp. 128–133.

[2] ICOMOS. Charter on the built vernacular heritage. International Council of Monuments and Sites (ICOMOS), ICOMOS 12th General Assembly, Mexico (1999).

[3] Ortega, J., Vasconcelos, G., Rodrigues, H., Correia, M. and Miranda, T. Development of a Numerical Tool for the Seismic Vulnerability Assessment of Vernacular Architecture. Journal of Earthquake Engineering (2019).

[4] Saloustros, S., Pelà, F.L., Contrafatto, P., Roca, P. and Petromichelakis, I. Analytical derivation of seismic fragility curves for historical masonry structures based on stochastic analysis of uncertain material parameters. International Journal of Architectural Heritage (2019).

[5] Petromichelakis, I. and Saloustros, S. Seismic assessment of historical masonry construction including uncertainty. In: Cunha Á, Caetano E, Ribeiro P, Müller G (eds) 9th Int. Conf. Struct. Dyn. EURODYN 2014, Porto (Portugal) (2014), pp. 297-304.

[6] Ortega, J., Vasconcelos, G., Rodrigues, H. and Correia, M. Seismic Vulnerability and Loss Assessment of Vila Real de Santo António, Portugal: Application of a Novel Method. International Journal of Architectural Heritage (2020).

[7] SGU. Plano de Pormenor de Salvaguarda do Núcleo Pombalino de Vila Real de Santo António, Sociedade de Gestão Urbana (SGU) de Vila Real de Santo António. Vila Real de Santo António, Portugal (2008).

[8] TNO. Displacement method analyser. User’s manual, release 9.4.4. TNO DIANA BV, Delft, Netherlands (2011).

[9] CNR-DT 212/2013. Guide for the Probabilistic Assessment of the Seismic Safety of Existing Buildings. Rome, Italy: 2014.

[10] Angelillo M, Lourenço PB, Milani G. Masonry behaviour and modelling. Mech. Mason. Struct., vol. 551, 2014. doi:10.1007/978-3-7091-1774-3.

[11] Federal Emergency Management Agency. HAZUS-MH MR4: Technical Manual, Vol. Earthquake Model. Washington DC: 2010.

[12] R Development Core Team. R: A language and environment for statistical computing. R. Foundation for Statistical Computing, Vienna, Austria (2008).

Back to Top
GET PDF

Document information

Published on 30/11/21
Submitted on 30/11/21

Volume Vulnerability and risk analysis, 2021
DOI: 10.23967/sahc.2021.235
Licence: CC BY-NC-SA license

Document Score

0

Views 4
Recommendations 0

Share this document

claim authorship

Are you one of the authors of this document?