Seismic fragility models for typical non-engineered URM residential buildings in Malawi

Abstract

Malawi is an earthquake-prone country that lies within the East African Rift. A large proportion of its population lives in non-engineered single-storey constructions made of clay bricks and low-strength mortar. Walls are typically single-skin and often lack adequate wall-to-wall connections, leaving them vulnerable to seismic actions. This work reports a comprehensive study on the seismic fragility of unreinforced masonry buildings of the Malawi housing stock. The probability of exceeding different levels of in-plane/out-of-plane damage is estimated by considering the aleatory and epistemic uncertainties of the problem. Inter-building and intra-building variability are accounted for by adopting material test results and building survey data collected in Malawi. The inplane capacity of building walls is calculated through a finite element model that considers the orthotropic properties of masonry. The out-of-plane capacity is computed using an analytical solution, developed for walls in one way bending. In addition, record-to-record variability is considered. The new country-specific fragility models result more conservative that global estimates, which reflects the high vulnerability of Malawian masonry buildings. These fragilities can be integrated into catastrophe modelling platforms for earthquake risk assessment in Malawi and in the wider East African region.

Fault-based Probabilistic Seismic Hazard Analysis in Regions with Low Strain Rates and a Thick Seismogenic Layer: A Case Study from Malawi

“…To fully explore and quantify the implications of this study for seismic risk in Malawi, results should be combined with seismic vulnerability and exposure assessments (Goda et al, 2016Ngoma et al, 2019;Kloukinas et al, 2020;Giordano et al, 2021). Nevertheless, some implications of this PSHA to seismic risk are apparent.…”

“…Nevertheless, some implications of this PSHA to seismic risk are apparent. For example, given the low quality and high turnover of building stock in Malawi (Giordano et al, 2021), the results that are of most practical importance are for high PoE and in these instances the MSSD sources affect hazard levels only at long vibration periods and/or sites close (< 40 km) to active faults (Fig. 12).…”

“…Malawi is also one of several countries along the EAR where seismic risk is being exacerbated by population growth and the development of seismically vulnerable building stock (Meghraoui et al, 2016;Goda et al, 2016;Poggi et al, 2017;World-Bank, 2019;Kloukinas et al, 2020;Giordano et al, 2021). However, PSHA in the EAR typically considers only the instrumental record of seismicity (e.g., Midzi et al, 1999;Bwambale et al, 2016;Delvaux et al, 2017;Goitom et al, 2017;Delvaux et al, 2017;Poggi et al, 2017;Tuluka et al, 2020;Msabi & Ferdinand, 2021).…”

The Luangwa Rift Active Fault Database and fault reactivation along the southwestern branch of the East African Rift

“…Recent moderate magnitude earthquakes in Malawi led to high levels of damage and large economic losses (World Bank, 2019) and research in Malawi indicates that building vulnerability in this region is higher than currently predicted by global models (e.g. the USGS WHE-PAGER model; Novelli et al, 2021;Giordano et al, 2021). We suggest that active fault mapping, such as has been carried out here in the LRAFD and in other active fault databases in southern Africa (Williams et al, 2021(Williams et al, , 2022 provides a framework for accurate probabilistic seismic hazard assessment, and thus for increasing resilience to seismic hazard throughout southern and eastern Africa.…”

Scenario-based earthquake risk assessment for central-southern Malawi: The case of the Bilila-Mtakataka Fault

“…There is major uncertainty regarding how a future rupture of the BMF may be realised in terms of earthquake size and geometry. The regional earthquake risk assessment tool presented in this study is innovative and upgrades the previous studies by Hodge et al (2015) and Goda et al (2016) in major ways: (i) numerous stochastic earthquake ruptures are generated based on the recent geological/geomorphological studies of the BMF (Hodge et al, 2018;Williams et al, 2021) to account for uncertainty associated with rupture geometry and location; (ii) exposure data are based on the most recent 2018 Malawi census (National Statistical Office of Malawi, 2018); and (iii) seismic vulnerability functions are derived from new mechanical failure-mode analyses and analytical and finite-element analyses (Giordano et al, 2021) of non-engineered masonry buildings in Malawi, parameters of which were obtained from building surveys and experimental tests of local construction materials (Kloukinas et al, 2019(Kloukinas et al, , 2020Voyagaki et al, 2020).…”