Ioanna Ioannou

Empirical fragility assessment of buildings affected by the 2011 Great East Japan tsunami using improved statistical models

Tsunamis are destructive natural phenomena which cause extensive damage to the built environment, affecting the livelihoods and economy of the impacted nations. This has been demonstrated by the tragic events of the Indian Ocean tsunami in 2004, or the Great East Japan tsunami in 2011. Following such events, a few studies have attempted to assess the fragility of the existing building inventory by constructing empirical stochastic functions, which relate the damage to a measure of tsunami intensity. However, these studies typically fit a linear statistical model to the available damage data, which are aggregated in bins of similar levels of tsunami intensity. This procedure, however, cannot deal well with aggregated data, low and high damage probabilities, nor does it result in the most realistic representation of the tsunami-induced damage. Deviating from this trend, the present study adopts the more realistic generalised linear models which address the aforementioned disadvantages. The proposed models are fitted to the damage database, containing 178,448 buildings surveyed in the aftermath of the 2011 Japanese tsunami, provided by the Ministry of Land, Infrastructure Transport and Tourism in Japan. In line with the results obtained in previous studies, the fragility curves show that wooden buildings (the dominant construction type in Japan) are the least resistant against tsunami loading. The diagnostics show that taking into account both the building’s construction type and the tsunami flow depth is crucial to the quality of the damage estimation and that these two variables do not act independently. In addition, the diagnostics reveal that tsunami flow depth estimates low levels of damage reasonably well; however, it is not the most representative measure of intensity of the tsunami for high damage states (especially structural damage). Further research using disaggregated damage data and additional explanatory variables is required in order to obtain reliable model estimations of building damage probability.

Evaluation of Existing Fragility Curves

There is a wealth of existing fragility curves for buildings and infrastructure. The main challenge in using these curves for future applications is how to identify and, if necessary, combine suitable fragility curves from a pool of curves with different characteristics and, often unknown, reliability. The present chapter aims to address this challenge by developing a procedure which identifies suitable fragility curves by firstly assessing their representativeness to the needs of the future application and then assessing the reliability of the most relevant relationships. The latter is based on a novel procedure which involves the assessment of the most significant factors affecting the robustness and quality for each fragility assessment methodology, also presented here. In addition, a decision-tree approach is adopted in order to combine more than one suitable fragility curves. The proposed selection and combination procedures are illustrated here with a simple case study which appraises the impact of different weighting schemes and highlights the importance of a deep understanding of the existing fragility curves and their limitations.

The Global Earthquake Model Physical Vulnerability Database

There are almost 50 years of research on fragility and vulnerability assessment, both key elements in seismic risk or loss estimation. This paper presents the online database of physical vulnerability models that has been created as part of the Global Earthquake Model (GEM) initiative. The database comprises fragility and vulnerability curves, damage-to-loss models, and capacity curves for various types of structures. The attributes that have been selected to characterize each function, the constraints of setting up a usable database, the challenges in collecting these models, and the current trends in the development of vulnerability models are discussed in this study. The current collection of models leverages upon the outputs of several initiatives, such as GEMs Global Vulnerability Consortium and the European Syner-G project. This database is publicly available through the web-based GEM OpenQuake-platform http://doi.org/10.13117/GEM.DATASET.VULN.WEB-V1.0

Seismic vulnerability functions for Australian buildings by using GEM empirical vulnerability assessment guidelines

Australia has a low to moderate seismicity by world standards. However, the seismic risk is significant due to the legacy of older buildings constructed prior to the national implementation of an earthquake building standard in Australia. The 1989 Newcastle and the 2010 Kalgoorlie earthquakes are the most recent Australian earthquakes to cause significant damage to unreinforced masonry (URM) and light timber frame structures and have provided the best opportunities to examine the earthquake vulnerability of these building types. This paper describes the two above-mentioned building types with a differentiation of older legacy buildings constructed prior to 1945 to the relatively newer ones constructed after 1945. Furthermore, the paper presents method to utilise the large damage and loss-related data (14,000 insurance claims in Newcastle and 400 surveyed buildings in Kalgoorlie) collected from these events to develop empirical vulnerability functions. The method adopted here followed the GEM empirical vulnerability assessment guidelines which involve preparing a loss database, selecting an appropriate intensity measure, selecting and applying a suitable statistical approach to develop vulnerability functions and the identification of optimum functions. The adopted method uses a rigorous statistical approach to quantify uncertainty in vulnerability functions and provides an optimum solution based on goodness-of-fit tests. The analysis shows that the URM structures built before 1945 are the most vulnerable to earthquake with post-1945 URM structures being the next most vulnerable. Timber structures appear to be the least vulnerable, with little difference observed in the vulnerability of timber buildings built before or after 1945. Moreover, the older structures (both URM and timber) exhibit more scatter in results reflecting greater variation in building vulnerability and performance during earthquakes. The analysis also highlights the importance of collecting high-quality damage and loss data which is not only a fundamental requirement for developing empirical vulnerability functions, but is also useful in validating analytically derived vulnerability functions. The vulnerability functions developed herein are the first publically available functions for Australian URM and timber structures. They can be used for seismic risk assessment and to focus the development of retrofit strategies to reduce the existing earthquake risk.

Expert judgment-based fragility assessment of reinforced concrete buildings exposed to fire

•The fire fragility of a generic modern, mid-rise, RC office building is assessed.•Fragility curves for its slabs and columns are constructed by expert elicitation.•The expert elicitation also used to construct a suitable fire damage scale.•The significance of spalling in the two RC elements is identified.

Surface and passive/active air mould sampling: A testing exercise in a North London housing estate

Despite indoor mould being one of the most common problems in residential properties in the UK, there are not any widely accepted methodologies for its measurement. This paper focusses on this problem of measurement and reports on the findings from a rigorous testing scheme carried out to quantify air and surface mould concentrations and particle counts within 71 rooms from 64 properties in North London, some with and some without visible mould. The aim was to investigate the potential of passive and active air sampling strategies (sampling from still and actively mixed air, respectively) to explain visible mould, and understand how home/room characteristics correlate with the obtained readings. Airborne mould levels were quantified using an Andersen sampler (passively and actively), as well as by a chemical method based on the quantification of the N-acetylhexosaminidase (NAHA) activity (actively), which was also used to quantify surface mould. The mould levels were then correlated against physical characteristics of the tested homes/rooms, collected by means of survey sheets developed as part of this study. The findings did not reveal any independent variable governing all or most of the response variables, but a complex analysis suggested that whether it is a house or a flat could depict mould levels in the air and on the surfaces. It was also shown that a robust testing protocol should combine air and surface based methods, and an active air sampling strategy leads to a more accurate appraisal of airborne mould levels. Finally, the results showed that while there is some correlation between visible mould (and other moisture induced problems such as condensation) and measured air mould concentrations, lack of visible mould within a room does not necessarily mean low air mould concentrations, and thus one should not rely solely on visual inspection.

Empirical Fragility and Vulnerability Assessment: Not Just a Regression

Abstract Empirical approaches to asset fragility and vulnerability are extensively used in the insurance industry, where they are commonly reputed the “gold standard” and to have high credibility because they are developed from past event data. However, the reliability of published empirical vulnerability and fragility functions is seen to vary greatly depending on the quality and quantity of the empirical data used and how the data is treated. This chapter presents an overview of some significant observations made by the Authors while working on earthquake and tsunami empirical fragility and vulnerability functions over the last 10 years. Common biases in event damage and loss data sets are presented, the consequences of ignoring the biases are discussed, and possible ways of dealing with them are suggested. The impact of different statistical model fitting approaches is described and illustrated with examples drawn from empirical earthquake and tsunami fragility and vulnerability studies. Throughout, areas for further research are highlighted, and it is observed that some sources of uncertainty remain largely unexplored.Empirical approaches to asset fragility and vulnerability are extensively used in the insurance industry, where they are commonly reputed the “gold standard” and to have high credibility because they are developed from past event data. However, the reliability of published empirical vulnerability and fragility functions is seen to vary greatly depending on the quality and quantity of the empirical data used and how the data is treated. This chapter presents an overview of some significant observations made by the Authors while working on earthquake and tsunami empirical fragility and vulnerability functions over the last 10 years. Common biases in event damage and loss data sets are presented, the consequences of ignoring the biases are discussed, and possible ways of dealing with them are suggested. The impact of different statistical model fitting approaches is described and illustrated with examples drawn from empirical earthquake and tsunami fragility and vulnerability studies. Throughout, areas for further research are highlighted, and it is observed that some sources of uncertainty remain largely unexplored.

Application of Expert Judgment to the Quantification of a Damage Scale for Reinforced Concrete Buildings Exposed to Fire

Essential in the fire fragility assessment of mid-rise reinforced concrete buildings is a relevant damage scale. This study adopts expert elicitation to construct a damage scale relevant to the slabs of these buildings by relating thresholds of four structural response measures (i.e., spalling, residual capacity, peak rebar temperature and deflection) to three qualitatively described damage states of increasing severity. The opinions of thirteen international experts are pooled together using Cooke’s Classical Model, which recognizes that uncertainty exists around each damage state threshold and seeks to quantify it. Compared to an approach which weights exert opinions equally, this Model results, in most cases, in conservative estimates of the damage state thresholds associated with well-constrained uncertainty. Areas where more research is needed are also identified. These areas include the determination of the thresholds of the first three measures when the extensively damaged slab cannot be repaired, and of the residual capacity of any of the three considered damage states.