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Handbook of seismic risk analysis and management of civil infrastructure systems

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What makes earthquake risks so catastrophic and dreadful? Possible reasons
are attributed to the sudden, unpredictable, involuntary, and large-scale
nature of the risks. As a consequence of a devastating earthquake, a tremendous
surge of seismic damage and loss may overwhelm the risk-bearing
capacities of households, companies, municipalities, and insurers, and may
eventually cause serious long-term effects on communities and the regional/
national economy. Recent earthquake catastrophes, including the 2004
Indian Ocean, 2008 Wenchuan, 2010 Haiti, and 2011 Christchurch earthquakes,
have demonstrated that urban cities and communities in seismic
regions are vulnerable to extreme seismic events. In the 2011 Tohoku, Japan
earthquake, the number of fatalities was in excess of 19 000, and the total
economic loss has reached 300–400 billion U.S. dollars. Earthquakes impact
entire physical infrastructure, including buildings and lifelines (water and
sewage networks, bridges, power supply, etc.). Furthermore, various stakeholders
(e.g. global companies with supply-chain networks around the
world and insurance/reinsurance companies with a widespread portfolio of
businesses and investments) are affected by such catastrophes due to the
complex and inter-connected global economy. In a nutshell, we live in a
highly uncertain and vulnerable world due to large-scale natural disasters,
and global earthquake risks must be mitigated to achieve more resilient
and sustainable society.

The current framework for seismic risk analysis addresses quantifi cation
of magnitude and recurrence of earthquake, vulnerability of infrastructure
systems, and consequences due to damage. Developing a comprehensive
model for all types of structures and lifelines is a challenging task. A systembased
model can be used, where a system is defi ned as an ‘assemblage of
components acting as a whole’; each system in turn encapsulates different
subcomponents, each of which can be described as a subsystem. In structural
safety evaluation, system response to earthquake loading is of paramount
importance and is often affected by complex interdependency of
subsystems in terms of structural resilience and functionality. A notable
example is the cascading failures of infrastructure systems during a natural
disaster; the functionality of a critical facility, such as a hospital, is infl uenced
by the structural resilience as well as the surrounding lifeline networks (e.g.
water, electricity, and staff availability). Different approaches and methods
are available to address a wide variety of engineering problems, and suitable
models are required to analyse the problems. It is also important
to recognise that all models are necessarily incomplete and somewhat in
error; and the system being modelled may have inherent variability or
un-measurability in its behaviour. Despite these limitations, the systems
approach has a great utility and future potential for assessing seismic performance
of civil infrastructure and for more effective seismic risk management
and decision making.

Primary role and purpose of risk analysis and management are to quantify
uncertainty and facilitate sound and effi cient decision making. Risk
management is a process of weighting alternatives (options) and selecting
the most appropriate action by integrating the results of risk assessment
with engineering data as well as social/economic/political factors to reach
an acceptable decision. Generally, the risk assessment/analysis process
involves objectivity, whereas risk management involves preferences and
attitudes which have both objective and subjective elements. In seismic risk
analysis and loss estimation, uncertainties are prevalent in hazard assessment,
ground condition, ground motion prediction equations, building stock
and infrastructure exposure, and vulnerability of infrastructure. Typology
and defi nition of uncertainty within the engineering community are broad.
In risk analysis, uncertainty can be categorised into aleatory and epistemic
uncertainty. Aleatory uncertainty (variability) is due to natural heterogeneity
or stochasticity of a physical process and it cannot be reduced, while
epistemic uncertainty is due to ignorance or subjectivity, which can be
reduced with availability of more information. Therefore, consideration of
uncertainty in any risk analysis is unavoidable, and modelling and treatment
of epistemic uncertainties are critically important.

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Informasi Detail

Judul Seri

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No. Panggil

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Penerbit

Oxford : Woodhead Publishing Limited., 2013

Deskripsi Fisik

xiv, 884 Hlm.

Bahasa

English

ISBN/ISSN

978-0-85709-898-6

Klasifikasi

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Tipe Isi

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Tipe Media

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Tipe Pembawa

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Edisi

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Subjek

TEKNIK SIPIL

Info Detail Spesifik

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Pernyataan Tanggungjawab

agus

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