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This book covers the application of algebraic inequalities for
reliability improvement and for uncertainty and risk reduction. It
equips readers with powerful domain-independent methods for
reducing risk based on algebraic inequalities and demonstrates the
significant benefits derived from the application for risk and
uncertainty reduction. Algebraic inequalities: * Provide a powerful
reliability improvement, risk and uncertainty reduction method that
transcends engineering and can be applied in various domains of
human activity * Present an effective tool for dealing with deep
uncertainty related to key reliability-critical parameters of
systems and processes * Permit meaningful interpretations which
link abstract inequalities with the real world * Offer a tool for
determining tight bounds for the variation of risk-critical
parameters and complying the design with these bounds to avoid
failure * Allow optimising designs and processes by minimising the
deviation of critical output parameters from their specified values
and maximising their performance This book is primarily for
engineering professionals and academic researchers in virtually all
existing engineering disciplines.
For a long time, conventional reliability analyses have been
oriented towards selecting the more reliable system and preoccupied
with maximising the reliability of engineering systems. On the
basis of counterexamples however, we demonstrate that selecting the
more reliable system does not necessarily mean selecting the system
with the smaller losses from failures! As a result, reliability
analyses should necessarily be risk-based, linked with the losses
from failures.
Accordingly, a theoretical framework and models are presented which
form the foundations of the reliability analysis and reliability
allocation linked with the losses from failures.
An underlying theme in the book is the basic principle for a
risk-based design: the larger the cost of failure associated with a
component, the larger its minimum necessary reliability level. Even
identical components should be designed to different reliability
levels if their failures are associated with different losses.
According to a classical definition, the risk of failure is a
product of the probability of failure and the cost given failure.
This risk measure however cannot describe the risk of losses
exceeding a maximum acceptable limit. Traditionally the losses from
failures have been 'accounted for' by the average production
availability (the ratio of the actual production capacity and the
maximum production capacity). As demonstrated in the book by using
a simple counterexample, two systems with the same production
availability can be characterised by very different losses from
failures.
As an alternative, a new aggregated risk measure based on the
cumulative distribution of the potential losses has been
introducedand the theoretical framework for risk analysis based on
the concept potential losses has also been developed. This new risk
measure incorporates the uncertainty associated with the exposure
to losses and the uncertainty in the consequences given the
exposure. For repairable systems with complex topology, the
distribution of the potential losses can be revealed by simulating
the behaviour of systems during their life-cycle. For this purpose,
fast discrete event-driven simulators are presented capable of
tracking the potential losses for systems with complex topology,
composed of a large number of components. The simulators are based
on new, very efficient algorithms for system reliability analysis
of systems comprising thousands of components.
An important theme in the book are the generic principles and
techniques for reducing technical risk. These have been classified
into three major categories: preventive (reducing the likelihood of
failure), protective (reducing the consequences from failure) and
dual (reducing both, the likelihood and the consequences from
failure). Many of these principles (for example: avoiding
clustering of events, deliberately introducing weak links, reducing
sensitivity, introducing changes with opposite sign, etc.) are
discussed in the reliability literature for the first time.
Significant space has been allocated to component reliability. In
the last chapter of the book, several applications are discussed of
a powerful equation which constitutes the core of a new theory of
locally initiated component failure by flaws whose number is a
random variable.
This book has been written with the intention to fill two big gaps
in the reliability and riskliterature: the risk-based reliability
analysis as a powerful alternative to the traditional reliability
analysis and the generic principles for reducing technical risk. I
hope that the principles, models and algorithms presented in the
book will help to fill these gaps and make the book useful to
reliability and risk-analysts, researchers, consultants, students
and practising engineers.
- Offers a shift in the existing paradigm for conducting
reliability analyses.
- Covers risk-based reliability analysis and generic principles for
reducing risk.
- Provides a new measure of risk based on the distribution of the
potential losses from failure as well as the basic principles for
risk-based design.
- Incorporates fast algorithms for system reliability analysis and
discrete-event simulators.
- Includes the probability of failure of a structure with complex
shape expressed with a simple equation.
Repairable flow networks are a new area of research, which
analyzes the repair and flow disruption caused by failures of
components in static flow networks. This book addresses a gap in
current network research by developing the theory, algorithms and
applications related to repairable flow networks and networks with
disturbed flows. The theoretical results presented in the book lay
the foundations of a new generation of ultra-fast algorithms for
optimizing the flow in networks after failures or congestion, and
the high computational speed creates the powerful possibility of
optimal control of very large and complex networks in real time.
Furthermore, the possibility for re-optimizing the network flows in
real time increases significantly the yield from real production
networks and reduces to a minimum the flow disruption caused by
failures. The potential application of repairable flow networks
reaches across many large and complex systems, including active
power networks, telecommunication networks, oil and gas production
networks, transportation networks, water supply networks, emergency
evacuation networks, and supply networks.
The book reveals a fundamental flaw in classical algorithms for
maximising the throughput flow in networks, published since the
creation of the theory of flow networks in 1956. Despite the years
of intensive research, the classical algorithms for maximising the
throughput flow leave highly undesirable directed loops of flow in
the optimised networks. These flow loops are associated with
wastage of energy and resources and increased levels of congestion
in the optimised networks.
Includes theory and practical examples to build a deep
understanding of the issuesWritten by the leading scholar and
researcher in this emerging fieldFeatures powerful software tools
for analysis, optimization and control of repairable flow
networks"
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