Enrico Zio – författare

Explores methods for the representation and treatment of uncertainty in risk assessment

In providing guidance for practical decision-making situations concerning high-consequence technologies (e.g., nuclear, oil and gas, transport, etc.), the theories and methods studied in Uncertainty in Risk Assessment have wide-ranging applications from engineering and medicine to environmental impacts and natural disasters, security, and financial risk management. The main focus, however, is on engineering applications.

While requiring some fundamental background in risk assessment, as well as a basic knowledge of probability theory and statistics, Uncertainty in Risk Assessment can be read profitably by a broad audience of professionals in the field, including researchers and graduate students on courses within risk analysis, statistics, engineering, and the physical sciences.

Uncertainty in Risk Assessment:

Explores methods for the representation and treatment of uncertainty in risk assessment

In providing guidance for practical decision-making situations concerning high-consequence technologies (e.g., nuclear, oil and gas, transport, etc.), the theories and methods studied in Uncertainty in Risk Assessment have wide-ranging applications from engineering and medicine to environmental impacts and natural disasters, security, and financial risk management. The main focus, however, is on engineering applications.

While requiring some fundamental background in risk assessment, as well as a basic knowledge of probability theory and statistics, Uncertainty in Risk Assessment can be read profitably by a broad audience of professionals in the field, including researchers and graduate students on courses within risk analysis, statistics, engineering, and the physical sciences.

Uncertainty in Risk Assessment:

This book offers a comprehensive overview of recently developed methods for assessing and optimizing system reliability. It consists of two main parts, for treating assessment methods and optimization methods, respectively.

The first part covers methods of multi-state system reliability modelling and evaluation, Markov processes, Monte Carlo simulation and uncertainty analysis. The methods considered range from piecewise-deterministic Markov processes to belief function analysis. The second part covers optimization methods of mathematical programming and evolutionary algorithms, and problems of multi-objective optimization and optimization under uncertainty. The methods of this part range from non-dominated sorting genetic algorithm to robust optimization.

The book also includes the application of the assessment and optimization methods considered on real case studies, particularly with respect to the reliability assessment and optimization of renewable energy systems, and bridges the gap between theoretical method development and engineering practice.

This book offers a comprehensive overview of recently developed methods for assessing and optimizing system reliability. It consists of two main parts, for treating assessment methods and optimization methods, respectively.

The first part covers methods of multi-state system reliability modelling and evaluation, Markov processes, Monte Carlo simulation and uncertainty analysis. The methods considered range from piecewise-deterministic Markov processes to belief function analysis. The second part covers optimization methods of mathematical programming and evolutionary algorithms, and problems of multi-objective optimization and optimization under uncertainty. The methods of this part range from non-dominated sorting genetic algorithm to robust optimization.

The book also includes the application of the assessment and optimization methods considered on real case studies, particularly with respect to the reliability assessment and optimization of renewable energy systems, and bridges the gap between theoretical method development and engineering practice.

Exciting new developments in risk assessment and management

Risk assessment and management is fundamentally founded on the knowledge available on the system or process under consideration. While this may be self-evident to the laymen, thought leaders within the risk community have come to recognize and emphasize the need to explicitly incorporate knowledge (K) in a systematic, rigorous, and transparent framework for describing and modeling risk.

Featuring contributions by an international team of researchers and respected practitioners in the field, this book explores the latest developments in the ongoing effort to use risk assessment as a means for characterizing knowledge and/or lack of knowledge about a system or process of interest. By offering a fresh perspective on risk assessment and management, the book represents a significant contribution to the development of a sturdier foundation for the practice of risk assessment and for risk-informed decision making.

How should K be described and evaluated in risk assessment? How can it be reflected and taken into account in formulating risk management strategies? With the help of numerous case studies and real-world examples, this book answers these and other critical questions at the heart of modern risk assessment, while identifying many practical challenges associated with this explicit framework. 

This book, written by international scholars and leaders in the field, and edited to make coverage both conceptually advanced and highly accessible:

Knowledge of Risk Assessment and Management is a must-read for risk assessment and management professionals, as well as graduate students, researchers and educators in the field. It is also of interest to policy makers and business people who are eager to gain a better understanding of the foundations and boundaries of risk assessment, and how its outcomes should be used for decision-making.

Exciting new developments in risk assessment and management

Risk assessment and management is fundamentally founded on the knowledge available on the system or process under consideration. While this may be self-evident to the laymen, thought leaders within the risk community have come to recognize and emphasize the need to explicitly incorporate knowledge (K) in a systematic, rigorous, and transparent framework for describing and modeling risk.

Featuring contributions by an international team of researchers and respected practitioners in the field, this book explores the latest developments in the ongoing effort to use risk assessment as a means for characterizing knowledge and/or lack of knowledge about a system or process of interest. By offering a fresh perspective on risk assessment and management, the book represents a significant contribution to the development of a sturdier foundation for the practice of risk assessment and for risk-informed decision making.

How should K be described and evaluated in risk assessment? How can it be reflected and taken into account in formulating risk management strategies? With the help of numerous case studies and real-world examples, this book answers these and other critical questions at the heart of modern risk assessment, while identifying many practical challenges associated with this explicit framework. 

This book, written by international scholars and leaders in the field, and edited to make coverage both conceptually advanced and highly accessible:

Knowledge of Risk Assessment and Management is a must-read for risk assessment and management professionals, as well as graduate students, researchers and educators in the field. It is also of interest to policy makers and business people who are eager to gain a better understanding of the foundations and boundaries of risk assessment, and how its outcomes should be used for decision-making.

Safety and Reliability of Complex Engineered Systems contains the Proceedings of the 25th European Safety and Reliability Conference, ESREL 2015, held 7-10 September 2015 in Zurich, Switzerland. Including 570 papers on theories and methods in the area of risk, safety and reliability, and their applications to a wide range of industrial, civil and social sectors, this book will be of interest to academics and professionals involved or interested in aspect of risk, safety and reliability in various engineering areas.

Safety and Reliability of Complex Engineered Systems contains the Proceedings of the 25th European Safety and Reliability Conference, ESREL 2015, held 7-10 September 2015 in Zurich, Switzerland. Including 570 papers on theories and methods in the area of risk, safety and reliability, and their applications to a wide range of industrial, civil and social sectors, this book will be of interest to academics and professionals involved or interested in aspect of risk, safety and reliability in various engineering areas.

The Handbook of RAMS in Railway Systems: Theory and Practice addresses the complexity in today''s railway systems, which use computers and electromechanical components to increase efficiency while ensuring a high level of safety. RAM (Reliability, Availability, Maintainability) addresses the specifications and standards that manufacturers and operators have to meet. Modeling, implementation, and assessment of RAM and safety requires the integration of railway engineering systems; mathematical and statistical methods; standards compliance; and financial/economic factors. This Handbook brings together a group of experts to present RAM and safety in a modern, comprehensive manner.

The Handbook of RAMS in Railway Systems: Theory and Practice addresses the complexity in today''s railway systems, which use computers and electromechanical components to increase efficiency while ensuring a high level of safety. RAM (Reliability, Availability, Maintainability) addresses the specifications and standards that manufacturers and operators have to meet. Modeling, implementation, and assessment of RAM and safety requires the integration of railway engineering systems; mathematical and statistical methods; standards compliance; and financial/economic factors. This Handbook brings together a group of experts to present RAM and safety in a modern, comprehensive manner.

Monte Carlo simulation is one of the best tools for performing realistic analysis of complex systems as it allows most of the limiting assumptions on system behavior to be relaxed. The Monte Carlo Simulation Method for System Reliability and Risk Analysis comprehensively illustrates the Monte Carlo simulation method and its application to reliability and system engineering. Readers are given a sound understanding of the fundamentals of Monte Carlo sampling and simulation and its application for realistic system modeling.

Whilst many of the topics rely on a high-level understanding of calculus, probability and statistics, simple academic examples will be provided in support to the explanation of the theoretical foundations to facilitate comprehension of the subject matter. Case studies will be introduced to provide the practical value of the most advanced techniques.

This detailed approach makes The Monte Carlo Simulation Method for System Reliability and Risk Analysis a key reference for senior undergraduate and graduate students as well as researchers and practitioners. It provides a powerful tool for all those involved in system analysis for reliability, maintenance and risk evaluations.

This handbook analyzes and develops methods and models to optimize solutions for energy access (for industry and the general world population alike) in terms of reliability and sustainability. With a focus on improving the performance of energy systems, it brings together state-of-the-art research on reliability enhancement, intelligent development, simulation and optimization, as well as sustainable development of energy systems. It helps energy stakeholders and professionals learn the methodologies needed to improve the reliability of energy supply-and-demand systems, achieve more efficient long-term operations, deal with uncertainties in energy systems, and reduce energy emissions.

Highlighting novel models and their applications from leading experts in this important area, this book will appeal to researchers, students, and engineers in the various domains of smart energy systems and encourage them to pursue research and development in this exciting and highly relevant field.