Dynamic Risk Analysis in the Chemical and Petroleum Industry focuses on bridging the gap between research and industry by responding to the following questions: What are the most relevant developments of risk analysis? How can these studies help industry in the prevention of major accidents? Paltrinieri and Khan provide support for professionals who plan to improve risk analysis by introducing innovative techniques and exploiting the potential of data share and process technologies. This concrete reference within an ever-growing variety of innovations will be most helpful to process safety managers, HSE managers, safety engineers and safety engineering students. This book is divided into four parts. The Introduction provides an overview of the state-of-the-art risk analysis methods and the most up-to-date popular definitions of accident scenarios. The second section on Dynamic Risk Analysis shows the dynamic evolution of risk analysis and covers Hazard Identification, Frequency Analysis, Consequence Analysis and Establishing the Risk Picture. The third section on Interaction with Parallel Disciplines illustrates the interaction between risk analysis and other disciplines from parallel fields, such as the nuclear, the economic and the financial sectors. The final section on Dynamic Risk Management addresses risk management, which may dynamically learn from itself and improve in a spiral process leading to a resilient system. Helps dynamic analysis and management of risk in chemical and process industry Provides industry examples and techniques to assist you with risk- based decision making Addresses also the human, economic and reputational aspects composing the overall risk picture

This book deals with the state-of-the-art of physical security knowledge and research in the chemical and process industries. Legislation differences between Europe and the USA are investigated, followed by an overview of the how, what and why of contemporary security risk assessment in this particular industrial sector. Innovative solutions such as attractiveness calculations and the use of game theory, advancing the present science of adversarial risk analysis, are discussed. The book further stands up for developing and employing dynamic security risk assessments, for instance based on Bayesian networks, and using OR methods to truly move security forward in the chemical and process industries.

The accelerated growth of the world population creates an increase of energy needs. This requires new paths for oil supply to its users, which can be potential hazardous sources for individuals and the environment. Risk Analysis for Prevention of Hazardous Situations in Petroleum and Natural Gas Engineering explains the potential hazards of petroleum engineering activities, emphasizing risk assessments in drilling, completion, and production, and the gathering, transportation, and storage of hydrocarbons. Designed to aid in decision-making processes for environmental protection, this book is a useful guide for engineers, technicians, and other professionals in the petroleum industry interested in risk analysis for preventing hazardous situations.

The tragic incident at Bhopal, India made it clear that safetyreviews for identification and control of accidents involving toxicchemicals must be more systematic. This guide shows how tointegrate hazard identification, risk assessment, consequenceanalysis, and risk mitigation into a formalized program forhandling hazardous chemicals. Most of the 21 contributors aresenior staff members at Stone & Webster EngineeringCorporation. They discuss how to perform and supervise safetystudies for chemical, petrochemical, petroleum refining, and otherfacilities. They discuss all aspects of detection, prevention, andmitigation of risks associated with processing, handling, andproduction of hazardous chemicals. Special attention is given tohazard identification and hazard assessment techniques ranging fromsimple screening checklists to highly structured Hazard andOperability (HAZOP) analysis. You're shown how to calculatepotential consequences of identified hazards, quantify thelikelihood of these events, and combine equipment failure rate dataand human reliability analysis with hazard assessment. You'll alsobenefit from the book's rundowns of how to * apply expert systems and artificial intelligence in riskmanagement * instill safety-oriented operating and maintenanceprocedures * train operators and emergency response personnel * conduct internal and external safety audits * perform chemical dispersion, explosion, and fire analyses * assess health effects from chemical releases * use insurance vehicles to deal with residual risk. Risk Assessment and Risk Management for the Chemical ProcessIndustry is an essential source on minimizing the dangers of toxicincidents and accidents. It is essential reading for safetyengineers, regulatory managers, environmental engineers, and otherprofessionals responsible for safety in chemical plants.

In oil/gas and chemical industries, dynamics is one of the most essential characteristics of any process. Time-dependent response is involved in most steps of both the physical/engineering processes and the equipment performance. The conventional Quantitative Risk Assessment (QRA) is unable to address the time dependent effect in such dynamic processes. In this dissertation, a methodology of Dynamic Operational Risk Assessment (DORA) is developed for operational risk analysis in oil/gas and chemical industries. Given the assumption that the component performance state determines the value of parameters in process dynamics equations, the DORA probabilistic modeling integrates stochastic modeling and process dynamics modeling to evaluate operational risk. The stochastic system-state trajectory is modeled based on the abnormal behavior or failure of the components. For each of the possible system-state trajectories, a process dynamics evaluation is carried out to check whether process variables, e.g., level, flow rate, temperature, pressure, or chemical concentration, remain in their desirable regions. Monte Carlo simulations are performed to calculate the probability of process variable exceeding the safety boundaries. Component testing/inspection intervals and repair time are critical parameters to define the system-state configuration; and play an important role for evaluating the probability of operational failure. Sensitivity analysis is suggested to assist selecting the DORA probabilistic modeling inputs. In this study, probabilistic approach to characterize uncertainty associated with QRA is proposed to analyze data and experiment results in order to enhance the understanding of uncertainty and improve the accuracy of the risk estimation. Different scenarios on an oil/gas separation system were used to demonstrate the application of DORA method, and approaches are proposed for sensitivity and uncertainty analysis. Case study on a knockout drum in the distillation unit of a refinery process shows that the epistemic uncertainty associated with the risk estimation is reduced through Bayesian updating of the generic reliability information using plant specific real time testing or reliability data. Case study on an oil/gas separator component inspection interval optimization illustrates the cost benefit analysis in DORA framework and how DORA probabilistic modeling can be used as a tool for decision making. DORA not only provides a framework to evaluate the dynamic operational risk in oil/gas and chemical industries, but also guides the process design and optimization of the critical parameters such as component inspection intervals.

Methods in Chemical Process Safety, Volume Four focuses on the process of learning from experience, including elements of process safety management, human factors in the chemical process industries, and the regulation of chemical process safety, including current approaches. Users will find this book to be an informative tool and user manual for process safety for a variety of professionals with this new release focusing on Advanced Methods of Risk Assessment and Management, Logic Based Methods for Dynamic Risk Assessment, Bayesian Methods for Dynamic Risk Assessment, Data Driven Methods, Rare Event Risk Assessment, Risk Management and Multi Criteria, and much more. Helps acquaint the reader/researcher with the fundamentals of process safety Provides the most recent advancements and contributions on the topic from a practical point-of-view Presents users with the views/opinions of experts in each topic Includes a selection of authors who are leading researchers and/or practitioners for each given topic

Safety and Reliability – Theory and Applications contains the contributions presented at the 27th European Safety and Reliability Conference (ESREL 2017, Portorož, Slovenia, June 18-22, 2017). The book covers a wide range of topics, including: • Accident and Incident modelling • Economic Analysis in Risk Management • Foundational Issues in Risk Assessment and Management • Human Factors and Human Reliability • Maintenance Modeling and Applications • Mathematical Methods in Reliability and Safety • Prognostics and System Health Management • Resilience Engineering • Risk Assessment • Risk Management • Simulation for Safety and Reliability Analysis • Structural Reliability • System Reliability, and • Uncertainty Analysis. Selected special sessions include contributions on: the Marie Skłodowska-Curie innovative training network in structural safety; risk approaches in insurance and fi nance sectors; dynamic reliability and probabilistic safety assessment; Bayesian and statistical methods, reliability data and testing; oganizational factors and safety culture; software reliability and safety; probabilistic methods applied to power systems; socio-technical-economic systems; advanced safety assessment methodologies: extended Probabilistic Safety Assessment; reliability; availability; maintainability and safety in railways: theory & practice; big data risk analysis and management, and model-based reliability and safety engineering. Safety and Reliability – Theory and Applications will be of interest to professionals and academics working in a wide range of industrial and governmental sectors including: Aeronautics and Aerospace, Automotive Engineering, Civil Engineering, Electrical and Electronic Engineering, Energy Production and Distribution, Environmental Engineering, Information Technology and Telecommunications, Critical Infrastructures, Insurance and Finance, Manufacturing, Marine Industry, Mechanical Engineering, Natural Hazards, Nuclear Engineering, Offshore Oil and Gas, Security and Protection, Transportation, and Policy Making.