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Deliberate attacks (security attacks) pose a significant threat to offshore Oil&Gas critical infrastructures as they have the potential of triggering major event scenarios with severe consequences on people, property, and the surrounding environment. The standards API RP 70 and API RP 70I address security issues in the offshore Oil&Gas sector, providing a semi-quantitative approach to evaluate the actual level of security risk. However, as the credibility of security attacks grows, security risk assessments should be approached in a more systematic and quantitative way to measure vulnerabilities and determine the level of protection available in the site. In this context, the present study introduces a systematic quantitative procedure using Bayesian Network (BN) to calculate the probability of success of physical attacks and the role of preventive and mitigative response strategies. The procedure is applied to a case study allowing to show its potential for improving security in the offshore Oil&Gas industry. [ABSTRACT FROM AUTHOR]

Accidents triggered by natural events are becoming an increasing issue for policy-makers and industrial practitioners in the last decades. These events are called Natech (natural hazards triggering technological disasters), and their study is critical due to an increase in both the frequency and the magnitude of the consequences. Considering the possible failure of safety systems and the several equipment items potentially involved in the accidents due to the occurrence of multiple simultaneous failures and cascading events, the emergency response results to be a crucial aspect in the risk assessment and management of Natech events. Despite this, the emergency response can also be affected by the occurrence of natural events. The purpose of the present work is to understand the effects of natural events on emergency response. To reach this goal, some relevant past accidents are studied. The result of the analysis allows highlighting the effects of the natural events on the emergency response. Moreover, lessons learned on the critical elements of the emergency response are derived when considering Natech accidents and related cascading events. [ABSTRACT FROM AUTHOR]

At the OCI Nitrogen ammonia plant, located at the Chemelot site in Geleen, The Netherlands, a project has been initiated to monitor major accident processes at the site. This contribution answers the question whether indicators can be derived from the barrier system status to provide information about the development and likelihood of the major accident processes in the ammonia production process. The accident processes are visualized as scenarios in bowties. This research focuses on the status of the preventive barriers on the so called 'left-hand side' of the bowtie, before a hazard becomes uncontrollable. Both the quality - expressed in reliability/availability and effectiveness - and the activation of the barrier system give an indication of the development of the accident scenarios and the likelihood of the central event. This likelihood is calculated as a loss of risk reduction compared to the original design. The calculation gives in an indicator called "preventive barrier indicator", which should initiate further action. Based on an example, it is demonstrated which actions should be taken and their urgency. [ABSTRACT FROM AUTHOR]

Due to the rapid development of technology, process systems become dynamic, automated, and complex, resulting in the strong interdependence and interaction among components and ensuring system safety by conventional methods a challenge. Compared with traditional risk assessment methods, resilience assessment is a more appropriate method for ensuring the safety of process systems under uncertain disruptions. Resilience refers to absorbing and adapting to changing conditions and recovering from disruptions. This paper presents a comprehensive assessment model that combines the catastrophe theory (CT) with the dynamic Bayesian network (DBN) to measure dynamic resilience. Firstly, the CT is employed to quantify the intensity of disruptions. Subsequently, the performance response function (PRF) of the system is determined by DBN. A resilience metric is then introduced to measure system resilience under uncertain disruptions. The method is demonstrated through a release prevention barrier system. [ABSTRACT FROM AUTHOR]

Safety and security barriers are implemented in various forms to protect chemical plants from undesired accidents and mitigate the disastrous consequences. However, the necessity and rationality of integrating safety and security barriers need to be investigated, and the difficulty in integrated management of safety and security barriers is still a challenge. In this study, the research status of integrated safety and security barrier management are reviewed before the necessity, and theoretical ground for integrating security and safety barriers are elaborated. Then, a unified classification of safety and security barriers is proposed to benefit the collection of performance indicator-related data and further support the performance assessment of safety and security barriers. Finally, a framework for integrated management of safety and security barriers is suggested to support the integrated management of safety and security barriers. [ABSTRACT FROM AUTHOR]

Industrial accidents triggered by natural disasters (Natech events) pose huge threats to chemical clusters. Flood is a significant cause of Natech events, the interactions between flood and chemical installations may lead to complex accident scenarios. However, the chemical clusters are often not well prepared for flood Natech events due to the lack of guidance on how to implement prevention and mitigation measures. In this paper, the characteristics of flood Natech events are firstly discussed, which provide a clear understanding of accident evolution. Based on the review of several Chinese standards related to flood prevention in chemical clusters, corresponding requirements are summarized. The requirements mainly focus on the planning and design stages. To cope with flood Natech events in a long-term vision, a comprehensive safety framework for chemical clusters is proposed in this article considering a resilient viewpoint, in which different roles of government, chemical cluster, and chemical plant are discussed. Moreover, three sub-models are divided to manage safety measures before, during, and after accidents, contributing to improving the resisting ability, adaptability, and recoverability of chemical clusters to flood Natech events, respectively. [ABSTRACT FROM AUTHOR]

Chemical process industries are threatened with accidental and intentional adverse events because of the storage and operation of large quantities of hazardous substances. Safety and security barriers play important roles in protecting the chemical plants from safety and security-related undesired events and mitigating the potentially catastrophic consequences. Aiming to identify major accident scenarios in terms of both safety and security and determine the corresponding safety and security barriers, a novel approach based on MIMAH (methodology for identifying major accident hazards) and historical data analysis is proposed. In this approach, the MIMAH is extended to identify accident scenarios related to safety, physical security, and cyber security by using a combination of bow-tie analysis and attack tree analysis. Then, data analysis is conducted to supplement the identified major accident scenarios before the critical safety and security barriers can be identified and illustrated based on an integrated bow-tie and attack tree model. This study helps to identify major hazards considering both safety and security perspectives and supports the integrated assessment and management of safety and security barriers in the chemical process industries. [ABSTRACT FROM AUTHOR]

Data uncertainties caused by the lack of knowledge and nature variation or randomness present vital challenges to domino effects modelling. To improve the assessment of the propagation probabilities and consequences of the domino-effect accidents, the influence of various types of uncertainties on risk assessment results needs to be investigated. However, a systematic identification of data uncertainties in domino effects has not been studied yet. In the current study, the data uncertainties in different categories (accidental, Natech, and intentional) of domino events are identified thoroughly based on historical data and literature. Meanwhile, the possible sources of the identified uncertainties are analysed by considering the environment, safety management, and operation factors. Finally, we discuss possible solutions to model uncertainties in risk assessments of domino effects. This study is a pilot study for uncertainty analysis and helps to identify the critical uncertainties that are of necessity to be considered in the domino effect risk assessments. [ABSTRACT FROM AUTHOR]

Hazardous events in process plants like the leakage of dangerous substances can result in severe damage, and such an event is often defined as the TOP event of a fault tree analysis (FTA) in a quantitative risk analysis. The TOP event probability can then be calculated if the basic events probabilities are provided. These probabilities are often determined based on generic reliability data which do not necessarily reflect the operational and environmental characteristics of a plant of interest. This paper presents an approach based on Bayesian network (BN) analysis to explicitly include experience data collected during the plant operation to make the generic probabilities more plant specific. The approach is illustrated via a pressure vessel containing a toxic substance in an Ammonia production plant. In this case study, the failure rate distribution in the BN is updated as the new information becomes available during plant operation. The results show that the suggested approach effectively reflects the operating experience of a specific plant. [ABSTRACT FROM AUTHOR]

The experience gathered from normal industrial operations allows us to associate its degrading conditions with the potential for an accident. Such association is the basis for the definition of the system risk and appropriate safety measures. If a skilled operator observes further degrading conditions, his/her mind quickly learns from this new experience, derives an updated risk level, and tunes the safety measures. Similarly, safety management techniques aim to construct a risk model while learning from past and new observations with the purpose to warn of an imminent accident. However, the model can be tested only in hindsight, after the occurrence (or the missed occurrence) of an accident. How can we generalise and model the risk analysis learning process? How can we optimise its configuration towards new observations? This study discusses these issues of meta-learning for safety management by considering the case study of a drive-off scenario involving an oil and gas drilling rig, for which a risk assessment approach based on machine learning is developed. The results indicate the way forward for a generalisation of risk analysis learning processes and their optimisation. [ABSTRACT FROM AUTHOR]

Earthquakes, floods and other natural disasters can lead to serious fires, explosions and other technical disasters, called Natech events, possibly triggering domino effects in chemical industrial parks. However, current studies only look at Natech events or domino effects separately, and don't consider domino effects triggered by Natech events with multiple primary accidents and with higher order accidents. This paper presents a method aiming to obtain all possible paths and probabilities of domino effects triggered by Natech events. Firstly, our suggested method is obtained by integrating conventional assessment frameworks for Natech events and domino effects. Secondly, the method is solved by a Matlab program based on (i) the scenario matrix, (ii) the scenario escalation matrix, and (iii) the path cell array. Finally, the method is illustrated and its availability is verified by a real chemical tank farm which suffered from a flood. The results show that this method can obtain and rank all the possible paths and their probabilities. Furthermore, the cumulative probabilities of each higher order level of domino effect and each tank can be obtained for a subsequent quantitative risk assessment considering both Natech events and their resulting domino effects. [ABSTRACT FROM AUTHOR]

Risk analysis in process systems is very important to design effective strategies for preventing and mitigating potential major accidents. Although conventional techniques as Bow-tie (BT) have widely been used in risk assessment of process systems, they fall short in effectively modelling epistemic uncertainty which is prevailing in risk assessment of process systems. The present study is aimed at alleviating this shortcoming by incorporating fuzzy set theory into BT, developing a so-called fuzzy extended Bow tie (FEBT) model. FEBT, compared with previous fuzzy BT methods, uses the intuitionistic fuzzy numbers and thus provides a more accurate cause - consequence model of accident scenarios. A natural gas transmission network is used to demonstrate the application of FEBT. [ABSTRACT FROM AUTHOR]

In recent years, many companies stepped up security efforts in chemical and process facilities. The need for the implementation of technological and organizational measures is accompanied by an increased attention for the human factor of the company's security policy. In order to create a strong security culture, a high level of security awareness among employees is needed. The aim of this paper is to measure the impact of a training session on the level of security awareness. Based on the results of a quantitative research, the effectiveness regarding the security knowledge, attitude and behavior.of employees is measured. [ABSTRACT FROM AUTHOR]

Industrial safety performance has, for a long time, been the domain of health and safety specialists, measuring injury and absenteeism rates to discover patterns and trying to prevent accidents from happening. The drawback of this approach is that safety is reactive to accidents, mostly caused by operations. As a result, safety (performance) has become the reverse side of operations (performance) and is often seen as a hinderance in making the best possible profit for organisations. However, now already for a period of time, industries have become aware of the possible benefits of a more proactive approach towards safety. Therefore, increasingly more organisations are looking for more proactive methods in measuring and achieving safety performance. As a result, in recent years, important efforts have been undertaken to improve the understanding of safety culture and safety climate and how to measure these concepts in organisations, for instance in the process industry and chemical plants. Likewise, substantial efforts have been made to determine and develop a wide range of leading and lagging safety indicators that can reflect and predict safety performance. While developing leading indicators and making culture measurements are helpful, they both measure safety conditions indirectly. Because, an organisational culture or climate can be regarded as a specific indicator of a possible future performance, in the same way leading safety indicators aim to predict the future. Yet, little tools are currently available for the instant measuring of actual safety conditions and performance in organisations, providing information that allows for benchmarking between different sectors and industries. Nevertheless, when safety and its opposite "unsafety" are carefully defined, it becomes imaginable to develop tools that instantly measure the safety performances and actual safety situations in organisations so that they can be used for benchmarking regardless of sector or industry. In this article we will expound this way of thinking, based on an original paradigm about safety, unsafety and performance. [ABSTRACT FROM AUTHOR]

Accident investigations in process industry indicate that inadequate barrier management has been one of the main causes of many major accidents. Barriers degrade over time and at different rates, and these degradations may gradually and unnoticeably drift the system towards a state of high risk. Conventional barrier management approaches apply fixed inspection and maintenance intervals with little direct influence on daily operations to evaluate safety barriers performance. Such issues are addressed by the dynamic barrier management (DBM) concept through the combination of all available information, such as inspection, preventive maintenance, audit, sensors, process control, and near misses or incident records. DBM main goal is to infer barrier status in near real-time and evaluate its impact on risk level. However, the framework for DBM is not detailed and easy to implement and therefore requires further development to clarify the steps. An approach based on system thinking is suggested. Systems engineering (SE) is a suitable approach for managing complex problems by considering the big picture and the SPADE framework from SE is applied to provide a practical roadmap for DBM. [ABSTRACT FROM AUTHOR]

Research was carried out in an ammonia plant of OCI Nitrogen, located at the Chemelot site in Geleen, The Netherlands. It focuses on the development of process safety accident processes in which loss of mechanical integrity is one of the root causes. A significant share of the mechanical integrity scenarios originate from corrosion mechanisms which develop over a relatively long time period, possibly taking months, years or even longer before turning into an event. Based on an example, a failure mechanism is worked out and visualized using a bow tie. Bow-ties have shown a good visual representation of the 'early warnings' and the barriers in place. The monitoring of the 'early warnings' and barriers can provide information about the current probability of the scenario in order to intervene prematurely. [ABSTRACT FROM AUTHOR]

Monitoring progress of accident scenarios, and effectiveness of control measures is a main goal of safety indicators. From an overview of scientific literature one may conclude that indicators do not logically relate to current safety theories and models, their relation with accident processes is far from perfect, and a 'silver bullet' has not been identified yet. Professional literature shows another picture, and divides indicators in leading and lagging. This distinction seems convincing. Not only companies, but also regulations adopted this division. Currently many indicators used in industry generate a number, while the relation with accident processes is questionable at least. In addition, it can be expected that regulators of major hazard companies will ask to identify and implement both lagging and leading indicators, and anchor these indicators in a safety management system. The subject 'safety indicators' will remain in the spotlight in the time to come. This presentation will focus on a review of scientific and professional literature. This article is written in 'praesens historicum', and based upon recent articles (Oostendorp et al., 2016, Swuste et al., 2010, 2014, 2016 a,b, 2018). [ABSTRACT FROM AUTHOR]

Past accident surveys reveal that loading and unloading operations (LUOs) are responsible for 11% of firerelated domino accidents. This study investigates the domino accidents during LUOs in the last two decades and identifies the main causes and features of these domino effects. An index-based approach is proposed to assess these domino effects, measuring the periodic escalation capability of installations. The proposed escalation capability index takes into account the special features being present in these accidents, including the spread of vapor cloud due to delayed ignition, multiple fires caused by vapor cloud explosion (VCE), the quantity variation of hazardous substances, and the change of primary event risk due to operations. From a risk management view, an emergency strategy is proposed to tackle the risk caused by LUOs. Therefore, this methodology can identify the most critical areas with regard to the starting or escalating of domino events during LUOs and support the decision-making of alert levels. [ABSTRACT FROM AUTHOR]

In order to control occupational accidents, it is crucial to have a clear view on the potential accident scenarios that are present in a company. The bow-tie method is a way to capture and visualise these accident processes in an integrative way. Included in the bow-tie are safety barriers (both technical as organisational and human) and management delivery systems that can intervene in these accident processes. Once bowties are composed, they are an excellent point of departure to assign indicators to the safety barriers and management delivery systems in order to control (i.e. prevent or mitigate) the accident scenarios. Two types of indicators can be distinguished. Firstly, there are general indicators that are linked to management delivery systems interrupting multiple accident scenarios, and which can yield a higher safety gain (as they intervene in multiple accident scenarios). Secondly, there are scenario-specific indicators targeting one specific accident scenario, and which can be valuable as they target a specific safety problem in the company. Some crucial aspects have to be taken into account when using indicators, such as sequentiality in follow-up and prioritization of indicators, and the focus on quality rather than quantity. [ABSTRACT FROM AUTHOR]