Modelling of BP Texas City refinery accident using dynamic risk assessment approach

Process industries involve handling of hazardous substances which on release may potentially cause catastrophic consequences in terms of assets lost, human fatalities or injuries and loss of public confidence of the company. In spite of using endless end-of-the-pipe safety systems, tragic accidents such as BP Texas City refinery still occur. One of the main reasons of such rare but catastrophic events is lack of effective monitoring and modelling approaches that provide early warnings and help to prevent such event. To develop a predictive model one has to rely on past occurrence data, as such events are rare, enough data are usually not available to better understand and model such behavior. In such situations, it is advisable to use near misses and incident data to predict system performance and estimate accident likelihood. This paper is an attempt to demonstrate testing and validation of one such approach, dynamic risk assessment, using data from the BP Texas City refinery incident.Dynamic risk assessment is a novel approach which integrates Bayesian failure updating mechanism with the consequence assessment. The implementation of this methodology to the BP Texas City incident proves that the approach has the ability to learn from near misses, incident, past accidents and predict event occurrence likelihood in the next time interval.     

A quantitative risk management framework for dust and hybrid mixture explosions

Dust and hybrid-mixture explosions continue to occur in industrial processes that handle fine powders and flammable gases. Considerable research is therefore conducted throughout the world with the objective of both preventing the occurrence and mitigating the consequences of such events. In the current work, research has been undertaken to help move the field of dust explosion prevention and mitigation from its current emphasis on hazards (with an accompanying reliance on primarily engineered safety features) to a focus on risk (with an accompanying reliance on hierarchical, risk-based, decision-making tools). Employing the principles of quantitative risk assessment (QRA) of dust and hybrid-mixture explosions, a methodological framework for the management of these risks has been developed.The QRA framework is based on hazard identification via credible accident scenarios for dust explosions, followed by probabilistic fault-tree analysis (using Relex – Reliability Excellence – software) and consequence severity analysis (using DESC – Dust Explosion Simulation Code – software). Identification of risk reduction measures in the framework is accomplished in a hierarchical manner by considering inherent safety measures, passive and active engineered devices, and procedural measures (in that order). An industrial case study is presented to show how inherent safety measures such as dust minimization and dust/process moderation can be helpful in reducing dust and hybrid-mixture explosion consequences in a 400-m³ polyethylene storage silo.     

Dynamic risk assessment using failure assessment and Bayesian theory

To ensure the safety of a process system, engineers use different methods to identify the potential hazards that may cause severe consequences. One of the most popular methods used is quantitative risk assessment (QRA) which quantifies the risk associated with a particular process activity. One of QRA's major disadvantages is its inability to update risk during the life of a process. As the process operates, abnormal events will result in incidents and near misses. These events are often called accident precursors. A conventional QRA process is unable to use the accident precursor information to revise the risk profile. To overcome this, a methodology has been proposed based on the work of Meel and Seider (2006). Similar to Meel and Seider (2006) work, this methodology uses Bayesian theory to update the likelihood of the event occurrence and also failure probability of the safety system. In this paper the proposed methodology is outlined and its application is demonstrated using a simple case study. First, potential accident scenarios are identified and represented in terms of an event tree, next, using the event tree and available failure data end-state probabilities are estimated. Subsequently, using the available accident precursor data, safety system failure likelihood and event tree end-state probabilities are revised. The methodology has been simulated using deterministic (point value) as well as probabilistic approach. This Methodology is applied to a case study demonstrating a storage tank containing highly hazardous chemicals. The comparison between conventional QRA and the results from dynamic failure assessment approach shows the significant deviation in system failure frequency throughout the life time of the process unit.     

Fire and explosion assessment on oil and gas floating production storage offloading (FPSO): An effective screening and comparison tool

Fires and explosions have been identified as major potential hazards for Oil and Gas Floating Production Storage Offloading (FPSO) installations and pose risk to personnel, assets, and the environment. Current fire and explosion assessment (FEA) tools require physical effect modeling software and follows standards from API, ISO, and engineering practices. However, the tools are not specific to any particular system such as an FPSO, and do not provide comprehensive guidance for safety engineers to perform FEA.This paper discusses the development of a screening and comparison tool for FEA on FPSOs and the incorporation of an expert system into the tool. The results are computerized using MS Excel/VBA to provide a structured and comprehensive assessment on each equipment and module handling natural gas, crude oil, methanol and diesel on FPSO topsides.This tool features built-in calculations for jet and pool fire size estimation for gas/liquid releases, and the ability to perform Quantitative Risk Analysis (QRA) to specify the personnel and equipment risk for varying leak sizes and process conditions. Control and recovery measures are incorporated as an expert system based on report findings, engineering practices, and relevant standards. Bowtie analysis is applied in the tool to define detailed control and recovery measures for the FPSO based on the incident scenarios. An explosion assessment is performed by incorporating physical effect modeling software results.Unique features provided in the tool include fire and radiation contour mapping on an FPSO layout to help determine personnel and equipment risk more accurately and fire pump sizing that can be used to verify the amount of water deluge system required to mitigate fires and explosions. In addition, flexibility of data input (process data, failure rate data, etc.) and user interfaces assist safety engineers to screen and compare process alternatives, check design quality, and evaluate design options at any design stage.     

A new look at release event frequencies

Within the context of a quantitative risk analysis (QRA), the two main constituents used to describe petrochemical risks are, and have always been, consequence and probability. The consequences of hazardous material accidents are easy to apprehend – if a hazard is realized it can injure people or cause fatalities, damage equipment or other assets, or cause environmental damage. Frequencies for these consequences, on the other hand, are not as easy to understand. Process safety professionals develop event frequencies by evaluating historical data and calculating incident rates, which represent, in the QRA context, how often a release of a hazardous material has occurred. Incident rates are further modified by probabilities for various hole sizes, release orientations, weather conditions, ignition timing, and other factors, to arrive at unique event probabilities that are applied in the QRA. This paper describes the development of incident rates from historical database information for various equipment types, as well as defining a methodology for assigning hole size probabilities from the same data, such that a hole size distribution can be assigned within each QRA study. The combination of total incident rates and a hole size distribution relationship can then serve as a foundation within the frequency side of many QRA studies.     

Inherent risk assessment—A new concept to evaluate risk in preliminary design stage

Quantitative Risk Assessment (QRA) has been a very popular and useful methodology which is widely accepted by the industry over the past few decades. QRA is typically carried out at a stage where complete plant has been designed and sited. At that time, the opportunity to include inherent safety design features is limited and may incur higher cost. This paper proposes a new concept to evaluate risk inherent to a process owing to the chemical it uses and the process conditions. The risk assessment tool is integrated with process design simulator (HYSYS) to provide necessary process data as early as the initial design stages, where modifications based on inherent safety principles can still be incorporated to enhance the process safety of the plant. The risk assessment tool consists of two components which calculate the probability and the consequences relating to possible risk due to major accidents. A case study on the potential explosion due to the release of flammable material demonstrates that the tool is capable to identify potential high risk of process streams. Further improvement of the process design is possible by applying inherent safety principles to make the process under consideration inherently safer. Since this tool is fully integrated with HYSYS, re-evaluation of the inherent risk takes very little time and effort. The new tool addresses the lack of systematic methodology and technology, which is one of the barriers to designing inherently safer plants.     

Does your facility have a dust problem: Methods for evaluating dust explosion hazards

The hazards of dust explosions prevailing in plants are dependent on a large variety of factors that include process parameters, such as pressure, temperature and flow characteristics, as well as equipment properties, such as geometry layout, the presence of moving elements, dust explosion characteristics and mitigating measures. A good dust explosion risk assessment is a thorough method involving the identification of all hazards, their probability of occurrence and the severity of potential consequences. The consequences of dust explosions are described as consequences for personnel and equipment, taking into account consequences of both primary and secondary events.While certain standards cover all the basic elements of explosion prevention and protection, systematic risk assessments and area classifications are obligatory in Europe, as required by EU ATEX and Seveso II directives. In the United States, NFPA 654 requires that the design of the fire and explosion safety provisions shall be based on a process hazard analysis of the facility, process, and the associated fire or explosion hazards. In this paper, we will demonstrate how applying such techniques as SCRAM (short-cut risk analysis method) can help identify potentially hazardous conditions and provide valuable assistance in reducing high-risk areas. The likelihood of a dust explosion is based on the ignition probability and the probability of flammable dust clouds arising. While all possible ignition sources are reviewed, the most important ones include open flames, mechanical sparks, hot surfaces, electric equipment, smoldering combustion (self-ignition) and electrostatic sparks and discharges. The probability of dust clouds arising is closely related to both process and dust dispersion properties.Factors determining the consequences of dust explosions include how frequently personnel are present, the equipment strength, implemented consequence-reducing measures and housekeeping, as risk assessment techniques demonstrate the importance of good housekeeping especially due to the enormous consequences of secondary dust explosions (despite their relatively low probability). The ignitibility and explosibility of the potential dust clouds also play a crucial role in determining the overall risk.Classes describe both the likelihood of dust explosions and their consequences, ranging from low probabilities and limited local damage, to high probability of occurrence and catastrophic damage. Acceptance criteria are determined based on the likelihood and consequence of the events. The risk assessment techniques also allow for choosing adequate risk reducing measures: both preventive and protective. Techniques for mitigating identified explosions risks include the following: bursting disks and quenching tubes, explosion suppression systems, explosion isolating systems, inerting techniques and temperature control. Advanced CFD tools (DESC) can be used to not only assess dust explosion hazards, but also provide valuable insight into protective measures, including suppression and venting.     

Quantitative risk analysis of urban natural gas pipeline networks using geographical information systems

This paper presents a novel quantitative risk analysis process for urban natural gas pipeline networks using geographical information systems (GIS). The process incorporates an assessment of failure rates of integrated pipeline networks, a quantitative analysis model of accident consequences, and assessments of individual and societal risks. Firstly, the failure rates of the pipeline network are calculated using empirical formulas influenced by parameters such as external interference, corrosion, construction defects, and ground movements. Secondly, the impacts of accidents due to gas leakage, diffusion, fires, and explosions are analyzed by calculating the area influenced by poisoning, burns, and deaths. Lastly, based on the previous analyses, individual risks and social risks are calculated. The application of GIS technology helps strengthen the quantitative risk analysis (QRA) model and allows construction of a QRA system for urban gas pipeline networks that can aid pipeline management staff in demarcating high risk areas requiring more frequent inspections.     

Incorporating inherent safety during the conceptual process design stage: A literature review

This paper reviews principal concepts, tools, and metrics for risk management and Inherently Safer Design (ISD) during the conceptual stage of process design. Even though there has been a profusion of papers regarding ISD, the targeted audience has typically been safety engineers, not process engineers. Thus, the goal of this paper is to enable process engineers to use all the available design degrees of freedom to mitigate risk early enough in the design process. Mainly, this paper analyzes ISD and inherent safety assessment tools (ISATs) from the perspective of inclusion in conceptual process design. The paper also highlights the need to consider safety as a major component of process sustainability. In this paper, 73 ISATs were selected, and these tools were categorized into three groups: hazard-based inherent safety assessment tools (H-ISATs) for 22 tools, risk-based inherent safety assessment tools (R-ISATs) for 33 tools, and cost-optimal inherent safety assessment tools (CO-ISATs) for 18 tools. This paper also introduces an integrated framework for coordinating the conventional process design workflow with safety analysis at various levels of detail.     

Application of dynamic risk analysis in offshore drilling processes

Process safety is the common global language used to communicate the strategies of hazard identification, risk assessment and safety management. Process safety is identified as an integral part of process development and focuses on preventing and mitigating major process accidents such as fires, explosions, and toxic releases in process industries. Accident probability estimation is the most vital step to all quantitative risk assessment methods. Drilling process for oil is a hazardous operation and hence safety is one of the major concerns and is often measured in terms of risk. Dynamic risk assessment method is meant to reassess risk in terms of updating initial failure probabilities of events and safety barriers, as new information are made available during a specific operation. In this study, a Bayesian network model is developed to represent a well kick scenario. The concept of dynamic environment is incorporated by feeding the real-time failure probability values (observed at different time intervals) of safety barriers to the Bayesian network in order to obtain the corresponding time-dependent variations in kick consequences. This study reveals the importance of real-time monitoring of safety barrier performances and quantitatively shows the effect of deterioration of barrier performance on kick consequence probabilities. The Macondo blowout incident is used to demonstrate how early warnings in barrier probability variations could have been observed and adequately managed to prevent escalation to severe consequences.     

Past,present and future of Quantitative Risk Assessment (QRA) and the incentive it obtained from Land-Use Planning (LUP)

This paper tells the story about the development of Quantitative Risk Assessment, how it was conceptualized in the early 1970s in the nuclear industry, how it was employed within the chemical industry soon after, and what its status is today. The different purposes of QRA are explained, and we elaborate on one of the purposes, that is, Land-Use Planning. The role of Professor Ben Ale, as a process safety pioneer, is discussed throughout the history. We finally provide some on-going state-of-the-art research and projects to further improve QRA approaches, and we sketch the future of QRA and its relation with LUP.     

Quantitative assessment of domino scenarios by a GIS-based software tool

A software procedure was developed for the quantitative assessment of domino effect. The procedure was based on a systematic methodology for the identification of domino scenarios and for the assessment of consequences and expected frequencies of the escalation events. A geographical information system (GIS) platform was interfaced to the domino assessment software. The implementation of plant lay-out data to the GIS allowed the automatic identification of the possible targets of escalation effects by the software procedure, and a straightforward calculation of the contribution to individual and societal risk indexes caused by the possible domino scenarios. The procedure was applied to the analysis of several case-studies based on actual plant lay-outs. The results evidenced that the approach allows the quantitative assessment of risk caused by escalation events with a limited additional effort with respect to that required by a conventional QRA. The use of a GIS-based software was a key element in the limitation of the effort required for the quantitative assessment of domino scenarios. Moreover, the results of the case-studies pointed out that the estimation of risk increase due to domino events is an important tool for an effective assessment and control of industrial risk in chemical and process plants.     

Case study: T2 Laboratories explosion

A tragic explosion resulting from a runaway chemical reaction occurred at the T2 Laboratories, Inc. facility in December 2007. The U.S. Chemical Safety Board (CSB) completed an incident investigation of the T2 explosion, identifying the root cause as a failure to recognize the runaway reaction hazard associated with the chemical it was producing. Understanding the consequences of process upset conditions is critical to determine risk. This paper will focus on lessons learned from this incident including a comprehensive hazard assessment for reactive chemicals as well as proper collection and application of adiabatic calorimetry data to characterize the chemical reaction and determine appropriate mitigation strategies. Examples will be provided to establish safer operating conditions, implement safeguards and reduce the overall risk.     

Operational risk assessment: A case of the Bhopal disaster

Accidental releases of hazardous chemicals from process facilities can cause catastrophic consequences. The Bhopal disaster resulting from a combination of inherently unsafe designs and poorly managed operations is a well-known case. Effective risk modeling approaches that provide early warnings are helpful to prevent and control such rare but catastrophic events. Probability estimation of these events is a constant challenge due to the scarcity of directly relevant data. Therefore, precursor-based methods that adopt the Bayesian theorem to update prior judgments on event probabilities using empirical data have been proposed. The updated probabilities are then integrated with consequences of varying severity to produce the risk profile.This paper proposes an operational risk assessment framework, in which a precursor-based Bayesian network approach is used for probability estimation, and loss functions are applied for consequence assessment. The estimated risk profile can be updated continuously given real-time operational data. As process facilities operate, this method integrates a failure-updating mechanism with potential consequences to generate a real-time operational risk profile. The real time risk profile is valuable in activating accident prevention and control strategies. The approach is applied to the Bhopal accident to demonstrate its applicability and effectiveness.     

Bi-directional connectivity diagram for accident propagation analysis considering the interactions between multiple-process units

An incident may propagate to an accident with different severity dependent on its propagation scenarios. Since the accident propagation is a two-way process, the current research is focusing on the one-way analysis. This paper aims to analyze the combined effect of multi-units sources and their interactions during the accident propagation. The bi-directional connectivity diagram (BDCD) is applied to visualize the interactions between multiple process units as hazardous sources. The deployed safety barriers interrupt the connection between the hazardous sources and thus minimize the influence of one BDCD node on another. Through which, the accident propagation is reduced. The proposed method can be suitable to the general accidents, and it is applied to a case study of the LNG terminal station to assess the potential consequences of explosion caused by the leakage, in which the cost of the safety barrier is also considered. The BDCD approach is found more effective than traditional single-hazardous source methods for analyzing the accident propagation of multi-units sources in the chemical plant and achieving intrinsic safety.     

A new simple methodology for evaluation of explosion risk in underground coal mines

The key objective of this paper is the presentation of a new risk assessment tool for underground coal mines based on a simplified semi-quantitative estimation and assessment method.In order to determine the risk of explosion of any work process or activity in underground coal mines it is necessary to assess the risk. The proposed method is based on a Risk Index obtained as a product of three factors: frequency of each individual scenario P_ucm, associated severity consequences C_ucm and exposure time to explosive atmospheres E_ucm. The influence of exposure time is usually not taken into account up to now. Moreover, the exposure to explosive atmospheres may affect factors of hazardous event probability as much as its consequences. There are many definitions of exposure to explosive atmospheres but in the case of underground coal mines the exposure is defined as frequency risk of firedamp and coal dust. The risk estimation and risk assessment are based on the developed of a risk matrix.The proposed methodology allows not only the estimation of the explosion risk but also gives an approach to decide if the proposal investment is well-justified or not in order to improve safety.     

An engineer-based methodology to perform Explosion Risk Analyses

Explosion Risk Analyses (ERA) are usually performed as part of the Quantitative Risk Assessment (QRA). The combination of frequencies and associated consequences allow to get a risk picture of the facility and provides decision support to the risk owner. The outcomes of this study allow also to provide, after adequate interpretation, Design Explosion Loads (DEL) to engineering disciplines (e.g. structures, piping and equipment) according to a given Risk Acceptance Criterion (RAC). For most of the offshore applications, the consequence part of the ERA is done with Computational Fluids Dynamics (CFD) to properly handle congestion and confinement effects as simple models cannot. With the increase of computational power, thanks to Moore's Law, there is an increasing trend to perform more and more CFD simulations with the expectation to improve confidence in results while taking more and more probabilistic variables into account. In the early 2000s, it was 10's of simulations, in the 2010s, it was 100's and now it is common to reach 1000's. However, one should remark that there is still a lot of uncertainties behind these studies since the geometry maturity is generally not enough especially at the early stage of detailed engineering when the preliminary Design Explosion Loads (pDEL) should be provided to disciplines. Anticipated congestion is normally put in the model, but it usually put a bias at the beginning of the consequence modelling part. In the risk-based approach, the frequency part is also of major importance. One need to keep in mind that consequence refinement should be done in close relation with the frequency refinement to ensure consistency in the approach. The practical methodology presented in this paper was developed to provide reliable inputs to engineering disciplines, taking into consideration uncertainties and potential spread of results while using a reasonable number of CFD scenarios. Finally, the safety engineers are still the key contributor in the performance of the ERA, and hence brain-based design is kept in the loop while minimizing computer-based design.