Dynamic risk assessment of process facilities using advanced probabilistic approaches

A process accident can escalate into a chain of accidents, given the degree of congestion and complex arrangement of process equipment and pipelines. To prevent a chain of accidents, (called the domino effect), detailed assessments of risk and appropriate safety measures are required. The present study investigates available techniques and develops an integrated method to analyze evolving process accident scenarios, including the domino effect. The work presented here comprises two main contributions: a) a predictive model for process accident analysis using imprecise and incomplete information, and b) a predictive model to assess the risk profile of domino effect occurrence. A brief description of each is presented below. In recent years the Bayesian network (BN) has been used to model accident causation and its evolution. Though widely used, conventional BN suffers from two major uncertainties, data and model uncertainties. The former deals with the used of evidence theory while the latter uses canonical probabilistic models. High interdependencies of chemical infrastructure makes it prone to the domino effect. This demands an advanced approach to monitor and manage the risk posed by the domino effect is much needed. Given the dynamic nature of the domino effect, the monitoring and modelling methods need to be continuous time-dependent. A Generalized Stochastic Petrinet (GSPN) framework was chosen to model the domino effect. It enables modelling of an accident propagation pattern as the domino effect. It also enables probability analysis to estimate risk profile, which is of vital importance to design effective safety measures

The domino effect and integrated probabilistic approaches for risk analysis

International audienceThe paper develops a probabilistic approach in order to deal with domino effects that may occur in industrial facilities : an explosion or accident may generate various sets of projectiles that may impact other existing facilities (tanks under high-pressure, etc) and may generate other sets of projectiles and so on. Three main parts are considered : 1- Source term : for the first set of generated projectiles, probabilistic distributions are considered for the number, masses, velocities, departure angles, geometrical form, dimensions, and constitutive materials properties. The authors have collected existing models from the literature. 2- Target term : for the set of impacted targets, probabilistic distributions are considered for the number of impacting projectiles, velocities, incidence angles and energy at impact, constitutive materials properties, dimensions of the impacted targets, and projectiles penetration depths into the targets. In this paper, new models for the impact are proposed to calculate the penetration depth after impact : case of cylindrical rods impacting rectangular plates, both are metal made. The theoretical results are compared to the experimental data (4 data sets) collected from the literature with the following features : projectiles mass ranging from 0.1g up to 250 kg, projectiles velocity ranging from 10 m/s up to 2100 m/s, projectiles diameters ranging from 1.5 mm up to 90 mm, target strength ranging from 300 MPa up to 1400 MPa and incidence angles ranging from 0 degree up to 70 degrees. 3- Domino effect term : evaluation of the risks of second set of explosions that may take place in the impacted components. Monte Carlo simulations are used in order to calculate the different probabilities : probability of impact, distribution of the penetration depth and probability of domino effect

Risk assessment of fire accidents in chemical and hydrocarbon processing industry

Fire disasters are among the most dangerous accidents in the chemical and hydrocarbon processing industry. Fires have been the source of major accidents such as the Piper Alpha disaster (1976), the BP Texas City disaster (2005), the Buncefield oil depot fire (2005), Puerto Rico’s fire accident (2009), and the Jaipur fire accident (2009). The catastrophic impact of fire accidents necessitates a detailed understanding of the mechanisms of their occurrence and evolution in a complex engineering system. Detailed understanding will help develop fire prevention and control strategies. This thesis aims to provide a detailed understanding of fire risk in the hydrocarbon production and processing industry. In order to realize this objective, the work presented in the thesis includes three parts: i) Developing a procedure to study potential fire accident scenarios in an offshore facility with different ignition source locations. This procedure helps to design safety measures. The effectiveness of safety measures is verified using a computational fluid dynamics (CFD) code. This work emphasizes that an FLNG layout must be considered with the utmost care since it is the most effective measure in limiting a potential LNG release and subsequent dispersion effect, and directly influences the fire dynamics and thus limits the potential damage. ii) An integrated probabilistic model for fire accident analysis considering the time-dependent nature of the fire is developed. The developed model captures the dynamics of fire evolution using three distinct techniques Bayesian networks, Petri Nets, and a CFD model. The Bayesian network captures the logical dependence of fire causation factors. The Petri Net captures the time-dependent evolution of a fire scenario. The CFD model captures the dimension and impact of the fire accident scenario. The results in this work show that a time-dependent probability analysis model is necessary for fire accidents. iii) Whether fire alone can cause a domino effect is demystified in the last work. A solid-flame model is used in a CFD framework to calculate the escalation vector for a domino effect; escalation probability is assessed using a probit model. The results demonstrate that a pool fire alone sometimes may not cause a domino effect in the current industry. It is other factors, such as explosion and hydrocarbon leakage, work together with a pool fire to escalate into a domino event, for example, the results shown in the case study of the Jaipur fire accident

QRA with respect to domino effects and property damage

In 1996 the European Union adopted the Seveso II Directive. The Directive stated actions to be taken in the process industry in order to prevent and limit the impact of serious chemical accidents. In the Directive it is clearly stated that domino effects shall be considered, but the level of detail required is not specified. Due to that fact and the high degree of complexity linked to domino effects, these aspects are mostly dealt with in a qualitative manner. Such approach leads to subjective assessments and is highly dependent on simplified assumptions, leading to results that may be questionable. Thus, it would be beneficial to develop a method that incorporates the risk of domino effects in a quantitative risk analysis (QRA), which has been the aim of this thesis. The method was developed based on a literature review of existing research. Focus was on integrating domino effects as a natural part of a QRA without compromising the timeframe associated to a QRA. The developed method has been applied in a case study of an oil refinery in order to evaluate how well it is applicable in practise. During the case study, the method has proven to enable the risk of property damage with regard to domino effects to be quantitatively analysed. The results from the case study, evidence the importance of taking domino effects into consideration in QRAs, as the risk may be underestimated if not

Quantitative Assessment of Safety Barrier Performance in the Prevention of Cascading Events

PresentationThe prevention of high-impact low-probability (HILP) events in industrial clusters or complex industrial areas where critical infrastructures are present critically depends on the presence and the performance of safety barriers that may have the potential to prevent escalation. In recent years a set of tools and models were developed for the quantitative assessment of risk due to cascading events and domino scenarios. The aim of the present study is the integration of tools for risk assessment with a specific approach allowing a detailed assessment of safety barrier performance. A LOPA (layer of protection analysis) based methodology, aimed at the definition and quantification of safety barrier performance in the prevention of escalation was developed. The method allowed the quantitative characterization of alternative mitigated and unmitigated escalation scenarios. Data were collected on the more common types of safety barriers aimed at the prevention of fire escalation. An example of application was developed, allowing the quantitative assessment of risk mitigation of cascading events triggered by fire escalation based on the assessment of safety barrier performance

A canonical theory of dynamic decision-making

Decision-making behavior is studied in many very different fields, from medicine and eco- nomics to psychology and neuroscience, with major contributions from mathematics and statistics, computer science, AI, and other technical disciplines. However the conceptual- ization of what decision-making is and methods for studying it vary greatly and this has resulted in fragmentation of the field. A theory that can accommodate various perspectives may facilitate interdisciplinary working. We present such a theory in which decision-making is articulated as a set of canonical functions that are sufficiently general to accommodate diverse viewpoints, yet sufficiently precise that they can be instantiated in different ways for specific theoretical or practical purposes. The canons cover the whole decision cycle, from the framing of a decision based on the goals, beliefs, and background knowledge of the decision-maker to the formulation of decision options, establishing preferences over them, and making commitments. Commitments can lead to the initiation of new decisions and any step in the cycle can incorporate reasoning about previous decisions and the rationales for them, and lead to revising or abandoning existing commitments. The theory situates decision-making with respect to other high-level cognitive capabilities like problem solving, planning, and collaborative decision-making. The canonical approach is assessed in three domains: cognitive and neuropsychology, artificial intelligence, and decision engineering

Safety of atmospheric storage tanks during accidental explosions

International audienceThe occurrence of a chain reaction from blast on atmospheric storage tanks in oil and chemical facilities is hard to predict. The current French practice for SEVESO facilities ignores projectiles and assumes a critical peak overpressure value observed from accident data. This method could lead to conservative or dangerous assessments. This study presents various simple mechanical models to facilitate quick effective assessment of risk analysis, the results of which are compared with the current practice. The damage modes are based on experience of the most recent accidents in France. Uncertainty propagation methods are used in order to evaluate the sensitivity and the failure probability of global tank models for a selection of overpressure signatures. The current work makes use of these evaluations to demonstrate the importance of a dynamic analysis to study domino effects in accidents.L'occurrence de réaction en chaîne, dite réaction par effets dominos, sur les réservoirs de stockage atmosphérique suite à une explosion accidentelle dans les installations pétrochimiques est difficile à prévoir. La pratique actuelle française pour les installations SEVESO consiste à ignorer les projectiles et à assumer une valeur de surpression maximale admissible pour les effets de souffle. Cette méthode est susceptible de conduire à des évaluations conservatrices ou dangereuses. Cette étude présente divers modèles mécaniques simples pouvant permettre une évaluation efficace et rapide des risques d'effet dominos. Les modes de comportement des réservoirs sont basées sur l'expérience des plus récents accidents en France. Plusieurs méthodes de propagation des incertitudes sont utilisées afin d'évaluer les sensibilités et la probabilité de défaillance des modèles de réservoir pour une sélection de signaux de surpression. L'étude aboutie sur la sélection de paramètres et de modèles dynamiques pertinents pour l'étude des effets dominos

Numerical Model of Fragmentation Hazards Caused by a Tank Explosion

The paper analyses the fragmentation of a horizontal cylindrical tank caused by the effect of boiling liquid expanding vapour explosion (BLEVE). A fragmentation model for identification of kinematic parameters is proposed. The originality of the model lies in the introduction of initial acceleration. Using this model, the initial velocity can be assessed without knowing the values of explosion energy and the mass of fragments. The application of this model reduces the uncertainty in assessing the range of fragments and the risk of fragmentation. The initial acceleration of fragments generated in an explosion is assessed according to the geometry and type of the tank material. The initial acceleration, which does not depend on the kinematic parameters of the constant wall thickness of the tank, allows a reliable assessment of the launch angle of a fragment. Characteristic forms of the fragment trajectory are identified, depending on the aerodynamic and thrust acceleration coefficients, and probability distributions of the fragment ranges are given. Relevant factors in the assessment of fragmentation hazards include the trajectory of a fragment, the height of a target and its distance from the tank. It was concluded that aerodynamic fragments at distances of up to 50 m are not a danger to targets of up to 15 m high. Fragments with high air resistance and low thrust can endanger targets of the same height at distances of over 200 m. The presented fragmentation model includes the effect of heating due to the BLEVE effect and can be applied to all types of tanks

Quantitative evaluation of the safety barriers to prevent fired domino effect

A simplified methodology was developed for the assessment of fire protection barriers and to support the Quantitative Risk Assessment (QRA) of industrial facilities. Given a generic fire scenario, the aim of the methodology was to evaluate the probability of fire damages on industrial equipment both considering the availability and effectiveness of the protective barriers. Fire protections for industrial equipment were first classified, and then literature reliability data were used to build a dataset of Probability of Failure on Demand (PFD) for each protection type. Next, the effectiveness was determined from specific studies and surveys available in the literature. For passive protections, the effectiveness evaluation was based on the protective barrier response to fire. A case study was presented and discussed in order to exemplify the methodology implementation and to show the potential application in simplified QRA studies

Methodology for probabilistic tsunami-triggered oil spill fire hazard assessment based on Natech cascading disaster modeling

A novel modeling methodology is presented for cascading disasters triggered by tsunami hazards considering uncertainties. The proposed methodology focuses on tsunami-triggered oil spills and subsequent fires, a type of natural hazard-triggered technological (Natech) event. The methodology numerically simulates the time-varying behavior of tsunami-triggered oil spill fires for numerous stochastically generated scenarios and performs a probabilistic mapping of the maximum radiative heat flux as a quantitative measure of the fire hazard. To enable these assessments, probabilistic tsunami hazard assessments are extended to include the tsunami-induced movement of oil storage tanks, resulting oil spills, tsunami-driven oil fire spread, and thermal radiation from fires. The uncertainty of the earthquake fault slip distribution, oil filling level of storage tanks, and fire starting time and position is incorporated into the new assessments. To demonstrate the methodology, a realistic case study is conducted for a coastal petrochemical industrial park in Japan conditioned on possible offshore moment magnitude 9.1 earthquakes. Contrary to typical tsunami direct impact assessments, the results highlight the cascading effects of tsunamis and large variability in key output variables concerning oil spills and fires. This indicates that the methodology is useful for deepening stakeholders’ understanding of tsunami-triggered cascading disasters and improving risk reduction plans