Impact of downward releases on the risk profile in hydrocarbon process plants

2020 ◽  
Vol 60 (1) ◽  
pp. 82
Author(s):  
Fariba Askari ◽  
Colin Crowley ◽  
Hojat Kord
Keyword(s):  
Risk Assessment ◽  
Sensitivity Analysis ◽  
High Pressure ◽  
Risk Profile ◽  
Quantitative Risk Assessment ◽  
Consequence Analysis ◽  
Simplifying Assumptions ◽  
Process Plants ◽  
The Cost

Quantitative risk assessment (QRA) calculations for major hazard installations often involve consequence analysis calculations for thousands of events, and therefore, some simplifying assumptions are generally required. The simplifications are usually designed to make the analysis reasonably practicable and reduce the cost of the QRA. Nevertheless, the overall methodology and the applied parameters should be chosen conservatively to cover possible uncertainties. One of the key assumptions in many QRAs is the release direction, which is usually assumed to be horizontal. This is generally assumed to provide a conservative representation of all other possible release directions, which may occur vertically (upward or downward) or at an angle. A sensitivity analysis has been performed and presented in this paper to investigate how different release direction assumptions affect the results of consequence analysis, and eventually, QRA outcomes, i.e. individual and societal risk results. A high-pressure hydrocarbon system is considered as a case study and SNC-Lavalin’s (formerly Atkins) in-house QRA software, ‘RiskTool’, has been used to carry out the QRA modelling. The overall conclusion is that the assumption that all releases are horizontal may lead to a significant underprediction of risks for some types of high-pressure release events. This is because an unimpeded horizontal jet may entrain air, and hence, dilute much more rapidly than a jet that impinges on the ground or nearby obstacles.

On the Use of Proper Fragility Models for Quantitative Seismic Risk Assessment of Process Plants in Seismic Prone Areas

2017 ◽  
Author(s):  
Silvia Alessandri ◽  
Antonio C. Caputo ◽  
Daniele Corritore ◽  
Giannini Renato ◽  
Fabrizio Paolacci ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Seismic Risk ◽  
Structural Damage ◽  
Fragility Curves ◽  
Probabilistic Method ◽  
Quantitative Risk Assessment ◽  
Actual Process ◽  
Consequence Analysis ◽  
Process Plant ◽  
Process Plants

Quantitative Risk Assessment (QRA) is a classical method for the calculation of risk in process plants, which is based on the logic of the consequence analysis. This intrinsically probabilistic method has been thought for classical accident conditions, where the damage events and the relevant consequences start from a preselected component and a standard loss of containment (LOC) and follow all possible scenarios for the calculation of individual and societal risk. This final risk metric is usually expressed in terms of probability of fatality in a specific location of the surrounding area or a certain number of fatalities in the area surrounding the accident. In presence of Na-Tech events, like earthquakes, a multi-source condition can be caused by multi-damage conditions simultaneously involving more than one equipment, which in turn can generate a multiple-chain of events and consequences. In literature, several attempts of modifying the classic QRA approach to account for this important aspect have been formalized without converging toward a unified approach. In this paper, a fragility-based method for Quantitative Seismic Risk Analysis (QSRA) of a process plant is investigated. This method takes into account all possible damage/losses of containment conditions in the most critical equipment, e.g., storage tanks. Fragility curves, which are analytically evaluated for each unit with respect to its seismic damage conditions, are utilized inside the procedure. The Monte Carlo Simulation (MCS) method is then used with the aim to follow all steps of QSRA. In particular, starting from the seismic hazard curve of the site where the plant is placed, a multi-level approach is proposed. In this approach, the first level is represented by the components seismically damaged, whereas the following levels are treated through a classical consequence analysis, including the propagation of multiple simultaneous and interacting chains of accidents. These latter are applied by defining proper correspondences for all relevant equipment between structural damage (i.e., limit states) and LOC events. The application of the method to an actual process plant permits to investigate its high potentiality and the dependency of the risk assessment from the proper fragility models.

Seismic Quantitative Risk Assessment of Process Plants Through Monte Carlo Simulations

2016 ◽  
Author(s):  
Silvia Alessandri ◽  
Antonio C. Caputo ◽  
Daniele Corritore ◽  
Renato Giannini ◽  
Fabrizio Paolacci
Keyword(s):  
Risk Assessment ◽  
Monte Carlo ◽  
Seismic Risk ◽  
Quantitative Risk Assessment ◽  
Damage Propagation ◽  
Process Plants ◽  
Physical Effects ◽  
Level 1 ◽  
Level I ◽  
Seismic Hazard Curve

This paper describes the application of Monte Carlo method for the quantitative seismic risk assessment (QSRA) of process plants. Starting from the seismic hazard curve of the site where the plant is located, the possible chains of accidents are modelled using a sequence of propagation levels in which Level 0 is represented by the components directly damaged by the earthquake whereas the subsequent Levels represent the resulting consequence propagation. In greater detail all units damaged by energy and materials releases from level 0 units are included in level 1 and so forth, so that referring to process units belonging to a generic i-th Level, they are damaged by level (i-1) units and damage units of level (i+1). The sequence of levels represents the damage propagation across the plant through any multiple interacting sequences of accidents. For each unit a damage (DM) - loss of containment (LOC) matrix is generated allowing to estimate the amount of energy and material releases as well as resulting physical effects based on which the scenario at i-th level is generated. The process stops when no further damage propagation is allowed.

Probability risk assessment of landslides: A case study at Finneidfjord

2008 ◽  
Vol 45 (9) ◽  
pp. 1250-1267 ◽  
Author(s):  
Mark J. Cassidy ◽  
Marco Uzielli ◽  
Suzanne Lacasse
Keyword(s):  
Risk Assessment ◽  
Probabilistic Approach ◽  
Quantitative Risk Assessment ◽  
Historical Case Study ◽  
Historical Case ◽  
Second Moment ◽  
Integrated Risk Assessment ◽  
First Order Second Moment ◽  
Probabilistic Risk Assessments

Probabilistic risk assessments are increasingly being considered the most appropriate framework for engineers to systematically base decisions on hazard mitigation issues. This paper aims to show the advantages of a quantitative risk assessment by application to a historical case study. The generalized integrated risk assessment framework has been applied retrospectively to a submarine landslide that occurred in 1996 near the village of Finneidfjord in northern Norway. Over 1 million cubic metres of predominantly quick clay was displaced. Even though it was triggered underwater on the embankment of the Sørfjord, the retrogressive nature of the slide resulted in it encroaching 100–150 m inland. The triggering mechanism is believed to have been the placement of fill, from a nearby tunnelling project, on the foreshore of the embankment. This paper is a retrospective quantitative evaluation of the risk to the neighbouring houses, the persons in those houses, and the persons in open spaces caused by the placement of increasing levels of embankment fill. A probabilistic approach, making use of second-moment modelling and first-order second-moment approximation is adopted. It aims to demonstrate the advantages of this type of risk assessment in understanding complex and integrated hazards, particularly those in populated environments.

Numerical Simulation of Seismic Risk and Loss Propagation Effects in Process Plants: An Oil Refinery Case Study

2017 ◽  
Author(s):  
Antonio C. Caputo ◽  
Alessandro Vigna
Keyword(s):  
Risk Assessment ◽  
Seismic Risk ◽  
Production Capacity ◽  
Industrial Process ◽  
Oil Refinery ◽  
Quantitative Methodology ◽  
Seismic Risk Assessment ◽  
Technical Standards ◽  
Process Plants

Process plants are vulnerable to natural hazards and, in particular, to earthquakes. Nevertheless, the quantitative assessment of seismic risk of process plants is a complex task because available methodologies developed in the field of civil and nuclear engineering are not readily applicable to process plants, while technical standards and regulations do not establish any procedure for the overall seismic risk assessment of industrial process plants located in earthquake-prone areas. This paper details the results of a case study performing a seismic risk assessment of an Italian refinery having a 85,000 barrels per day production capacity, and a storage capacity of over 1,500,000 m3. The analysis has been carried out resorting to a novel quantitative methodology developed in the framework of a European Union research program (INDUSE 2 SAFETY). The method is able to systematically generate potential starting scenarios, deriving from simultaneous interactions of the earthquake with each separate equipment, and to account for propagation of effects between distinct equipment (i.e. Domino effects) keeping track of multiple simultaneous and possibly interacting chains of accidents. In the paper the methodology, already described elsewhere, is briefly resumed, and numerical results are presented showing relevant accident chains and expected economic loss, demonstrating the capabilities of the developed tool.

scholarly journals Domain-specific risk assessment using integrated simulation: A case study of an onshore wind project

2021 ◽  
Author(s):  
Emad Mohamed ◽  
Nima Gerami Seresht ◽  
Stephen Hague ◽  
Adam Chehouri ◽  
Simaan M. AbouRizk
Keyword(s):  
Risk Assessment ◽  
Wind Farm ◽  
Critical Path ◽  
Quantitative Risk Assessment ◽  
Integrated Simulation ◽  
Domain Specific ◽  
Risk Assessment Models ◽  
First Case ◽  
Assessment Approach

Although many quantitative risk assessment models have been proposed in literature, their use in construction practice remain limited due to a lack of domain-specific models, tools, and application examples. This is especially true in wind farm construction, where the state-of-the-art integrated Monte Carlo simulation and critical path method (MCS-CPM) risk assessment approach has yet to be demonstrated. The present case study is the first reported application of the MCS-CPM method for risk assessment in wind farm construction and is the first case study to consider correlations between cost and schedule impacts of risk factors using copulas. MCS-CPM provided reasonable risk assessment results for a wind farm project, and its use in practice is recommended. Aimed at facilitating the practical application of quantitative risk assessment methods, this case study provides a much-needed analytical generalization of MCS-CPM, offering application examples, discussion of expected results, and recommendations to wind farm construction practitioners.

scholarly journals An extension of the codas method based on Interval Rough Numbers for multi-criteria group decision making

2021 ◽  
Vol 16 ◽  
pp. 23-43
Author(s):  
Mouna Regaieg Cherif ◽  
◽  
Hela Moalla Frikha ◽  
Keyword(s):  
Risk Assessment ◽  
Decision Making ◽  
Sensitivity Analysis ◽  
Decision Maker ◽  
Group Decision Making ◽  
Group Decision ◽  
Real Life ◽  
Multiple Criteria ◽  
Linguistic Terms

This study aims to develop a new Interval Rough COmbinative Distance-based Assessment (IR CODAS) method for handling multiple criteria group decision making problems using linguistic terms. A single decision maker is unable to express his opinions or preferences on multiple criteria decisions, while a Multi-Criteria Group Decision Making MCGDM process ensures successful outcomes when handling greater imprecision and vagueness information. A real-life case study of risk assessment is investigated using our proposed IR-CODAS method to test and validate its application; a sensitivity analysis is also performed. Keywords: Interval Rough Numbers, group decision making, IR-CODAS method, risk assessment.

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