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.

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.

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.

The Application of Quantitative Risk Assessment to Microbial Food Safety

1998 ◽  
Vol 61 (5) ◽  
pp. 640-648 ◽  
Author(s):  
DAVID JOHN VOSE
Keyword(s):  
Risk Assessment ◽  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Food Safety ◽  
Probability Distributions ◽  
Simulation Models ◽  
Practical Method ◽  
Assessment Model ◽  
Quantitative Risk Assessment ◽  
Suitable Model

Quantitative risk assessment (QRA) is rapidly accumulating recognition as the most practical method for assessing the risks associated with microbial contamination of foodstuffs. These risk analyses are most commonly developed in commercial Computer spreadsheet applications, combined with Monte Carlo simulation add-ins that enable probability distributions to be inserted into a spreadsheet. If a suitable model structure can be defined and all of the variables within that model reasonably quantified, a QRA will demonstrate the sensitivity of the severity of the risk to each stage in the risk-assessment model. It can therefore provide guidance for the selection of appropriate risk-reduction measures and a quantitative assessment of the benefits and costs of these proposed measures. However, very few reports explaining QRA models have been submitted for publication in this area. There is, therefore, little guidance available to those who intend to embark on a full microbial QRA. This paper looks at a number of modeling techniques that can help produce more realistic and accurate Monte Carlo simulation models. The use and limitations of several distributions important to microbial risk assessment are explained. Some simple techniques specific to Monte Carlo simulation modelling of microbial risks using spreadsheets are also offered which will help the analyst more realistically reflect the uncertain nature of the scenarios being modeled. simulation, food safety

scholarly journals Risk Assessment Models to Improve Environmental Safety in the Field of the Economy and Organization of Construction: A Case Study of Russia

2021 ◽  
Vol 13 (24) ◽  
pp. 13539
Author(s):  
Arkadiy Larionov ◽  
Ekaterina Nezhnikova ◽  
Elena Smirnova
Keyword(s):  
Risk Assessment ◽  
Monte Carlo ◽  
Monte Carlo Method ◽  
Rapid Development ◽  
Environmental Safety ◽  
Quantitative Risk Assessment ◽  
Optimal Decision ◽  
Environmental Damage ◽  
The Monte Carlo Method ◽  
The Future

This article assesses risks in order to substantiate the economic and organizational efficiency of housing and industrial construction. This topic is relevant because it is necessary for sustainable development. In Russia, environmental safety in construction and housing, as well as communal services, is poorly developed and not regulated by the legal system. As building construction, housing, and communal services should be based on environmental safety, this topic requires rapid development. Methods related to quantifying environmental risk and making decisions under conditions of uncertainty were studied. A quantitative risk assessment was performed using the Monte Carlo method for pessimistic and optimistic options to prevent environmental damage. The model reproduced the distribution derived from the evidence-based fit. The results of sensitivity analysis are also presented to prove the hypothesis. The selection of the most appropriate probability density functions for each of the input quantities was implemented through settings in a computer program. The simulation modeling results clearly illustrate the choice of the general principle of assessment and the adoption of the optimal decision. In conditions of uncertainty, the decision to choose the optimistic options with high cost (to maintain the reliability of the technical system) but less risk plays a decisive role in the future environmental safety strategies of construction projects. The Monte Carlo method is preferable for environmental impact assessments. In the future, the amended methodology can be applied to raise environmental safety in the field of construction.

scholarly journals Impact of wildfires on Canada's oilsands facilities

2018 ◽  
Author(s):  
Nima Khakzad
Keyword(s):  
Risk Assessment ◽  
Global Warming ◽  
Oil And Gas ◽  
The Other ◽  
Quantitative Risk Assessment ◽  
Assessment Framework ◽  
Dynamic Risk ◽  
Dynamic Risk Assessment ◽  
Process Plants ◽  
Increasing Risk

Abstract. Exponential growth of oil and gas facilities in wildlands from one side and an anticipated increase of global warming from the other have exposed such facilities to an ever-increasing risk of wildfires. Extensive oilsands operations in Canadian wildlands especially in the Province of Alberta along with the recent massive wildfires in the province requires the development of quantitative risk assessment (QRA) methodologies which are presently lacking in the context of wildfire-related technological accidents. The present study is an attempt to integrate Canadian online wildfire information systems with current QRA techniques in a dynamic risk assessment framework for wildfire-prone process plants. The developed framework can easily be customized to other process plants potentially exposed to wildfires worldwide provided that the required wildfire information is available.

Quantification of Risks Associated With a Representative Production Well in the Gulf of Mexico

2015 ◽  
Author(s):  
Muhammad Zulqarnain ◽  
Mayank Tyagi
Keyword(s):  
Risk Assessment ◽  
Monte Carlo ◽  
Gulf Of Mexico ◽  
Fault Tree ◽  
Quantitative Risk Assessment ◽  
Delayed Response ◽  
Production Well ◽  
Reservoir Properties ◽  
Worst Case ◽  
Sand Control

After Macondo incident a great effort is under way to improve the safety of deepwater drilling and production operations and enhance the capabilities of different well barrier to stop the oil spill on its earliest stages. This study is a part of that collective effort to make offshore operations safe and decrease the associated risks. The main objective of this study is to quantify and categorize the risk associated with a representative well in the Gulf of Mexico during its normal production operations. In order to achieve an appropriate balance between safety and economics of deepwater oil and gas operations, Quantitative Risk Assessment (QRA) techniques can be successfully used. Quantified risk is computed from the product of blowout frequency and volume of oil spilled as a consequence. Blowout frequency is calculated from Fault Tree Analysis (FTA) and spilled oil volume is estimated from simulating multiphase fluid flow and heat transfer in wellbores. A large number wells are completed with some sort of bottom hole sand control elements to prevent production of sand. The failure of these control elements may have severe consequence and in some cases may result in uncontrolled hydrocarbon flow to the environment as well. A representative production well from the Mississippi Canyon in the Gulf of Mexico is selected for the for quantitative risk assessment (QRA) analysis. The well is completed with cased hole gravel pack and with sand control elements in place. The representative reservoir properties for this well are selected from the literature and uncertainties in properties are accounted for by fitting lognormal distribution and carrying out Monte Carlo simulations. P50 value for the reservoir properties from Monte Carlo simulation is used to find worst case discharge rates by using a commercially available multiphase flow simulator with black oil model. A Fault Tree is constructed to find the blowout probability based on the equipment failure data. From the minimal cut set method the importance and sensitivity of different well barrier is analyzed and most important areas to focus on are identified. The analysis showed that the constructed fault tree is most sensitive to sand screen failures, followed by subsea production tree and delayed response to a situation of immediate concern.

A Model for Probabilistic Seismic Risk Assessment of Process Plants

2016 ◽  
Author(s):  
Antonio C. Caputo
Keyword(s):  
Risk Assessment ◽  
Seismic Risk ◽  
Seismic Vulnerability ◽  
Industrial Process ◽  
Nuclear Industry ◽  
International Standards ◽  
Hazardous Substances ◽  
Seismic Risk Assessment ◽  
Damage Scenarios ◽  
Process Plants

Seismic vulnerability of industrial plants processing hazardous substances is widely documented, and thousands of such facilities are located in areas of medium to high seismicity near population centers. Nevertheless, with the exception of the nuclear industry, national or international standards do not establish any procedure for the overall seismic risk assessment of industrial process plants located in earthquake-prone areas. Moreover, existing Probabilistic Seismic Risk Assessment (PSRA) methods developed by the nuclear industry are not readily applicable to process plants. In order to overcome this limitation, in this paper a novel general-purpose PSRA method is presented, 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. This allows to dynamically generate damage scenarios, and to rank their risk levels determining the critical process units that can be involved.

scholarly journals Seismic Risk Assessment of Actively Controlled Buildings under Probable Mainshock-Aftershock Scenarios during their Lifetime

2021 ◽  
Author(s):  
Ali Khansefid ◽  
Ali Bakhshi
Keyword(s):  
Risk Assessment ◽  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Control System ◽  
Vibration Control ◽  
Control Systems ◽  
Seismic Risk ◽  
Active Vibration Control ◽  
Earthquake Scenarios ◽  
Active Vibration

Abstract This paper focuses on a new comprehensive probabilistic approach for lifetime risk assessment of buildings equipped with active vibration control systems under future probable mainshock-aftershock scenarios. This procedure starts from the seismic hazard simulation, continues with the building performance evaluation, and ends with the seismic risk assessment. The procedure attempts to reflect the effects of major uncertainty sources existing in both building properties and earthquake scenarios using the Monte-Carlo simulation technique. The method is applied to steel moment-resisting frame buildings armed with the optimally designed active vibration control system (using the linear quadratic regulator algorithm). In each realization of the Monte-Carlo simulation, first, a random earthquake scenario containing probable future mainshock-aftershock sequences and their corresponding synthetic stochastic accelerograms are procreated. Next, the buildings are designed in two separate cases, with and without the presence of active vibration control systems. The former is designed based on the international design codes, while the latter properties are obtained via an advanced optimization method. In the last step, considering all generated samples, the loss curve of buildings with the active control system is developed for two separate cases: with or without taking aftershocks’ effects into account. The application of this method indicates that the active control system works well in decreasing the loss value (on average 66%) of buildings during their 50-year lifetime, especially in the more intensive earthquake scenarios. Additionally, it is shown that by neglecting the aftershocks, the life-cycle cost of building will be estimated tangibly (on average 70%) less than what it would be. Finally, it is observed that the non-structural acceleration-sensitive damages have a higher contribution in total building losses in uncontrolled structures in comparison with the actively controlled building by considering aftershocks.

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