Numerical simulations of short-range wildfire firebrand exposure to industrial cylindrical storage tank

T10-3 - A Comparison of Deterministic and Probabilistic Risk Assessment Methodologies for Land Use Planning

Biogas plants are a specific facility from the QRA (Quantitative Risk Assessment) methodologies' point of view, especially in the case of the determination of the event frequency of accident scenarios for biogas leakage from a gas holder and subsequent initiation. QRA methodologies determine event frequencies for different types of accident events related to vessels made of steel. Gas holders installed at biogas plants are predominantly made of other materials and are often integrated with the fermenter. It is therefore a specific type of gas holder, differing from that which is commonly used in the chemical industry. In addition, long-term experience is not available for the operation of biogas plants, unlike in the chemical industry. The event frequencies listed in the QRA methodologies are not relevant for the risk assessment of biogas plants. This work is focused on setting the prerequisites for QRA of biogas storage, including for example: information on hazardous chemical substances occurring at biogas plants, their classification, and information on the construction of integrated gas holders. For the purpose of the work, a scenario was applied where the greatest damage (to life or property) is expected. This scenario is the leakage of the total volume of hazardous gas substance from the gas holder and subsequent initiation. Based on this information, a "tree" was processed for "Fault Tree Analysis" (FTA), and frequencies were estimated for each event. Thereafter, an "Event Tree Analysis" was carried out. This work follows up on a discussion by experts on the determination of scenario frequencies for biogas plants that was conducted in the past.

Using PBPK modeling and comprehensive realism methodology for the quantitative cancer risk assessment of butadiene

GDF SUEZ Exploration & Production INTERNATIONAL (EPI) is committed to grant the same level of safety in all its facilities worldwide. Over the years, Quantitative Risk Assessment (QRA) has established itself as a standard component of the risk management program for offshore and onshore facilities. The QRA studies in the different affiliates of GDF SUEZ EPI vary depending on country regulations, experience and complexity of the facilities. The affiliates refer to internal methodology when conducting these studies. Risk Acceptance Criteria used during these QRA studies are affiliate dependant. GDF SUEZ EPI believes there is a benefit in developing a consistent approach in the review of risks associated with operations. This approach is contributing to improve the relevance of the QRA studies,share feedback of QRA between affiliates,compare results of the QRA studies in different regulatory regimes,bring the assurance to corporate management of the quality of risk assessments. The central component of this harmonized approach is to promote common practices regarding Quantitative Risk Assessment and related Risk Acceptance Criteria. This study covers the following points: Comparing existing practices and QRA methodology in the different affiliates,Integrating the Regulatory guidance in making the required demonstrations in QRA studies,Reviewing recommendations by OGP, standards and regulations (HSE-UK, NORSOK, NL, etc.) to determine best practices.Harmonizing QRA studies (Common methodology, Level of detail of these studies, ALARP demonstration, QRA for major changes, etc.) This analysis investigates the QRA process, the selection and use of databases and analytical techniques, the effect modeling, and the risk acceptance criteria. The study will improve practices for operations performed under the control of GDF SUEZ EPI by enhancing the safety of its installations and grant that affiliates use "all measures necessary" to avoid major risks.

This paper determines the capability of current failure frequency methodology and models for assessing dense phase CO2 pipelines. An overview of these models is given in order to explain their applicability to CO2 pipelines, structure and to highlight the similarities and differences between each model. A pipeline must comply with the relevant design code in order to ensure conformity with pipeline safety regulations, for example in the UK it is PD-8010 (BSI, 2015). In this particular code the maximum allowable operating stress in the pipeline and the minimum allowable distance between the pipeline and any occupied buildings near to the pipeline route must be defined by the product being transported. The code was originally written to be applied to products which pose a thermal hazard and therefore there is currently no hazard category included in the code for dense phase CO2 and therefore cannot be applied to the design of dense phase CO2 pipelines. Where no design code for dense phase CO2 pipelines exists, to ensure the safe design, construction and operation, a quantitative risk assessment (QRA) approach is required (Barnett, 2014; Cooper, 2014). The purpose of a pipeline QRA is to determine the risks posed by the failure of the pipeline to people located nearby. The procedure involves the identification of hazard scenarios and considers both the probability of failure and the consequences of failure in order to calculate values for the individual and societal risk due to the pipeline. In general a QRA procedure covers the following steps: i) Identify hazards ii) Identify failure causes iii) Calculate the frequency of failure for each cause iv) Evaluate the consequences of failure v) Calculate the individual and societal risk a specific locations along the pipeline vi) Assess the tolerability of the calculated risks by comparison with recognised criteria In terms of failure causes, pipeline failure can occur due to numerous different mechanisms including, third party external interference, corrosion, material or construction defects, natural events and operational error; all of which must be considered as part of the assessment (Goodfellow, 2006). For oil and gas pipelines, the frequency of pipeline failure due to third party external interference has traditionally been calculated using models based upon probabilistic, structural reliability methods. Structural reliability methods are applied by combining the following: • Limit state functions, the mathematical models which define the conditions for failure; • Probability distributions based around selected random variables; • A mathematical technique to calculate the probability of failure (e.g. Numerical Integration, Monte Carlo, First Order Reliability Methods). For pipelines the limit state functions are based on semi-empirical fracture mechanics failure models; and the probability distributions are based on pipeline damage and derived from historical operational data. The failure probability is converted into a failure frequency to take into account the regularity of third party external interference damage. The various models currently in use within the oil and natural gas pipeline industry differ in their subtleties; however all are based upon a methodology originally developed in the 1980s. To calculate pipeline failure frequency for dense phase CO2 pipelines it would be desirable to extend the use of the current pipeline failure frequency methodology. The methodology has been employed for over 25 years, and as a result is tried, tested and well understood. The transportation of dense phase CO2 by pipeline however requires operational pressures in excess of the CO2 triple point; potentially up to 200bara. This high design pressure requirement necessitates the use of thick wall linepipe in pipeline construction, potentially with wall thickness dimensions outside of the limits of current operational experience. Consequently, the reliance of the failure frequency methodology on empirical data and semi-empirical relations needs to be examined. The requirement to develop a robust Quantitative Risk Assessment (QRA) methodology for high pressure CO2 pipelines has been recognised as critical to the implementation of CCS. Consequently, failure frequency models are required that are appropriate for high pressure CO2 pipelines. This paper addresses key components from the failure frequency for QRA methodology development.

Quantitative risk assessment integrated with dynamic process simulation for reactor section in heavy oil desulfurization process

The objectives of the study were to evaluate the risk of illness from the consumption of Mutton contaminated with Escherichia coli O157:H7 in Qatar and to highlight intervention points that would contribute to mitigating its associated risk. The quantitative risk assessment (QRA) methodology was employed to address this objective. Our approach consisted of a combination of deterministic and stochastic approaches. Data on the probability of E. coli O157:H7 in animals, animal products, retail, and humans were obtained through repeat cross-sectional studies. Estimates of the adverse health effects were computed using risk characterization which integrated data on hazard characterization and exposure assessment, including dose-response models. The probability of illness for a healthy female from the consumption of mutton contaminated with E. coli O157:H7 eating at a restaurant ranged from 7×10-3 to 28×10-2 depending on the amount of food consumed. However, the risk for the same female eating at home is less (5×10-3 to 24×10-2). The estimates of illness are three times higher for immunocompromised females exposed either at a restaurant or at home. The risk of illness due to this pathogen could be significantly reduced for either gender under different scenarios by increasing the efficacy of roasting the mutton before consumption.

During the Gulf of Mexico (GoM) hurricane seasons of 2004, 2005 and 2008, numerous moored Mobile Offshore Drilling Units (MODUs) had complete mooring system failures and thus were later found to be adrift. Also, a few units suffered failure of one or more mooring lines but at least one line held to keep the unit from going adrift. As a result of these mooring failures, operators and rig owners expended much effort in recovering the vessels, the mooring components, and then in making the required repairs in order to restart operations. Other major consequences of the mooring failures were: direct damage to the industry's infrastructure such as pipelines and umbilicals, loss of production, and delays in several well programs. MODUs in the GoM are a critical part of the necessary infrastructure for exploration and development of oil and gas. Industry standards that allow safe and economic operations of MODUs are important to the industry and regulatory authorities. Much work has been done since the events in the 2004 and 2005 GoM hurricane seasons to better understand the causes of moored MODU failures and learn from these failures. This knowledge has resulted in changes to the industry standards regarding mooring of MODUs. As an example, selection of the design return period is no longer prescriptive but based on performing a suitable risk assessment. Using a Quantitative Risk Assessment (QRA) approach, the risk can be evaluated at every well location planned to be drilled during the GoM hurricane season. These results can be used to make more informed decisions regarding rig deployments during the GoM hurricane season. In addition, the QRA methodology can be extended to more comprehensive considerations (e.g. all of the GoM) in order to better understand the risk posed by the moored MODU fleet to an operator's entire portfolio of deepwater facilities and infrastructure. This paper describes a process that can be used to assess the risk associated with moored MODU operations and provides some examples to demonstrate the utility of the process. Introduction As a result of the numerous moored MODU failures during hurricanes Ivan, Katrina and Rita, the industry has reexamined the API guidelines for design of MODU moorings. Changes have been made to the current API guidelines as discussed in Refs. 1 and 2. The cornerstone of API RP 2SK, Appendix K (Ref. 3) is a risk assessment process to provide a consistent technical basis on which to make decisions of suitability of a particular rig at a specific site for a specific period of the GoM hurricane season. Per MMS NTL No. 2009-G09 (Ref. 4), a mooring risk assessment is required with every drilling permit. The QRA approach provides a means to rationally assess the risks, document the results, and compare the results to a company's internal guidelines in order to make better decisions regarding rig deployments. The process also provides a framework for consistently comparing the risk over multiple well locations. An example site is presented herein that includes nearby surface and subsea infrastructure (at 10 miles or less) to demonstrate how the process works. Results are presented to particulary show the impact of drilling during the peak of the GoM hurricane season (approximately August 15 through October 15). Additionally, a second example shows the conclusions from a QRA that considers a comprehensive portfolio of deepwater infrastructure (surface facilities, pipelines and flowlines) being exposed to the fleet of moored MODUs during GoM (both peak and non-peak) hurricane season is presented. The second example further considers both the pre and post upgraded MODU mooring systems (i.e., relative to their 2004 condition). It is shown that proximity of the MODU to the infrastructure and the lost value placed on that infrastructure greatly influence the outcome of the QRA.

Quantitative microbiological risk assessment (QMRA) methodology aims to estimate and describe the transmission of pathogenic microorganisms from animals and food to humans. In microbiological literature, the availability of whole genome sequencing (WGS) data is rapidly increasing, and incorporating this data into QMRA has the potential to enhance the reliability of risk estimates. This study provides insight into which are the key pathogen properties for incorporating WGS data to enhance risk estimation, through examination of example risk assessments for important foodborne pathogens: Listeria monocytogenes (Lm), Salmonella, Campylobacter and Shiga toxin‐producing Escherichia coli. By investigating the relationship between phenotypic pathogen properties and genetic traits, a better understanding was gained regarding their impact on risk assessment. Virulence of Lm was identified as a promising property for associating different symptoms observed in humans with specific genotypes. Data from a genome‐wide association study were used to correlate lineages, serotypes, sequence types, clonal complexes and the presence or absence of virulence genes of each strain with patient's symptoms. We also investigated the effect of incorporating WGS data into a QMRA model including relevant genomic traits of Lm, focusing on the dose–response phase of the risk assessment model, as described with the case/exposure ratio. The results highlighted that WGS studies which include phenotypic information must be encouraged, so as to enhance the accuracy of QMRA models. This study also underscores the importance of executing more risk assessments that consider the ongoing advancements in OMICS technologies, thus allowing for a closer investigation of different bacterial subtypes relevant to human health.

Consequence assessment of the BBC H2 refuelling station using the ADREA-HF code

Benchmark exercise on risk assessment methods applied to a virtual hydrogen refuelling station

In this study, the Quantitative Microbial Risk Assessment (QMRA) methodology was applied to estimate the annual risk of Giardia and Cryptosporidium infection associated with a water treatment plant in southern Brazil. The efficiency of the treatment plant in removing protozoa and the effectiveness of the Brazilian legislation on microbiological protection were evaluated, emphasizing the relevance of implementing the QMRA in this context. Two distinct approaches were employed to estimate the mechanical removal of protozoa:The definitions provided by the United States Environmental Protection Agency (USEPA), and the model proposed by Neminski and Ongerth.Although the raw water collected had a higher concentration of Giardia cysts than Cryptosporidium oocysts, the estimated values for the annual risk of infection were significantly higher for Cryptosporidium than for Giardia. From a general perspective, the risk values of protozoa infection were either below or very near the limit set by the World Health Organization (WHO). In contrast, all the risk values of Cryptosporidium infection exceeded the threshold established by theUSEPA. Ultimately, it was concluded that the implementation of the QMRA methodology should be considered by the Brazilian authorities, as the requirements and guidelines provided by the Brazilian legislation proved to be insufficient to guarantee the microbiological safety of drinking water. In this context, the QMRA application can effectively contribute to the prevention and investigation of outbreaks of waterborne disease.

Qualitative analysis processes are currently used to design and allocate maintenance monies for linear infrastructure on permafrost. The routing and maintenance locations are generally selected using a qualitative process, with probabilities and consequences of each potential failure mode evaluated using a scalar rating system. A quantitative risk assessment utilizes calculated values of failure probability and consequence. In either analysis method, the values of probability and consequence are multiplied to determine a risk importance factor, which is used to rank and analyze each risk. While qualitative analysis methods have been used for many years, there is a push within the engineering community towards probability-based methodologies, quantifying the analysis process. This paper presents a review of probabilistic methods used to analyze geotechnical properties and calculation uncertainty, problems and failure modes of embankment-supported infrastructure on permafrost, and risk analysis methods. This review is an initial step in the development of a tool and methodology for quantitative risk assessment of linear infrastructure on permafrost; a brief discussion of the research plan is also included.

A methodology for quantitative risk assessment of petroleum pipeline has been presented and applied in this paper. The proposed methodology consists of both the analysis of probability of failure and the consequences of fatalities are analysed using commercial software CANARY v.4.2. Based on the outcome of probability of failure and consequences, the individual and societal risk of pipeline is then estimated. The time of presence of an individual in the hazardous zone is taken into account during calculations of the individual risk. Societal risk is represented by an F-N plot that defines the relationship between frequency and the number of people suffering from fire and explosion due to fuel spills. Both individual and societal risks are modelled using SAFETI FX 6.5.1 software by DNV. The methodology is capable of analysing quantitative risk of any pipeline, irrespective of location. The approach has been applied to conduct quantitative risk assessment as well as study the differences in consequences and risks arising from the failure of gasoline and natural gas pipelines. The methodology is robust and can be broadened to cover different failure factors.

Summary Assessing risks during carbon dioxide (CO2) sequestration involves a systematic process to identify them (risk assessment), analyze, prioritize, score them (risk analysis), develop mitigation strategies, and plan for measurement, monitoring, and verification (MMV) activities. In this context, risk assessment and analysis are often conducted involving qualitative approaches and/or subjective evaluations based on experts judgments. In this paper, we propose to use numerical results of dynamic subsurface modeling to assess risks in a more precise, less subjective, and quantitative manner, enabling a comprehensive definition of effective MMV plans. In this context, MMV evolves into modeling, measurements, monitoring, and verification [(M)MMV]. The conceptual model used for this study integrates flow and geomechanical-coupled behavior to assess caprock integrity, faults reactivation, and ultimately the risk of CO2 leakage. Uncertainty analysis and a 4D probabilistic workflow are used to quantify the likelihood and consequences of CO2 leakage and to score risks. The proposed approach offers a general framework to enable subsurface-modeling-based quantitative risk assessment (QRA) for the definition of successful (M)MMV plans. In this study, we have focused on the QRA of leakage risks through the fault and intact caprock. Other applications are possible, such as: (1) leakage risks through the caprock resulting from caprock failure; (2) lateral CO2 migration leading to permit limits violation or inducing interferences with neighboring activities; (3) leakage risks resulting from loss of well integrity; (4) risks of faults reactivation; (5) risks of surface heave; and (6) risks of induced seismicity. All these results can be used to formulate effective (M)MMV strategies for an optimized and cost-effective risk mitigation.