Quantitative Risk Assessment Methods Research Articles

A quantitative risk assessment method for synthetic biology products in the environment

The need to prevent possible adverse environmental health impacts resulting from synthetic biology (SynBio) products is widely acknowledged in both the SynBio risk literature and the global regulatory community. To-date, however, discussions of potential risks of SynBio products have been largely speculative, and the limited attempts to characterize the risks of SynBio products have been non-uniform and entirely qualitative. As the SynBio discipline continues to accelerate and bring forth novel, highly-engineered life forms, a standardized risk assessment framework will become critical for ensuring that the environmental risks of these products are characterized in a consistent, reliable, and objective manner that incorporates all SynBio-unique risk factors. In their current forms, established risk assessment frameworks – including those that address traditional genetically modified organisms – fall short of the features required of this standard framework. To address this gap, we propose the Quantitative Risk Assessment Method for Synthetic Biology Products (QRA-SynBio) – an incremental build on established risk assessment methodologies that supplements traditional paradigms with the SynBio risk factors that are currently absent, and necessitates quantitative analysis for more transparent and objective risk characterizations. We demonstrate through a hypothetical case study that the proposed framework facilitates defensible quantification of the environmental risks of SynBio products in both foreseeable and hypothetical use scenarios. Additionally, we show how the quantitative nature of the proposed method can promote increased experimental investigation into the true likelihood of hazard and exposure parameters and highlight the most sensitive parameters where uncertainty should be reduced, ultimately leading to more targeted SynBio risk research and yielding more precise characterizations of risk.

Financial Engineering of Infrastructure Projects: The Concessional Mechanism

Purpose: The article considers the model of financial engineering, in which financial resources for an infrastructure project are formed based on syndicated loans. Design/Methodology/Approach: The study is based on modern concepts of uncertainty and risk management theories and the concept of digital economy. It includes a system and diagnostic analysis, methods of financial analytics as well as quantitative and qualitative risk assessment methods. Findings: Authors analyzed the investment in the infrastructure projects development in the Russian Federation. The railways’ export potential is analyzed and determined to depend on coal and container terminals. Authors highlighted the need for business consolidation and new infrastructure projects based on technologies of digitalization in the transport industry, reviewed the strategic importance of concession agreement for the construction of “Northern Latitudinal Railway”. Practical Implications: The research findings revealed that implementation of large infrastructure projects is capable to render breakthrough effect on GDP and economic growth rates of the Russian Federation. The adjusted experience could be introduced in the transport framework of the Russian Federation and abroad. Originality/Value: The main contribution of this study is in the highlighting features of concessional mechanism in the framework of large infrastructure projects.

Integrated Airworthiness Certification Criteria and Security Risk Assessment for UAVs

The proportion of software in UAVs has increased rapidly in recent years. However, it is becoming increasingly difficult to secure the avionic software against security threats. There are no airworthiness certification criteria for the security as well as the safety of UAVs. Therefore, it will be necessary to study on the airworthiness certification criteria and methodology for the safety and security of UAVs, considering the recent trend of the increase in the use of UAVs. The integrated airworthiness certification criteria for safety and security in avionic software to save time and cost were most recently proposed. This paper introduces the comparison between CC, DO-178C, and airworthiness security activities. It also presents the quantitative risk assessment method that is capable of analyzing vulnerabilities and assesses risks quantitatively using the case of security threats to the avionic software of UAVs. It derives the security objectives and requirements for UAVs’ avionic software based on the result of the security risk assessment. Finally, this paper proves the effectiveness of the risk assessment methods by applying them to real case of UAVs.

Providing the Developmental Model of a Comprehensive System of Prioritizing Occupational Risks Using Analytical Hierarchy Process (AHP) Technique in the Management of Integrated Health, Safety and Environment (Case Study of Oil Industrial Contractors)

In this study, researchers designed a functional decision supporting model for workplaces for managers and showed its application by implementing it in health, safety and environment fields.
 
 Researchers used Excel software to demonstrate the ease of use of this method. This model is designed to help managers for decision-making to select and allocate resources to optimize risk of irreversible and unacceptable risks. In this regard, detailed quantitative risk assessment methods and techniques AHP expert’s extraction, classification and has been structured; to help managing workplaces risks and reducing the effects other than representing the applications of multi-criteria decision making techniques especially Analytical Hierarchy Process (AHP) technique, and in the end, to attribute resources in the best possible way. This model comes as a decision support system and is used to ease, the accuracy of decisions and reassuring them.
 
 This study suggests the use of multi-criteria decision-making techniques in large-scale projects and organizational risk management process for managers and reassuring them in terms of efficiency and effectiveness of steps taken to reduce and control occupational risks in the workplace and promise reduction irreparable effects for both organizations and for society, and to optimize the allocation of limited resources of organization. To carry out all stages of computational and analytic hierarchy process technique, Excel software was used in this study to show that this technique with capacity is also applicable in various companies.

Risk of establishment of canine leishmaniasis infection through the import of dogs into South Africa.

Canine leishmaniasis is a vector-borne disease caused by protozoa of the genus Leishmania that affect dogs, humans and wildlife. Sandflies of the genera Phlebotomus and Lutzomyia are the primary vectors. Canine leishmaniasis is an exotic and controlled disease in South Africa. The main purpose of our risk assessment study was to evaluate the likelihood that this exotic disease could enter and be established in South Africa through importation of live dogs. Risk analysis to the spread of the disease follows the World Organization for Animal Health (OIE) formal method of quantitative risk assessment documented as a step-by-step process. We have identified and discussed 11 possible risk factors involved in three steps for final assessment. The annual average number of diagnostic tests performed on imported dogs from 44 countries for 2011–2015 was 1158. Leishmania is reported to occur in 21/44 (47.7%) exporting countries. A total of 71.1% of Leishmania positive dogs were imported from these endemic countries. The yearly percentage of Leishmania positive dogs ranged from 0.2% to 2%. Three confirmed clinical and fatal cases of leishmaniasis in dogs of unidentified origin have been reported by our laboratory and the state veterinarians. The disease has been reported in neighbouring countries as well as the putative sandfly vectors. This study concluded that the risk for the introduction and degree of uncertainty of Leishmania in imported dogs in South Africa are moderate. Risk mitigation and recommendations such as investigations into possible occurrence of autochthonous leishmaniasis in the country, surveillance in its wildlife reservoirs and systematic surveillance of sandfly populations are discussed.

Probabilistic Risk Assessment of Life Safety for a Six-Storey Commercial Building with an Open Stair Interconnecting Four Storeys: A Case Study

The gold standard for complying Performance Requirements is based on a Quantitative Probabilistic Risk Assessment method. This case study demonstrates the application of this approach to performance based design of a six-storey commercial building with an open stair interconnecting four storeys. Computational Fluid Dynamics based and zone fire as well as evacuation simulations are used to quantify consequences whilst detailed event trees underpinned by statistical data and analysis are utilised to calculate corresponding probabilities. Results are combined in a trade-off analysis tool which calculates the Expected Risk to Life (ERL) based on the trial design features included in each design option. The approach was used to determine a preferred design that achieves an acceptably low ERL and compliance with the Performance Requirements of the Building Code of Australia. The benchmark ERL was set as 1.36 deaths/1000 fires or a probability of death from a fire of 1.36 × 10−3 based on local statistical data. To obtain an optimum fire safety design (Alternative Solution) a layered approach was adopted in which fire safety systems were added until the risk to occupants in the building due to a fire is the same or less than the benchmark ERL. Eventually three sets of trial design were considered and in all cases the calculated ERL were roughly 22% lower than the benchmark. Eventually the trial design with the least number of fire safety systems was recommended as the Alternative Solution. The trade-off analysis shows the sprinklers and wall-wetting sprinklers in the office area resulted in a 20-fold difference in the building wide ERL, each.

Regional risk assessment of debris flows in China—An HRU-based approach

By considering the integrity of microcosmic and comprehensive geomorphological features, this article intends to develop a quantitative method for regional risk assessment of debris flow by analyzing the in-depth relations among hazard-forming environments, disaster factors and elements at risk. Taking the debris flows in the Longxi River Basin in China as a case study, an approach based on the hydrological response unit (HRU) is proposed by establishing both a model and system for regional risk assessment to analyze the hazard of debris flows and the exposure and vulnerability of elements at risk. The HRU-based approach consists of 11 disaster factors: topographic slope; relative elevation difference; lithology; channel gradient; fault; disturbed area; rainfall; and the type, location, fragility and economic value of the elements at risk. Specifically, a hazard integrated model is built by considering the hazard factors and their corresponding weights to evaluate the hazard level of debris flow. Through determining the type, quantity, distribution, economic value and fragility of hazard-affected objects in a region, methods are established to determine the exposure and vulnerability of different elements at risk. Validated by using a field study of actual debris flows, a debris-flow risk map is obtained, and the assessment results are in accordance with the actual disaster situation. The analyses show that the distributions of zones with high risk and above (i.e., where hazard densities and economic activities are considerably high) are closely correlated with the topographic and socioeconomic characteristics of the debris flow catchment. These findings suggest that the assessment results provide scientific support for planning measures to prevent or reduce debris flow hazards; thus, the presented method may serve as a pertinent guidance for regional risk assessment of debris flows in both the Longxi River Basin and beyond.

Research on Quantitative Risk Assessment Method of Packaged Cargoes Carried By Ship Based on Online Dynamic Big Data Fusion Technology

In this paper, a quantitative risk assessment method of packaged cargoes carried by ship based on online dynamic big data fusion technology was researched. In recent years, major accidents such as oil spill, fire, explosion and ship loss occurred frequently in shipborne cargo transportation. Due to the lack of real-time dynamic risk analysis, both early warning and emergency handling of those accidents are extremely difficult. In this paper, a risk transmission model was built, which based on the flow chain for cargo transportation. A system including the analysis of cargo transportation risk and quantitative assessment model based on real-time dynamic big data fusion technology was built. Finally, a scientific quantitative assessment method was formed. And a container ship passing through Shenzhen waters was taken as an example in order to verify the practicality of the method. In this way, it can realize the quantitative assessment of risk (especially the risk of dangerous packaged cargoes)in the waterage. What’s more, according to the assessment results, it can analyze the high-risk factors and high-risk parts in the process of waterage, and then realize the informationalized and modernized intelligent supervision in a whole process and all round way, which will effectively improve the level of accident prevention in China.

Approaches to the assessment the innovation-and-investment projects within the system of “Smart City” criteria

The article clarifies the understanding of modern approaches to risk management in construction organizations. The authors have formed a classification of the sources of risks in construction and the reasons causing the uncertainty of the conditions of operation of construction companies. The researchers identified factors that require control in the construction industry. The authors offer, that “smart city” assumes six criteria, including smart economy, smart mobility, smart environment, smart people, smart living, smart governance. The consideration of the tendency to innovations and the assessment of innovation-and-investment risks within the concept “Smart city” was carried out for the Russian practice for the first time. The risk assessment is offered to be carried out with the use of the modern approach. The proposed approach to improve risk management, according to which all the basic processes of risk management should be carried out at each stage of the life cycle of a construction object. The authors propose to use certain methods of qualitative and quantitative risk assessment, enshrined in the risk management standard, at the appropriate stages of the life cycle of a construction object in terms of their advantages. This will increase the effectiveness of risk management and minimize the impact of risk factors identified by researchers on the performance of construction organizations. Research of risk management systems allowed us to determine the priorities and problems of construction companies in the field of risk management and increase its efficiency.

Development of an automobile industry risk index

The aim of this research is to construct a Bayesian belief network (BBN) model, which encompasses all the risk factors relevant to the Indian automotive sector that can give a fair, empirical idea as to how much the risk factors drive down the gross turnover of the industry. The BBN model is used to gauge business, economic and external risks and evaluate its impact on gross turnover of the industry. Empirical model draws a lot of implications to streamline the risk effects in the industry, but it clearly shows that the three factors - business risks, economic risks and external risks are not entirely independent and are positively correlated with each other. Bayesian networks provide a very useful risk assessment tool that takes into account the advantages of both quantitative and qualitative risk assessment methods. This is a novel, empirical effort to provide a generalised model to integrate all risks - domestic, global, economic, legal - relevant to the automotive industry.

Development of an automobile industry risk index

The aim of this research is to construct a Bayesian belief network (BBN) model, which encompasses all the risk factors relevant to the Indian automotive sector that can give a fair, empirical idea as to how much the risk factors drive down the gross turnover of the industry. The BBN model is used to gauge business, economic and external risks and evaluate its impact on gross turnover of the industry. Empirical model draws a lot of implications to streamline the risk effects in the industry, but it clearly shows that the three factors - business risks, economic risks and external risks are not entirely independent and are positively correlated with each other. Bayesian networks provide a very useful risk assessment tool that takes into account the advantages of both quantitative and qualitative risk assessment methods. This is a novel, empirical effort to provide a generalised model to integrate all risks - domestic, global, economic, legal - relevant to the automotive industry.

Problems and Perspectives in Seismic Quantitative Risk Analysis of Chemical Process Plants

Earthquakes represent a class of natural-technical (NaTech) hazards which in the past have been responsible of major accidents and significant losses in many industrial sites. However, while codes and standards are issued to design specific structures and equipment in both the civil and industrial domain, established procedures for seismic quantitative risk assessment (QRA) of process plants are not yet available. In this paper, a critical review of seismic QRA methods applicable to process plants is carried out. Their limitations are highlighted and areas where further research is needed are identified. This will allow to refine modeling tools in order to increase the capabilities of risk analysis in process plants subjected to earthquakes.

A Quantitative Individual Risk Assessment Method in Process Facilities with Toxic Gas Release Hazards: A Combined Scenario Set and CFD Approach

Individuals working in process facilities containing toxic gases may face gas releases and poisoning risks. Many studies regarding individual risk (IR) have been carried out on a worst scenario basis. However, the worst scenario‐based approach cannot represent realistic release risks and may overestimate the IR. In this study, an approach based on complete accident scenario set (CASS) and computational fluid dynamics (CFD) is proposed to quantitatively assess IR of toxic gas release in process facilities. By combining the gas leakage probability and joint distribution probability of the wind direction and speed, a CASS can be built. The CFD method is used to predict the concentration field of gas release and dispersion. Then, the toxic gas concentration can be converted to poisoning fatality probabilities according to the dose–response model. A virtual IR contour can finally be defined by the accumulative assessment of all release scenarios. A case study of an IR area classification in a natural gas process and carbon dioxide recycle terminal processing facility that contains an ammonia refrigeration system is also investigated. With the proposed methodology, the quantitatively classified IR level in process facilities can provide scientific references for safety decision makers. © 2018 American Institute of Chemical Engineers Process Process Saf Prog 38: 52–60, 2019

Applying a stochastic-based approach for developing a quantitative risk assessment method on the fire safety of underground road tunnels

Fire safety is an important aspect of underground road tunnels’ operation. Undertaking high traffic volumes, they are one of the most critical infrastructure for the daily operation of modern urban networks. Aiming to guarantee their safety, risk assessment has been established as a valuable tool. However, the deterministic approach of existing methods has weaknesses in addressing the embedded uncertainty included in important parameters of the system. This paper, applying a stochastic-based approach, proposes a novel quantitative risk assessment method, named SIREN. Initially, the system’s parameters are investigated and the ones which should be treated as stochastic are identified. Subsequently, the method considers both tunnel airflows and trapped-users’ evacuation in order to estimate their potential losses. Finally, the system’s level of safety is provided through the distribution of the trapped-users losses, which occurred by accumulating the results that derived from the Monte Carlo Simulation. The proposed method is illustrated through the case of an urban underground road tunnel during rush hour. The outcome highlights a significant proportion of scenarios that exceed the number of losses estimated by the traditional methods. Meanwhile, the method examines the parameters’ criticality supporting, thus, safety analysts in selecting additional to standard safety measures, if needed. Furthermore, the proposed method aids analysts to act consistently with the as low as reasonable practicable principle.

A fuzzy Fine-Kinney-based risk evaluation approach with extended MULTIMOORA method based on Choquet integral

Abstract The Fine-Kinney as a comprehensive and quantitative risk assessment method has been commonly applied to aid in controlling occupational hazards in practice. However, the Fine-Kinney-based risk evaluation approach suffers from the drawbacks of failing to deal with the interaction relationships between risk parameters and determine the risk priority of occupational hazards. The purpose of this paper is to propose a novel Fine-Kinney-based risk evaluation approach combining triangular fuzzy number, MULTIMOORA method and Choquet integral to overcome the limitations in the current Fine-Kinney-based risk evaluation approach. First, the triangular fuzzy number is employed to determine the risk parameters scores in Fine-Kinney approach. Second, the relative preference relation based triangular fuzzy number ranking method is integrated with the Choquet integral to determine importance weights of risk parameters. Third, an extended MULTIMOORA method with Choquet integral is proposed to determine the risk priority order of hazards by considering the interaction relationships between risk parameters. Finally, a case study of ballast tank maintenance is selected to demonstrate the application and feasibility of the proposed hybrid Fine-Kinney-based risk evaluation method, and comparison and sensitivity analysis are also conducted to validate the effectiveness of the new risk assessment model.

Development of an Integrated Risk Assessment Method to Quantify the Life Safety Risk in Buildings in Case of Fire

An integrated probabilistic risk assessment methodology is developed for the purpose of quantifying the life safety level of people present in buildings in the context of fire safety design. Multiple risk based concepts and tools have been developed in previous research to objectify performance based design methods for simple building types and layouts. However, these available models lack an integrated approach for challenging building designs and moreover they are not adequately coupled, most often resulting in a significant computational effort. Hence, there is a need for a pratical and efficient framework for dealing with complicated building layouts and different occupancy types. Therefore, a computationally efficient quantitative risk assessment method is developed that provides a framework by combining deterministic sub-models and probabilistic techniques to quantify the fire safety level by means of failure probabilities, individual and societal risk. The deterministic framework is supported by analytical and numerical models. The probabilistic framework is supported by response surface modelling, sampling techniques and limit state design. Following the theoretical description of the model, a case study of a five storey commercial shopping mall of 25,000 m² is elaborated and discussed as proof of concept. Multiple fire, building and occupant variables are implemented in the model. Three different fire safety designs are compared, resulting in quantified risks between 10-6 and 10-8. The case study proves the validity of the newly developed integrated methodology for this type of buildings and its benefits in fire safety engineering.

Qualitative and Quantitative Risk Assessment Method for Fire Safety Accident in Liquefied Natural Gas Storage

Liquefied natural gas (LNG) has the characteristics of low temperature, volatile, flammable and explosive, and its safety issues are being highlighted. The probability and consequences of accident were quantitatively analyzed in combination with the possibility of LNG filling station pump or pipeline spillage. The DEGADIS and LNGFire3 models were used to determine the consequences of the accident. Based on the injury criterion data provided by relevant literature, the article concludes that the personal risk value derived from personal injury level and mortality rate, when compared with personal risk standards of United Kingdom, Netherlands and other countries and institutions, the personal risk value is much lower than the standard limit value, and shows the rationality of establishing 5kW/m2 as the safety distance from critical thermal radiation intensity.

A method for facility layout optimisation including stochastic risk assessment

Abstract Facility siting and layout configuration are essential factors during design and expansion of any industrial installation. In the recent past, cost-driven layout arrangements and the proximity of chemical facilities to densely populated areas, among other factors, have also contributed to the severity and propagation of various chemical incidents. Although several studies have been reported to address such problems, there is still a need for incorporating safety into the facility layout problem (FLP); especially for a method combining quantitative risk assessment (QRA) and layout reformulation. Based on that, the objective of this study is to develop a framework integrating layout formulation with a quantitative risk assessment method to support risk-based decisions throughout the lifecycle of process facilities. The proposed methodology is divided into three steps: risk calculation, determination of safety distances, and layout optimisation. In the first stage, an in-house code has been developed to quantify risks associated with loss of human life and structural damage stochastically. Subsequently, minimum separation distances between process units are obtained to prevent escalation events. In the last stage, risk maps and safety distances are accounted in a mixed-integer linear programming (MILP) for layout optimisation. The application of the proposed methodology is demonstrated through a case study. Sensitivity analysis is performed by varying risk values, safe distances, and risk acceptance criteria. Even though different layout options are generated, a trend is observed towards placing the equipment by its type.

Dynamic Risk Assessment Based on Statistical Failure Data and Condition-Monitoring Degradation Data

Traditional quantitative risk assessment methods (e.g., event tree analysis) are static in nature, i.e., the risk indexes are assessed before operation, which prevents capturing time-dependent variations as the components and systems operate, age, fail, are repaired and changed. To address this issue, we develop a dynamic risk assessment (DRA) method that allows online estimation of risk indexes using data collected during operation. Two types of data are considered: statistical failure data, which refer to the counts of accidents or near misses from similar systems and condition-monitoring data, which come from online monitoring the degradation of the target system of interest. For this, a hierarchical Bayesian model is developed to compute the reliability of the safety barriers and a Bayesian updating algorithm, which integrates particle filtering (PF) with Markov Chain Monte Carlo, is developed to update the reliability evaluations based on both the statistical and condition-monitoring data. The updated safety barriers reliabilities, are, then, used in an event tree (ET) for consequence analysis and the risk indexes are updated accordingly. A case study on a high-flow safety system is conducted to demonstrate the developed methods. A comparison to the DRA method which only uses statistical failure data shows that by introducing condition-monitoring data on the system degradation process, it is possible to capture the system-specific characteristics, and, therefore, provide a more complete and accurate description of the risk of the target system.

A “solution-focused” comparative risk assessment of conventional and synthetic biology approaches to control mosquitoes carrying the dengue fever virus

Emerging technologies often pose various uncertain health risks that cause policymakers to hesitate to allow resultant products and processes to enter the market—but they also may offer large benefits, including the potential to greatly reduce some of the very risks currently most greatly affecting public health and the environment. Synthetic biology serves as one such emerging technology that, despite its potential benefits to various fields, gives policymakers pause until the human and environmental health risks posed by genetically engineered organisms are better characterized and assessed. Given various limitations of our current paradigm for making risk management decisions, some of which are caused by limitations of conventional methods of quantitative risk assessment (QRA), a modified approach to emerging technology characterization and assessment might be a needed step change. This paper demonstrates how one such approach—“solution-focused risk assessment” (Finkel, Hum Ecol Risk Assess 17(4):754–787, 2011)—can help evaluate synthetic biology products against conventional competitors. Specifically, this paper conducts a SFRA for Oxitec’s engineered Aedes aegypti mosquito, which serves as a synthetic biology option for dengue virus vector control.