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This paper compares and contrasts two approaches to the treatment of pipeline corrosion “risk” – the probabilistic approach and the more traditional, deterministic approach. The paper aims to discuss the merits and potential pitfalls of each approach.

Provides an outline of each approach. The probabilistic approach to the assessment of pipeline corrosion risks deals with many of the uncertainties that are common to the data employed and those with regard to the predictive models that are used also. Rather than considering each input parameter as an average value the approach considers the inputs as a series of probability density functions, the collective use during the assessment of risk yields a risk profile that is quantified on the basis of uncertain data. This approach differs from the traditional deterministic assessment in that the output yields a curve that shows how the “risk” of failure increases with time. The pipeline operator simply chooses the level of risk that is acceptable and then devises a strategy to deal with those risks. The traditional (deterministic) approach merely segments the output risks as either “high”, “medium” or “low”; a strategy for managing is devised based on the selection of an appropriate time interval to allow a reasonable prospect of detecting deterioration before the pipeline corrosion allowance is exceeded, or no longer complies with code. Applies both approaches to the case of a 16.1 km long, 14 in. main export line in the North Sea.

The deterministic assessment yielded a worst‐case failure probability of “medium” with a corresponding consequence of “high”; classifications that are clearly subjective. The probabilistic assessments quantified pipeline failure probabilities, although it is important to note that more effort was required when performing such an assessment. Using target probabilities for “high” and “normal” consequence pipeline segments, indications were that between 8.5 and 13 years was the time period for which the target (predicted) failure probabilities would be reached, again depending on how effective corrosion mitigation activities are in practice. Basing pipeline inspections in particular on the outputs from the deterministic assessment would therefore be conservative in this instance; but this may not necessarily always be so. That the probabilistic assessment indicates that inspections justifiably may be extended beyond that suggested by the deterministic assessment is a clear benefit, in that it affords the opportunity to defer expenditure on pipeline inspections to a later date, but it may be the case that the converse may be required. It may be argued therefore, that probabilistic assessment provides a superior basis for driving pipeline corrosion management activities given that the approach deals with the uncertainties in the basic input data.

A probabilistic assessment approach that effectively mirrors pipeline operations, provides a superior basis upon which to manage risk and would therefore likely maximize both safety and business performance.

The development of multi-hazard risk assessment frameworks has gained momentum in the recent past. Nevertheless, the common practice with openly available risk data sets, such as the ones derived from the United Nations Office for Disaster Risk Reduction Global Risk Model, has been to assess risk individually for each peril and afterwards aggregate, when possible, the results. Although this approach is sufficient for perils that do not have any interaction between them, for the cases where such interaction exists, and losses can be assumed to occur simultaneously, there may be underestimation of losses. The paper aims to discuss these issues.

This paper summarizes a methodology to integrate simultaneous losses caused by earthquakes and tsunamis, with a peril-agnostic approach that can be expanded to other hazards. The methodology is applied in two relevant locations in Latin America, Acapulco (Mexico) and Callao (Peru), considering in each case building by building exposure databases with portfolios of different characteristics, where the results obtained with the proposed approach are compared against those obtained after the direct aggregation of individual losses.

The fully probabilistic risk assessment framework used herein is the same of the global risk model but applied at a much higher resolution level of the hazard and exposure data sets, showing its scalability characteristics and the opportunities to refine certain inputs to move forward into decision-making activities related to disaster risk management and reduction.

This paper applies for the first time the proposed methodology in a high-resolution multi-hazard risk assessment for earthquake and tsunami in two major coastal cities in Latin America.

Accounting’s definition of accountability should include attributes of socioenvironmental degradation manufactured by unsustainable technologies. Beck argues that emergent accounts should reflect the following primary characteristics of technological degradation: complexity, uncertainty, and diffused responsibility. Financial stewardship accounts and probabilistic assessments of risk, which are traditionally employed to allay the public’s fear of uncontrollable technological hazards, cannot reflect these characteristics because they are constructed to perpetuate the status quo by fabricating certainty and security. The process through which safety thresholds are constructed and contested represents the ultimate form of socialized accountability because these thresholds shape how much risk people consent to be exposed to. Beck’s socialized total accountability is suggested as a way forward: It has two dimensions, extended spatiotemporal responsibility and the psychology of decision-making. These dimensions are teased out from the following constructs of Beck’s Risk Society thesis: manufactured risks and hazards, organized irresponsibility, politics of risk, radical individualization and social learning. These dimensions are then used to critically evaluate the capacity of full cost accounting (FCA), and two emergent socialized risk accounts, to integrate the multiple attributes of sustainability. This critique should inform the journey of constructing more representative accounts of technological degradation.

Stable approach concept has great importance for the safe operation of an airline during the approach and landing phases. The purpose of this study is to analyse the unstabilized approaches with bow-tie method and determine the threats that may cause risk in an unstable approach.

In this study, risk assessment of the unstabilized approaches is carried out by using fuzzy bow-tie method and Bayesian networks. Bow-tie method is the combination of event tree analysis and fault tree analysis. Bayesian network is used in the analysis to see interrelationship of basic and intermediate events as well as to update posterior probabilities. Finally, analysis results are verified by the safety performance indicator values.

In this study, the probabilistic values of the numerical model presented by the risk assessment system for risks were calculated using the fuzzy bow-tie method. Thus, the risk assessment system has been transformed into a structure that can be expressed in a probabilistic manner, and the relationship of the risks within the system has been examined and the effect of a possible change on the risk value has been found to be prevalent.

The bow-tie model is widely applied to assess the risks in aviation. Obtaining prior probabilities is not always possible in the risk assessment process. In this paper, innovative fuzzy bow-tie method is used to assess the risks to overcome the lack of prior probability problem in aviation operations.

The Reprocessing Engineering Division of British Nuclear Fuels undertakes the design of nuclear chemical plants for construction and subsequent operation at the Sellafield Works of the Reprocessing Operations Division. Plant construction cannot take place until it has been demonstrated that the chosen design will allow the plant to operate in an adequately safe manner, corresponding to an extremely low level of risk. Risk, or the cumulative frequency and consequences of all potential hazards, is evaluated by means of probabilistic risk assessments (PRA).

The paper aims to apply the probabilistic analysis of risks, improve the prediction and control of infections and optimise the use of resources and the knowledge available at all times.

First, a model based on Bayesian inference, which can be solved with the WinBUGS (Windows interface Bayesian inference Using Gibbs Sampling) simulation software, is described to reduce the uncertainty of the parameter that most influences air transmission: the rate of quanta emitted by the infected. Second, a method for predicting the expected number of infections and combining available resources to reduce parameter is described.

The results indicate that it is possible to initiate a powerful learning process when all available knowledge is integrated alongside the newly observed data and that it is possible to quantify the interaction between the environment and the spaces, improving the communication process by providing the values in a format that facilitates the objective perception of danger.

The implementation of the inference model requires access to the spaces where there were infected.

The current study provides a model and a method to improve the probabilistic analysis of risks, which allows the systematisation of the risk-based management approach to control community transmission caused by infectious agents that use the airway.

The application of the risk assessment and treatment method requires collaboration between the parties that will help the effective implementation of the improvements, such as to verify whether the available resources are sufficient to achieve control.

A hierarchical Bayesian inference model is presented to control the uncertainty in the quanta rate. Bayesian inference initiates a learning process to better understand random uncertainty. A method to quantify and communicate risk was also presented, which proposes to decompose the risk into four components to predict the expected number of infected individuals, helping to implement improvement measures, with the resources and knowledge available.

The purpose of this paper is to present a fault tree (FT)-based approach for quantitative risk analysis in the construction industry that can take into account both objective and subjective uncertainties.

In this research, the identified basic events (BEs) are first categorized based on the availability of historical data into probabilistic and possibilistic. The probabilistic and possibilistic events are represented by probability distributions and fuzzy numbers, respectively. Hybrid uncertainty analysis is then performed through a combination of Monte Carlo simulation and fuzzy set theory. The probability of occurrence of the top event is finally calculated using the proposed FT-based hybrid uncertainty analysis method.

The efficiency of the proposed method is demonstrated by implementing in a real steel structure project. A quantitative risk assessment is performed for weld cracks, taking into account of both types of uncertainties. An importance analysis is finally performed to evaluate the contribution of each BE to the probability of occurrence of weld cracks and adopt appropriate response strategies.

In this research, the impact of objective (aleatory) dependence between the occurrences of different BEs and subjective (epistemic) dependence between estimates of the epistemically uncertain probabilities of some BEs are not considered. Moreover, there exist limitations to the application of fuzzy set rules, which were used for aggregating experts’ opinions and ranking purposes of the BEs in the FT model. These limitations can be investigated through further research.

It is believed that the proposed hybrid uncertainty analysis method presents a robust and powerful tool for quantitative risk analysis, as both types of uncertainties are taken into account appropriately.

The purpose of this paper is to improve risk assessment processes in airline flight operations by introducing a dynamic risk assessment method.

Fuzzy logic and Bayesian network are used together to form a dynamic structure in the analysis. One of the most challenging factors of the analyses in aviation is to get quantitative data. In this study, the fuzzy data quantification technique is used to perform dynamic risk assessment. Dynamic structure in the analysis is obtained by transforming the bow-tie model into a Bayesian network equivalent.

In this study, the probability of top-event from fault tree analysis is calculated as 1.51 × 10⁻⁶. Effectiveness of the model is measured by comparing the analysis with the safety performance indicator data that reflects past performance of the airlines. If two data are compared with each other, they are at the same order of value, with small difference (0.6 × 10⁻⁷).

This study proposes a dynamic model to be used in risk assessment processes in airline flight operations. A dynamic model for safety analysis provides real-time, autonomous and faster risk assessment. Moreover, it can help in the decision-making process and reduce airline response time to undesired states, which means that the proposed model can contribute to the efficiency of the risk management process in airline flight operations.

Tropical storms Urduja and Vinta battered the Philippines in December 2017. Despite advances in disaster risk reduction efforts of the country, the twin December storms caused numerous deaths in the Visayas and Mindanao regions. Analysis of these events shows that alerts raised during the Pre-Disaster Risk Assessment (PDRA) for both storms were largely ineffective because they were too broad and general calling for forced evacuations in too many provinces. Repeated multiple and general warnings that usually do not end up in floods or landslides, desensitize people and result in the cry-wolf effect where communities do not respond with urgency when needed. It was unlike the previous execution of PDRA from 2014 to early 2017 by the National Disaster Risk Reduction and Management Council (NDRRMC), which averted mass loss of lives in many severely impacted areas because of hazard-specific, area-focused and time-bound warnings. PDRA must reinstate specific calls, where mayors of communities are informed by phone hours in advance of imminent danger to prompt and ensure immediate action. Mainstreaming Climate Change Adaptation and Disaster Risk Reduction information using probabilistic (multi-scenario) hazard maps is also necessary for an effective early warning system to elicit appropriate response from the community. The paper aims to discuss these issues.

Methods of early warning through the PDRA of the National Disaster Mitigation and Management Council (NDRRMC) of the Philippines during tropical storm Urduja and Typhoon Vinta were assessed in this study and compared to the previous PDRA system from 2014 to early 2017.

It was found out that the numerous casualties were due to inadequate warning issued during the approach of the tropical cyclones. During an impending hazard, warnings must be accurate, reliable, understandable and timely. Despite the availability of maps that identified safe zones for different communities, warnings raised during the PDRA for both tropical cyclones were deemed too general calling for evacuations of whole provinces. As such, not all communities were evacuated in a timely manner because of failure in the key elements of an effective early warning system.

To avoid future disasters from happening, it is recommended that the PDRA reinstate its hazards-specific, area-focused and time-bound warnings. Similarly, to increase the resilience of communities, more work on mainstreaming of Climate Change Adaptation and Disaster Risk and Vulnerability Reduction systems for communities must be done as well. Learning from the lessons of these previous disasters will enable communities, their leaders and every stakeholder, not to repeat the same mistakes in the future.

The purpose of this paper is to examine the effectiveness of building codes in earthquake risk mitigation in Taiwan.

Using probabilistic risk analysis tools with available data, this study assesses the exceedance probability of extensive damage limit for general buildings in their 50‐year useful lives. The buildings were classified into 15 categories according to their construction materials and building height. Then, the effects of construction materials, building height and construction years are detected.

The exceedance probabilities of extensive damage limit for all of the investigated buildings in their 50‐year useful lives are on the order of 10⁻². The effect of construction materials and building height on seismic risk of buildings is decreasing with the development of a seismic design code. Significant discrepancy of seismic risk still exists among some buildings.

Seismic risk analysis requires quite restrictive statistical idealizations for the relevant probabilistic terms in the mathematical formulation. The problem of imperfect simplification and lack of sufficient empirical data has shown the research needs for improvements of seismic risk assessment. The questions of what constitutes acceptable risk for various performance levels and how safe is safe enough remain context‐specific.

Although probabilistic risk analysis provides a tool for quantifying the probability of structural failure, current earthquake‐resistant design procedures do not relate performance levels to probability. The paper explores some probability information for current earthquake‐resistant design for general buildings during their 50‐year useful lives and the information may provide some valuable information for future code calibration.