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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.

Many educational systems are currently establishing standards frameworks for school principals’ work. This paper critiques three current examples and describes an alternative approach. The authors argue that by combining qualitative case studies with probabilistic measurement techniques, the alternative approach provides contextually rich descriptions of the growth in performance on a series of dimensions.

This paper aims to describe a multi-scenario assessment of the seismogenic tsunami hazard for Bangladesh from active subduction zones in the Indian Ocean region. Two segments of the Sunda arc, namely, Andaman and Arakan, appear to pose a tsunamigenic seismic threat to Bangladesh.

High-resolution numerical simulations of tsunami propagation toward the coast of Bangladesh have been carried out for eight plausible seismic scenarios in Andaman and Arakan subduction zones. The numerical results have been analyzed to obtain the spatial variation of the maximum tsunami amplitudes as well as tsunami arrival times for the entire coastline of Bangladesh.

The results suggest that the tsunami heights are amplified on either side of the axis of the submarine canyon which approaches the nearshore sea off Barisal in the seaboard off Sundarban–Barisal–Sandwip. Moreover, the computed tsunami amplitudes are comparatively higher north of the latitude 21.5o in the Teknaf–Chittagong coastline. The calculated arrival times indicate that the tsunami waves reach the western half of the Sundarban–Barisal–Sandwip coastline sooner, while shallow water off the eastern half results in a longer arrival time for that part of the coastline, in the event of an earthquake in the Andaman seismic zone. On the other hand, most parts of the Chittagong–Teknaf coastline would receive tsunami waves almost immediately after an earthquake in the northern segment of the Arakan seismic zone.

The present assessment includes probabilistic measures of the tsunami hazard by incorporating several probable seismic scenarios corresponding to recurrence intervals ranging from 25 years to over 1,000 years.

This study aims to introduce a methodology for optimal allocation of spinning reserves taking into account load, wind and solar generation by application of the univariate and bivariate parametric models, conventional intra and inter-zonal spinning reserve capacity as well as demand response through utilization of capacity outage probability tables and the equivalent assisting unit approach.

The method uses a novel approach to model wind power generation using the bivariate Farlie–Gumbel–Morgenstern probability density function (PDF). The study also uses the Bayesian network (BN) algorithm to perform the adjustment of spinning reserve allocation, based on the actual unit commitment of the previous hours.

The results show that the utilization of bivariate wind prediction model along with reserve allocation adjustment algorithm improve reliability of the power grid by 2.66% and reduce the total system operating costs by 1.12%.

The method uses a novel approach to model wind power generation using the bivariate Farlie–Gumbel–Morgenstern PDF. The study also uses the BN algorithm to perform the adjustment of spinning reserve allocation, based on the actual unit commitment of the previous hours.

The purpose of this study is to improve the computational efficiency and accuracy of fatigue reliability analysis.

By absorbing the advantages of Markov chain and active Kriging model into the hierarchical collaborative strategy, an enhanced active Kriging-based hierarchical collaborative model (DCEAK) is proposed.

The analysis results show that the proposed DCEAK method holds high accuracy and efficiency in dealing with fatigue reliability analysis with high nonlinearity and small failure probability.

The effectiveness of the presented method in more complex reliability analysis problems (i.e. noisy problems, high-dimensional issues etc.) should be further validated.

The current efforts can provide a feasible way to analyze the reliability performance and identify the sensitive variables in aeroengine mechanisms.

To improve the computational efficiency and accuracy of fatigue reliability analysis, an enhanced active DCEAK is proposed and the corresponding fatigue reliability framework is established for the first time.

The operating costs and production losses due to equipment failure of offshore gas and oil production systems can exceed initial investment cost. The article explores the probability distribution of downtime associated with random equipment failure and applies availability assessment to design optimisation.

Container shipping is a crucial component of the global supply chain that is affected by a large range of operational risks with high uncertainty, threatening the stability of service, manufacture, distribution and profitability of involved parties. However, quantitative risk analysis (QRA) of container shipping operational risk (CSOR) is being obstructed by the lack of a well-established theoretical structure to guide deeper research efforts. This paper proposes a methodological framework to strengthen the quality and reliability of CSOR analysis (CSORA).

Focusing on addressing uncertainties, the framework establishes a solid, overarching and updated basis for quantitative CSORA. The framework consists of clearly defined elements and processes, including knowledge establishing, information gathering, aggregating multiple sources of data (social/deliberative and mathematical/statistical), calculating risk and uncertainty level and presenting and interpreting quantified results. The framework is applied in a case study of three container shipping companies in Vietnam.

Various methodological contributions were rendered regarding CSOR characteristics, settings of analysis models, handling of uncertainties and result interpretation. The empirical study also generated valuable managerial implications regarding CSOR management policies.

This paper fills the gap of an updated framework for CSORA considering the recent advancements of container shipping operations and risk management. The framework can be used by both practitioners as a tool for CSORA and scholars as a test bench to facilitate the comparison and development of QRA models.

The purpose of this paper is to develop an advanced decision-making support for the appropriate responding to critical alarms in the hazardous industrial facilities.

A fuzzy analytical hierarchy process is suggested by considering three alternatives and four criteria using triangular fuzzy numbers to handle the associated uncertainty. A logarithmic fuzzy preference programming (LFPP)-based nonlinear priority method is employed to analyze the suggested model.

A quantitative decision-making support is not only a necessity in responding to critical alarms but also easy to implement even in a relatively short reaction time. Confirmation may not be the appropriate option to deal with a critical alarm, even with the availability of the needed resources.

A situation related to a flammable gas alarm in a gas plant is treated using the developed model showing its practical efficiency and practicality.

The proposed model provides a rational, simple and holistic fuzzy multi criteria tool with a refined number of criteria and alternatives using an LFPP method to handle process alarms.

Human error data in the form of human error probabilities should ideally form the corner‐stone of human reliability theory and practice. In the history of human reliability assessment, however, the collection and generation of valid and usable data have been remarkably elusive. In part the problem appears to extend from the requirement for a technique to assemble the data into meaningful assessments. There have been attempts to achieve this, THERP being one workable example of a (quasi) database which enables the data to be used meaningfully. However, in recent years more attention has been focused on the PerformanceShaping Factors (PSF) associated with human reliability. A “database for today” should therefore be developed in terms of PSF, as well as task/ behavioural descriptors, and possibly even psychological error mechanisms. However, this presumes that data on incidents and accidents are collected and categorised in terms of the PSF contributing to the incident, and such classification systems in practice are rare. The collection and generation of a small working database, based on incident records are outlined. This has been possible because the incident‐recording system at BNFL Sellafield does give information on PSF. Furthermore, the data have been integrated into the Human Reliability Management System which is a PSF‐based human reliability assessment system. Some of the data generated are presented, as well as the PSF associated with them, and an outline of the incident collection system is given. Lastly, aspects of human common mode failure or human dependent failures, particularly at the lower human error probability range, are discussed, as these are unlikely to be elicited from data collection studies, yet are important in human reliability assessment. One possible approach to the treatment of human dependent failures, the utilisation of human performance‐limiting values, is described.