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Natural and technological hazards have a major impact on environmental and human safety. Risk assessment plays an essential role in the risk management of the effects of such hazards. This contribution summarizes first the general formulation of risk depending on two parameters: hazard probability and associated consequences. Problems faced in industrial applications based on the experience of the author are discussed. Risk acceptance criteria for the contributors to risk i.e. human, economic and environment are critically reviewed. Resilience based criteria are also included and conclusions for future developments are provided.
Structural health monitoring (SHM) projects are mostly based on semi-empirical decisions, emphasising the importance of the structure and lacking a rational comparison of the benefits and costs. The present work offers guidance to overcome this, based on an objective framework using the quantification of the value of SHM in an engineering context. Firstly, procedures for practising engineers are outlined on the basis of the COST guidelines. Secondly, a case study, focused on the reliability of a historic masonry structure, demonstrates the optimisation of surveys based on non-destructive tests calibrated by destructive tests. Both the outlined procedures and case study are carefully prepared and in tune, so the reader can easily understand the feasibility of the framework. Decisions on the utilisation of SHM in practical applications can be effectively achieved based on the highest expected utility gained by SHM. For this, two scenarios are needed: (i) a scenario with at least one SHM strategy and (ii) a scenario without any SHM.
Masonry structures were built by various techniques using different materials, the properties of which exhibit a considerable scatter dependent on periods of construction and region-specific conditions. For historic structures with a heritage value, various non- or minor-destructive tests (NDTs) are commonly applied, while the application of destructive tests (DTs) is minimized. The contribution is based on investigations of 15 historic stone and clay brick masonry structures, for which NDT strengths of masonry units are verified by DTs. The proposed operational approach makes it possible to account for statistical uncertainty due to a limited number of DTs used to calibrate NDTs.
A Bayesian network is applied in this contribution in order to assess the risks of a selected production unit in a fossil power station. A general framework for the risk assessment of production units of a power station is presented first by implementing statistical methods and Bayesian networks. Special emphasis is given to the input data consisting of failure rates which are obtained on the basis of recorded data and expert judgements. The consequences of failure are divided into economical and human (societal): economic consequences include outages of key technological devices, societal consequences cover potential injuries and fatalities. Probabilistic risk assessment methods are applied to the selected production unit of a power station. The influence of the uncertainties in the considered technical parameters on the availability of the unit is assessed and the acceptance of the calculated availability represented through the mean value and the standard deviation is discussed. Societal risks given in terms of weighted injuries and fatalities are obtained and respective risk acceptance criteria are presented. Uncertainties affecting the risks are discussed. It appears that the proposed framework provides a valuable assessment of the influence individual devices and their components on availability and societal risk. For that purpose the used methodology, intentionally simplified for operational applications, includes important factors affecting risks of production units. It is concluded that Bayesian networks are a transparent method for the probabilistic risk assessment of complex technological systems. The results of the performed analyses can be easily updated when additional information becomes available as illustrated in characteristic examples.
The assessment of existing infrastructures in the energy sector is of great economic significance worldwide. Fossil power stations are reaching their design service life and rational decisions concerning extensions of service life, maintenance and replacements of devices should be based on updated information of the actual conditions of the energy devices and their components, and on cost-benefit analysis using risk analysis and probabilistic optimisation procedures.
The contribution provides an integrated framework for probabilistic reliability and risk assessment of existing energy production units considering availability and human safety criteria. An extensive case study focused on risks of an energy production unit in a fossil power station is provided to support practical applications. A Bayesian network is thereby implemented to assess the risks of the selected production unit. Special emphasis is given to the input data consisting of failure rates obtained from recorded data and expert judgements. The influence of uncertainties in the considered performance indicators on the availability of the unit is analysed. It is shown that a reasonably simplified framework can provide a valuable assessment of the influence of individual devices and their components on availability and societal risk, identifying thus the major risk contributors. (C) 2017 Elsevier Ltd. All rights reserved.
Compressive Strength of Historic Masonry based on Destructive and Non-Destructive Test Results
(2017)
Specifying the target reliability levels is one of the key issues in the assessment of existing structures. For a majority of existing buildings and infrastructures, the design life has been reached or will be reached in the near future. These structures need to be reassessed in order to verify their safety. Eurocodes provide a general basis primarily intended for the design of new structures, but the basic principles can be used for assessing existing buildings, too. Reliability levels are generally based on both economic optimization and criteria for human safety. In this study, both methods are elaborated for existing structures. It appears that the requirement for the same target reliability for existing and new structures is uneconomical. Further, cost optimization seems to yield rather low reliability levels and human safety criteria often become the critical factor. The study concludes with practical guidelines for establishing reliability indices for existing structures linked to Eurocode principles.
Specifying the target reliability levels is one of the key issues in the assessment of existing structures. For a majority of existing buildings and infrastructures, the design life has been reached or will be reached in the near future. These structures need to be reassessed in order to verify their safety. Eurocodes provide a general basis primarily intended for the design of new structures, but the basic principles can be used for assessing existing buildings, too. Reliability levels are generally based on both economic optimization and criteria for human safety. In this study, both methods are elaborated for existing structures. It appears that the requirement for the same target reliability for existing and new structures is uneconomical. Further, cost optimization seems to yield rather low reliability levels and human safety criteria often become the critical factor. The study concludes with practical guidelines for establishing reliability indices for existing structures linked to Eurocode principles.
Codes of practice aim to assure structures have acceptable risks to the public and the minimum total costs over the working life of a design. However, current codified criteria for structural design correspond to a broad range of reliability levels, specified for dissimilar reference periods even though their recalculation for different periods is uncertain due to unknown dependence of failure events in time. In this contribution, target reliability levels are specified on the basis of probabilistic risk optimization considering the objective function as a sum of various costs including effects of time to failure and discounting. A case study presents probabilistic optimization of the roof of a stadium for 4,000 spectators and illustrates the effect of the considered input parameters. Failure consequences and relative cost of safety measure are shown to be major factors affecting the optimum reliability level. Less important factors are the discount rate and working life. Large uncertainty in failure cost estimates seems to have only a marginal effect on derived optimum reliability levels.