Improving technical specifications from a risk perspective

The Technical Specifications (TSs) for a nuclear power plant is an important licensing document which defines various operational requirements or conditions. In light of the recent trends to move towards risk-based regulation, many researchers analyzed the risk impacts associated with the TS requirements, using the plant models, such as event trees or fault trees, that were developed as part of probabilistic safety assessments. This paper presents the insights gained from a review of these risk-based analyses of TSs, focussing on surveillance requirements and AOT (allowed outage time) requirements.     

The role of interactions in a world implementing adaptation and mitigation solutions to climate change

The papers in this volume discuss projections of climate change impacts upon humans and ecosystems under a global mean temperature rise of 4°C above preindustrial levels. Like most studies, they are mainly single-sector or single-region-based assessments. Even the multi-sector or multi-region approaches generally consider impacts in sectors and regions independently, ignoring interactions. Extreme weather and adaptation processes are often poorly represented and losses of ecosystem services induced by climate change or human adaptation are generally omitted. This paper addresses this gap by reviewing some potential interactions in a 4°C world, and also makes a comparison with a 2°C world. In a 4°C world, major shifts in agricultural land use and increased drought are projected, and an increased human population might increasingly be concentrated in areas remaining wet enough for economic prosperity. Ecosystem services that enable prosperity would be declining, with carbon cycle feedbacks and fire causing forest losses. There is an urgent need for integrated assessments considering the synergy of impacts and limits to adaptation in multiple sectors and regions in a 4°C world. By contrast, a 2°C world is projected to experience about one-half of the climate change impacts, with concomitantly smaller challenges for adaptation. Ecosystem services, including the carbon sink provided by the Earth's forests, would be expected to be largely preserved, with much less potential for interaction processes to increase challenges to adaptation. However, demands for land and water for biofuel cropping could reduce the availability of these resources for agricultural and natural systems. Hence, a whole system approach to mitigation and adaptation, considering interactions, potential human and species migration, allocation of land and water resources and ecosystem services, will be important in either a 2°C or a?4°C world.     

A systems perspective on responses to climate change

The science of climate change integrates many scientific fields to explain and predict the complex effects of greenhouse gas concentrations on the planet’s energy balance, weather patterns, and ecosystems as well as economic and social systems. A changing climate requires responses to curtail climate forcing as well as to adapt to impending changes. Responses can be categorized into mitigation and adaptation—the former involving efforts to reduce greenhouse gas emissions, and the latter involving strategies to adapt to predicted changes. These responses must be of significant scale and extent to be effective, but significant tradeoffs and unintended effects must be avoided. Concepts and science based on systems theory are needed to reduce the risk of unintended consequences from potential responses to climate change. We propose expanding on a conventional risk-based approach to include additional ways of analyzing risks and benefits, such as considering potential cascading ecological effects, full life cycle environmental impacts, and unintended consequences, as well as considering possible co-benefits of responses. Selected responses to climate change are assessed with this expanded set of criteria, and we find that mitigation measures that involve reducing emissions of greenhouse gases that provide corollary benefits are likely to have less negative indirect impacts than large-scale solar radiation management approaches. However, because effects of climate change are unavoidable in the near and medium-term, adaptation strategies that will make societies more resilient in the face of impending change are essential to sustainability.     

Calculating and addressing uncertainty for risk-based allowable outage times

This article examines the calculation and treatment of uncertainty in risk-based allowable outage times (AOTs) for operational control at nuclear power plants, where an AOT is defined as the time that a component or system is permitted to be out of service. The US Nuclear Regulatory Commission (NRC) has explored the possibility of using a nuclear power plant's probabilistic risk assessment results to determine component or system AOTs. The analysis and results from previous work prepared for the NRC on determining risk-based AOTs are presented. As part of the discussion, the article examines the inherent uncertainty in calculating risk-based AOTs and presents the difficulties in calculating these risk-based AOTs. It is noted that care should be taken when dealing with uncertainty analysis results where a time-interval is the outcome of the analysis. In addition, potential improvements in the mechanism of calculating risk-based AOTs are suggested.     

Using ‘soft’ and ‘hard’ social impact indicators to understand societal change caused by mining: a Western Australia case study

The paper explores the qualitative changes occurring in the local social landscape as a result of mining. Building on Colantonio's social sustainability assessment framework, we argue that there are three thematic areas (related to demographics, social capital and well-being) which identify change generally and specifically caused by mining. By studying the social impacts of mining, we examine both ‘hard’ themes around quantifiable indicators and ‘soft’ themes which deal with less tangible community characteristics and values. The analysis of the Western Australian Boddington case study demonstrates that such an approach can generate important insights about a community's nature and potential capabilities to cope and respond to change. We argue that if social impact assessment is to be used as a development tool, which is a tool that facilitates development, there is need to understand those aspects of the social environment that impact positively and/or negatively its demographic, quality and operational attributes as they influence the overall capacity of communities to maintain and enhance their long-term functioning.     

Questioning the assumptions: the role of vulnerability assessments in climate change adaptation

A number of challenges prevent climate change adaptation activities from contributing to vulnerability reduction. Some of these relate to the nature and quality of vulnerability assessments, while others concern how well assessments link with adaptation actions. By highlighting four persistent assumptions about the role of vulnerability assessments in adaptation, this paper seeks to identify ways in which the practice of vulnerability assessment can better support progressive adaptation actions. This paper argues that, for adaptation actions identified within vulnerability assessments to be successful, there is a need for assessment to: (i) engage with marginalized perspectives; (ii) draw upon diverse knowledge domains; (iii) integrate scales of analysis with appropriate scales of action; and (iv) build political will. This requires vulnerability assessment to be considered as more than just a method for information generation on who is most vulnerable to climate change, where they are located and the underlying reasons for their vulnerability. In addition, improving the rigor and transparency of assessments and engagement with stakeholders during the assessment process can better facilitate vulnerability-focused adaptation.     

Security risks and probabilistic risk assessment of glazing subject to explosive blast loading

A probabilistic risk assessment (PRA) procedure is developed which can predict risks of explosive blast damage to built infrastructure. The present paper focuses on window glazing since this is a load-capacity system which, when subject to blast loading, has caused significant damage and injury to building occupants. Structural reliability techniques are used to derive fragility and blast reliability curves (BRCs) for annealed and toughened glazing subjected to explosive blast, for a variety of threat scenarios. The probabilistic analyses include the uncertainties associated with blast modelling, glazing response and glazing failure criteria. Damage risks are calculated for an individual window and for windows in the facade of a multi-storey commercial building. If threat probabilities can be estimated then the paper shows illustrative examples of how this information, when combined with risk-based decision-making criteria, can be used to optimise risk mitigation strategies.     

Fuzzy belief propagation in constrained Bayesian networks with application to maintenance decisions

Bayesian networks have been widely applied to domains such as medical diagnosis, fault analysis, and preventative maintenance. In some applications, because of insufficient data and the complexity of the system, fuzzy parameters and additional constraints derived from expert knowledge can be used to enhance the Bayesian reasoning process. However, very few methods are capable of handling the belief propagation in constrained fuzzy Bayesian networks (CFBNs). This paper therefore develops an improved approach which addresses the inference problem through a max-min programming model. The proposed approach yields more reasonable inference results and with less computational effort. By integrating the probabilistic inference drawn from diverse sources of information with decision analysis considering a decision-maker's risk preference, a CFBN-based decision framework is presented for seeking optimal maintenance decisions in a risk-based environment. The effectiveness of the proposed framework is validated based on an application to a gas compressor maintenance decision problem.     

Estimating the regional economic impacts of retiring agricultural land: methodology and an application in California

This report is of a study to assess the efficiency and sustainability impacts of a seed-based technology for pigeonpea in semi-arid central India. The problem of integrating environmental assessment with economic and social impact assessment arises from an artificial separation of the social and natural sciences, and the ‘disciplinization’ of the social sciences. Thus sustainability must be defined in a way that pre-empts the need to integrate results obtained from different approaches. Sustainability assessment then is a dynamic not a static framework. It involves changes in labor requirements, in soil and agro-climatic conditions, and in notions and perceptions of efficiency and profitability with differential social and economic impacts. This approach requires a methodology that uses a combination of techniques — survey research, case study, and rapid/participatory rural appraisals — with the flexibility of adjustment and adaptation during the course of research.     

A risk-based optimisation for pavement preventative maintenance with probabilistic LCCA: a Chinese case

Compared to major structural repair or even replacement, preventative preservation of in-service pavements has been more popular in engineering practices, but recently, pavement preventative maintenance (PPM) has become more complex in China as the competition for pavement preservation funds has grown and the need to justify decisions has increased. Therefore, the life cycle cost analysis (LCCA) has increasingly attracted attention from transportation agencies. However, most of previous studies were conducted deterministically or only focused on a single factor, while PPM is apparently affected by many potential sources of uncertainty. The risk-based analysis to investigate potential risks and combined effects of multiple factors is a necessary component of PPM. This paper aims at presenting a risk-based PPM with the probabilistic LCCA for a Chinese highway case. Major analysis variables of different range are examined to probe risks of different scenarios, investigate combined effects of multiple variables and identify an optimal preservation strategy.     

A framework to integrate software behavior into dynamic probabilistic risk assessment

Software plays an increasingly important role in modern safety-critical systems. Although, research has been done to integrate software into the classical probabilistic risk assessment (PRA) framework, current PRA practice overwhelmingly neglects the contribution of software to system risk. Dynamic probabilistic risk assessment (DPRA) is considered to be the next generation of PRA techniques. DPRA is a set of methods and techniques in which simulation models that represent the behavior of the elements of a system are exercised in order to identify risks and vulnerabilities of the system. The fact remains, however, that modeling software for use in the DPRA framework is also quite complex and very little has been done to address the question directly and comprehensively. This paper develops a methodology to integrate software contributions in the DPRA environment. The framework includes a software representation, and an approach to incorporate the software representation into the DPRA environment SimPRA. The software representation is based on multi-level objects and the paper also proposes a framework to simulate the multi-level objects in the simulation-based DPRA environment. This is a new methodology to address the state explosion problem in the DPRA environment. This study is the first systematic effort to integrate software risk contributions into DPRA environments.     

考虑土体参数空间变异性边坡失稳风险定量评估

边坡失稳风险定量评估是制定滑坡风险防治措施和建立滑坡风险预警体系的重要前提,然而目前方法不能有效地解决考虑土体参数二维空间变异性的边坡失稳风险定量评估问题,该文在蒙特卡洛模拟（MCS）和极限平衡分析框架下提出了一种有效的考虑参数二维空间变异性的边坡失稳风险定量评估方法,依次从土体参数二维空间变异性模拟、空间变异边坡稳定性分析、边坡代表性滑动面识别和边坡失稳风险定量分析这四个方面对提出方法进行了详细介绍。最后通过对3种工况下两层不排水饱和黏土边坡的失稳风险定量分析验证了提出方法的有效性。结果表明:该文提出方法具有以下优势:1）可以有效地识别空间变异边坡代表性滑动面,即边坡关键破坏模式;2）具有较高的边坡失稳风险评估计算效率,可为解决考虑参数二维空间变异性的低概率水平边坡失稳风险定量评估问题提供一个有效的工具;3）可以定量地计算每个关键破坏模式对边坡失效概率和失稳风险的贡献权重,从而可为制定有效的滑坡风险控制措施提供重要的参考依据。     

Issues related to structural aging in probabilistic risk assessment of nuclear power plants

Structural components and systems have an important safety function in nuclear power plants. Although they are essentially passive under normal operating conditions, they play a key role in mitigating the impact of extreme environmental events such as earthquakes, winds, fire and floods on plant safety. Moreover, the importance of structural components and systems in accident mitigation is amplified by common-cause effects. Reinforced concrete structural components and systems in NPPs are subject to a phenomenon known as aging, leading to time-dependent changes in strength and stiffness that may impact their ability to withstand various challenges during their service lives from operation, the environment and accidents. Time-dependent changes in structural properties as well as challenges to the system are random in nature. Accordingly, condition assessment of existing structures should be performed within a probabilistic framework. The mathematical formalism of a probabilistic risk assessment (PRA) provides a means for identifying aging structural components that may play a significant role in mitigating plant risk. Structural condition assessments supporting a decision regarding continued service can be rendered more efficient if guided by the logic of a PRA.     

Probabilistic design and management of environmentally sustainable repair and rehabilitation of reinforced concrete structures

This paper presents a probabilistic sustainability design framework for the design of concrete repairs and rehabilitations intended to achieve targeted improvements in quantitative sustainability indicators. The framework consists of service life prediction models combining deterioration mechanisms with limit states and life cycle assessment models for measuring the impact of a repair or rehabilitation. Both types of models (service life or LCA) are formulated stochastically so that the time to repair and the accumulated sustainability impact are described by probability density functions. This leads to a probabilistic calculation of cumulative impacts throughout the structure’s service life, from initial repair to functional obsolescence (end of life). The methods discussed are in accordance with sustainability design requirements within the 2010 fib Model Code. A case study is presented which computes the probability that reinforced concrete repair strategies using thicker concrete cover will meet future greenhouse gas emission reduction targets proposed by the UN Intergovernmental Panel on Climate Change.     

ELPIS-JP: a dataset of local-scale daily climate change scenarios for Japan

We developed a dataset of local-scale daily climate change scenarios for Japan (called ELPIS-JP) using the stochastic weather generators (WGs) LARS-WG and, in part, WXGEN. The ELPIS-JP dataset is based on the observed (or estimated) daily weather data for seven climatic variables (daily mean, maximum and minimum temperatures; precipitation; solar radiation; relative humidity; and wind speed) at 938 sites in Japan and climate projections from the multi-model ensemble of global climate models (GCMs) used in the coupled model intercomparison project (CMIP3) and multi-model ensemble of regional climate models form the Japanese downscaling project (called S-5-3). The capability of the WGs to reproduce the statistical features of the observed data for the period 1981-2000 is assessed using several statistical tests and quantile-quantile plots. Overall performance of the WGs was good. The ELPIS-JP dataset consists of two types of daily data: (i) the transient scenarios throughout the twenty-first century using projections from 10 CMIP3 GCMs under three emission scenarios (A1B, A2 and B1) and (ii) the time-slice scenarios for the period 2081-2100 using projections from three S-5-3 regional climate models. The ELPIS-JP dataset is designed to be used in conjunction with process-based impact models (e.g. crop models) for assessment, not only the impacts of mean climate change but also the impacts of changes in climate variability, wet/dry spells and extreme events, as well as the uncertainty of future impacts associated with climate models and emission scenarios. The ELPIS-JP offers an excellent platform for probabilistic assessment of climate change impacts and potential adaptation at a local scale in Japan.     

Different sets of reliability data and success criteria in a probabilistic safety assessment for a plant producing nitroglycol

The lack of plant-specific reliability data for probabilistic safety assessments usually makes it necessary to use generic reliability data. Justifiably different assessments of plant behaviour (success criteria) lead to different models of plant systems. Both affect the numerical results of a probabilistic safety assessment. It is shown how these results change, if different sets of reliability data and different choices of success criteria for the safety system are employed. Differences in results may influence decisions taken on their basis and become especially important if compliance with a safety goal has to be proved, e.g. a safety integrity level. For the purpose of demonstration an accident sequence from a probabilistic safety assessment of a plant producing nitroglycol is used. The analysis relies on plant-specific reliability data so that it provides a good yardstick for comparing it with results obtained using generic data. The superiority of plant-specific data, which should of course be acquired, cannot be doubted. Nevertheless, plant safety can be improved even if generic data are used. However, the assignment to a safety integrity level may be affected by differences in both data and success criteria.     

Integrating ecosystem services in Swedish environmental assessments: an empirical analysis

Given the growing number of policies and laws that encourage inclusion of ecosystem services (ES) in processes, we have investigated environmental impact assessments (EIA) and strategic environmental assessments (SEA) conducted in Sweden in order to analyse whether ES may be integrated to enhance and improve environmental assessment of today. Representative Swedish environmental projects were reviewed. Three cases with different geographic and environmental settings were selected to allow us to study consideration of a wide range of different ES. We investigated the processes and discussions taking place using documentation from the cases. We formalized and labelled the expected impacts into an ES framework. Summarizing each case, we described conformities and divergences in explicit and implicit prioritizations between the actors. We discussed the benefits of integrating ES into current practices and possible improvements in the processes and methodologies. When ES could be integrated into EIAs and SEAs more aspects would be visualized and a larger stakeholder engagement stimulated leading to improved support for decision-making.     

The economics of abrupt climate change

The US National Research Council defines abrupt climate change as a change of state that is sufficiently rapid and sufficiently widespread in its effects that economies are unprepared or incapable of adapting. This may be too restrictive a definition, but abrupt climate change does have implications for the choice between the main response options: mitigation (which reduces the risks of climate change) and adaptation (which reduces the costs of climate change). The paper argues that by (i) increasing the costs of change and the potential growth of consumption, and (ii) reducing the time to change, abrupt climate change favours mitigation over adaptation. Furthermore, because the implications of change are fundamentally uncertain and potentially very high, it favours a precautionary approach in which mitigation buys time for learning. Adaptation-oriented decision tools, such as scenario planning, are inappropriate in these circumstances. Hence learning implies the use of probabilistic models that include socioeconomic feedbacks.     

Integrated assessment of pedestrian head impact protection in testing secondary safety and autonomous emergency braking

Pedestrian impact testing is used to provide information to the public about the relative level of protection provided by different vehicles to a struck pedestrian. Autonomous Emergency Braking (AEB) is a relatively new technology that aims to reduce the impact speed of such crashes. It is expected that vehicles with AEB will pose less harm to pedestrians, and that the benefit will come about through reductions in the number of collisions and a change in the severity of impacts that will still occur. In this paper, an integration of the assessment of AEB performance and impact performance is proposed based on average injury risk. Average injury risk is calculated using the result of an impact test and a previously published distribution of real world crash speeds. A second published speed distribution is used that accounts for the effects of AEB, and reduced average risks are implied. This principle allows the effects of AEB systems and secondary safety performance to be integrated into a single measure of safety. The results are used to examine the effect of AEB on Euro NCAP and ANCAP assessments using previously published results on the likely effect of AEB. The results show that, given certain assumptions about AEB performance, the addition of AEB is approximately the equivalent of increasing Euro NCAP test performance by one band, which corresponds to an increase in the score of 25% of the maximum.     

Risk-based inspection and maintenance in process plants and their practices in Taiwan

The content of risk-based assessment and management and risk-based inspection and maintenance (RBI&M) employed in process plants are addressed in this article. Probabilistic analyses including probabilistic risk assessment developed in the engineering field over the past few decades are reviewed first. Following that, RBI and risk-informed management employed in the nuclear industry and risk-based inspection, maintenance, and other risk-based approaches used in chemical plants as well as their developments are reviewed, respectively. While most of the above were developed and practiced in industrialized countries, the current situation in Taiwan is also mentioned. Special attention is paid to the possibility and difficulties of employing RBI&M in Taiwan’s power and process plants. The difficulties in adopting existing risk-based approaches to inspect and manage Kaohsiung’s underground pipelines are pointed out in particular. Comments are made at the end of the article.