Risk-based Decision Analysis Research Articles

Risk analysis framework for the optimum remediation of a contaminated aquifer under uncertainty: application in Lake Karla aquifer, Thessaly, Greece

A risk analysis framework is proposed for the optimum remediation of a contaminated aquifer under hydrogeological uncertainty. The limited information and the spatial variation of hydraulic conductivity in a real-world large-scale aquifer create uncertain conditions for decision-making when remediation schemes ought to be accompanied by the minimum possibility of failure. The primary concern is focused on safeguarding public health when groundwater is used for urban drinking purposes from a contaminated aquifer. The proposed framework is based on the conjunctive use of stochastic simulation–optimization modelling followed up by a risk analysis application on remediation trade-offs. The framework includes three main steps/procedures: (i) the model formulation of multiple realizations of groundwater flow and contaminant transport, (ii) the optimal positioning and operation of the clean-up wells determined by the method of stochastic optimization, and (iii) the risk analysis of the optimum remediation strategies through a proposed decision model, so as the one with the minimum cost and risk of failure is chosen as the most appropriate. The proposed framework is tested for two scenarios of nitrogen fertilizer application in the cultivated areas. The strategic target is the groundwater nitrate concentration minimization in an area where exceedances of nitrate concentrations have been observed and water supply wells have been operating for the last twenty years satisfying domestic needs. The results demonstrate that, when decision-making is under hydrogeological uncertainty, the combined use of stochastic optimization and risk-based decision analysis can commend the remediation strategy with the minimum cost and the highest possibility of success.

Risk-based multi-criteria decision analysis method for considering the effects of climate change on bridges

Recent studies have identified many potential climate change impacts on bridges. Considering the sheer number of these potential impacts, how can a bridge owner prioritise which impacts to consider, and for which bridges? This paper proposes a risk-based multi-criteria decision analysis method for systematically addressing these two questions simultaneously. The proposed method can be used to address both extreme and non-extreme impacts as opposed to focussing solely on extreme impacts as has been done in previous prioritisation studies related to climate change risks. The proposed method is based on four main components of risk: hazard, impact, vulnerability and consequences. Several indices characterising these components are used to address the previous two questions. To reflect the uncertainty in the analysis, the different indices are assessed optimistically and pessimistically. Additionally, to ensure a more transparent decision-making process the inclusion of a strength of evidence assessment is also proposed. The applicability of the method is then demonstrated on three illustrative case studies for three different potential climate change impacts. It is concluded that the proposed method is both feasible and appropriately fulfils its purpose. Nevertheless, the proposed method should be more elaborately tested on practical bridge case studies to further establish its applicability.

Risk-based multi-criteria decision analysis of gas power plants placement in semi-arid regions

The purpose of this research is to determine the optimum location to construct gas power plants (GPPs) in semi-arid regions. A combination of ordered weight averaging (OWA) and analytic hierarchy process (AHP) method named OWA-AHP is utilized to prepare land suitability maps with different risk scenarios when fuzzy method is to homogenize inputs. In the proposed method, AHP is to weigh each different parameter while OWA considers risk levels. In order to validate the accuracy of the proposed method, the receiver operating characteristics (ROC) curve is investigated. Besides, the self-organizing map (SOM) algorithm and Pearson correlation are used to determine the most important parameters for constructing GPP. According to obtained results, the areas located in the north and parts of the east and south of the selected case study (about 15%) at all risk levels are the optimum areas to be hosted for GPPs. Furthermore, ROC curve shows that the Area Under the Curve (AUC) values are high for both AHP and OWA-AHP methods (AUC Fuzzy-AHP = 94.0%, AUC OWA = 89.0%). The results of the SOM algorithm and Pearson correlation with high accuracy (RModel1: 0.853 and RModel2: 0.940) also depict that distance to the pipeline and road are the most important parameters to identify suitable locations for GPP.

A Risk-Based Multi-Criteria Decision Analysis Approach to Evaluating Transboundary Water Development—The Case of Lower Mekong River Basin

The Lower Mekong River basin (LMB) covers the lower part of the Mekong river basin, including Laos, Thailand, Cambodia and Vietnam. Due to numerous pressures from high population growth and intensive hydropower development, the LMB has been facing significant challenges concerning its biodiversity and ecosystem. In 2017, Mekong River Commission (MRC), an intergovernmental organisation founded in 1995 among LMB countries, established the Council Study, which analysed the impacts of water development scenarios concerning the environmental, socioeconomic aspects of the LMB. This paper explores the nature of risks to the LMB water development and subsequently evaluates LMB’s water development scenarios described in the Council Study by using a multi-criteria decision analysis (MCDA) method. MCDA method has been widely applied in the field of water resource management in order to assist the decision-making process by systematically evaluating a certain number of alternatives against well-selected criteria through a preference rating scheme. By implementing a risk-based comprehensive assessment of the LMB transboundary water, this study provides insights into the impacts of the increasing risks to the ecosystem and human beings on the water development of the basin over time, which assists to change the awareness and the perspective toward humans’ risks and transboundary river ecosystem of decision-makers. This paper provides valuable recommendations for MRC to improve their policy concerning benefit-sharing scheme, water planning and risk mitigation strategies.

Risk-based planning of assessment actions for fatigue life prediction

It is vital to extend the service life of existing bridges as far as possible as a means for improved sustainability leading to reduced economic cost and resource consumption. This requirement is especially valid for bridges which are critical components of highly vulnerable infrastructure systems. Achieving this aim requires enhanced methods involving various actions and methods influencing different aspects of the assessment process. A framework is presented in this paper based on three common factors used to describe the assessment actions of existing bridges; (i) model sophistication, (ii) uncertainty consideration, and (iii) knowledge content. The framework elucidates the influence of different decisions on the assessment process and facilitates the planning of appropriate assessment actions. Furthermore, it provides a basic scheme for a risk-based decision analysis for determining suitable assessment actions or activities. A fatigue assessment of an existing bridge detail is used to demonstrate the application of the framework in practical cases.

A multi-attribute methodology for the prioritisation of oil contaminated sites in the Niger Delta.

The Ogoniland region of the Niger Delta contains a vast number of sites contaminated with petroleum hydrocarbons that originated from Nigeria's active oil sector. The United Nations Environment Programme (UNEP) reported on this widespread contamination in 2011, however, wide-scale action to clean-up these sites has yet to be initiated. A challenge for decision makers responsible for the clean-up of these sites has been the prioritisation of sites to enable appropriate allocation of scarce resources. In this study, a risk-based multi-criteria decision analysis framework was used to prioritise high-risk sites contaminated with petroleum hydrocarbons in the Ogoniland region of Nigeria. The prioritisation method used a set of risk-based attributes that took into account chemical and ecological impacts, as well as socio-economic impacts, providing a holistic assessment of the risk. Data for the analysis was taken from the UNEP Environmental Assessment of Ogoniland, where over 110 communities were assessed for oil-contamination. Results from our prioritisation show that the highest-ranking sites were not necessarily the sites with the highest observed level of hydrocarbon contamination. This differentiation was due to our use of proximity as a surrogate measure for likelihood of exposure. Composite measures of risk provide a more robust assessment, and can enrich discussions about risk management and the allocation of resources for the clean-up of affected sites.

Creating a Holistic Extractables and Leachables (E&L) Program for Biotechnology Products.

The risk mitigation of extractables and leachables presents significant challenges to regulators and drug manufacturers with respect to the development, as well as the lifecycle management, of drug products. A holistic program is proposed, using a science- and risk-based strategy for testing extractables and leachables from primary containers, drug delivery devices, and single-use systems for the manufacture of biotechnology products. The strategy adopts the principles and concepts from ICH Q9 and ICH Q8(R2). The strategy is phase-appropriate, progressing from extractables testing for material screening/selection/qualification through leachables testing of final products. The strategy is designed primarily to ensure patient safety and product quality of biotechnology products. The holistic program requires robust extraction studies using model solvents, with careful consideration of solvation effect, pH, ionic strength, temperature, and product-contact surface and duration. From a wide variety of process- and product-contact materials, such extraction studies have identified and quantified over 200 organic extractable compounds. The most commonly observed compounds were siloxanes, fatty acid amides, and methacrylates. Toxicology assessments were conducted on these compounds using risk-based decision analysis. Parenteral permitted daily exposure limits were derived, as appropriate, for the majority of these compounds. Analysis of the derived parenteral permitted daily exposure limits helped to establish action thresholds to target high-risk leachables in drug products on stability until expiry. Action thresholds serve to trigger quality investigations to determine potential product impact. The holistic program also evaluates the potential risk for immunogenicity. This approach for primary drug containers and delivery devices is also applicable to single-use systems when justified with a historical knowledge base and understanding of the manufacturing processes of biotechnology products. In the development of a drug product, careful consideration is given to impurities that may originate from manufacturing equipment, process components, and packaging materials. The majority of such impurities are common chemical additives used to improve the physicochemical properties of a wide range of plastic materials. Suppliers and drug manufacturers conduct studies to extract chemical additives from the plastic materials in order to screen and predict those that may leach into a drug product. In this context, the term extractables refers to a profile of extracted compounds observed in studies under harsh conditions. In contrast, the term leachables refers to those impurities that leach from the materials under real-use conditions and may be present in final drug products. The purpose of this article is to present a holistic approach that effectively minimizes the risk of leachables to patient safety and product quality.

Economic incentives in sustainable water management: a Risk-Based Decision Analysis approach for determining groundwater pollution charges under uncertainty

A risk-based decision analysis methodology is presented, that can be used as a water policy tool in the design of economic incentive instruments, under conditions of uncertainty. A contaminated groundwater resource system with unknown hydrogeological parameters is used as a case study. The polluter has to select the policy to be followed among a series of alternatives, ranging from the extreme and environmentally risky scenario of paying pollution charges as long as the aquifer will remain polluted, up to the conservative option in terms of reduced environmental risks policy of safely rehabilitating the groundwater system. The full-cost price of water, including direct, opportunity, and environmental costs, both actual and probabilistic, as well as the risks of failure of the alternative scenarios due to the uncertainty, as they result from stochastic simulation, are embedded in a risk-cost-benefit decision model, developed for the evaluation of the alternatives. The pollution charges to be imposed by the local water authority are determined through the appropriate development of this model and the use of a proposed algorithm, in a way that these charges can act as incentives to the polluters, forcing them, or the authorities, to select the most environmentally sustainable water policy, namely that of safely restoring the aquifer.

Risk-based economic decision analysis of remediation options at a PCE-contaminated site

Remediation methods for contaminated sites cover a wide range of technical solutions with different remedial efficiencies and costs. Additionally, they may vary in their secondary impacts on the environment i.e. the potential impacts generated due to emissions and resource use caused by the remediation activities. More attention is increasingly being given to these secondary environmental impacts when evaluating remediation options. This paper presents a methodology for an integrated economic decision analysis which combines assessments of remediation costs, health risk costs and potential environmental costs. The health risks costs are associated with the residual contamination left at the site and its migration to groundwater used for drinking water. A probabilistic exposure model using first- and second-order reliability methods (FORM/SORM) is used to estimate the contaminant concentrations at a downstream groundwater well. Potential environmental impacts on the local, regional and global scales due to the site remediation activities are evaluated using life cycle assessments (LCA). The potential impacts on health and environment are converted to monetary units using a simplified cost model. A case study based upon the developed methodology is presented in which the following remediation scenarios are analyzed and compared: (a) no action, (b) excavation and off-site treatment of soil, (c) soil vapor extraction and (d) thermally enhanced soil vapor extraction by electrical heating of the soil. Ultimately, the developed methodology facilitates societal cost estimations of remediation scenarios which can be used for internal ranking of the analyzed options. Despite the inherent uncertainties of placing a value on health and environmental impacts, the presented methodology is believed to be valuable in supporting decisions on remedial interventions.

Applicability of risk-based management and the need for risk-based economic decision analysis at hazardous waste contaminated sites

Decision analysis in subsurface contamination management is generally carried out through a traditional engineering economic viewpoint. However, new advances in human health risk assessment, namely, the probabilistic risk assessment, and the growing awareness of the importance of soft data in the decision-making process, require decision analysis methodologies that are capable of accommodating non-technical and politically biased qualitative information. In this work, we discuss the major limitations of the currently practiced decision analysis framework, which evolves around the definition of risk and cost of risk, and its poor ability to communicate risk-related information. A demonstration using a numerical example was conducted to provide insight on these limitations of the current decision analysis framework. The results from this simple ground water contamination and remediation scenario were identical to those obtained from studies carried out on existing Superfund sites, which suggests serious flaws in the current risk management framework. In order to provide a perspective on how these limitations may be avoided in future formulation of the management framework, more matured and well-accepted approaches to decision analysis in dam safety and the utility industry, where public health and public investment are of great concern, are presented and their applicability in subsurface remediation management is discussed. Finally, in light of the success of the application of risk-based decision analysis in dam safety and the utility industry, potential options for decision analysis in subsurface contamination management are discussed.

Risk-based decision analysis in support of precautionary policies

A decision-analytic model for avoiding a risky activity is presented. The model considers the benefit and cost of avoiding the activity, the probability that the activity is unsafe, and scientific tests or studies that could be conducted to revise the probability that the activity is unsafe. For a single decision maker, thresholds are identified for his or her current subjective probability that the activity is unsafe. These thresholds indicate whether the preferred course of action is avoiding the activity without further study, engaging in the activity without further study, or conducting a test or research programme to obtain additional information and following the result. When these thresholds are low, precautionary action is more likely to be warranted. When there are multiple stakeholders, differences in their perceptions of the benefit and cost of avoidance and differences in their perceptions of the accuracy of the additional information provided by the test or research programme combine to create differences in their decision thresholds. Thus, the model allows for the rational expression of differences among parties in a way that highlights disagreements and possible paths to conflict resolution. The model is illustrated with an application to phytosanitary standards in international trade and examined in terms of recent empirical research on lay perceptions of risks, benefits, and trust. Further research is suggested to improve the elicitation of model components, as a way of fostering the legitimate application of risk-based decision analysis in precautionary policy making.

Risk based inspection planning

ABSTRACT Optimal inspection planning for structures is a topic of considerable interest in various industries. An efficient framework for inspection planning is risk-based decision analysis. Using this framework, it is possible to establish Risk Based Inspection (RBI) methodologies, that is to say inspection plans which are based on the criticality of structural components. This paper presents the detailed RBI analysis which may be applied to the most critical components of the structure. An example of the application of the procedure is given for a steel offshore tripod structure.

Fuzzy stochastic risk-based decision analysis with the mobile offshore base as a case study

The Office of Naval Research in a feasibility study of a mobile offshore base (MOB) has proposed several concepts for very large ocean structures and will make risk informed assessments of alternative concepts. Using the MOB as a case study, this paper provides methodology for fuzzy-stochastic cost and schedule risk-based decision analysis of alternative MOB hull construction concepts. The uncertainty intrinsic in a system influences requisite risk-based decision analysis methodology. Probabilistic, ambiguous, or aleatory uncertainty entails stochastic methods. Cognitive, vague, or epistemic uncertainty requires fuzzy sets and logic. Simulation is used to overcome difficulty, or known intractability, associated with mathematical formulation of analytical models of complex engineering systems. This paper provides generalized fuzzy-stochastic risk-based decision analysis methodology and demonstrates fuzzy set quantification of MOB subjective information. Fuzzy-Bayesian updating of the state-of-knowledge of MOB cost and schedule information as it is piecewise accumulated is also discussed.

Risk-based decision analysis in radioactive waste management processes: methodology with examples

This paper starts with a formal definition of risk and couples risk and uncertainty analysis in a decision analysis process. This risk-based decision analysis process is illustrated with two examples where significant decisions needed to be made relative to radioactive waste management processes. The first example illustrates a schedule risk assessment where the risks associated with achieving a major schedule were determined, quantified and managed. The second example illustrates the importance of quantifying the risk for cost-benefit (reduced risk) evaluations.

Probability, Statistics, and Reliability for Engineers

Introduction: Introduction. - Types of Uncertainty. - Taylor Series Expansion. - Applications. - Problems. - Data Description and Treatment: Introduction.- Classification of Data. - Graphical Description of Data. - Histograms and Frequency Diagrams. - Descriptive Measures. - Applications. - Problems. - Fundamentals Of Probability: Introduction. - Sample Spaces, Sets, and Events. - Mathematics of Probability. - Random Variables and Their Probability Distributions. - Moment.- Common Discrete Probability Distributions. - Common Continuous Probability Distributions. - Applications. - Problems. - Multiple Random Variables: Introduction. - Joint Random Variables and Their Probability Distributions. - Functions of Random Variables. - Applications. - Problems. - Fundamentals of Statistical Analysis: Introduction. - Estimation of Parameters. - Sampling Distributions. - Hypothesis Testing: Procedure. - Hypothesis Tests of Means. - Hypothesis Tests of Variances. - Confidence Intervals. - Sample-Size Determination. - Selection of Model Probability Distributions. - Applications. Problems. - Curve Fitting and Regression Analysis: Introduction. - Correlation Analysis. - Introduction to Regression. - Principle of Least Squares. - Reliability of the Regression Equation. - Reliability of Point Estimates of the Regression Coefficients. - Confidence Intervals of the Regression Equation. - Correlation Versus Regression. - Applications of Bivariate Regression Analysis. - Multiple Regression Analysis. - Regression Analysis of Nonlinear Models. - Applications. Problems. - Simulation: Introduction. - Monte Carlo Simulation. - Random Numbers. - Generation of Random Variables. - Generation of Selected Discrete Random Variables. - Generation of Selected Continuous Random Variables. - Applications. - Problems. - Reliability and Risk Analysis: Introduction. - Time to Failure. - Reliability of Components. - Reliability of Systems. - Risk-Based Decision Analysis. - Applications. - Problems. - Bayesian Methods: Introduction. - Bayesian Probabilities. - Bayesian Estimation of Parameters. - Bayesian Statistics. - Applications. - Problems. - Appendix A: Probability and Statistics Tables. - Appendix B: Values of the Gamma Function. - Subject Index.

A JOINT RISK-BASED DECISION ANALYSIS AND STOCHASTIC OPTIMIZATION METHODOLOGY IN THE REMEDIATION DESIGN OF A CONTAMINATED GROUNDWATER RESOURCE IN GREECE

A risk-based decision model is developed and applied in the remediation design of a contaminated aquifer in Greece. Due to limited information and data concerning the spatially-varying hydraulic conductivity parameter, decision making takes place under conditions of uncertainty. The decision analysis method is successfully combined with the stochastic optimization method to determine the optimal positioning and operation of the clean-up wells for each alternative decision strategy.The combined risk-based decision analysis and stochastic optimization methodology presented in this paper proves that this framework is an effective way of solving groundwater management problems under uncertainty. This is due to the combination of the main advantages of the two methodologies, the determination of globally optimal solutions offered by the stochastic optimization, and the inclusion of costs, benefits, and risks of failure into a single objective function offered by the decision analysis.

Risk-based decision analysis in the design of water supply projects

The application of a decision analysis methodology to a small-scale water-supply/aquifer-contamination problem is presented. The main characteristic of the study is the development of a series of alternative strategies to ensure a continuous water supply to a village under variable risk conditions. It is assumed that the risks involved in the analysis reflect the uncertainty as to the hydraulic conductivity. Thus, a stochastic simulation model for groundwater flow and contaminant transport is employed in order to evaluate the implications of uncertainty in the system's behaviour upon the overall design decisions. Alternative decision strategies are formulated by considering both actual and probabilistic costs, and they are finally compared using a risk–cost–benefit objective function.

Reliability and risk analysis data base development: an historical perspective

Reliability and risk analysis data base development: an historical perspective