Probabilistic Risk Assessment Framework Research Articles

Probabilistic framework for the estimation of the adult and child toxicokinetic intraspecies uncertainty factors.

Human health risk assessments use point values to develop risk estimates and thus impart a deterministic character to risk, which, by definition, is a probability phenomenon. The risk estimates are calculated based on individuals and then, using uncertainty factors (UFs), are extrapolated to the population that is characterized by variability. Regulatory agencies have recommended the quantification of the impact of variability in risk assessments through the application of probabilistic methods. In the present study, a framework that deals with the quantitative analysis of uncertainty (U) and variability (V) in target tissue dose in the population was developed by applying probabilistic analysis to physiologically-based toxicokinetic models. The mechanistic parameters that determine kinetics were described with probability density functions (PDFs). Since each PDF depicts the frequency of occurrence of all expected values of each parameter in the population, the combined effects of multiple sources of U/V were accounted for in the estimated distribution of tissue dose in the population, and a unified (adult and child) intraspecies toxicokinetic uncertainty factor UFH-TK was determined. The results show that the proposed framework accounts effectively for U/V in population toxicokinetics. The ratio of the 95th percentile to the 50th percentile of the annual average concentration of the chemical at the target tissue organ (i.e., the UFH-TK) varies with age. The ratio is equivalent to a unified intraspecies toxicokinetic UF, and it is one of the UFs by which the NOAEL can be divided to obtain the RfC/RfD. The 10-fold intraspecies UF is intended to account for uncertainty and variability in toxicokinetics (3.2x) and toxicodynamics (3.2x). This article deals exclusively with toxicokinetic component of UF. The framework provides an alternative to the default methodology and is advantageous in that the evaluation of toxicokinetic variability is based on the distribution of the effective target tissue dose, rather than applied dose. It allows for the replacement of the default adult and children intraspecies UF with toxicokinetic data-derived values and provides accurate chemical-specific estimates for their magnitude. It shows that proper application of probability and toxicokinetic theories can reduce uncertainties when establishing exposure limits for specific compounds and provide better assurance that established limits are adequately protective. It contributes to the development of a probabilistic noncancer risk assessment framework and will ultimately lead to the unification of cancer and noncancer risk assessment methodologies.

Opportunities for a probabilistic risk assessment of chemicals in the European Union

In risk assessment of new and existing substances, it is current practice to characterise risk using a deterministic quotient of the exposure concentration, or the dose, and a no-effect level. A sense of uncertainty is tackled by introducing worst-case assumptions in the methodology. Since this procedure leads to an assessment with an unknown degree of conservatism, it is advisable to deal quantitatively with uncertainties. This paper discusses the advantages and possibilities of a probabilistic risk assessment framework, illustrated with an example calculation. Furthermore, representatives of EU Member States and the chemical industry were interviewed to find out their views on applying uncertainty analysis to risk assessment of industrial chemicals.

A methodology for collection and analysis of human error data based on a cognitive model: IDA

This paper presents a model-based human error taxonomy and data collection. The underlying model, IDA (described in two companion papers), is a cognitive model of behavior developed for analysis of the actions of nuclear power plant operating crew during abnormal situations. The taxonomy is established with reference to three external reference points (i.e. plant status, procedures, and crew) and four reference points internal to the model (i.e. information collected, diagnosis, decision, action). The taxonomy helps the analyst: (1) recognize errors as such; (2) categorize the error in terms of generic characteristics such as ‘error in selection of problem solving strategies’ and (3) identify the root causes of the error. The data collection methodology is summarized in post event operator interview and analysis summary forms. The root cause analysis methodology is illustrated using a subset of an actual event. Statistics, which extract generic characteristics of error prone behaviors and error prone situations are presented. Finally, applications of the human error data collection are reviewed. A primary benefit of this methodology is to define better symptom-based and other auxiliary procedures with associated training to minimize or preclude certain human errors. It also helps in design of control rooms, and in assessment of human error probabilities in the probabilistic risk assessment framework.

Conclusions of the EPRI Concrete Containment Research Program

Six years of EPRI sponsored research aimed at studying the overpressure behavior of reinforced and prestressed concrete containments has brought about the development of a test-validated methodology for the prediction of concrete containment capacity and leakage. The results of many large scale panel tests in the EPRI program and the Sandia 1:6 Scale Reinforced Concrete Containment Test have been instrumental in supporting this work. This paper describes the development of the leakage prediction criteria and analysis guidelines by summarizing the EPRI research program and the conclusions that have been reached regarding concrete containment overpressure behavior. The methodology for predicting linear tearing consists of using ABAQUS-EPGEN (a general purpose finite element program co-sponsored by EPRI and Hibbitt, Karlsson, and Sorensen, Inc.) to perform 2D global analyses and then applying curves of liner strain magnification factors to the global liner strains. The 2D axisymmetric analysis procedure has been automated by the development of “library models” for two families of concrete containments commonly found in the United States. Post test conclusions of the Sandia 1:6 Scale Model experiment are also discussed in support of the leakage prediction methodology. Finally, the conclusions that have been reached with regard to liner tearing and subsequent equilibrium leakage in a quasi-static pressurization scenario are reviewed in the context of current industry operating procedures and regulatory requirements. The paper introduces the most recent work in the EPRI program which evaluates the uncertainties of the leakage prediction procedure and recasts the procedure in a probabilistic risk assessment framework for use with recent U.S. regulatory documents.

The Application of a Coupled Chemical Transport Model in a Trial Assessment of Deep Disposal of Low and Intermediate Level Radioactive Waste

ABSTRACTA series of trial assessments are being undertaken within the United Kingdom to rehearse procedures for post-closure radiological risk analysis of low and intermediate level radioactive waste disposal sites. These trial or “Dry Run” studies draw together workers from a variety of scientific disciplines allowing simultaneous rather than isolated development of assessment procedures. This paper illustrates the use of chemical codes and data within a probabilistic risk assessment framework through a demonstration exercise performed on a hypothetical repository located beneath Harwell, Oxfordshire. The implications for risk assessment practices reliant on the assumption of “conservative” parameters are highlighted by comparison with a more mechanistic approach which takes into account competitive effects.

Prototype Framework for Dynamic Probabilistic Risk Assessment of Space-Flight Medical Events

Medical problems in space, while not necessarily common, can be life and mission threatening. Because of this, a model has been created to assess the risk of certain medical events under space mission conditions called the Integrated Medical Model (IMM). The model uses a type of risk analysis called Probabilistic Risk Assessment. An effort is being conducted to convert these static models to Dynamic PRA (DynaPRA) models. These models would integrate changing conditions in space missions such as human interaction, changing system components, and environmental factors and apply a risk analysis to find more complete and useful probabilities of certain medical events occurring to astronauts in space. To this end, a prototype DynaPRA framework was created during the first three months of the project using the existing IMM hip, wrist, and lumbar spine bone fracture models as a case study. After the initial implementation was complete, ideas were generated for applying this framework to the rest of the IMM.Â