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The report 'Probability of Defect Detection of Posiva's electron beam weld' describes POD curves of four NDT methods radiographic testing, ultrasonic testing, eddy current testing and visual testing. POD-curves are based on the artificial defects in reference blocks. The results are devoted to the demonstration of suitability of the methods for EB weld testing. Report describes methodology and procedure applied by BAM.
Report creates a link from the assessment of the reliability and inspection performance to the risk assessment process of the canister final disposal project. Report ensures the confirmation of the basic quality of the NDT methods and their capability to describe the quality of the EB-weld.
The probability of detection curves are determined based on the MIL-1823 standard and it's reliability guidelines. The MIL-1823 standard was developed for the determination of integrity of gas turbine engines for the US military.
In the POD-process there are determined as a key parameter for the defect detectability the a90/95 magnitudes, i.e. the size measure a of the defect, for which the lower 95 % confidence band crosses the 90 % POD level. By this way can be confirmed that defects with a size of a90/95 will be detected with 90 % probability. In case the experiment will be repeated 5 % might fall outside this confidence limit.
This paper gives an introduction to the field of human factors with the focus on their influence on the reliability of NDT in the nuclear energy production (in-service inspections) and final storage of highly radioactive nuclear waste. A set of methodological tools has been developed in the scope of three projects, namely: 1) a theoretical model describing potential human factors influencing manual ultrasonic inspection performance during inservice inspections in nuclear power plants; 2) a method for identifying potential human errors during acquisition and evaluation of data gathered with mechanized ultrasonic, radiographic and eddy-current systems, as well as visual testing with a remote camera (Failure Modes and Effects Analysis, FMEA); and 3) use of eye tracking methodology to optimize existing procedures and practices. The experimental results have shown that time pressure, mental workload and experience influence the quality of the inspection performance. Noticeable were influences from the organization of the working schedule, communication, procedures, supervision and demonstration task. Implementing human redundancy in critical tasks, such as defect identification, as well as using an automated aid (software) to help operators in decision making about the existence and size of defects, could lead to other kinds of problems, namely social loafing (excerpting less effort when working on tasks collectively as compared to working alone) and automation bias (uncritical reliance on the proper function of an automated system without recognizing its limitations and the possibilities of automation failure) that might affect the reliability of NDT in an undesired manner.
The Probability of Detection (POD) is used to evaluate the detectability of non-destructive testing (NDT) systems. The POD is highly dependent on the amount of available data. The Bayesian approach provides a solution to compute POD-curves in case of a small amount of real defects without losing the necessary information. The result contains the needed information for the computation of POD-curves for real defects with an acceptable amount of information, even for sparse amount of data. In this paper is shown limitations of the Bayesian approach and how it can be applied to NDT. The Bayesian approach is applied in this case to the evaluation of radiographic testing. Bayesian approach is applied to determine POD-curves for the inspection techniques of nuclear fuel disposal canisters. The reason for using Bayesian approach is the high safety demands and also the low amount of real defects due to the high quality of the reliable production techniques.
New methodologies for evaluating the reliability of NDE systems are discussed in accordance with the specific
requirements of industrial application. After a review of the substantive issues from the previous decades, the go
forward guidance is concluded.
For high safety demands a quantitative probability of detection (POD) created from hit miss
experiments or signal response analysis and ROC (Receiver Operating Characteristics) are typically created. The
modular model distinguishes between the influence of pure physics and technique, industrial application factors
and the human factor and helps to learn what factors are covered by modelling, open or blind trials. A new
paradigm is offered to consider the POD or reliability of the system as a function of the configuration of input
variables and use it for optimisation rather than for a final judgement. New approaches are considered dealing
with real defects in a realistic environment, affordable but precisely like the Bayesian approach or model assisted
methods.
Among the influencing parameters, the human factor is of high importance. A systematic psychological
approach helps to find out where the bottlenecks are and shows possibilities for improvement.
Human factors approach to the reliability of NDT in nuclear waste management in Sweden and Finland
(2010)
Nuclear power industry has the responsibility to manage and dispose of all radioactive waste from its
plants. Finnish Posiva and Swedish SKB are leading in the world in the development of disposal of
spent nuclear fuel. Their method consists of encapsulating spent nuclear fuel in copper canisters and
depositing them in the bedrock at a depth of about 500 meters for the next 100 000 years, leaving the
radioactivity to decrease naturally through the decay of the radioisotopes in it. The copper canisters,
consisting of a copper tube, a lid and a bottom (which make the outer shell) and an insert made of a
cast iron, need to be inspected for their structural integrity to ensure no critical defects are present in
the materials and welds that could lead to a leakage of the waste into the environment. Data acquired
by 4 different non-destructive testing (NDT) methods (i.e. UT, ET, RT and VT with a remote camera)
are evaluated by skilled human operators and therefore could be subject to human error.
Human Factors approach lies in identifying potential errors made by the human, their causes
and ways of preventing them. A customized Failure Modes and Effects Analysis (FMEA) was
conducted to anticipate possible human failures during the data evaluation. The results led to
designing several experiments (e.g. diffusion of responsibility within the 4-eye principle, over trust in
automated systems) which are being experimentally tested in ongoing projects. The results are
expected to lead to the optimization of the procedures followed by the NDT operators and
consequently to the improvement of the overall NDT reliability.