This PDF file contains the front matter associated with SPIE Proceedings Volume 12491, including the Title Page, Copyright information, Table of Contents, and Conference Committee information.

Reliability evaluations are useful tools to assess the capability of non-destructive testing (NDT) methods. The knowledge of reliability leads to a deeper understanding of the methods applied and to a more advanced use of equipment, material and work force. In addition, each condition assessment also depends on the reliability of the inspection data acquired. However, only in a few industrial sectors, such as nuclear, aviation or aerospace, the performance of reliability evaluations is a regular procedure. Mostly due to the fact, that institutions require reliability evaluations and therefore specifications guide the way for a standardized assessment. In other sectors, like civil engineering or automotive, the performance of NDT reliability evaluation is uncommon. Firstly, because it is not mandatory and secondly, there are very few experiences and also guidance, in form of specifications, is missing as well. Consequently, the benefit of knowing about the reliability of NDT methods is unexploited. In order to change the mind-set and to support sectors, like the civil engineering and automotive sector, the normPOD-project developed a generalized POD approach. This approach demonstrates (i) how to include different data sources (e.g., simulation), (ii) how to plan a correct set up for experiments in which mathematical methods can be used and (iii) how to evaluate the results, so they contribute towards the quality assessment of the components. For the sake of validation, two different case studies have been following the approach. The first case study focused on the inspection of ferritic welds extracted from a power plant and the second one assessed the reliability of reinforced concrete tunnel inspections. This paper emphasizes the variety of testing conditions and highlights the steps for a standardized reliability assessment. The case studies reveal the applicability of the future standard and show the benefit of knowing the NDT capability

This paper is intended to show the methodology for extending Probability of Detection (POD) modeling for continuously-valued (â vs a) signal responses to allow for the addition of multiple factors beyond the simple flaw size model, along with higher-level interactions. The statistical methodology for correctly transforming these more complex linear models into probability of detection curves is provided, and the approach is illustrated with a motivating real-world POD study

Even though, POD assessments of NDT techniques have been well demonstrated in various industrial sectors such as aviation, nuclear, oil and gas, railways, etc., they lack the inclusion of several influences as explained from the modular model. Influences due to intrinsic capabilities or due to application/environmental parameters can somehow be demonstrated under controlled laboratory and field inspection procedures. However, nowadays the biggest challenge lies in the inclusion of human factors and the organization context into the POD assessments and this can be mainly due to not being able to quantify the human factors. Hence, in the current work on accounting human factors influence on POD curves, the main idea is based on identifying majority of the human related tasks while carrying out the inspection procedures in terms of various statistical metrics. This topic on quantification of human factors is a part of the ongoing WIPANO project "normPOD", for the standardization of reliability assessment in Germany. This method of representation in terms of statistical metrics would enable holistic inclusion of human related influences in the form of the scatter parameters required for POD assessments. Efforts towards inclusion of these quantified human factor parameters into the POD assessments were shown by the adoption of Monte-Carlo approaches.

Human factors (HF) are little understood, and particularly in non-destructive testing (NDT) experimental data is rare, samples are often small, and statistical methods are rarely used to evaluate results [1]. HF have been widely implicated in major occurrences of technical failure, for example at North Anna power plant and on United Airlines Flight 232. Understanding HF is vital for reliable detection and prevention of failures. Reliability assessments, though known to be affected by intrinsic capability, application factors, and HF, have thus far only concentrated to a sufficient degree on intrinsic capability. The addition of HF to that assessment has proven difficult due to the lack of a method of quantifying HF. This paper presents the first attempt from a psychological perspective to quantify HF from qualitative data. HF data was derived from qualitative human-oriented Failure Modes and Effects Analysis (Human-FMEA) workshops for visual inspection of tunnels by laser scanning and for ultrasonic testing of welds. Data was collected on human failure modes, causes, consequences and preventive measures, as well as eliciting a risk priority number (RPN). Using this data, a system of quantitative weightings was created to allocate errors to inductively derived HF categories for further allocation to existing HF categorisation models. This weighting model proved useful for creating quantitative summaries of HF, informing and validating qualitative FMEA results, and comparing existing HF categorisation models. Further potential lies within a planned interface to quantitative reliability assessment methods such as POD (Probability of Detection). While providing quantifications, the method retains a qualitative and holistic nature, can, thus, bridge the gap between psychological and engineering concerns of HF and reliability, contributing to future interdisciplinary work.

The Model-Assisted Probability of Detection (MAPOD) approach is a promising technique for cost-effective and time-efficient assessment of the reliability of Guided Wave Structural Health Monitoring (GWSHM) systems. While it has the capability to generate statistically independent datasets, it has a weakness in taking into account the influence of structural, environmental and operational parameters. This paper presents one possible solution to addresss this weakness. The approach is based on combining simulated damage scenarios with data taken from a real GWSHM system at the undamaged stage and under the influence of these parameters. The resulting dataset is then processed using the conventional POD analysis. The approach is demonstrated on a steel pipe with a GWSHM system employing an array of PZT shear elements bonded around the circumference of the pipe to excite a fundamental torsional mode, T(0,1). Different damage sizes are simulated, taking into account small pipe thickness variations. Finally, the simulation dataset is combined with the experimental one to generate a realistic, specific POD curve for that system.

Sustainability efforts and global climate targets coincide with degradation of the built environment. Changes in use, increasing loads, and—especially in transport infrastructure— sharply rising traffic flows are encountering an infrastructure that has largely reached or exceeded its service life. During the entire lifecycle of structures and materials, the engineer needs to decide which action(s) are optimal, e.g., most eco-efficient at what time. This decision-making process is based on the reassessment of the structure or network, which depends substantially on the information available about the system. It is well known that available and continuously further developed NDT methods allow the collection of manifold information highly relevant in structural assessment. However, the condition (i.e., the quality) of the information measured on-site and the reliability of inspection systems need to be known before NDT results can be used in such safety-relevant calculations. This contribution attempts to shed light on the application of POD analyses and measurement uncertainty calculations in nondestructive testing of concrete structures to provide useful and quality-assured information for reliability assessments of our built environment—with an emphasis on ground penetrating radar. It is shown that signal processing techniques affect POD analysis results to varying degrees, that measurement uncertainties are useful to validate PODs, and that the utilization of both POD analysis and measurement uncertainty calculations can pave the way to NDT-based reliability assessment, which will be exemplarily demonstrated in conclusion—generally aiming to derive those maintenance strategies and actions that are in line with actual demands.

Various micro and nano-manufacturing techniques were investigated to create controlled flaws for x-ray computed tomography (XCT) phantoms. We explored the use of focused ion beam, laser micromachining, and projection photolithography with deep reactive ion etching to generate controlled pores from 100s of micrometers to a few micrometers in size. Principles of each technique, fabrication results, and the calibration processes for the manufactured pores are discussed, as well as possible assembly techniques for building up larger pore-containing structure and initial results for such assemblies. Example scanning electron microscope and XCT measurements of the phantoms are shown.

This presentation mainly focuses on the major aspects of the reliability of non-destructive testing (NDT) techniques. From the safety point of view, evaluation of NDT techniques is vital for many risk-involved industries such as in aero-industry, railways, nuclear, oil and gas, etc. In addition, successful implementation of the damage tolerance concept highly relies on the reliability of NDT techniques. In other words, due to the aims of NDE 4.0, the qualitative evaluation of NDT is becoming vital. The presentation deals with the importance of NDT reliability with regards to the economical, jurisdictional and safety-critical requirements. Upon highlighting the importance of NDT and provides an overview of the understanding on the reliability of NDT. Also, the presentation focuses on the topic of the reliability evaluation under NDE 4.0 along with discussion on the need and possibilities of the reliability evaluation.

In Quantitative Nondestructive Evaluation (QNDE), assessing the reliability of the NDT method is crucial. Technology advances and the development of new life estimation models based on the damage tolerance concept have led to the maturing of QNDE techniques. Nowadays, the concept is widely used for such models in fitness-for-service (FFS) assessments. As an input to these models, flaws size plays a very important role. In these concepts, Probability of Rejection (PoR) was introduced around 2007 and combined the concepts of Probability of Detection (PoD) with the need to accurately size flaws when using fracture mechanics-based acceptance criteria. Improvements in sizing techniques have been made and fracture-mechanics acceptance criteria are becoming more commonly accepted instead of the traditional workmanship criteria. However, experimental PoD campaigns are excessively time and money-consuming, rapidly making them almost prohibitive. On the other hand, recent advances in technology to accurately simulate nondestructive testing (NDT) processes made available new tools for reliability study. This paper uses CIVA’s ultrasonic inspection simulation to demonstrate how small changes on the flaw sizing characterization would affect probability of rejection.