Eddy current testing of AGR fuel cladding

The scope of the presented study was to investigate feasibility of Eddy Current Testing (ECT) for detection in storage of inter-granular attack (IGA) cracking and general clad thinning of irradiated fuel cladding from Advanced Gas-cooled Reactors (AGR). The impact of the storage environment, particularly the effect of immersion in water compared to measurements in air, has also been investigated. A miniature EC probe was developed to induce eddy currents in a pin and to read out EC response. The transducer was robotically moved along the AGR pin and multi-frequency EC responses were acquired using a spectrum analyser. Main results of the experimental investigation are the following: even very small artificial defects such as short EDM notches of depth of 100μm produce distinguishable EC response; localised clad thinning of depth of 100μm and above produces considerable EC response levels; effect of water environment on the EC response is negligible; effect of anti-stacking grooves on the EC response is considerable

Sensor Fusion for Electromagnetic Stress Measurement and Material Characterisation

Detrimental residual stresses and microstructure changes are the two major precursors for future sites of failure in ferrous steel engineering components and structures. Although numerous Non-Destructive Evaluation (NDE) techniques can be used for microstructure and stress assessment, currently there is no single technique which would have the capability to provide a comprehensive picture of these material changes. Therefore the fusion of data from a number of different sensors is required for early failure prediction Electromagnetic (EM) NDE is a prime candidate for this type of inspection, since the response to Electromagnetic excitation can be quantified in several different ways: e.g. eddy currents, Barkhausen emission, flux leakage, and a few others. This chapter reviews the strengths of different electromagnetic NDE methods, provides an analysis of the different sensor fusion techniques such as sensor physical system fusion through different principles and detecting devices, and/or feature selection and fusion, and/or information fusion. Two sensor fusion case studies are presented: pulsed eddy current thermography at sensor level and integrative electromagnetic methods for stress and material characterisation at feature (parameters) level

Dynamic Properties of Molecular Motors in Burnt-Bridge Models

Dynamic properties of molecular motors that fuel their motion by actively interacting with underlying molecular tracks are studied theoretically via discrete-state stochastic ``burnt-bridge'' models. The transport of the particles is viewed as an effective diffusion along one-dimensional lattices with periodically distributed weak links. When an unbiased random walker passes the weak link it can be destroyed (``burned'') with probability p, providing a bias in the motion of the molecular motor. A new theoretical approach that allows one to calculate exactly all dynamic properties of motor proteins, such as velocity and dispersion, at general conditions is presented. It is found that dispersion is a decreasing function of the concentration of bridges, while the dependence of dispersion on the burning probability is more complex. Our calculations also show a gap in dispersion for very low concentrations of weak links which indicates a dynamic phase transition between unbiased and biased diffusion regimes. Theoretical findings are supported by Monte Carlo computer simulations.Comment: 14 pages. Submitted to J. Stat. Mec

Robotic ultrasonic testing of AGR fuel cladding

The purpose of the presented work was to undertake experimental trials to demonstrate the potential capabilities of an in-situ robotic ultrasonic scanning technique for measuring and monitoring loss of the cladding wall thickness in fuel pins of Advanced Gas-cooled Reactors (AGR) using inactive (i.e. non-radioactive) samples. AGR fuel pins are stainless steel cylindrical ribbed pipes of length circa of 1000 mm, inner diameter of the rod being circa 15 mm and wall thickness of circa 300µm. Spent AGR fuel pins are stored in a water pond and thus may be prone to corrosion and stresscorrosion cracking under adverse conditions. An ultrasonic immersion transducer with central frequency of 25MHz was used to measure wall thickness of the AGR fuel cladding using a frequency domain technique. Cylindrical ultrasonic scan of the samples 2 was performed using industrial robotic arm KUKA KR 5 arc HW. Also, very short (2.5mm long) and shallow (100µm in depth) crack-like defects were detected using time-domain technique

Machining-based coverage path planning for automated structural inspection

The automation of robotically delivered nondestructive evaluation inspection shares many aims with traditional manufacture machining. This paper presents a new hardware and software system for automated thickness mapping of large-scale areas, with multiple obstacles, by employing computer-aided drawing (CAD)/computer-aided manufacturing (CAM)-inspired path planning to implement control of a novel mobile robotic thickness mapping inspection vehicle. A custom postprocessor provides the necessary translation from CAM numeric code through robotic kinematic control to combine and automate the overall process. The generalized steps to implement this approach for any mobile robotic platform are presented herein and applied, in this instance, to a novel thickness mapping crawler. The inspection capabilities of the system were evaluated on an indoor mock-inspection scenario, within a motion tracking cell, to provide quantitative performance figures for positional accuracy. Multiple thickness defects simulating corrosion features on a steel sample plate were combined with obstacles to be avoided during the inspection. A minimum thickness mapping error of 0.21 mm and a mean path error of 4.41 mm were observed for a 2 m² carbon steel sample of 10-mm nominal thickness. The potential of this automated approach has benefits in terms of repeatability of area coverage, obstacle avoidance, and reduced path overlap, all of which directly lead to increased task efficiency and reduced inspection time of large structural assets