Numerical Modelling of Eddy Current Probes for CANDU® Fuel Channel Inspection

Multi-frequency Eddy Current (EC) inspection with a transmit-receive probe (two horizontally offset coils) is used to monitor the Pressure Tube (PT) to Calandria Tube (CT) gap of CANDU® fuel channels. Accurate gap measurements are crucial to ensure fitness of service; however, variations in probe liftoff, PT electrical resistivity, and PT wall thickness can generate systematic measurement errors. Validated mathematical models of the EC probe are very useful for data interpretation, and may improve the gap measurement under inspection conditions where these parameters vary. As a first step, exact solutions for the electromagnetic response of a transmit-receive coil pair situated above two parallel plates separated by an air gap were developed. This model was validated against experimental data with flat-plate samples. Finite element method models revealed that this geometrical approximation could not accurately match experimental data with real tubes, so analytical solutions for the probe in a double-walled pipe (the CANDU® fuel channel geometry) were generated using the Second-Order Vector Potential (SOVP) formalism. All electromagnetic coupling coefficients arising from the probe, and the layered conductors were determined and substituted into Kirchhoff’s circuit equations for the calculation of the pickup coil signal. The flat-plate model was used as a basis for an Inverse Algorithm (IA) to simultaneously extract the relevant experimental parameters from EC data. The IA was validated over a large range of second layer plate resistivities (1.7 to 174 µΩ∙cm), plate wall thickness (~1 to 4.9 mm), probe liftoff (~2 mm to 8 mm), and plate-to plate gap (~0 mm to 13 mm). The IA achieved a relative error of less than 6% for the extracted FP resistivity and an accuracy of ±0.1 mm for the LO measurement. The IA was able to achieve a plate gap measurement with an accuracy of less than ±0.7 mm error over a ~2.4 mm to 7.5 mm probe liftoff and ±0.3 mm at nominal liftoff (2.42±0.05 mm), providing confidence in the general validity of the algorithm. This demonstrates the potential of using an analytical model to extract variable parameters that may affect the gap measurement accuracy.

Differential contributions of the mIPS and PMd in the movement planning of reaches investigated through HD-tDCS

To reach for a target, we must formulate a movement plan - a difference vector of the target position with respect to the starting hand position. While it is known that the medial part of the intraparietal sulcus (mIPS) and the dorsal premotor (PMd) activity reflects aspects of a kinematic plan for a reaching movement, it is unclear whether or how the two regions may differ. We investigated the functional roles of the mIPS and PMd in the planning of reaching movements using high definition transcranial direct current stimulation (HD-tDCS) and examined changes in horizontal endpoint error when participants were subjected to anodal and cathodal stimulation. The left mIPS and PMd were functionally localized with fMRI in each participant using an interleaved center-out pointing and saccade task and mapped onto the scalp using Brainsight. We adopted a randomized, single-blind design and applied anodal and cathodal stimulation (2mA for 20 min; 3cm radius 4x1 electrode placement) during 4 separate visits scheduled at least a week apart. Each participant performed 250 baseline, stimulation, and post-stimulation memory-guided reaches starting from one of two initial hand positions (IHPs) to one of 4 briefly flashed targets (20 cm distant, 5 cm apart horizontally) while fixating on a straight-ahead cross located at the target line. Separate 2-way repeated measures ANOVAs of horizontal endpoint error difference after cathodal tDCS at each stimulation site revealed a significant IHP by target position interaction effect at the left mIPS, and significant IHP and target main effects at the left PMd. Behaviorally, these effects corresponded to IHP-dependent contractions after cathodal mIPS tDCS and IHP-independent contractions after cathodal PMd tDCS. These results suggest that the movement vector is not yet formed at the input level of mIPS, but is encoded at the input of PMd. These results also indicate that tDCS is a viable, useful method in investigating movement planning properties through temporary perturbations of the system.

Karst hazard analysis towards the development of predictive karst models for southern Ontario

An investigation into karst hazard in southern Ontario has been undertaken with the intention of leading to the development of predictive karst models for this region. The reason these are not currently feasible is a lack of sufficient karst data, though this is not entirely due to the lack of karst features. Geophysical data was collected at Lake on the Mountain, Ontario as part of this karst investigation. This data was collected in order to validate the long-standing hypothesis that Lake on the Mountain was formed from a sinkhole collapse. Sub-bottom acoustic profiling data was collected in order to image the lake bottom sediments and bedrock. Vertical bedrock features interpreted as solutionally enlarged fractures were taken as evidence for karst processes on the lake bottom. Additionally, the bedrock topography shows a narrower and more elongated basin than was previously identified, and this also lies parallel to a mapped fault system in the area. This suggests that Lake on the Mountain was formed over a fault zone which also supports the sinkhole hypothesis as it would provide groundwater pathways for karst dissolution to occur. Previous sediment cores suggest that Lake on the Mountain would have formed at some point during the Wisconsinan glaciation with glacial meltwater and glacial loading as potential contributing factors to sinkhole development. A probabilistic karst model for the state of Kentucky, USA, has been generated using the Weights of Evidence method. This model is presented as an example of the predictive capabilities of these kind of data-driven modelling techniques and to show how such models could be applied to karst in Ontario. The model was able to classify 70% of the validation dataset correctly while minimizing false positive identifications. This is moderately successful and could stand to be improved. Finally, suggestions to improving the current karst model of southern Ontario are suggested with the goal of increasing investigation into karst in Ontario and streamlining the reporting system for sinkholes, caves, and other karst features so as to improve the current Ontario karst database.