2 resultados para structural equations modelling

em QSpace: Queen's University - Canada


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The Greater Himalayan leucogranites are a discontinuous suite of intrusions emplaced in a thickened crust during the Miocene southward ductile extrusion of the Himalayan metamorphic core. Melt-induced weakening is thought to have played a critical role in strain localization that facilitated the extrusion. Recent advancements in centrifuge analogue modelling techniques allow for the replication of a broader range of crustal deformation behaviors, enhancing our understanding of large hot orogens. Polydimethylsiloxane (PDMS) is commonly used in centrifuge experiments to model weak melt zones. Difficulties in handling PDMS had, until now, limited its emplacement in models prior to any deformation. A new modelling technique has been developed where PDMS is emplaced into models that have been subjected to some shortening. This technique aims to better understand the effects of melt on strain localization and potential decoupling between structural levels within an evolving orogenic system. Models are subjected to an early stage of shortening, followed by the introduction of PDMS, and then a final stage of shortening. Theoretical percentages of partial melt and their effect on rock strength are considered when adding a specific percentage of PDMS in each model. Due to the limited size of the models, only PDMS sheets of 3 mm thickness were used, which varied in length and width. Within undeformed packages, minimal surface and internal deformation occurred when PDMS is emplaced in the lower layer of the model, showing a vertical volume increase of ~20% within the package; whereas the emplacement of PDMS into the middle layer showed internal dragging of the middle laminations into the lower layer and a vertical volume increase ~30%. Emplacement of PDMS results in ~7% shortening for undeformed and deformed models. Deformed models undergo ~20% additional shortening after two rounds of deformation. Strain localization and decoupling between units occur in deformed models where the degree of deformation changes based on the amount of partial melt present. Surface deformation visible by the formation of a bulge, mode 1 extension cracks and varying surface strain ellipses varies depending if PDMS is present. Better control during emplacement is exhibited when PDMS is added into cooler models, resulting in reduced internal deformation within the middle layer.

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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.