Characterisation of dynamic behaviour of alumina ceramics: evaluation of stress uniformity

Accurate characterisation of dynamic behaviour of ceramics requires the reliable split-Hopkinson pressure bar (SHPB) technique and the condition of uniaxial homogeneous specimen deformation. In this study, an experimentally validated 3D finite element model of the full scale SHPB experiment was developed to quantitatively evaluate the wave propagation in the bars and the stress distribution/evolution in the alumina specimen. Wave signals in both the SHPB experiments and the finite element model were analysed to characterise the dynamic behaviour of alumina. It was found that the equilibrium of both stresses within the specimen and forces at the specimen ends can be established in the intermediate stage of deformation. The validity of stress uniformity in the alumina specimen supports the assumption of uniaxial homogeneous specimen deformation in the SHPB and validates the characterisation of dynamic behaviour of alumina ceramics

Voronoi cell finite element modelling of the intergranular fracture mechanism in polycrystalline alumina

The mechanisms of fracture in polycrystalline alumina were investigated at the grain level using both the micromechanical tests and finite element (FE) model. First, the bending experiments were performed on the alumina microcantilever beams with a controlled displacement rate of 10 nm s–1 at the free end; it was observed that the intergranular fracture dominates the failure process. The full scale 3D Voronoi cell FE model of the microcantilever bending tests was then developed and experimentally validated to provide the insight into the cracking mechanisms in the intergranular fracture. It was found that the crystalline morphology and orientation of grains have a significant impact on the localised stress in polycrystalline alumina. The interaction of adjacent grains as well as their different orientations determines the localised tensile and shear stress state in grain boundaries. In the intergranular fracture process, the crack formation and propagation are predominantly governed by tensile opening (mode I) and shear sliding (mode II) along grain boundaries. Additionally, the parametric FE predictions reveal that the bulk failure load of the alumina microcantilever increases with the cohesive strength and total fracture energy of grain boundaries

Do exchange rate bubbles deflate faster than they inflate?

Some theories predict that exchange rate bubbles should deflate faster than they inflate. We find no empirical support for this hypothesis for currencies that floated against the US dollar. The bursting of exchange rate bubbles is not analogous to collapses in the prices of financial assets. Financial asset prices tend to fall faster than they rise, which suggests that the same might be true of relatively risky currencies. We find no evidence that other currencies depreciate faster against the US dollar than they appreciate, even though the US dollar is commonly regarded as a potential safe-haven currency. This is true even of emerging-market currencies.exchange rates, price bubbles, risk

Data-Driven Adaptive Reynolds-Averaged Navier-Stokes \u3cem\u3ek - ω\u3c/em\u3e Models for Turbulent Flow-Field Simulations

The data-driven adaptive algorithms are explored as a means of increasing the accuracy of Reynolds-averaged turbulence models. This dissertation presents two new data-driven adaptive computational models for simulating turbulent flow, where partial-but-incomplete measurement data is available. These models automatically adjust (i.e., adapts) the closure coefficients of the Reynolds-averaged Navier-Stokes (RANS) k-ω turbulence equations to improve agreement between the simulated flow and a set of prescribed measurement data. The first approach is the data-driven adaptive RANS k-ω (D-DARK) model. It is validated with three canonical flow geometries: pipe flow, the backward-facing step, and flow around an airfoil. For all 3 test cases, the D-DARK model improves agreement with experimental data in comparison to the results from a non-adaptive RANS k-ω model that uses standard values of the closure coefficients. The second approach is the Retrospective Cost Adaptation (RCA) k-ω model. The key enabling technology is that of retrospective cost adaptation, which was developed for real-time adaptive control technology, but is used in this work for data-driven model adaptation. The algorithm conducts an optimization, which seeks to minimize the surrogate performance, and by extension the real flow-field error. The advantage of the RCA approach over the D-DARK approach is that it is capable of adapting to unsteady measurements. The RCA-RANS k-ω model is verified with a statistically steady test case (pipe flow) as well as two unsteady test cases: vortex shedding from a surface-mounted cube and flow around a square cylinder. The RCA-RANS k-ω model effectively adapts to both averaged steady and unsteady measurement data