Characterisation of ultrafast micro-structuring of alumina (Al 2O3)

Alumina ceramic, Al2O3, presents a challenge to laser micro-structuring due to its neglible linear absorption coefficient in the optical region coupled with its physical properties such as extremely high melting point and high thermal conductivity. In this work, we demonstrate clean micro-structuring of alumina using NIR (λ=775 nm) ultrafast optical pulses with 180 fs duration at 1kHz repetition rate. Sub-picosecond pulses can minimise thermal effects along with collateral damage when processing conditions are optimised, consequently, observed edge quality is excellent in this regime. We present results of changing micro-structure and morphology during ultrafast processing along with measured ablation rates and characteristics of developing surface relief. Initial crystalline phase (alpha Al2O3) is unaltered by femtosecond processing. Multi-pulse ablation threshold fluence Fth, ∼ 1.1 Jcm-2 and at low fluence ∼ 3 Jcm -2, independent of machined depth, there appears to remain a ∼ 2 μm thick rapidly re-melted layer. On the other hand, micro-structuring at high fluence F ∼ 21 Jcm-2 shows no evidence of melting and the machined surface is covered with a fine layer of debris, loosely attached. The nature of debris produced by femtosecond ablation has been investigated and consists mainly of alumina nanoparticles with diameters from 20 nm to 1 micron with average diameter ∼ 300 nm. Electron diffraction shows these particles to be essentially single crystal in nature. By developing a holographic technique, we have demonstrated periodic micrometer level structuring on polished samples of this extremely hard material.

Gaussian Process training with input noise

In standard Gaussian Process regression input locations are assumed to be noise free. We present a simple yet effective GP model for training on input points corrupted by i.i.d. Gaussian noise. To make computations tractable we use a local linear expansion about each input point. This allows the input noise to be recast as output noise proportional to the squared gradient of the GP posterior mean. The input noise variances are inferred from the data as extra hyperparameters. They are trained alongside other hyperparameters by the usual method of maximisation of the marginal likelihood. Training uses an iterative scheme, which alternates between optimising the hyperparameters and calculating the posterior gradient. Analytic predictive moments can then be found for Gaussian distributed test points. We compare our model to others over a range of different regression problems and show that it improves over current methods.

Heat transfer and aerodynamics of turbine blade tips in a linear cascade

Local measurements of the heat transfer coefficient and pressure coefficient were conducted on the tip and near tip region of a generic turbine blade in a five-blade linear cascade. Two tip clearance gaps were used: 1.6% and 2.8% chord. Data was obtained at a Reynolds number of 2.3 × 10 5 based on exit velocity and chord. Three different tip geometries were investigated: a flat (plain) tip, a suction-side squealer, and a cavity squealer. The experiments reveal that the flow through the plain gap is dominated by flow separation at the pressure-side edge and that the highest levels of heat transfer are located where the flow reattaches on the tip surface. High heat transfer is also measured at locations where the tip-leakage vortex has impinged onto the suction surface of the aerofoil. The experiments are supported by flow visualisation computed using the CFX CFD code which has provided insight into the fluid dynamics within the gap. The suction-side and cavity squealers are shown to reduce the heat transfer in the gap but high levels of heat transfer are associated with locations of impingement, identified using the flow visualisation and aerodynamic data. Film cooling is introduced on the plain tip at locations near the pressure-side edge within the separated region and a net heat flux reduction analysis is used to quantify the performance of the successful cooling design. copyright © 2005 by ASME.

Re-examination of the coefficient of determination (r2) using road materials engineering case studies

The analysis of scientific data is integral to materials engineering and science. The correlation between measured variables is often quantified by estimating the coefficient of determination or the r2 value. This is the recognised procedure for determining linear relationships. The authors review the derivation of the r2 value and derive an associated quantity, termed the relative deviation (RD), which is the ratio of the root mean square of the deviations about the fitted line to the root mean square of the deviations about the y bar line expressed as a percentage. The relative deviation has an advantage over the coefficient of determination in that it has greater numerical sensitivity to changes in the spread of data about the fitted line, especially when the scatter is small. In addition, the relative deviation is able to define, in percentage terms, the reduction in scatter when different independent variables are correlated with a common dependent variable. Four case studies in the materials field (aggregate crushing value, Atterberg limits, permeability and creep of asphalt) from work carried out at the Queensland Main Roads Department are presented to show the use of the new parameter RD.

Optimal displacement mechanisms beneath shallow foundations on linear-elastic perfectly plastic soil

An energy method for a linear-elastic perfectly plastic method utilising the von Mises yield criterion with associated flow developed in 2013 by McMahon and co-workers is used to compare the ellipsoidal cavity-expansion mechanism, from the same work, and the displacement fields of other research by Levin, in 1995, and Osman and Bolton, in 2005, which utilise the Hill and Prandtl mechanisms respectively. The energy method was also used with a mechanism produced by performing a linear-elastic finite-element analysis in Abaqus. At small values of settlement and soil rigidity the elastic mechanism provides the lowest upper-bound solution, and matches well with finite-element analysis results published in the literature. At typical footing working loads and settlements the cavity-expansion mechanism produces a more optimal solution than the displacement fields within the Hill and Prandtl mechanisms, and also matches well with the published finite-element analysis results in this range. Beyond these loads, at greater footing settlements, or soil rigidity, the Prandtl mechanism is shown to be the most appropriate.

Investigation of the Young's modulus and thermal expansion of amorphous titania-doped tantala films

The current generation of advanced gravitational wave detectors utilize titania-doped tantala/silica multilayer stacks for their mirror coatings. The properties of the low-refractive-index silica are well known; however, in the absence of detailed direct measurements, the material parameters of Young's modulus and coefficient of thermal expansion (CTE) of the high refractive index material, titania-doped tantala, have been assumed to be equal to values measured for pure tantala coatings. In order to ascertain the true values necessary for thermal noise calculations, we have undertaken measurements of Young's modulus and CTE through the use of nanoindentation and thermal-bending measurements. The measurements were designed to assess the effects of titania doping concentration and post-deposition heat-treatment on the measured values in order to evaluate the possibility of optimizing material parameters to further improve thermal noise in the detector. Young's modulus measurements on pure tantala and 25% and 55% titania-doped tantala show a wide range of values, from 132 to 177 GPa, dependent on both titania concentration and heat-treatment. Measurements of CTE give values of (3.9 +/- 0.1) x 10^-6 K^-1 and (4.9 +/- 0.3) x 10^-6 K^-1 for 25% and 55% titania-doped tantala, respectively, without dependence on post-deposition heat-treatment.