Formulation of Locally Reacting Surfaces in FDTD/K-DWM Modelling of Acoustic Spaces

In this paper, we present new methods for constructing and analysing formulations of locally reacting surfaces that can be used in finite difference time domain (FDTD) simulations of acoustic spaces. Novel FDTD formulations of frequency-independent and simple frequency-dependent impedance boundaries are proposed for 2D and 3D acoustic systems, including a full treatment of corners and boundary edges. The proposed boundary formulations are designed for virtual acoustics applications using the standard leapfrog scheme based on a rectilinear grid, and apply to FDTD as well as Kirchhoff variable digital waveguide mesh (K-DWM) methods. In addition, new analytic evaluation methods that accurately predict the reflectance of numerical boundary formulations are proposed. numerical experiments and numerical boundary analysis (NBA) are analysed in time and frequency domains in terms of the pressure wave reflectance for different angles of incidence and various impedances. The results show that the proposed boundary formulations structurally adhere well to the theoretical reflectance. In particular, both reflectance magnitude and phase are closely approximated even at high angles of incidence and low impedances. Furthermore, excellent agreement was found between the numerical boundary analysis and the experimental results, validating both as tools for researching FDTD boundary formulations.

Modelling and Instrumentation of Stretch Blow Moulding

The injection stretch blow moulding process is used to manufacture PET containers used in the soft drinks and carbonated soft drinks industry. The process consists of a test tube like specimen known as a preform which is heated, stretch and blown into a mould to form the container. This research is focused on developing a validated simulation of the process thus enabling manufacturers to design their products in a virtual environment without the need to waste time, material and energy. The simulation has been developed using the commercial FEA package Abaqus and has been validated using state of the art data acquisition system consisting of measurements for preform temperature (inner and outer wall) using a device known as THERMOscan (Figure 1), stretch rod force and velocity, internal pressure and air temperature inside the preform using an instrumented stretch rod and the?exact?timing of when the preform touches the mould wall using contact sensors.? In addition, validation studies have also been performed by blowing a perform without a mould and using high sped imaging technology in cooperation with an advanced digital image correlation system (VIC 3D) to provided new quantitative information on the behaviour of PET during blowing.? The approach has resulted in a realistic simulation in terms of accurate input parameters, preform shape evolution and prediction of final properties.

Flow due to multiple jets downstream of a barrage: Experiments, 3-D CFD and depth-averaged modelling

The flow through and downstream of a row of seven open draft tubes in a barrage has been investigated through laboratory experiments in a wide flume, a three-dimensional (3D) computational fluid dynamics simulation, and a two-dimensional depth-averaged computation. Agreement between the experiments and the 3D modeling is shown to be good, including the prediction of an asymmetric Coandă effect. One aim is to determine the distance downstream at which depth-averaged modeling provides a reasonable prediction; this is shown to be approximately 20 tube diameters downstream of the barrage. Upstream of this, the depth-averaged modeling inaccurately predicts water level, bed shear, and the 3D flow field. The 3D model shows that bed shear stress can be markedly magnified near the barrage, particularly where the jets become attached.

The Rossiter-McLaughlin effect reloaded: Probing the 3D spin-orbit geometry, differential stellar rotation, and the spatially-resolved stellar spectrum of star-planet systems

When a planet transits its host star, it blocks regions of the stellar surface from view; this causes a distortion of the spectral lines and a change in the line-of-sight (LOS) velocities, known as the Rossiter-McLaughlin (RM) effect. Since the LOS velocities depend, in part, on the stellar rotation, the RM waveform is sensitive to the star-planet alignment (which provides information on the system’s dynamical history). We present a new RM modelling technique that directly measures the spatially-resolved stellar spectrum behind the planet. This is done by scaling the continuum flux of the (HARPS) spectra by the transit light curve, and then subtracting the infrom the out-of-transit spectra to isolate the starlight behind the planet. This technique does not assume any shape for the intrinsic local profiles. In it, we also allow for differential stellar rotation and centre-to-limb variations in the convective blueshift. We apply this technique to HD 189733 and compare to 3D magnetohydrodynamic (MHD) simulations. We reject rigid body rotation with high confidence (>99% probability), which allows us to determine the occulted stellar latitudes and measure the stellar inclination. In turn, we determine both the sky-projected (λ ≈ −0.4 ± 0.2◦) and true 3D obliquity (ψ ≈ 7+12 −4 ◦ ). We also find good agreement with the MHD simulations, with no significant centre-to-limb variations detectable in the local profiles. Hence, this technique provides a new powerful tool that can probe stellar photospheres, differential rotation, determine 3D obliquities, and remove sky-projection biases in planet migration theories. This technique can be implemented with existing instrumentation, but will become even more powerful with the next generation of high-precision radial velocity spectrographs.

Face recognition using a unified 3D morphable model

We address the problem of 3D-assisted 2D face recognition in scenarios when the input image is subject to degradations or exhibits intra-personal variations not captured by the 3D model. The proposed solution involves a novel approach to learn a subspace spanned by perturbations caused by the missing modes of variation and image degradations, using 3D face data reconstructed from 2D images rather than 3D capture. This is accomplished by modelling the difference in the texture map of the 3D aligned input and reference images. A training set of these texture maps then defines a perturbation space which can be represented using PCA bases. Assuming that the image perturbation subspace is orthogonal to the 3D face model space, then these additive components can be recovered from an unseen input image, resulting in an improved fit of the 3D face model. The linearity of the model leads to efficient fitting. Experiments show that our method achieves very competitive face recognition performance on Multi-PIE and AR databases. We also present baseline face recognition results on a new data set exhibiting combined pose and illumination variations as well as occlusion.