Mixing layer oscillations for a submerged horizontal wall-jet

Measurements of the horizontal velocity component were made for a horizontal wall-jet emanating from a submerged sluice gate forming one side of a large flow compartment. The existence of large-scale vortex structures was quantified by spectral analysis of the velocity measurements taken at various distances from the floor of the flow compartment, for different measurement stations from the jet exit. Close to the jet exit, the spectra of the velocity measurements within the potential core exhibit multiple peaks. Further downstream, the spectra are more defined and peak at the same frequency, irrespective of whether the measurements were made within the potential core or the mixing layer. The spectral peak corresponds to the passage frequency of large-scale vortex structures. Downstream of the potential core, the peak frequencies of the velocity spectra increase as the measurement location was moved towards the floor of the flow compartment. The increase in peak frequencies is attributed to fluctuations associated with the wall boundary layer. Predictions of the mixing layer instabilities were made using linear stability analysis. The predictions are in good agreement with the observed vortex shedding frequencies in the mixing layer

1915 in Australia: the reality of total war sinks in

1915 was a critical year for Australians, and not just because of the pride and myth-making associated with Gallipoli. Today we struggle to capture a sense of the profound shock and anxiety the landing at Anzac Cove brought to Australia. But it was this, together with a wider understanding that the war was not going well, that defined 1915 and drew Australians ever deeper into the vortex of total war.

Assessing the economic benefits of starling detection and control to Western Australia

The common starling (Sturnus vulgaris) has a proven invasion history in many countries, and at a continental scale in North America and Australasia. In Australia, starlings are firmly established throughout the eastern states and Tasmania. Incursions of starlings into Western Australia (WA) represent a significant threat to this State’s agricultural, public amenity and biodiversity assets. We present models of starling population dynamics that incorporate environmental and control effort variability. We incorporate knowledge of starling ecology with economic data to assess the potential economic cost of starlings establishing in WA, evaluating the cost–benefits for each management scenario. We calculated starling population size will approach carrying capacity in WA within as little as 30 years if left unchecked. A population of this size could cost the WA economy up to $43.7 million annually in 2011/2012 dollars. Over a 50 year horizon, the conservative benefit–cost ratio for ongoing detection and control at the current level of expenditure is 6.03:1. However, even under current levels of control, starling numbers are projected to increase to almost 11 million by 2061. Further improvements in the efficiency of starling detection and control and/or an increased level of expenditure on detection and control are required.

Driver behaviour prediction for motion simulators using changepoint segmentation

Driving phenomenon is a repetitive process, that permits sequential learning under identifying the proper change periods. Sequential filtering is widely used for tracking and prediction of state dynamics. However, it suffers at abrupt changes, which cause sudden incremental prediction error. We provide a sequential filtering approach using online Bayesian detection of change points to decrease prediction error generally, and specifically at abrupt changes. The approach learns from optimally detected segments for identifying driving behaviour. Change points detection is done by the Pruned Exact Linear Time algorithm. Computational cost of our approach is bounded by the cost of the implemented sequential filter. This computational performance is suitable to the online nature of motion simulator's delay reduction. The approach was tested on a simulated driving scenario using Vortex by CM Labs. The state dimensions are simulated 2D space coordinates, and velocity. Particle filter was used for online sequential filtering. Prediction results show that change-point detection improves the quality of state estimation compared to traditional sequential filters, and is more suitable for predicting behavioural activities.