Particle Image Velocimetry Investigation of a finite amplitude pressure wave

Particle image velocimetry is used to study the motion of gas within a duct subject to the passage of a finite amplitude pressure wave. The wave is representative of the pressure waves found in the exhaust systems of internal combustion engines. Gas particles are accelerated from stationary to 150 m/s and then back to stationary in 8 ms. It is demonstrated that gas particles at the head of the wave travel at the same velocity across the duct cross section at a given point in time. Towards the tail of the wave viscous effects are plainly evident causing the flow profile to tend towards parabolic. However, the instantaneous mean particle velocity across the section is shown to match well with the velocity calculated from a corresponding measured pressure history using 1D gas dynamic theory. The measured pressure history at a point in the duct was acquired using a high speed pressure transducer of the type typically used for engine research in intake and exhaust systems. It is demonstrated that these are unable to follow the rapid changes in pressure accurately and that they are prone to resonate under certain circumstances.

Comparison of Experimental PIV Data and CFD Simulations for Flow in a Diesel Particulate Filter Inlet Diffuser

Flow maldistribution of the exhaust gas entering a Diesel Particulate Filter (DPF) can cause uneven soot distribution during loading and excessive temperature gradients during the regeneration phase. Minimising the magnitude of this maldistribution is therefore an important consideration in the design of the inlet pipe and diffuser, particularly in situations where packaging constraints dictate bends in the inlet pipe close to the filter, or a sharp diffuser angle. This paper describes the use of Particle Image Velocimetry (PIV) to validate a Computational Fluid Dynamic (CFD) model of the flow within the inlet diffuser of a DPF so that CFD can be used with confidence as a tool to minimise this flow maldistribution. PIV is used to study the flow of gas into a DPF over a range of steady state flow conditions. The distribution of flow approaching the front face of the substrate was of particular interest to this study. Optically clear diffusing cones were designed and placed between pipe and substrate to allow PIV analysis to take place. Stereoscopic PIV was used to eliminate any error produced by the optical aberrations caused by looking through the curved wall of the inlet cone. In parallel to the experiments, numerical analysis was carried out using a CFD program with an incorporated DPF model. Boundary conditions for the CFD simulations were taken from the experimental data, allowing an experimental validation of the numerical results. The CFD model incorporated a DPF model, the cement layers seen in segmented filters and the intumescent matting that is commonly used to pack the filter into a metal casing. The mesh contained approximately 580,000 cells and used the realizable ?-e turbulence model. The CFD simulation predicted both pressure drop across the DPF and the velocity field within the cone and at the DPF face with reasonable accuracy, providing confidence in the use the CFD in future work to design new, more efficient cones.

Influence of a boundary on the development of a propeller wash

When vessels operate within harbours or over a density interface in an estuary, the seabed or interface may be close to the tip of the propeller blades. The presence of this boundary will have an effect on the propeller wash and this can affect the erosion of the boundary. The influence of such a boundary on the characteristics of a propeller wash was studied in experiments using a horizontal fixed boundary to confine a propeller jet. Detailed velocity measurements within the jet were obtained using a 3D Particle Image Velocimetry (PIV) system. The bottom stream of a propeller jet was found to expand at a faster rate due to the reduction in pressure beneath the jet caused by the suppression of the replacement fluid. The boundary was found to significantly increase the axial velocities close to it, and reduce the rate of decay of the maximum axial velocity due to the confinement, reducing the height of the jet. Three zones within the propeller wash were identified, the first being before the jet impacted the boundary, the second in which the boundary layer developed at the fixed boundary, followed by a fully developed boundary layer region. Predictive equations to estimate the influence of the boundary have been developed and are presented.

Experimental investigation of flow and segregation behaviour of bulk solids in silos under high gravity conditions

Many researchers have investigated the flow and segregation behaviour in model scale experimental silos at normal gravity conditions. However it is known that the stresses experienced by the bulk solid in industrial silos are high when compared to model silos. Therefore it is important to understand the effect of stress level on flow and segregation behaviour and establish the scaling laws governing this behaviour. The objective of this paper is to understand the effect of gravity on the flow and segregation behaviour of bulk solids in a silo centrifuge model. The materials used were two mixtures composed of Polyamide and glass beads. The discharge of two bi-disperse bulk solids in a silo centrifuge model were recorded under accelerations ranging from 1g to 15g. The velocity distribution during discharge was evaluated using Particle Image Velocimetry (PIV) techniques and the concentration distribution of large and small particles were obtained by imaging processing techniques. The flow and segregation behaviour at high gravities were then quantified and compared with the empirical equations available in the literature.

Rao-Blackwellised particle filter for colour-based tracking

Colour-based particle filters have been used exhaustively in the literature given rise to multiple applications However tracking coloured objects through time has an important drawback since the way in which the camera perceives the colour of the object can change Simple updates are often used to address this problem which imply a risk of distorting the model and losing the target In this paper a joint image characteristic-space tracking is proposed which updates the model simultaneously to the object location In order to avoid the curse of dimensionality a Rao-Blackwellised particle filter has been used Using this technique the hypotheses are evaluated depending on the difference between the model and the current target appearance during the updating stage Convincing results have been obtained in sequences under both sudden and gradual illumination condition changes Crown Copyright (C) 2010 Published by Elsevier B V All rights reserved

An efficient particle filter for color-based tracking in complex scenes

In this paper, we introduce an efficient method for particle selection in tracking objects in complex scenes. Firstly, we improve the proposal distribution function of the tracking algorithm, including current observation, reducing the cost of evaluating particles with a very low likelihood. In addition, we use a partitioned sampling approach to decompose the dynamic state in several stages. It enables to deal with high-dimensional states without an excessive computational cost. To represent the color distribution, the appearance of the tracked object is modelled by sampled pixels. Based on this representation, the probability of any observation is estimated using non-parametric techniques in color space. As a result, we obtain a Probability color Density Image (PDI) where each pixel points its membership to the target color model. In this way, the evaluation of all particles is accelerated by computing the likelihood p(z|x) using the Integral Image of the PDI.

Rao-blackwellized particle filter for human appearance and position tracking

In human motion analysis, the joint estimation of appearance, body pose and location parameters is not always tractable due to its huge computational cost. In this paper, we propose a Rao-Blackwellized Particle Filter for addressing the problem of human pose estimation and tracking. The advantage of the proposed approach is that Rao-Blackwellization allows the state variables to be splitted into two sets, being one of them analytically calculated from the posterior probability of the remaining ones. This procedure reduces the dimensionality of the Particle Filter, thus requiring fewer particles to achieve a similar tracking performance. In this manner, location and size over the image are obtained stochastically using colour and motion clues, whereas body pose is solved analytically applying learned human Point Distribution Models.

Assessing the occupational risk of dust particles in the Kenyan tanning industry using rapid image processing and microscopy techniques

The purpose of this study was to investigate the occupational hazards within the tanning industry caused by contaminated dust. A qualitative assessment of the risk of human exposure to dust was made throughout a commercial Kenyan tannery. Using this information, high-risk points in the processing line were identified and dust sampling regimes developed. An optical set-up using microscopy and digital imaging techniques was used to determine dust particle numbers and size distributions. The results showed that chemical handling was the most hazardous (12 mg m(-3)). A Monte Carlo method was used to estimate the concentration of the dust in the air throughout the tannery during an 8 h working day. This showed that the high-risk area of the tannery was associated with mean concentrations of dust greater than the UK Statutory Instrument 2002 No. 2677. stipulated limits (exceeding 10 mg m(-3) (Inhalable dust limits) and 4 mg m(-3) (Respirable dust limits). This therefore has implications in terms of provision of personal protective equipment (PPE) to the tannery workers for the mitigation of occupational risk.

Adaptive Fusion Of Particle Filtering And Spatio-Temporal Motion Energy For Human Tracking

Object tracking is an active research area nowadays due to its importance in human computer interface, teleconferencing and video surveillance. However, reliable tracking of objects in the presence of occlusions, pose and illumination changes is still a challenging topic. In this paper, we introduce a novel tracking approach that fuses two cues namely colour and spatio-temporal motion energy within a particle filter based framework. We conduct a measure of coherent motion over two image frames, which reveals the spatio-temporal dynamics of the target. At the same time, the importance of both colour and motion energy cues is determined in the stage of reliability evaluation. This determination helps maintain the performance of the tracking system against abrupt appearance changes. Experimental results demonstrate that the proposed method outperforms the other state of the art techniques in the used test datasets.