118 resultados para Filters and filtration

em Queensland University of Technology - ePrints Archive


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This study aimed to quantify the efficiency of deep bag and electrostatic filters, and assess the influence of ventilation systems using these filters on indoor fine (<2.5 µm) and ultrafine particle concentrations in commercial office buildings. Measurements and modelling were conducted for different indoor and outdoor particle source scenarios at three office buildings in Brisbane, Australia. Overall, the in-situ efficiency, measured for particles in size ranges 6 to 3000 nm, of the deep bag filters ranged from 26.3 to 46.9% for the three buildings, while the in-situ efficiency of the electrostatic filter in one building was 60.2%. The highest PN and PM2.5 concentrations in one of the office buildings (up to 131% and 31% higher than the other two buildings, respectively) were due to the proximity of the building’s HVAC air intakes to a nearby bus-only roadway, as well as its higher outdoor ventilation rate. The lowest PN and PM2.5 concentrations (up to 57% and 24% lower than the other two buildings, respectively) were measured in a building that utilised both outdoor and mixing air filters in its HVAC system. Indoor PN concentrations were strongly influenced by outdoor levels and were significantly higher during rush-hours (up to 41%) and nucleation events (up to 57%), compared to working-hours, for all three buildings. This is the first time that the influence of new particle formation on indoor particle concentrations has been identified and quantified. A dynamic model for indoor PN concentration, which performed adequately in this study also revealed that using mixing/outdoor air filters can significantly reduce indoor particle concentration in buildings where indoor air was strongly influenced by outdoor particle levels. This work provides a scientific basis for the selection and location of appropriate filters and outdoor air intakes, during the design of new, or upgrade of existing, building HVAC systems. The results also serve to provide a better understanding of indoor particle dynamics and behaviours under different ventilation and particle source scenarios, and highlight effective methods to reduce exposure to particles in commercial office buildings.

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The internet by its very nature challenges an individual’s notions of propriety, moral acuity and social correctness. A tension will always exist between the censorship of obscene and sensitive information and the freedom to publish and/or access such information. Freedom of expression and communication on the internet is not a static concept: ‘Its continual regeneration is the product of particular combinations of political, legal, cultural and philosophical conditions’.

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Filtration membrane technology has already been employed to remove various organic effluents produced from the textile, paper, plastic, leather, food and mineral processing industries. To improve membrane efficiency and alleviate membrane fouling, an integrated approach is adopted that combines membrane filtration and photocatalysis technology. In this study, alumina nanofiber (AF) membranes with pore size of about 10 nm (determined by the liquid-liquid displacement method) have been synthesized through an in situ hydrothermal reaction, which permitted a large flux and achieved high selectivity. Silver nanoparticles (Ag NPs) are subsequently doped on the nanofibers of the membranes. Silver nanoparticles can strongly absorb visible light due to the surface plasmon resonance (SPR) effect, and thus induce photocatalytic degradation of organic dyes, including anionic, cationic and neutral dyes, under visible light irradiation. In this integrated system, the dyes are retained on the membrane surface, their concentration in the vicinity of the Ag NPs are high and thus can be efficiently decomposed. Meanwhile, the usual flux deterioration caused by the accumulation of the filtered dyes in the passage pores can be avoided. For example, when an aqueous solution containing methylene blue is processed using an integrated membrane, a large flux of 200 L m-2 h-1 and a stable permeating selectivity of 85% were achieved. The combined photocatalysis and filtration function leads to superior performance of the integrated membranes, which have a potential to be used for the removal of organic pollutants in drinking water.

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Results of an interlaboratory comparison on size characterization of SiO2 airborne nanoparticles using on-line and off-line measurement techniques are discussed. This study was performed in the framework of Technical Working Area (TWA) 34—“Properties of Nanoparticle Populations” of the Versailles Project on Advanced Materials and Standards (VAMAS) in the project no. 3 “Techniques for characterizing size distribution of airborne nanoparticles”. Two types of nano-aerosols, consisting of (1) one population of nanoparticles with a mean diameter between 30.3 and 39.0 nm and (2) two populations of non-agglomerated nanoparticles with mean diameters between, respectively, 36.2–46.6 nm and 80.2–89.8 nm, were generated for characterization measurements. Scanning mobility particle size spectrometers (SMPS) were used for on-line measurements of size distributions of the produced nano-aerosols. Transmission electron microscopy, scanning electron microscopy, and atomic force microscopy were used as off-line measurement techniques for nanoparticles characterization. Samples were deposited on appropriate supports such as grids, filters, and mica plates by electrostatic precipitation and a filtration technique using SMPS controlled generation upstream. The results of the main size distribution parameters (mean and mode diameters), obtained from several laboratories, were compared based on metrological approaches including metrological traceability, calibration, and evaluation of the measurement uncertainty. Internationally harmonized measurement procedures for airborne SiO2 nanoparticles characterization are proposed.

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Protecting slow sand filters from high turbidity waters by pre-treatment using Pebble Matrix Filtration (PMF) has been studied in the laboratory at University College London followed by pilot field trials in Papua New Guinea and Serbia. Subsequently, the construction of two full-scale PMF units, one out of concrete (4.8m x4.8m x 3.0m high) and the other using pre-cast Ferro-cement panels (900mm x 1600mm x 20mm thick) with an effective diameter of 4.7m and 3m height, and the combined effective plan area of 40 m2 was completed to protect an existing Slow Sand Filter system at the National Water Supply Drainage Board (NWSDB) in Sri Lanka. Although the plant was completed in April 2008 due to some major repairs to address some leaks and other construction defects in both filters, monitoring was intermittent until November 2008. The results on the plant performance are presented here along with some of the construction problems encountered during the project.

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Dirt collected with sugarcane is processed and separated from the juice in the sugar factory by filtration equipment for return to the cane fields. New technologies over the past decade have enabled performance improvements to be obtained for this key unit operation. Filter mud product still contains a reasonable amount of sugar and the transportation of high moisture mud product has considerable cost. Australia’s traditional approach has been to use Rotary Vacuum Filters for processing and separating mud and other impurities from juice, but in recent years there has been interest in reducing sugar losses and transportation costs through utilisation of new technologies such as Horizontal Bed Filters, Vacuum Belt Press Filters, Membrane Press Filters and Centrifuges. Increasingly, these alternative equipment are being installed in new factories. This chapter describes the general principles of mud filtration theory and mud conditioning followed by a detailed description and review of the various filtration technologies and analysis of the relative merits associated with the equipment.

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This paper presents a prototype tracking system for tracking people in enclosed indoor environments where there is a high rate of occlusions. The system uses a stereo camera for acquisition, and is capable of disambiguating occlusions using a combination of depth map analysis, a two step ellipse fitting people detection process, the use of motion models and Kalman filters and a novel fit metric, based on computationally simple object statistics. Testing shows that our fit metric outperforms commonly used position based metrics and histogram based metrics, resulting in more accurate tracking of people.

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Uninhabited aerial vehicles (UAVs) are a cutting-edge technology that is at the forefront of aviation/aerospace research and development worldwide. Many consider their current military and defence applications as just a token of their enormous potential. Unlocking and fully exploiting this potential will see UAVs in a multitude of civilian applications and routinely operating alongside piloted aircraft. The key to realising the full potential of UAVs lies in addressing a host of regulatory, public relation, and technological challenges never encountered be- fore. Aircraft collision avoidance is considered to be one of the most important issues to be addressed, given its safety critical nature. The collision avoidance problem can be roughly organised into three areas: 1) Sense; 2) Detect; and 3) Avoid. Sensing is concerned with obtaining accurate and reliable information about other aircraft in the air; detection involves identifying potential collision threats based on available information; avoidance deals with the formulation and execution of appropriate manoeuvres to maintain safe separation. This thesis tackles the detection aspect of collision avoidance, via the development of a target detection algorithm that is capable of real-time operation onboard a UAV platform. One of the key challenges of the detection problem is the need to provide early warning. This translates to detecting potential threats whilst they are still far away, when their presence is likely to be obscured and hidden by noise. Another important consideration is the choice of sensors to capture target information, which has implications for the design and practical implementation of the detection algorithm. The main contributions of the thesis are: 1) the proposal of a dim target detection algorithm combining image morphology and hidden Markov model (HMM) filtering approaches; 2) the novel use of relative entropy rate (RER) concepts for HMM filter design; 3) the characterisation of algorithm detection performance based on simulated data as well as real in-flight target image data; and 4) the demonstration of the proposed algorithm's capacity for real-time target detection. We also consider the extension of HMM filtering techniques and the application of RER concepts for target heading angle estimation. In this thesis we propose a computer-vision based detection solution, due to the commercial-off-the-shelf (COTS) availability of camera hardware and the hardware's relatively low cost, power, and size requirements. The proposed target detection algorithm adopts a two-stage processing paradigm that begins with an image enhancement pre-processing stage followed by a track-before-detect (TBD) temporal processing stage that has been shown to be effective in dim target detection. We compare the performance of two candidate morphological filters for the image pre-processing stage, and propose a multiple hidden Markov model (MHMM) filter for the TBD temporal processing stage. The role of the morphological pre-processing stage is to exploit the spatial features of potential collision threats, while the MHMM filter serves to exploit the temporal characteristics or dynamics. The problem of optimising our proposed MHMM filter has been examined in detail. Our investigation has produced a novel design process for the MHMM filter that exploits information theory and entropy related concepts. The filter design process is posed as a mini-max optimisation problem based on a joint RER cost criterion. We provide proof that this joint RER cost criterion provides a bound on the conditional mean estimate (CME) performance of our MHMM filter, and this in turn establishes a strong theoretical basis connecting our filter design process to filter performance. Through this connection we can intelligently compare and optimise candidate filter models at the design stage, rather than having to resort to time consuming Monte Carlo simulations to gauge the relative performance of candidate designs. Moreover, the underlying entropy concepts are not constrained to any particular model type. This suggests that the RER concepts established here may be generalised to provide a useful design criterion for multiple model filtering approaches outside the class of HMM filters. In this thesis we also evaluate the performance of our proposed target detection algorithm under realistic operation conditions, and give consideration to the practical deployment of the detection algorithm onboard a UAV platform. Two fixed-wing UAVs were engaged to recreate various collision-course scenarios to capture highly realistic vision (from an onboard camera perspective) of the moments leading up to a collision. Based on this collected data, our proposed detection approach was able to detect targets out to distances ranging from about 400m to 900m. These distances, (with some assumptions about closing speeds and aircraft trajectories) translate to an advanced warning ahead of impact that approaches the 12.5 second response time recommended for human pilots. Furthermore, readily available graphic processing unit (GPU) based hardware is exploited for its parallel computing capabilities to demonstrate the practical feasibility of the proposed target detection algorithm. A prototype hardware-in- the-loop system has been found to be capable of achieving data processing rates sufficient for real-time operation. There is also scope for further improvement in performance through code optimisations. Overall, our proposed image-based target detection algorithm offers UAVs a cost-effective real-time target detection capability that is a step forward in ad- dressing the collision avoidance issue that is currently one of the most significant obstacles preventing widespread civilian applications of uninhabited aircraft. We also highlight that the algorithm development process has led to the discovery of a powerful multiple HMM filtering approach and a novel RER-based multiple filter design process. The utility of our multiple HMM filtering approach and RER concepts, however, extend beyond the target detection problem. This is demonstrated by our application of HMM filters and RER concepts to a heading angle estimation problem.

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Introduction: An observer, looking sideways from a moving vehicle, while wearing a neutral density filter over one eye, can have a distorted perception of speed, known as the Enright phenomenon. The purpose of this study was to determine how the Enright phenomenon influences driving behaviour. Methods: A geometric model of the Enright phenomenon was developed. Ten young, visually normal, participants (mean age = 25.4 years) were tested on a straight section of a closed driving circuit and instructed to look out of the right side of the vehicle and drive at either 40 Km/h or 60 Km/h under the following binocular viewing conditions: with a 0.9 ND filter over the left eye (leading eye); 0.9 ND filter over the right eye (trailing eye); 0.9 ND filters over both eyes, and with no filters over either eye. The order of filter conditions was randomised and the speed driven recorded for each condition. Results: Speed judgments did not differ significantly between the two baseline conditions (no filters and both eyes filtered) for either speed tested. For the baseline conditions, when subjects were asked to drive at 60 Km/h they matched this speed well (61 ± 10.2 Km/h) but drove significantly faster than requested (51.6 ± 9.4 Km/h) when asked to drive at 40 Km/h. Subjects significantly exceeded baseline speeds by 8.7± 5.0 Km/h, when the trailing eye was filtered and travelled slower than baseline speeds by 3.7± 4.6 Km/h when the leading eye was filtered. Conclusions: This is the first quantitative study demonstrating how the Enright effect can influence perceptions of driving speed, and demonstrates that monocular filtering of an eye can significantly impact driving speeds, albeit to a lesser extent than predicted by geometric models of the phenomenon.

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Circulating tumour cells (CTCs) have attracted much recent interest in cancer research as a potential biomarker and as a means of studying the process of metastasis. It has long been understood that metastasis is a hallmark of malignancy, and conceptual theories on the basis of metastasis from the nineteenth century foretold the existence of a tumour "seed" which is capable of establishing discrete tumours in the "soil" of distant organs. This prescient "seed and soil" hypothesis accurately predicted the existence of CTCs; microscopic tumour fragments in the blood, at least some of which are capable of forming metastases. However, it is only in recent years that reliable, reproducible methods of CTC detection and analysis have been developed. To date, the majority of studies have employed the CellSearch™ system (Veridex LLC), which is an immunomagnetic purification method. Other promising techniques include microfluidic filters, isolation of tumour cells by size using microporous polycarbonate filters and flow cytometry-based approaches. While many challenges still exist, the detection of CTCs in blood is becoming increasingly feasible, giving rise to some tantalizing questions about the use of CTCs as a potential biomarker. CTC enumeration has been used to guide prognosis in patients with metastatic disease, and to act as a surrogate marker for disease response during therapy. Other possible uses for CTC detection include prognostication in early stage patients, identifying patients requiring adjuvant therapy, or in surveillance, for the detection of relapsing disease. Another exciting possible use for CTC detection assays is the molecular and genetic characterization of CTCs to act as a "liquid biopsy" representative of the primary tumour. Indeed it has already been demonstrated that it is possible to detect HER2, KRAS and EGFR mutation status in breast, colon and lung cancer CTCs respectively. In the course of this review, we shall discuss the biology of CTCs and their role in metastagenesis, the most commonly used techniques for their detection and the evidence to date of their clinical utility, with particular reference to lung cancer.

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In order to provide realistic data for air pollution inventories and source apportionment at airports, the morphology and composition of ultrafine particles (UFP) in aircraft engine exhaust were measured and characterized. For this purpose, two independent measurement techniques were employed to collect emissions during normal takeoff and landing operations at Brisbane Airport, Australia. PM1 emissions in the airfield were collected on filters and analyzed using the particle-induced X-ray emission (PIXE) technique. Morphological and compositional analyses of individual ultrafine particles in aircraft plumes were performed on silicon nitride membrane grids using transmission electron microscopy (TEM) combined with energy-dispersive X-ray microanalysis (EDX). TEM results showed that the deposited particles were in the range of 5 to 100 nm in diameter, had semisolid spherical shapes and were dominant in the nucleation mode (18 – 20 nm). The EDX analysis showed the main elements in the nucleation particles were C, O, S and Cl. The PIXE analysis of the airfield samples was generally in agreement with the EDX in detecting S, Cl, K, Fe and Si in the particles. The results of this study provide important scientific information on the toxicity of aircraft exhaust and their impact on local air quality.

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This thesis establishes performance properties for approximate filters and controllers that are designed on the basis of approximate dynamic system representations. These performance properties provide a theoretical justification for the widespread application of approximate filters and controllers in the common situation where system models are not known with complete certainty. This research also provides useful tools for approximate filter designs, which are applied to hybrid filtering of uncertain nonlinear systems. As a contribution towards applications, this thesis also investigates air traffic separation control in the presence of measurement uncertainties.

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Development of technologies for water desalination and purification is critical to meet the global challenges of insufficient water supply and inadequate sanitation, especially for point-of-use applications. Conventional desalination methods are energy and operationally intensive, whereas adsorption-based techniques are simple and easy to use for point-of-use water purification, yet their capacity to remove salts is limited. Here we report that plasma-modified ultralong carbon nanotubes exhibit ultrahigh specific adsorption capacity for salt (exceeding 400% by weight) that is two orders of magnitude higher than that found in the current state-of-the-art activated carbon-based water treatment systems. We exploit this adsorption capacity in ultralong carbon nanotube-based membranes that can remove salt, as well as organic and metal contaminants. These ultralong carbon nanotube-based membranes may lead to next-generation rechargeable, point-of-use potable water purification appliances with superior desalination, disinfection and filtration properties. © 2013 Macmillan Publishers Limited.

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In this paper conditional hidden Markov model (HMM) filters and conditional Kalman filters (KF) are coupled together to improve demodulation of differential encoded signals in noisy fading channels. We present an indicator matrix representation for differential encoded signals and the optimal HMM filter for demodulation. The filter requires O(N3) calculations per time iteration, where N is the number of message symbols. Decision feedback equalisation is investigated via coupling the optimal HMM filter for estimating the message, conditioned on estimates of the channel parameters, and a KF for estimating the channel states, conditioned on soft information message estimates. The particular differential encoding scheme examined in this paper is differential phase shift keying. However, the techniques developed can be extended to other forms of differential modulation. The channel model we use allows for multiplicative channel distortions and additive white Gaussian noise. Simulation studies are also presented.

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Parabens, benzophenone-3 and triclosan are common ingredients used as preservatives, ultraviolet radiation filters and antimicrobial agents, respectively. Human exposure occurs through consumption of processed food and use of cosmetics and consumer products. The aim of this study was to provide a preliminary characterisation of exposure to selected personal care product chemicals in the general Australian population. De-identified urine specimens stratified by age and sex were obtained from a community-based pathology laboratory and pooled (n= 24 pools of 100). Concentrations of free and total (sum of free plus conjugated) species of methyl, ethyl, propyl and butyl paraben, benzophenone-3 and triclosan were quantified using isotope dilution tandem mass spectrometry; with geometric means 232, 33.5, 60.6, 4.32, 61.5 and 87.7. ng/mL, respectively. Age was inversely associated with paraben concentration, and females had concentrations approximately two times higher than males. Total paraben and benzophenone-3 concentrations are significantly higher than reported worldwide, and the average triclosan concentration was more than one order of magnitude higher than in many other populations. This study provides the first data on exposure of the general Australian population to a range of common personal care product chemical ingredients, which appears to be prevalent and warrants further investigation.