992 resultados para Exhaust systems.


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Fault tree analysis (FTA) is presented to model the reliability of a railway traction power system in this paper. First, the construction of fault tree is introduced to integrate components in traction power systems into a fault tree; then the binary decision diagram (BDD) method is used to evaluate fault trees qualitatively and quantitatively. The components contributing to the reliability of overall system are identified with their relative importance through sensitivity analysis. Finally, an AC traction power system is evaluated by the proposed methods.

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Streaming SIMD Extensions (SSE) is a unique feature embedded in the Pentium III class of microprocessors. By fully exploiting SSE, parallel algorithms can be implemented on a standard personal computer and a theoretical speedup of four can be achieved. In this paper, we demonstrate the implementation of a parallel LU matrix decomposition algorithm for solving power systems network equations with SSE and discuss advantages and disadvantages of this approach.

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Streaming SIMD Extensions (SSE) is a unique feature embedded in the Pentium III and IV classes of microprocessors. By fully exploiting SSE, parallel algorithms can be implemented on a standard personal computer and a theoretical speedup of four can be achieved. In this paper, we demonstrate the implementation of a parallel LU matrix decomposition algorithm for solving linear systems with SSE and discuss advantages and disadvantages of this approach based on our experimental study.

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Real-world business processes are resource-intensive. In work environments human resources usually multitask, both human and non-human resources are typically shared between tasks, and multiple resources are sometimes necessary to undertake a single task. However, current Business Process Management Systems focus on task-resource allocation in terms of individual human resources only and lack support for a full spectrum of resource classes (e.g., human or non-human, application or non-application, individual or teamwork, schedulable or unschedulable) that could contribute to tasks within a business process. In this paper we develop a conceptual data model of resources that takes into account the various resource classes and their interactions. The resulting conceptual resource model is validated using a real-life healthcare scenario.

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Groundwater is increasingly recognised as an important yet vulnerable natural resource, and a key consideration in water cycle management. However, communication of sub-surface water system behaviour, as an important part of encouraging better water management, is visually difficult. Modern 3D visualisation techniques can be used to effectively communicate these complex behaviours to engage and inform community stakeholders. Most software developed for this purpose is expensive and requires specialist skills. The Groundwater Visualisation System (GVS) developed by QUT integrates a wide range of surface and sub-surface data, to produce a 3D visualisation of the behaviour, structure and connectivity of groundwater/surface water systems. Surface data (elevation, surface water, land use, vegetation and geology) and data collected from boreholes (bore locations and subsurface geology) are combined to visualise the nature, structure and connectivity of groundwater/surface water systems. Time-series data (water levels, groundwater quality, rainfall, stream flow and groundwater abstraction) is displayed as an animation within the 3D framework, or graphically, to show water system condition changes over time. GVS delivers an interactive, stand-alone 3D Visualisation product that can be used in a standard PC environment. No specialised training or modelling skills are required. The software has been used extensively in the SEQ region to inform and engage both water managers and the community alike. Examples will be given of GVS visualisations developed in areas where there have been community concerns around groundwater over-use and contamination.

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This correspondence paper addresses the problem of output feedback stabilization of control systems in networked environments with quality-of-service (QoS) constraints. The problem is investigated in discrete-time state space using Lyapunov’s stability theory and the linear inequality matrix technique. A new discrete-time modeling approach is developed to describe a networked control system (NCS) with parameter uncertainties and nonideal network QoS. It integrates a network-induced delay, packet dropout, and other network behaviors into a unified framework. With this modeling, an improved stability condition, which is dependent on the lower and upper bounds of the equivalent network-induced delay, is established for the NCS with norm-bounded parameter uncertainties. It is further extended for the output feedback stabilization of the NCS with nonideal QoS. Numerical examples are given to demonstrate the main results of the theoretical development.

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The development of locally-based healthcare initiatives, such as community health coalitions that focus on capacity building programs and multi-faceted responses to long-term health problems, have become an increasingly important part of the public health landscape. As a result of their complexity and the level of investment, it has become necessary to develop innovative ways to help manage these new healthcare approaches. Geographical Information Systems (GIS) have been suggested as one of the innovative approaches that will allow community health coalitions to better manage and plan their activities. The focus of this paper is to provide a commentary on the use of GIS as a tool for community coalitions and discuss some of the potential benefits and issues surrounding the development of these tools.

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With the advances in computer hardware and software development techniques in the past 25 years, digital computer simulation of train movement and traction systems has been widely adopted as a standard computer-aided engineering tool [1] during the design and development stages of existing and new railway systems. Simulators of different approaches and scales are used extensively to investigate various kinds of system studies. Simulation is now proven to be the cheapest means to carry out performance predication and system behaviour characterisation. When computers were first used to study railway systems, they were mainly employed to perform repetitive but time-consuming computational tasks, such as matrix manipulations for power network solution and exhaustive searches for optimal braking trajectories. With only simple high-level programming languages available at the time, full advantage of the computing hardware could not be taken. Hence, structured simulations of the whole railway system were not very common. Most applications focused on isolated parts of the railway system. It is more appropriate to regard those applications as primarily mechanised calculations rather than simulations. However, a railway system consists of a number of subsystems, such as train movement, power supply and traction drives, which inevitably contains many complexities and diversities. These subsystems interact frequently with each other while the trains are moving; and they have their special features in different railway systems. To further complicate the simulation requirements, constraints like track geometry, speed restrictions and friction have to be considered, not to mention possible non-linearities and uncertainties in the system. In order to provide a comprehensive and accurate account of system behaviour through simulation, a large amount of data has to be organised systematically to ensure easy access and efficient representation; the interactions and relationships among the subsystems should be defined explicitly. These requirements call for sophisticated and effective simulation models for each component of the system. The software development techniques available nowadays allow the evolution of such simulation models. Not only can the applicability of the simulators be largely enhanced by advanced software design, maintainability and modularity for easy understanding and further development, and portability for various hardware platforms are also encouraged. The objective of this paper is to review the development of a number of approaches to simulation models. Attention is, in particular, given to models for train movement, power supply systems and traction drives. These models have been successfully used to enable various ‘what-if’ issues to be resolved effectively in a wide range of applications, such as speed profiles, energy consumption, run times etc.

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Atmospheric ions are produced by many natural and anthropogenic sources and their concentrations vary widely between different environments. There is very little information on their concentrations in different types of urban environments, how they compare across these environments and their dominant sources. In this study, we measured airborne concentrations of small ions, particles and net particle charge at 32 different outdoor sites in and around a major city in Australia and identified the main ion sources. Sites were classified into seven groups as follows: park, woodland, city centre, residential, freeway, power lines and power substation. Generally, parks were situated away from ion sources and represented the urban background value of about 270 ions cm-3. Median concentrations at all other groups were significantly higher than in the parks. We show that motor vehicles and power transmission systems are two major ion sources in urban areas. Power lines and substations constituted strong unipolar sources, while motor vehicle exhaust constituted strong bipolar sources. The small ion concentration in urban residential areas was about 960 cm-3. At sites where ion sources were co-located with particle sources, ion concentrations were inhibited due to the ion-particle attachment process. These results improved our understanding on air ion distribution and its interaction with particles in the urban outdoor environment.

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Measurements in the exhaust plume of a petrol-driven motor car showed that molecular cluster ions of both signs were present in approximately equal amounts. The emission rate increased sharply with engine speed while the charge symmetry remained unchanged. Measurements at the kerbside of nine motorways and five city roads showed that the mean total cluster ion concentration near city roads (603 cm-3) was about one-half of that near motorways (1211 cm-3) and about twice as high as that in the urban background (269 cm-3). Both positive and negative ion concentrations near a motorway showed a significant linear increase with traffic density (R2=0.3 at p<0.05) and correlated well with each other in real time (R2=0.87 at p<0.01). Heavy duty diesel vehicles comprised the main source of ions near busy roads. Measurements were conducted as a function of downwind distance from two motorways carrying around 120-150 vehicles per minute. Total traffic-related cluster ion concentrations decreased rapidly with distance, falling by one-half from the closest approach of 2m to 5m of the kerb. Measured concentrations decreased to background at about 15m from the kerb when the wind speed was 1.3 m s-1, this distance being greater at higher wind speed. The number and net charge concentrations of aerosol particles were also measured. Unlike particles that were carried downwind to distances of a few hundred metres, cluster ions emitted by motor vehicles were not present at more than a few tens of metres from the road.

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Abstract Computer simulation is a versatile and commonly used tool for the design and evaluation of systems with different degrees of complexity. Power distribution systems and electric railway network are areas for which computer simulations are being heavily applied. A dominant factor in evaluating the performance of a software simulator is its processing time, especially in the cases of real-time simulation. Parallel processing provides a viable mean to reduce the computing time and is therefore suitable for building real-time simulators. In this paper, we present different issues related to solving the power distribution system with parallel computing based on a multiple-CPU server and we will concentrate, in particular, on the speedup performance of such an approach.

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While critical success factors (CSFs) of enterprise system (ES) implementation are mature concepts and have received considerable attention for over a decade, researchers have very often focused on only a specific aspect of the implementation process or a specific CSF. Resultantly, there is (1) little research documented that encompasses all significant CSF considerations and (2) little empirical research into the important factors of successful ES implementation. This paper is part of a larger research effort that aims to contribute to understanding the phenomenon of ES CSFs, and reports on preliminary findings from a case study conducted at a Queensland University of Technology (QUT) in Australia. This paper reports on an empirically derived CSFs framework using a directed content analysis of 79 studies; from top IS outlets, employing the characteristics of the analytic theory, and from six different projects implemented at QUT.

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A number of instrumented laboratory-scale soil embankment slopes were subjected to artificial rainfall until they failed. The factor of safety of the slope based on real-time measurements of pore-water pressure (suction) and laboratory measured soil properties were calculated as the rainfall progressed. Based on the experiment measurements and slope stability analysis, it was observed that slope displacement measurements can be used to warn the slope failure more accurately. Further, moisture content/pore-water pressure measurements near the toe of the slope and the real-time factor of safety can also be used for prediction of rainfall-induced embankment failures with adequate accuracy.

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The economiser is a critical component for efficient operation of coal-fired power stations. It consists of a large system of water-filled tubes which extract heat from the exhaust gases. When it fails, usually due to erosion causing a leak, the entire power station must be shut down to effect repairs. Not only are such repairs highly expensive, but the overall repair costs are significantly affected by fluctuations in electricity market prices, due to revenue lost during the outage. As a result, decisions about when to repair an economiser can alter the repair costs by millions of dollars. Therefore, economiser repair decisions are critical and must be optimised. However, making optimal repair decisions is difficult because economiser leaks are a type of interactive failure. If left unfixed, a leak in a tube can cause additional leaks in adjacent tubes which will need more time to repair. In addition, when choosing repair times, one also needs to consider a number of other uncertain inputs such as future electricity market prices and demands. Although many different decision models and methodologies have been developed, an effective decision-making method specifically for economiser repairs has yet to be defined. In this paper, we describe a Decision Tree based method to meet this need. An industrial case study is presented to demonstrate the application of our method.