167 resultados para Active Flow Control


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Bioclastic flow deposits offshore from the Soufrie`re Hills volcano on Montserrat in the Lesser Antilles were deposited by the largest volume sediment flows near this active volcano in the last 26 kyr. The volume of these deposits exceeds that of the largest historic volcanic dome collapse in the world, which occurred on Montserrat in 2003. These flows were most probably generated by a large submarine slope failure of the carbonate shelf comprising the south west flank of Antigua or the east flank of Redonda; adjacent islands that are not volcanically active. The bioclastic flow deposits are relatively coarse-grained and either ungraded or poorly graded, and were deposited by non cohesive debris flow and high density turbidity currents. The bioclastic deposit often comprises multiple sub-units that cannot be correlated between core sites; some located just 2 km apart. Multiple sub-units in the bioclastic deposit result from either flow reflection, stacking of multiple debris flow lobes, and/or multi-stage collapse of the initial landslide. This study provides unusually precise constraints on the age of this mass flow event that occurred at ca 14 ka. Few large submarine landslides have been well dated, but the slope failures that have been dated are commonly associated with periods of rapid sea-level change.

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A model has been developed to track the flow of cane constituents through the milling process. While previous models have tracked the flow of fibre, brix and water through the process, this model tracks the soluble and insoluble solid cane components using modelling theory and experiment data, assisting in further understanding the flow of constituents into mixed juice and final bagasse. The work provided an opportunity to understand the factors which affect the distribution of the cane constituents in juice and bagasse. Application of the model should lead to improvements in the overall performance of the milling train.

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Quality oriented management systems and methods have become the dominant business and governance paradigm. From this perspective, satisfying customers’ expectations by supplying reliable, good quality products and services is the key factor for an organization and even government. During recent decades, Statistical Quality Control (SQC) methods have been developed as the technical core of quality management and continuous improvement philosophy and now are being applied widely to improve the quality of products and services in industrial and business sectors. Recently SQC tools, in particular quality control charts, have been used in healthcare surveillance. In some cases, these tools have been modified and developed to better suit the health sector characteristics and needs. It seems that some of the work in the healthcare area has evolved independently of the development of industrial statistical process control methods. Therefore analysing and comparing paradigms and the characteristics of quality control charts and techniques across the different sectors presents some opportunities for transferring knowledge and future development in each sectors. Meanwhile considering capabilities of Bayesian approach particularly Bayesian hierarchical models and computational techniques in which all uncertainty are expressed as a structure of probability, facilitates decision making and cost-effectiveness analyses. Therefore, this research investigates the use of quality improvement cycle in a health vii setting using clinical data from a hospital. The need of clinical data for monitoring purposes is investigated in two aspects. A framework and appropriate tools from the industrial context are proposed and applied to evaluate and improve data quality in available datasets and data flow; then a data capturing algorithm using Bayesian decision making methods is developed to determine economical sample size for statistical analyses within the quality improvement cycle. Following ensuring clinical data quality, some characteristics of control charts in the health context including the necessity of monitoring attribute data and correlated quality characteristics are considered. To this end, multivariate control charts from an industrial context are adapted to monitor radiation delivered to patients undergoing diagnostic coronary angiogram and various risk-adjusted control charts are constructed and investigated in monitoring binary outcomes of clinical interventions as well as postintervention survival time. Meanwhile, adoption of a Bayesian approach is proposed as a new framework in estimation of change point following control chart’s signal. This estimate aims to facilitate root causes efforts in quality improvement cycle since it cuts the search for the potential causes of detected changes to a tighter time-frame prior to the signal. This approach enables us to obtain highly informative estimates for change point parameters since probability distribution based results are obtained. Using Bayesian hierarchical models and Markov chain Monte Carlo computational methods, Bayesian estimators of the time and the magnitude of various change scenarios including step change, linear trend and multiple change in a Poisson process are developed and investigated. The benefits of change point investigation is revisited and promoted in monitoring hospital outcomes where the developed Bayesian estimator reports the true time of the shifts, compared to priori known causes, detected by control charts in monitoring rate of excess usage of blood products and major adverse events during and after cardiac surgery in a local hospital. The development of the Bayesian change point estimators are then followed in a healthcare surveillances for processes in which pre-intervention characteristics of patients are viii affecting the outcomes. In this setting, at first, the Bayesian estimator is extended to capture the patient mix, covariates, through risk models underlying risk-adjusted control charts. Variations of the estimator are developed to estimate the true time of step changes and linear trends in odds ratio of intensive care unit outcomes in a local hospital. Secondly, the Bayesian estimator is extended to identify the time of a shift in mean survival time after a clinical intervention which is being monitored by riskadjusted survival time control charts. In this context, the survival time after a clinical intervention is also affected by patient mix and the survival function is constructed using survival prediction model. The simulation study undertaken in each research component and obtained results highly recommend the developed Bayesian estimators as a strong alternative in change point estimation within quality improvement cycle in healthcare surveillances as well as industrial and business contexts. The superiority of the proposed Bayesian framework and estimators are enhanced when probability quantification, flexibility and generalizability of the developed model are also considered. The empirical results and simulations indicate that the Bayesian estimators are a strong alternative in change point estimation within quality improvement cycle in healthcare surveillances. The superiority of the proposed Bayesian framework and estimators are enhanced when probability quantification, flexibility and generalizability of the developed model are also considered. The advantages of the Bayesian approach seen in general context of quality control may also be extended in the industrial and business domains where quality monitoring was initially developed.

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In this paper we present a fast power line detection and localisation algorithm as well as propose a high-level guidance architecture for active vision-based Unmanned Aerial Vehicle (UAV) guidance. The detection stage is based on steerable filters for edge ridge detection, followed by a line fitting algorithm to refine candidate power lines in images. The guidance architecture assumes an UAV with an onboard Gimbal camera. We first control the position of the Gimbal such that the power line is in the field of view of the camera. Then its pose is used to generate the appropriate control commands such that the aircraft moves and flies above the lines. We present initial experimental results for the detection stage which shows that the proposed algorithm outperforms two state-of-the-art line detection algorithms for power line detection from aerial imagery.

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With the advent of large-scale wind farms and their integration into electrical grids, more uncertainties, constraints and objectives must be considered in power system development. It is therefore necessary to introduce risk-control strategies into the planning of transmission systems connected with wind power generators. This paper presents a probability-based multi-objective model equipped with three risk-control strategies. The model is developed to evaluate and enhance the ability of the transmission system to protect against overload risks when wind power is integrated into the power system. The model involves: (i) defining the uncertainties associated with wind power generators with probability measures and calculating the probabilistic power flow with the combined use of cumulants and Gram-Charlier series; (ii) developing three risk-control strategies by specifying the smallest acceptable non-overload probability for each branch and the whole system, and specifying the non-overload margin for all branches in the whole system; (iii) formulating an overload risk index based on the non-overload probability and the non-overload margin defined; and (iv) developing a multi-objective transmission system expansion planning (TSEP) model with the objective functions composed of transmission investment and the overload risk index. The presented work represents a superior risk-control model for TSEP in terms of security, reliability and economy. The transmission expansion planning model with the three risk-control strategies demonstrates its feasibility in the case study using two typical power systems

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Carbon nanotubes (CNTs) have excellent electrical, mechanical and electromechanical properties. When CNTs are incorporated into polymers, electrically conductive composites with high electrical conductivity at very low CNT content (often below 1% wt CNT) result. Due to the change in electrical properties under mechanical load, carbon nanotube/polymer composites have attracted significant research interest especially due to their potential for application in in-situ monitoring of stress distribution and active control of strain sensing in composite structures or as strain sensors. To sucessfully develop novel devices for such applications, some of the major challenges that need to be overcome include; in-depth understanding of structure-electrical conductivity relationships, response of the composites under changing environmental conditions and piezoresistivity of different types of carbon nanotube/polymer sensing devices. In this thesis, direct current (DC) and alternating current (AC) conductivity of CNT-epoxy composites was investigated. Details of microstructure obtained by scanning electron microscopy were used to link observed electrical properties with structure using equivalent circuit modeling. The role of polymer coatings on macro and micro level electrical conductivity was investigated using atomic force microscopy. Thermal analysis and Raman spectroscopy were used to evaluate the heat flow and deformation of carbon nanotubes embedded in the epoxy, respectively, and related to temperature induced resistivity changes. A comparative assessment of piezoresistivity was conducted using randomly mixed carbon nanotube/epoxy composites, and new concept epoxy- and polyurethane-coated carbon nanotube films. The results indicate that equivalent circuit modelling is a reliable technique for estimating values of the resistance and capacitive components in linear, low aspect ratio-epoxy composites. Using this approach, the dominant role of tunneling resistance in determining the electrical conductivity was confirmed, a result further verified using conductive-atomic force microscopy analysis. Randomly mixed CNT-epoxy composites were found to be highly sensitive to mechanical strain and temperature variation compared to polymer-coated CNT films. In the vicinity of the glass transition temperature, the CNT-epoxy composites exhibited pronounced resistivity peaks. Thermal and Raman spectroscopy analyses indicated that this phenomenon can be attributed to physical aging of the epoxy matrix phase and structural rearrangement of the conductive network induced by matrix expansion. The resistivity of polymercoated CNT composites was mainly dominated by the intrinsic resistivity of CNTs and the CNT junctions, and their linear, weakly temperature sensitive response can be described by a modified Luttinger liquid model. Piezoresistivity of the polymer coated sensors was dominated by break up of the conducting carbon nanotube network and the consequent degradation of nanotube-nanotube contacts while that of the randomly mixed CNT-epoxy composites was determined by tunnelling resistance between neighbouring CNTs. This thesis has demonstrated that it is possible to use microstructure information to develop equivalent circuit models that are capable of representing the electrical conductivity of CNT/epoxy composites accurately. New designs of carbon nanotube based sensing devices, utilising carbon nanotube films as the key functional element, can be used to overcome the high temperature sensitivity of randomly mixed CNT/polymer composites without compromising on desired high strain sensitivity. This concept can be extended to develop large area intelligent CNT based coatings and targeted weak-point specific strain sensors for use in structural health monitoring.

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This paper presents an analytical model to study the effect of stiffening ribs on vibration transmission between two rectangular plates coupled at right angle. Interesting wave attenuation patterns were observed by placing the stiffening rib either on the source or on the receiving plate. The result can be used to improve the understanding of vibration and for vibration control of more complex structures such as transformer tanks and machine covers.

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An advanced rule-based Transit Signal Priority (TSP) control method is presented in this paper. An on-line transit travel time prediction model is the key component of the proposed method, which enables the selection of the most appropriate TSP plans for the prevailing traffic and transit condition. The new method also adopts a priority plan re-development feature that enables modifying or even switching the already implemented priority plan to accommodate changes in the traffic conditions. The proposed method utilizes conventional green extension and red truncation strategies and also two new strategies including green truncation and queue clearance. The new method is evaluated against a typical active TSP strategy and also the base case scenario assuming no TSP control in microsimulation. The evaluation results indicate that the proposed method can produce significant benefits in reducing the bus delay time and improving the service regularity with negligible adverse impacts on the non-transit street traffic.

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A juice flow model has been developed to estimate the juice expression at the four nips of a sixroller mill. An extended volumetric theory was applied to determine the juice expressed at each nip. The model was applied to a first and final mill, using typical mill settings and an empirical equation to estimate reabsorption. Results of using the model for typical heavy-duty pressure feeder settings show that most of the juice is expressed at the pressure feeder nip. Since the pressure feeders are remote from the mill, a significant portion of the juice is expressed before the bagasse enters the mill.

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As one of the measures for decreasing road traffic noise in a city, the control of the traffic flow and the physical distribution is considered. To conduct the measure effectively, the model for predicting the traffic flow in the citywide road network is necessary. In this study, the existing model named AVENUE was used as a traffic flow prediction model. The traffic flow model was integrated with the road vehicles' sound power model and the sound propagation model, and the new road traffic noise prediction model was established. As a case study, the prediction model was applied to the road network of Tsukuba city in Japan and the noise map of the city was made. To examine the calculation accuracy of the noise map, the calculated values of the noise at the main roads were compared with the measured values. As a result, it was found that there was a possibility that the high accuracy noise map of the city could be made by using the noise prediction model developed in this study.

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The feral pig, Sus scrofa, is a widespread and abundant invasive species in Australia. Feral pigs pose a significant threat to the environment, agricultural industry, and human health, and in far north Queensland they endanger World Heritage values of the Wet Tropics. Historical records document the first introduction of domestic pigs into Australia via European settlers in 1788 and subsequent introductions from Asia from 1827 onwards. Since this time, domestic pigs have been accidentally and deliberately released into the wild and significant feral pig populations have become established, resulting in the declaration of this species as a class 2 pest in Queensland. The overall objective of this study was to assess the population genetic structure of feral pigs in far north Queensland, in particular to enable delineation of demographically independent management units. The identification of ecologically meaningful management units using molecular techniques can assist in targeting feral pig control to bring about effective long-term management. Molecular genetic analysis was undertaken on 434 feral pigs from 35 localities between Tully and Innisfail. Seven polymorphic and unlinked microsatellite loci were screened and fixation indices (FST and analogues) and Bayesian clustering methods were used to identify population structure and management units in the study area. Sequencing of the hyper-variable mitochondrial control region (D-loop) of 35 feral pigs was also examined to identify pig ancestry. Three management units were identified in the study at a scale of 25 to 35 km. Even with the strong pattern of genetic structure identified in the study area, some evidence of long distance dispersal and/or translocation was found as a small number of individuals exhibited ancestry from a management unit outside of which they were sampled. Overall, gene flow in the study area was found to be influenced by environmental features such as topography and land use, but no distinct or obvious natural or anthropogenic geographic barriers were identified. Furthermore, strong evidence was found for non-random mating between pigs of European and Asian breeds indicating that feral pig ancestry influences their population genetic structure. Phylogenetic analysis revealed two distinct mitochondrial DNA clades, representing Asian domestic pig breeds and European breeds. A significant finding was that pigs of Asian origin living in Innisfail and south Tully were not mating randomly with European breed pigs populating the nearby Mission Beach area. Feral pig control should be implemented in each of the management units identified in this study. The control should be coordinated across properties within each management unit to prevent re-colonisation from adjacent localities. The adjacent rainforest and National Park Estates, as well as the rainforest-crop boundary should be included in a simultaneous control operation for greater success.

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Often voltage rise along low voltage (LV) networks limits their capacity to accommodate more renewable energy (RE) sources. This paper proposes a robust and effective approach to coordinate customers' resources and control voltage rise in LV networks, where photovoltaics (PVs) are considered as the RE sources. The proposed coordination algorithm includes both localized and distributed control strategies. The localized strategy determines the value of PV inverter active and reactive power, while the distributed strategy coordinates customers' energy storage units (ESUs). To verify the effectiveness of proposed approach, a typical residential LV network is used and simulated in the PSCAD-EMTC platform.

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OBJECTIVE: To compare patellar tendon sonographic findings in active, currently asymptomatic, elite athletes with those in nonathletic controls. DESIGN: Cross-sectional cohort study with convenience control sample. SETTING: The Victorian Institute of Sport Tendon Study Group, an institutional elite athlete study group in Australia. PATIENTS AND PARTICIPANTS: Two hundred elite male and female athletes from the sports of basketball, cricket, netball, and Australian rules football. Forty athletes who had current symptoms of jumper's knee were excluded from analysis, leaving 320 subject tendons in athletes who were currently asymptomatic. Twenty-seven nonathletic individuals served as controls. MAIN OUTCOME MEASURE: Sonographic patellar tendon appearance. We measured the dimensions of subject tendons and noted the presence or absence of hypoechoic regions and tendon calcification. Dimensions of hypoechoic regions were measured, and approximate cross-sectional areas were calculated. Chi-squared analysis was used to test the prevalence of hypoechoic regions in subjects and controls and men and women. RESULTS: In currently asymptomatic subjects, hypoechoic regions were more prevalent in athlete tendons (22%) than in controls (4%), in male subject tendons (30%) than in female subjects (14%), and in basketball players (32%) than in other athletes (9%) (all p < 0.01). Bilateral tendon abnormalities were equally prevalent in men and women but more prevalent in basketball players (15%) than in other athletes (3%) (p < 0.05). Sonographic hypoechoic regions were present in 35 of 250 (14%) patellar tendons in athletes who had never had anterior knee pain. CONCLUSIONS: Patellar tendon sonographic hypoechoic areas were present in asymptomatic patellar tendons of a proportion of elite athletes but rarely present in controls. This has implications for clinicians managing athletes with anterior knee pain.

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Numerical investigation is carried out for natural convection heat transfer in an isosceles triangular enclosure partitioned in the centre by a vertical wall with infinite conductivity. A sudden temperature difference between two zones of the enclosure has been imposed to trigger the natural convection. As a result, heat is transferred between both sides of the enclosure through the conducting vertical wall with natural convection boundary layers forming adjacent to the middle partition and two inclined surfaces. The Finite Volume based software, Ansys 14.5 (Fluent) is used for the numerical simulations. The numerical results are obtained for different values of aspect ratio, A (0.2, 0.5 and 1.0) and Rayleigh number, Ra (10^5 <= Ra <= 10^8) for a fixed Prandtl number, Pr = 0.72 of air. It is anticipated from the numerical simulations that the coupled thermal boundary layers development adjacent to the partition undergoes several distinct stages including an initial stage, a transitional stage and a steady stage. Time dependent features of the coupled thermal boundary layers as well as the overall natural convection flow in the partitioned enclosure have been discussed in this study.

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Rotary ventricular assist device (VAD) support of the cardiovascular system is susceptible to suction events due to the limited preload sensitivity of these devices. This may be of particular concern with rotary biventricular support (BiVAD) where the native, flow-balancing Starling response is diminished in both ventricles. The reliability of sensor and sensor-less based control systems which aim to control VAD flow based on preload have limitations and thus an alternative solution is desired. This study introduces a compliant inflow cannula (CIC) which could improve the preload sensitivity of a rotary VAD by passively altering VAD flow depending on preload. To evaluate the design, both the CIC and a standard rigid inflow cannula were inserted into a mock circulation loop to enable biventricular heart failure support using configurations of atrial and ventricular inflow, and arterial outflow cannulation. A range of left (LVAD) and right VAD (RVAD) rotational speeds were tested as well as step changes in systemic/pulmonary vascular resistance to alter relative preloads, with resulting flow rates recorded. Simulated suction events were observed, particularly at higher VAD speeds, during support with the rigid inflow cannula, while the CIC prevented suction events under all circumstances. The compliant section passively restricted its internal diameter as preload was reduced, which increased the VAD circuit resistance and thus reduced VAD flow. Therefore, a compliant inflow cannula could potentially be used as a passive control system to prevent suction events in rotary left, right and biventricular support.