992 resultados para Wind Patterns
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Buffeting response of a cable-stayed bridge under construction is investigated through wind tunnel tests and numerical simulations. Two configurations of the erection stage have been considered and compared in terms of dynamic response and internal forces using the results of the experimental aeroelastic models. Moreover the results of a numerical model able to simulate the simultaneous effects of vortex shedding from tower and aeroelastic response of the deck are compared to the wind tunnel ones.
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The integration of large amount of wind power into a power system imposes a new challenge for the secure and economic operation of the system. It is necessary to investigate the impacts of wind power generation on the dynamic behavior of the power system concerned. This paper investigates the impacts of large amount of wind power on small signal stability and the corresponding control strategies to mitigate the negative effects. The concepts of different types of wind turbine generators (WTGs) and the principles of the grid-connected structures of wind power generation systems are first briefly introduced. Then, the state-of-the-art of the studies on the impacts of WTGs on small signal stability as well as potential problems to be studied are clarified. Finally, the control strategies on WTGs to enhance power system damping characteristics are presented.
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With the ever-increasing penetration level of wind power, the impacts of wind power on the power system are becoming more and more significant. Hence, it is necessary to systematically examine its impacts on the small signal stability and transient stability in order to find out countermeasures. As such, a comprehensive study is carried out to compare the dynamic performances of power system respectively with three widely-used power generators. First, the dynamic models are described for three types of wind power generators, i. e. the squirrel cage induction generator (SCIG), doubly fed induction generator (DFIG) and permanent magnet generator (PMG). Then, the impacts of these wind power generators on the small signal stability and transient stability are compared with that of a substituted synchronous generator (SG) in the WSCC three-machine nine-bus system by the eigenvalue analysis and dynamic time-domain simulations. Simulation results show that the impacts of different wind power generators are different under small and large disturbances.
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OBJECTIVE The aim of the study is to examine the spatiotemporal pattern of Japanese Encephalitis (JE) in mainland China during 2002-2010. Specific objectives of the study were to quantify the temporal variation in incidence of JE cases, to determine if clustering of JE cases exists, to detect high risk spatiotemporal clusters of JE cases and to provide evidence-based preventive suggestions to relevant stakeholders. METHODS Monthly JE cases at the county level in mainland China during 2002-2010 were obtained from the China Information System for Diseases Control and Prevention (CISDCP). For the purpose of the analysis, JE case counts for nine years were aggregated into four temporal periods (2002; 2003-2005; 2006; and 2007-2010). Local Indicators of Spatial Association and spatial scan statistics were performed to detect and evaluate local high risk space-time clusters. RESULTS JE incidence showed a decreasing trend from 2002 to 2005 but peaked in 2006, then fluctuated over the study period. Spatial cluster analysis detected high value clusters, mainly located in Southwestern China. Similarly, we identified a primary spatiotemporal cluster of JE in Southwestern China between July and August, with the geographical range of JE transmission increasing over the past years. CONCLUSION JE in China is geographically clustered and its spatial extent dynamically changed during the last nine years in mainland China. This indicates that risk factors for JE infection are likely to be spatially heterogeneous. The results may assist national and local health authorities in the development/refinement of a better preventive strategy and increase the effectiveness of public health interventions against JE transmission.
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OBJECTIVES To identify the meteorological drivers of dengue vector density and determine high- and low-risk transmission zones for dengue prevention and control in Cairns, Australia. METHODS Weekly adult female Ae. aegypti data were obtained from 79 double sticky ovitraps (SOs) located in Cairns for the period September 2007-May 2012. Maximum temperature, total rainfall and average relative humidity data were obtained from the Australian Bureau of Meteorology for the study period. Time series-distributed lag nonlinear models were used to assess the relationship between meteorological variables and vector density. Spatial autocorrelation was assessed via semivariography, and ordinary kriging was undertaken to predict vector density in Cairns. RESULTS Ae. aegypti density was associated with temperature and rainfall. However, these relationships differed between short (0-6 weeks) and long (0-30 weeks) lag periods. Semivariograms showed that vector distributions were spatially autocorrelated in September 2007-May 2008 and January 2009-May 2009, and vector density maps identified high transmission zones in the most populated parts of Cairns city, as well as Machans Beach. CONCLUSION Spatiotemporal patterns of Ae. aegypti in Cairns are complex, showing spatial autocorrelation and associations with temperature and rainfall. Sticky ovitraps should be placed no more than 1.2 km apart to ensure entomological coverage and efficient use of resources. Vector density maps provide evidence for the targeting of prevention and control activities. Further research is needed to explore the possibility of developing an early warning system of dengue based on meteorological and environmental factors.
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Malaria has been a heavy social and health burden in the remote and poor areas in southern China. Analyses of malaria epidemic patterns can uncover important features of malaria transmission. This study identified spatial clusters, seasonal patterns, and geographic variations of malaria deaths at a county level in Yunnan, China, during 1991–2010. A discrete Poisson model was used to identify purely spatial clusters of malaria deaths. Logistic regression analysis was performed to detect changes in geographic patterns. The results show that malaria mortality had declined in Yunnan over the study period and the most likely spatial clusters (relative risk [RR] = 23.03–32.06, P < 0.001) of malaria deaths were identified in western Yunnan along the China–Myanmar border. The highest risk of malaria deaths occurred in autumn (RR = 58.91, P < 0.001) and summer (RR = 31.91, P < 0.001). The results suggested that the geographic distribution of malaria deaths was significantly changed with longitude, which indicated there was decreased mortality of malaria in eastern areas over the last two decades, although there was no significant change in latitude during the same period. Public health interventions should target populations in western Yunnan along border areas, especially focusing on floating populations crossing international borders.
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BACKGROUND Pandemic influenza A (H1N1) has a significant public health impact. This study aimed to examine the effect of socio-ecological factors on the transmission of H1N1 in Brisbane, Australia. METHODOLOGY We obtained data from Queensland Health on numbers of laboratory-confirmed daily H1N1 in Brisbane by statistical local areas (SLA) in 2009. Data on weather and socio-economic index were obtained from the Australian Bureau of Meteorology and the Australian Bureau of Statistics, respectively. A Bayesian spatial conditional autoregressive (CAR) model was used to quantify the relationship between variation of H1N1 and independent factors and to determine its spatiotemporal patterns. RESULTS Our results show that average increase in weekly H1N1 cases were 45.04% (95% credible interval (CrI): 42.63-47.43%) and 23.20% (95% CrI: 16.10-32.67%), for a 1 °C decrease in average weekly maximum temperature at a lag of one week and a 10mm decrease in average weekly rainfall at a lag of one week, respectively. An interactive effect between temperature and rainfall on H1N1 incidence was found (changes: 0.71%; 95% CrI: 0.48-0.98%). The auto-regression term was significantly associated with H1N1 transmission (changes: 2.5%; 95% CrI: 1.39-3.72). No significant association between socio-economic indexes for areas (SEIFA) and H1N1 was observed at SLA level. CONCLUSIONS Our results demonstrate that average weekly temperature at lag of one week and rainfall at lag of one week were substantially associated with H1N1 incidence at a SLA level. The ecological factors seemed to have played an important role in H1N1 transmission cycles in Brisbane, Australia.
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OBJECTIVE: To evaluate patterns of physical activity (PA), the prevalence of physical inactivity and the relationships between PA and sociodemographic, clinical and biochemical parameters among Sri Lankan adults. DESIGN: Descriptive cross-sectional study. SETTING: Nationally representative population-based survey conducted in Sri Lanka. SUBJECTS: Data on PA and associated details were obtained from 5000 adults. PA was assessed using the International Physical Activity Questionnaire (short-form). A binary logistic regression analysis was performed using the dichotomous variable ‘health-enhancing PA’ (05‘active’, 15‘inactive’). RESULTS: Sample size was 4485. Mean age was 46.1 (SD 15.1) years, 39.5% were males. The mean weekly total MET (metabolic equivalents of task) minutes of PA among the study population was 4703 (SD 4369). Males (5464 (SD 5452)) had a significantly higher weekly total MET minutes than females (4205 (SD 3394); P,0.001). Rural adults (5175 (SD 4583)) were significantly more active than urban adults (2956 (SD 2847); P<0.001). Tamils had the highest mean weekly total MET minutes among ethnicities. Those with tertiary education had lowest mean weekly total MET minutes. In all adults 60.0% were in the ‘highly active’ category, while only 11.0% were ‘inactive’ (males 14.6%, females 8.7%; P<0.001). Of the ‘highly active’ adults, 85.8% were residing in rural areas. Results of the binary logistic regression analysis indicated that female gender (OR52?1), age .70 years (OR53.8), urban living (OR52.5), Muslim ethnicity (OR52.7), tertiary education (OR53.6), obesity (OR51.8), diabetes (OR51.6), hypertension (OR51.2) and metabolic syndrome (OR51.3) were all associated with significantly increased odds of being physically ‘inactive’. CONCLUSIONS: The majority of Sri Lankan adults were ‘highly active’ physically. Female gender, older age, urban living, Muslim ethnicity and tertiary education were all significant predictors of physical inactivity. Physical inactivity was associated with obesity, diabetes, hypertension and metabolic syndrome.
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In policy circles, transit oriented development (TOD) is believed to enhance social capital, however empirical evidence of this relationship is lacking. This research compares levels of social capital between TOD vs. non-TOD areas in Brisbane, Australia. Using a Two Step cluster analysis technique, three types of neighbourhood groupings were identified based on net employment density, net residential density, land use diversity, intersection density, and public transport accessibility: TODs, transit adjacent development (TADs) and traditional suburbs. Two dimensions of social capital were measured (trust and reciprocity, connections with neighbours) based on factor analysis of eight items representing elements of social capital. Multivariate regression analyses were conducted to identify links between the distributions of the dimensions of social capital on areas defined as TODs, TADs, and traditional suburbs controlling for socio-demographics and environmental factors. Results show that individuals living in TODs had a significantly higher level of trust and reciprocity and connections with neighbours compared with residents of TADs. It appears that TODs may foster the development of social sustainability.
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It has become more and more demanding to investigate the impacts of wind farms on power system operation as ever-increasing penetration levels of wind power have the potential to bring about a series of dynamic stability problems for power systems. This paper undertakes such an investigation through investigating the small signal and transient stabilities of power systems that are separately integrated with three types of wind turbine generators (WTGs), namely the squirrel cage induction generator (SCIG), the doubly fed induction generator (DFIG), and the permanent magnet generator (PMG). To examine the effects of these WTGs on a power system with regard to its stability under different operating conditions, a selected synchronous generator (SG) of the well-known Western Electricity Coordinating Council (WECC three-unit nine-bus system and an eight-unit 24-bus system is replaced in turn by each type of WTG with the same capacity. The performances of the power system in response to the disturbances are then systematically compared. Specifically, the following comparisons are undertaken: (1) performances of the power system before and after the integration of the WTGs; and (2) performances of the power system and the associated consequences when the SCIG, DFIG, or PMG are separately connected to the system. These stability case studies utilize both eigenvalue analysis and dynamic time-domain simulation methods.
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Wind power is one of the world's major renewable energy sources, and its utilization provides an important contribution in helping solve the energy problems of many countries. After nearly 40 years of development, China's wind power industry now not only manufactures its own massive six MW turbines but also has the largest capacity in the world with a national output of 50 million MW•h in 2010 and set to rise by eight times of that amount by 2020. This paper investigates this development route by analyzing relevant academic literature, statistics, laws and regulations, policies and research and industry reports. The main drivers of the development in the industry are identified as technologies, turbines, wind farm construction, pricing mechanism and government support systems, each of which is also divided into different stages with distinctive features. A systematic review of these aspects provides academics and practitioners with a better understanding of the history of the wind power industry in China and reasons for its rapid development with a view to enhancing progress in wind power development both in China and the world generally.
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Low speed rotating machines which are the most critical components in drive train of wind turbines are often menaced by several technical and environmental defects. These factors contribute to mount the economic requirement for Health Monitoring and Condition Monitoring of the systems. When a defect is happened in such system result in reduced energy loss rates from related process and due to it Condition Monitoring techniques that detecting energy loss are very difficult if not possible to use. However, in the case of Acoustic Emission (AE) technique this issue is partly overcome and is well suited for detecting very small energy release rates. Acoustic Emission (AE) as a technique is more than 50 years old and in this new technology the sounds associated with the failure of materials were detected. Acoustic wave is a non-stationary signal which can discover elastic stress waves in a failure component, capable of online monitoring, and is very sensitive to the fault diagnosis. In this paper the history and background of discovering and developing AE is discussed, different ages of developing AE which include Age of Enlightenment (1950-1967), Golden Age of AE (1967-1980), Period of Transition (1980-Present). In the next section the application of AE condition monitoring in machinery process and various systems that applied AE technique in their health monitoring is discussed. In the end an experimental result is proposed by QUT test rig which an outer race bearing fault was simulated to depict the sensitivity of AE for detecting incipient faults in low speed high frequency machine.
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Objective This article explores patterns of terrorist activity over the period from 2000 through 2010 across three target countries: Indonesia, the Philippines and Thailand. Methods We use self-exciting point process models to create interpretable and replicable metrics for three key terrorism concepts: risk, resilience and volatility, as defined in the context of terrorist activity. Results Analysis of the data shows significant and important differences in the risk, volatility and resilience metrics over time across the three countries. For the three countries analysed, we show that risk varied on a scale from 0.005 to 1.61 “expected terrorist attacks per day”, volatility ranged from 0.820 to 0.994 “additional attacks caused by each attack”, and resilience, as measured by the number of days until risk subsides to a pre-attack level, ranged from 19 to 39 days. We find that of the three countries, Indonesia had the lowest average risk and volatility, and the highest level of resilience, indicative of the relatively sporadic nature of terrorist activity in Indonesia. The high terrorism risk and low resilience in the Philippines was a function of the more intense, less clustered pattern of terrorism than what was evident in Indonesia. Conclusions Mathematical models hold great promise for creating replicable, reliable and interpretable “metrics” to key terrorism concepts such as risk, resilience and volatility.
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This Arts Based Education Research (Eisner 2008) work provides potent opportunity to consider different problems and challenges that impact on the progress of research (art as data making) and the theories being explored. It provides opportunity to transport ideas across between research activity, and teaching practices...