61 resultados para Hypersonic wind tunnels.


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The forecasting behavior of the high volatile and unpredictable wind power energy has always been a challenging issue in the power engineering area. In this regard, this paper proposes a new multi-objective framework based on fuzzy idea to construct optimal prediction intervals (Pis) to forecast wind power generation more sufficiently. The proposed method makes it possible to satisfy both the PI coverage probability (PICP) and PI normalized average width (PINAW), simultaneously. In order to model the stochastic and nonlinear behavior of the wind power samples, the idea of lower upper bound estimation (LUBE) method is used here. Regarding the optimization tool, an improved version of particle swam optimization (PSO) is proposed. In order to see the feasibility and satisfying performance of the proposed method, the practical data of a wind farm in Australia is used as the case study.

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Water quality monitoring and prediction are critical for ensuring the sustainability of water resources which are essential for social security, especially for countries with limited land like Singapore. For example, the Singapore government identified water as a new growth sector and committed in 2006 to invest S$ 330 million over the following five years for water research and development [1]. To investigate the water quality evolution numerically, some key water quality parameters at several discrete locations in the reservoir (e.g., dissolved oxygen, chlorophyll, and temperature) and some environmental parameters (e.g., the wind distribution above water surface, air temperature and precipitation) are used as inputs to a three-dimensional hydrodynamics-ecological model, Estuary Lake and Coastal Ocean Model - Computational Aquatic Ecosystem Dynamics Model (ELCOM-CAEDYM) [2]. Based on the calculation in the model, we can obtain the distribution of water quality in the whole reservoir. We can also study the effect of different environmental parameters on the water quality evolution, and finally predict the water quality of the reservoir with a time step of 30 seconds. In this demo, we introduce our data collection system which enables water quality studies with real-time sensor data.

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Jared Diamond asked the acclaimed evolutionary biologist Ernst Mayr (1904-2005) why Aristotle didn’t come up with the theory of evolution. Mayr’s answer was ‘Frage stellen’ which Diamond translates as ‘a way of asking questions [sic]’ (Byrne 2013). The idea that a particular way-of-asking might generate a particular way-of-knowing and, indeed, a particular branch-of-knowledge, is utterly intriguing, especially when we frame the practice of creative writing in those terms: as a way of asking questions.Drusilla Modjeska unpacks the concept of ‘temporising’ in her article ‘Writing Poppy’ (Modjeska 2002: 75). This discussion invites us to consider the generative capabilities of the temporising space – as an imaginative space for writers, as an alternate way of asking questions … of seeing, being, knowing. In narrative, the questions that underpin the work do not necessarily appear in the surface-content of the text. In this way, the story is a metaphorical representation of the questions that lie beneath. As Aristotle suggests, metaphor relies on ‘an intuitive perception of the similarity [to homoion theorein] in dissimilars’ (Ricoeur 1977: 23). In narrative we contemplate a question, or an idea, within the context of a metaphorical other. This is a form of temporising: of ‘slip[ping] into other time frames’ as a means of ‘retreat[ing] and consider[ing]’ (Modjeska 2002: 75, 76). In narrative time, we consider one thing through an alternate temporal lens. We prevaricate in otherness.Fiction-making represents a very particular way of asking questions. With reference to the process of writing the short story – ‘Everything that matters is silvery white’ – it is clear that ‘making’ narrative is a way of asking questions that is assisted by the transformative temporising space.

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'Sowing the wind' is a chapter from the novel manuscript 'The Earth does not get fat'

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We study the water quality in an urban district, where the surface wind distribution is an essential input but undergoes high spatial and temporal variations due to the impact of surrounding buildings. In this work, we develop an optimal sensor placement scheme to measure the wind distribution over a large urban reservoir using a limited number of wind sensors. Unlike existing solutions that assume Gaussian process of target phenomena, this study measures the wind that inherently exhibits strong non-Gaussian yearly distribution. By leveraging the local monsoon characteristics of wind, we segment a year into different monsoon seasons that follow a unique distribution respectively. We also use computational fluid dynamics to learn the spatial correlation of wind. The output of sensor placement is a set of the most informative locations to deploy the wind sensors, based on the readings of which we can accurately predict the wind over the entire reservoir in real time. Ten wind sensors are deployed. The in-field measurement results of more than 3 months suggest that the proposed sensor placement and spatial prediction scheme provides accurate wind measurement that outperforms the state-of-the-art Gaussian model based on interpolation-based approaches.

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Because energy reserves limit flight range, wind assistance may be of crucial importance for migratory birds. We tracked eight Bewick's swans Cygnus columbianus bewickii, using 95-g satellite transmitters with altimeters and activity sensors, during their spring migration from Denmark to northern Russia in 1996. During the 82 occasions where a swan's location was recorded in flight, average flight altitude was 165 m a.s.1. with a maximum of 759 m a.s.1., despite winds often being more favourable at higher altitudes. We also counted Bewick's swans departing from the Gulf of Finland and subsequently passing an observatory in the next major stop-over area 800 km further north in the White Sea, northern Russia, during the springs of 1994, 1995 and 1996. A comparison of these counts with wind data provided evidence for Bewick's swans using favourable changes in wind conditions to embark on migration. Changes in the numbers of birds arriving in the White Sea correlated best with favourable changes in winds in the Gulf of Finland 1 day earlier. Again, migratory volume showed a correlation with winds at low altitudes only, despite wind conditions for the swans being more favourable at high altitudes. We conclude that the relatively large Bewick's swan tends to gear its migration to wind conditions at low altitude only. We argue that Bewick's swans do not climb to high altitudes because of mechanical and physiological limitations with respect to the generation of power for flight and to avoid rapid dehydration.

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Some migratory birds refuel at stopover sites that they by-pass on the return trip. In theory, this skipping behaviour is only expected in time-selected migrants when the overflown site is of a lower quality than the departure site. We provide empirical evidence that quality differences in stopover sites are the cause for skipping in Bewick's Swans Cygnus bewickii tracked by satellite telemetry. Two and five complete tracks were recorded in spring and autunm, respectively, showing that the White Sea was visited for c. 2 weeks in spring, but by-passed (or visited for a few days at the most) in autumn. Skipping of the White Sea in autumn was predicted by a dynamic programming model which was based on calculated gain rates during stopover in the Pechora Delta and the White Sea. This prediction was not sensitive to plausible variations in gain rates. Relative to the Pechora Delta the White Sea is a poor site because a large tidal amplitude precludes foraging on the beds of the submerged macrophyte Fennel Pondweed Potamogeton pectinatus during high tide. The dynamic programming model predicted a fast autunm migration. However, the phenology of autunm arrival dates of Bewick's Swans on the wintering grounds revealed that only in three out of ten years a significant number of birds was able to reach the wintering grounds without refuelling. In the other years, unfavourable wind conditions along the Russian/Baltic part of the route prevented such non-stop migration.

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We studied the energy and protein balance of a Thrush Nightingale Luscinia luscinia, a small long-distance migrant, during repeated 12-hr long flights in a wind tunnel and during subsequent two-day fueling periods. From the energy budgets we estimated the power requirements for migratory flight in this 26 g bird at 1.91 Watts. This is low compared to flight cost estimates in birds of similar mass and with similar wing shape. This suggests that power requirements for migratory flight are lower than the power requirements for nonmigratory flight. From excreta production during flight, and nitrogen and energy balance during subsequent fueling, the dry protein proportion of stores was estimated to be around 10%. A net catabolism of protein during migratory flight along with that of fat may reflect a physiologically inevitable process, a means of providing extra water to counteract dehydration, a production of uric acid for anti-oxidative purposes, and adaptive changes in the size of flight muscles and digestive organs in the exercising animal.

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1. We studied the changes in body mass, metabolizable energy intake rate (ME) and basal metabolic rate (BMR) of a Thrush Nightingale, Luscinia luscinia, following repeated 12-h migratory flights in a wind tunnel. In total the bird flew for 176 h corresponding to 6300 km. This is the first study where the fuelling phase has been investigated in a bird migrating in captivity.

2. ME was very high, supporting earlier findings that migrating birds have among the highest intake rates known among homeotherms. ME was significantly higher the second day of fuelling, indicating a build-up of the capacity of the digestive tract during the first day of fuelling.

3. Further indications of an increase in size or activity level of metabolically active structures during fuelling come from the short-term variation in BMR, which increased over the 2-day fuelling period with more than 20%, and in almost direct proportion to body mass. However, mass-specific BMR decreased over the season.

4. The patterns of mass change, ME and BMR of our focal bird following two occasions of 12-h fasts were the same as after flights, indicating that fast and flight may involve similar physiological processes.

5. The relatively low ME the first day following a flight may be a contributing factor to the well-known pattern that migrating birds during stopover normally lose mass the first day of fuelling.

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A teal (Anas crecca) and a thrush nightingale (Luscinia luscinia) were trained to fly in the Lund wind tunnel for periods of up to 3 and 16 h respectively. Both birds flew in steady flapping flight, with such regularity that their wingbeat frequencies could be determined by viewing them through a shutter stroboscope. When flying at a constant air speed, the teal's wingbeat frequency varied with the 0.364 power of the body mass and the thrush nightingale's varied with the 0.430 power. Both exponents differed from zero, but neither differed from the predicted value (0.5) at the 1 % level of significance. The teal continued to flap steadily as the tunnel tilt angle was varied from -1° (climb) to +6° (descent), while the wingbeat frequency declined progressively by about 11%. In both birds, the plot of wingbeat frequency against air speed in level flight was U-shaped, with small but statistically significant curvature. We identified the minima of these curves with the minimum power speed (Vmp) and found that the values predicted for Vmp, using previously published default values for the required variables, were only about two-thirds of the observed minimum-frequency speeds. The discrepancy could be resolved if the body drag coefficients (CDb) of both birds were near 0.08, rather than near 0.40 as previously assumed. The previously published high values for body drag coefficients were derived from wind-tunnel measurements on frozen bird bodies, from which the wings had been removed, and had long been regarded as anomalous, as values below 0.01 are given in the engineering literature for streamlined bodies. We suggest that birds of any size that have well-streamlined bodies can achieve minimum body drag coefficients of around 0.05 if the feet can be fully retracted under the flank feathers. In such birds, field observations of flight speeds may need to be reinterpreted in the light of higher estimates of Vmp. Estimates of the effective lift:drag ratio and range can also be revised upwards. Birds that have large feet or trailing legs may have higher body drag coefficients. The original estimates of around CDb=0.4 could be correct for species, such as pelicans and large herons, that also have prominent heads. We see no evidence for any progressive reduction of body drag coefficient in the Reynolds number range covered by our experiments, that is 21600-215 000 on the basis of body cross-sectional diameter.

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Wind farms are producing a considerable portion of the world renewable energy. Since the output power of any wind farm is highly dependent on the wind speed, the power extracted from a wind park is not always a constant value. In order to have a non-disruptive supply of electricity, it is important to have a good scheduling and forecasting system for the energy output of any wind park. In this paper, a new hybrid swarm technique (HAP) is used to forecast the energy output of a real wind farm located in Binaloud, Iran. The technique consists of the hybridization of the ant colony optimization (ACO) and particle swarm optimization (PSO) which are two meta-heuristic techniques under the category of swarm intelligence. The hybridization of the two algorithms to optimize the forecasting model leads to a higher quality result with a faster convergence profile. The empirical hourly wind power output of Binaloud Wind Farm for 364 days is collected and used to train and test the prepared model. The meteorological data consisting of wind speed and ambient temperature is used as the inputs to the mathematical model. The results indicate that the proposed technique can estimate the output wind power based on the wind speed and the ambient temperature with an MAPE of 3.513%.