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Range (aeronautics)

About: Range (aeronautics) is a research topic. Over the lifetime, 7268 publications have been published within this topic receiving 67495 citations. The topic is also known as: autonomy.


Papers
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Journal ArticleDOI
01 Dec 2001
TL;DR: Promising applications for fuel cells include portable power, transportation, building cogeneration, and distributed power for utilities, which appear poised to meet the power needs of a variety of applications.
Abstract: At the beginning of the 21st century, fuel cells appear poised to meet the power needs of a variety of applications. Fuel cells are electrochemical devices that convert chemical energy to electricity and thermal energy. Fuel cell systems are available to meet the needs of applications ranging from portable electronics to utility power plants. In addition to the fuel cell stack itself, a fuel cell system includes a fuel processor and subsystems to manage air, water thermal energy, and power. The overall system is efficient at full and part-load, scaleable to a wide range of sizes, environmentally friendly, and potentially competitive with conventional technology in first cost. Promising applications for fuel cells include portable power, transportation, building cogeneration, and distributed power for utilities. For portable power a fuel cell coupled with a fuel container can offer a higher energy storage density and more convenience than conventional battery systems. In transportation applications, fuel cells offer higher efficiency and better part-load performance than conventional engines. In stationary power applications, low emissions permit fuel cells to be located in high power density areas where they can supplement the existing utility grid. Furthermore, fuel cell systems can be directly connected to a building to provide both power and heat with cogeneration efficiencies as high as 80%.

447 citations

Journal ArticleDOI
TL;DR: The total energy cost of migration is roughly divided between flight and stopover as 1:2, probably with a relatively longer stopover time in larger species and strong selection pressures to optimize the fuel accumulation strategies during stopover episodes are expected.

415 citations

Journal ArticleDOI
TL;DR: In this paper, a study was conducted to determine how demand for clean-fuel vehicles and their fuel is likely to vary as a function of attributes that distinguish these vehicles from conventional gasoline vehicles.
Abstract: A study was conducted to determine how demand for clean-fuel vehicles and their fuel is likely to vary as a function of attributes that distinguish these vehicles from conventional gasoline vehicles. For the purposes of the study, clean-fuel vehicles are defined to encompass both electric vehicles and unspecified (methanol, ethanol, compressed natural gas or propane) liquid and gaseous fuel vehicles, in both dedicated or multiple-fuel versions. The attributes include vehicle purchase price, fuel operating cost, vehicle range between refueling, availability of fuel, dedicated versus multiple-fuel capability and the level of reduction in emissions (compared to current vehicles). In a mail-back stated preference survey, approximately 700 respondents in the California South Coast Air Basin gave their choices among sets of hypothetical future vehicles, as well as their choices between alternative fuel versus gasoline for hypothetical multiple-fuel vehicles. Estimates of attribute importance and segment differences are made using discrete-choice nested multinomial logit models for vehicle choice and binomial logit models for fuel choice. These estimates can be used to modify present vehicle-type choice and utilization models to accomodate clean-fuel vehicles; they can also be used to evaluate scenarios for alternative clean-fuel vehicle and fuel supply configurations. Results indicate that range between refueling is an important attribute, particularly if range for an alternative fuel is substantially less than that for gasoline. For fuel choice, the most important attributes are range and fuel cost, but the predicted probability of choosing alternative fuel is also affected by emissions levels, which can compensate for differences in fuel prices.

371 citations

Journal ArticleDOI
03 Apr 2008-Ibis
TL;DR: A theory is presented for calculating the relation between mechanical power required to fly and forward speed, for a bird flying horizontally, and the significance of this for migration is explained, and quick methods are given for calculating key points on the curve.
Abstract: Summary A theory is presented for calculating the relation between mechanical power required to fly and forward speed, for a bird flying horizontally. The significance of this for migration is explained, and quick methods are given (and summarized in the Appendix) for calculating key points on the curve. Speed ranges and effective lift: drag ratios are calculated for a number of different flying animals. Factors affecting migration range are discussed, and the effects of head- and tailwinds are considered. Still-air range depends on effective lift: drag ratio, but not on size or weight as such. The relation of power required to that available from the muscles is considered. Small birds have a greater margin of power available over power required than large ones, and tend to run their flight muscles at a lower stress, or lower specific shortening, or both. There is an upper limit to the mass of practicable flying birds, represented approximately by the Kori Bustard Ardeotit kori. The effect of adding extra weight (food or fuel) is to increase both minimum-power speed, and maximum-range speed, in proportion to the square root of the weight, and to increase the corresponding powers in proportion to the three-halves power of the weight. Birds up to about 750 g (fat-free) can double their fat-free mass, and still have sufficient power to fly at the maximum-range speed. Larger birds are progressively more severely limited in the maximum loads they can carry, and this reduces their range. Many large birds migrate by thermal soaring, thus economizing on fuel at the expense of making slower progress. During a long flight both speed and power have to be progressively reduced as fuel is used up. A formula is given for calculating the still-air range of a bird which does this in an optimal fashion. The only data required are the effective lift: drag ratio, and the proportion of the take-off mass devoted to fuel. Increase of height has no effect on the still-air range, but the optimum cruising speed (and power) is increased. The optimum cruising height is reached when the bird can absorb oxygen just fast enough to maintain the required power. The optimum height increases progressively as fuel is used up. No range is lost as a result of the work done in climbing to the cruising height.

353 citations

Book
01 Jan 2006
TL;DR: Tischler and Remple as discussed by the authors presented proven methods, practical guidelines, and real-world flight-test results for a wide range of state-of-the-art flight vehicles, addressing the entire process of aircraft and rotorcraft system identification from instrumentation and flight testing to model determination, validation and application of the results.
Abstract: Presenting proven methods, practical guidelines, and real-world flight-test results for a wide range of state-of-the-art flight vehicles, "Aircraft and Rotorcraft System Identification, Second Edition" addresses the entire process of aircraft and rotorcraft system identification from instrumentation and flight testing to model determination, validation, and application of the results. In this highly anticipated second edition, authors Tischler and Remple have added dedicated in-depth chapters presenting extended model structures and identification results for large flexible transport aircraft, and the detailed methodology to develop a continuous full flight envelope simulation model from individual system identification models and trim test data. Topics Discussed include: Frequency-response methods that are especially well suited for system identification of flight vehicle models from flight-test data; specific guidelines for flight testing, data analysis, and the proper selection of model structure complexity; and emphasis on the importance of physical insight in model development and applications. Special features: student version of CIFER[registered] with updated graphical user interface using MATLAB[registered]; numerous flight-test results for both manned and unmanned vehicles illustrating the wide-ranging roles of system identification, including the analysis of flight mechanics, feedback control, handling qualities, subsystem dynamics, structural analysis, higher-order models for aircraft and rotorcraft, and simulation; and, extensive problem sets at the end of each chapter, with many exercises based on flight-test data provided for the XV-15 in hover and cruise giving the reader hands-on real-world experience with system identification methods and interpretation of the results.

339 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
20243
20236,437
202212,746
2021419
2020317
2019294