10th AIAA Aviation Technology, Integration, and Operations (ATIO) Conference 2010
DOI: 10.2514/6.2010-9139
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Aircraft Trajectory Optimization and Contrails Avoidance in the Presence of Winds

Abstract: There are indications that persistent contrails can lead to adverse climate change, although the complete effect on climate forcing is still uncertain. A flight trajectory optimization algorithm with fuel and contrails models, which develops alternative flight paths, provides policy makers the necessary data to make tradeoffs between persistent contrails mitigation and aircraft fuel consumption. This study develops an algorithm that calculates wind-optimal trajectories for cruising aircraft while avoiding the … Show more

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Cited by 23 publications
(31 citation statements)
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“…The wind derivatives are not approximated as they are assumed to be calculated by Eq. (2). Replacing all the other derivative terms with their approximations and rearranging the equations such that they are in form of f(x) = 0 yields the following algebraic equations.…”
Section: Discretized Dynamics Model For Input Predictionmentioning
confidence: 99%
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“…The wind derivatives are not approximated as they are assumed to be calculated by Eq. (2). Replacing all the other derivative terms with their approximations and rearranging the equations such that they are in form of f(x) = 0 yields the following algebraic equations.…”
Section: Discretized Dynamics Model For Input Predictionmentioning
confidence: 99%
“…For example, wind can be utilized to fly through optimal trajectories to save time or/and fuel. 2 Wind is also used for soaring by extracting energy in the form of airspeed or altitude gain. 3 Thus, whether detrimental or beneficial, information about the wind aircraft is exposed to is important to know.…”
Section: Introductionmentioning
confidence: 99%
“…Assign as t b Recalculate the input/control variables based-on intent information Propagate the states from t b − 1 → ∆tLH Store the result from t k → t k + ∆tLH Go to next step [2] No : Go to next step 3: End Prediction.…”
Section: Figure 2 Trajectory Prediction Process Block Diagrammentioning
confidence: 99%
“…, q, which indicates the number of the aircraft in the vicinity. [2] Read current aircraft position : x k j , y k j [3] Read ownership aircraft flight data : x k , y k , V k , µ k 2: Estimation.…”
Section: Weighted Least Square Estimation Algorithmmentioning
confidence: 99%
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