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
“…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.…”
This paper presents a method of input prediction for an aircraft flying in spatially and/or temporally varying wind field. Input prediction is done using inverse simulation to compute the required control variables (control surface deflections and thrust level) for an aircraft to fly through a prescribed trajectory. Various simulation cases are presented to demonstrate the feasibility of input prediction method and the importance of including wind field information in inverse simulations.
“…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.…”
This paper presents a method of input prediction for an aircraft flying in spatially and/or temporally varying wind field. Input prediction is done using inverse simulation to compute the required control variables (control surface deflections and thrust level) for an aircraft to fly through a prescribed trajectory. Various simulation cases are presented to demonstrate the feasibility of input prediction method and the importance of including wind field information in inverse simulations.
“…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%
“…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.…”
This work develops a method for onboard estimation of wind field with spatial and temporal variation based on local wind vector estimation and/or measurements from multiple aircraft flying in the same airspace. Aircraft flying in the same airspace of operation are considered airborne wind sensors scattered over the airspace because of the fact that aircraft carry along with them wind information inherent in their dynamics and kinematics. The onboard wind field estimation is formulated in the framework of parameter estimation based on various wind field models, which are different function of position and time. The online wind field estimation is utilized in trajectory prediction of aircraft flying in spatially and/or temporally varying wind. Various simulation cases are presented to demonstrate the feasibility of wind field estimation and the benefit of using such information in trajectory prediction.
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