scholarly journals Fuel Consumption Model of the Climbing Phase of Departure Aircraft Based on Flight Data Analysis

2019 ◽  
Vol 11 (16) ◽  
pp. 4362 ◽  
Author(s):  
Zhang ◽  
Huang ◽  
Liu ◽  
Zhang
Keyword(s):  
Wind Tunnel ◽  
Fuel Consumption ◽  
Operating Cost ◽  
Fuel Load ◽  
Accurate Estimation ◽  
Flight Data ◽  
Proposed Model ◽  
Aircraft Performance ◽  
Aerodynamic Parameters ◽  
Consumption Model

Accurate estimation of the fuel consumed during aircraft operation is key for determining the fuel load, reducing the airline operating cost, and mitigating environmental impacts. Aerodynamic parameters in current fuel consumption models are obtained from a static diagram extracted from the outcomes of wind tunnel experiments. Given that these experiments are performed in a lab setting, the parameters cannot be used to estimate additional fuel consumption caused by aircraft performance degradation. In addition, wind tunnel experiment results rarely involve the influence of crosswind on fuel consumption; thus, the results could be inaccurate when compared with field data. This study focuses on the departure climbing phase of aircraft operation and proposes a new fuel consumption model. In this model, the relationships between aerodynamic parameters are extracted by fitting quick access recorder (QAR) actual flight data, and the crosswind effect is also considered. Taking QAR data from two airports in China, the accuracy of the proposed model and its transferability are demonstrated. Applying the proposed model, the fuel saving of a continuous climb operation (CCO) compared with the traditional climb operation is further quantified. Finally, how aircraft mass, climbing angle, and different aircraft models could affect the fuel consumption of the climbing phase of aircraft operation is investigated. The proposed fuel consumption model fills gaps in the existing literature, and the method can be used for developing specific fuel consumption models for more aircraft types at other airports.

Investigation on Evaluation of Terminal Departure Capacity Based on Route Intersection

2013 ◽  
Vol 655-657 ◽  
pp. 2262-2265
Author(s):  
Jian Guo Kong
Keyword(s):  
Mathematical Model ◽  
Traffic Flow ◽  
Air Traffic ◽  
Flow Management ◽  
Air Traffic Flow Management ◽  
Flight Data ◽  
Proposed Model ◽  
Combining Data ◽  
Traffic Flow Management ◽  
Airport Terminal

Air traffic flow management is the key to evaluate airspace capacity reasonably and accurately. Based on the flight features of terminal route intersection, this paper builds a mathematical model for scattered flight of departure aircraft, and then evaluates the terminal capacity based on this model. By combining data from Flight Data Recorder (FDR) and flight schedule with the model, an example-runway 02R of Guangzhou Baiyun airport terminal was given to show the effectiveness of the proposed model.

A Multidisciplinary Approach for the Comprehensive Assessment of Integrated Rotorcraft–Powerplant Systems at Mission Level

2014 ◽  
Vol 137 (1) ◽  
Author(s):  
Ioannis Goulos ◽  
Fakhre Ali ◽  
Konstantinos Tzanidakis ◽  
Vassilios Pachidis ◽  
Roberto d'Ippolito
Keyword(s):  
Environmental Impact ◽  
Fuel Consumption ◽  
Comprehensive Assessment ◽  
Pollutant Emissions ◽  
Operational Performance ◽  
Civil Aviation ◽  
Accurate Estimation ◽  
Nox Emissions ◽  
Reactor Model ◽  
Stirred Reactor

This paper presents an integrated methodology for the comprehensive assessment of combined rotorcraft–powerplant systems at mission level. Analytical evaluation of existing and conceptual designs is carried out in terms of operational performance and environmental impact. The proposed approach comprises a wide-range of individual modeling theories applicable to rotorcraft flight dynamics and gas turbine engine performance. A novel, physics-based, stirred reactor model is employed for the rapid estimation of nitrogen oxides (NOx) emissions. The individual mathematical models are implemented within an elaborate numerical procedure, solving for total mission fuel consumption and associated pollutant emissions. The combined approach is applied to the comprehensive analysis of a reference twin-engine light (TEL) aircraft modeled after the Eurocopter Bo 105 helicopter, operating on representative mission scenarios. Extensive comparisons with flight test data are carried out and presented in terms of main rotor trim control angles and power requirements, along with general flight performance charts including payload-range diagrams. Predictions of total mission fuel consumption and NOx emissions are compared with estimated values provided by the Swiss Federal Office of Civil Aviation (FOCA). Good agreement is exhibited between predictions made with the physics-based stirred reactor model and experimentally measured values of NOx emission indices. The obtained results suggest that the production rates of NOx pollutant emissions are predominantly influenced by the behavior of total air inlet pressure upstream of the combustion chamber, which is affected by the employed operational procedures and the time-dependent all-up mass (AUM) of the aircraft. It is demonstrated that accurate estimation of on-board fuel supplies ahead of flight is key to improving fuel economy as well as reducing environmental impact. The proposed methodology essentially constitutes an enabling technology for the comprehensive assessment of existing and conceptual rotorcraft–powerplant systems, in terms of operational performance and environmental impact.

A Novel Header Bits Estimation Scheme for H.264/AVC Standard

2013 ◽  
Vol 333-335 ◽  
pp. 787-790
Author(s):  
Shu Qian He ◽  
Zheng Jie Deng ◽  
Chun Shi
Keyword(s):  
Rate Control ◽  
Rate Distortion ◽  
Accurate Estimation ◽  
Rate Estimation ◽  
Proposed Model ◽  
Estimation Function ◽  
Estimation Scheme ◽  
Block Based ◽  
Coding Bits ◽  
Distortion Rate

Rate estimation is useful for many H.264/AVC applications including rate-distortion optimization (RDO) for fast mode decision and precise rate control. In this paper, we propose a new header rate prediction model and an adaptive algorithm to provide more accurate estimation of the number of total coding bits for rate control compared to previously proposed methods. The header bit rate estimation is modeled by a linear combination of the number of mode block, and the sum of absolute values of all motion vectors for each block. Based on the proposed model, a header rate estimation function is also proposed to give a more accurate rate-distortion rate control. The proposed schemes can achieve better results in rate-distortion and rate control to previously proposed approaches.

A Simplified CO2 and Fuel Consumption Model for Buses Derived from VECTO Simulations

2021 ◽  
Author(s):  
Stijn Broekaert ◽  
Evangelos Bitsanis ◽  
Georgios Fontaras
Keyword(s):  
Fuel Consumption ◽  
Consumption Model

scholarly journals A Study on Sustainable Consumption of Fuel—An Estimation Method of Aircraft

Energies ◽  
2021 ◽  
Vol 14 (22) ◽  
pp. 7559
Author(s):  
Lisha Li ◽  
Shuming Yuan ◽  
Yue Teng ◽  
Jing Shao
Keyword(s):  
Neural Network ◽  
Fuel Consumption ◽  
Influencing Factors ◽  
Carbon Emission ◽  
Estimation Method ◽  
Civil Aviation ◽  
Accurate Estimation ◽  
Low Carbon ◽  
Fuel Price ◽  
Aircraft Fuel

Though the development of China’s civil aviation and the improvement of control ability have strengthened the safety operation and support ability effectively, the airlines are under the pressure of operation costs due to the increase of aircraft fuel price. With the development of optimization controlling methods in flight management systems, it becomes increasingly challenging to cut down flight fuel consumption by control the flight status of the aircraft. Therefore, the airlines both at home and abroad mainly rely on the accurate estimation of aircraft fuel to reduce fuel consumption, and further reduce its carbon emission. The airlines have to take various potential factors into consideration and load more fuel to cope with possible negative situation during the flight. Therefore, the fuel for emergency use is called PBCF (Performance-Based Contingency Fuel). The existing PBCF forecasting method used by China Airlines is not accurate, which fails to take into account various influencing factors. This paper aims to find a method that could predict PBCF more accurately than the existing methods for China Airlines.This paper takes China Eastern Airlines as an example. The experimental data of flight fuel of China Eastern Airlines Co, Ltd. were collected to find out the relevant parameters affecting the fuel consumption, which is followed by the establishment of the LSTM neural network through the parameters and collected data. Finally, through the established neural network model, the PBCF addition required by the airline with different influencing factors is output. It can be seen from the results that the all the four models are available for the accurate prediction of fuel consumption. The amount of data of A319 is much larger than that of A320 and A330, which leads to higher accuracy of the model trained by A319. The study contributes to the calculation methods in the fuel-saving project, and helps the practitioners to learn about a particular fuel calculation method. The study brought insights for practitioners to achieve the goal of low carbon emission and further contributed to their progress towards circular economy.

scholarly journals Fuel Consumption Prediction for Construction Trucks: A Noninvasive Approach Using Dedicated Sensors and Machine Learning

2021 ◽  
Vol 6 (11) ◽  
pp. 157
Author(s):  
Gonçalo Pereira ◽  
Manuel Parente ◽  
João Moutinho ◽  
Manuel Sampaio
Keyword(s):  
Machine Learning ◽  
Fuel Consumption ◽  
Great Variability ◽  
Accurate Estimation ◽  
Estimation Model ◽  
Digital Twins ◽  
Significant Step ◽  
The Cost ◽  
Consumption Prediction ◽  
Insight Into

Decision support and optimization tools to be used in construction often require an accurate estimation of the cost variables to maximize their benefit. Heavy machinery is traditionally one of the greatest costs to consider mainly due to fuel consumption. These typically diesel-powered machines have a great variability of fuel consumption depending on the scenario of utilization. This paper describes the creation of a framework aiming to estimate the fuel consumption of construction trucks depending on the carried load, the slope, the distance, and the pavement type. Having a more accurate estimation will increase the benefit of these optimization tools. The fuel consumption estimation model was developed using Machine Learning (ML) algorithms supported by data, which were gathered through several sensors, in a specially designed datalogger with wireless communication and opportunistic synchronization, in a real context experiment. The results demonstrated the viability of the method, providing important insight into the advantages associated with the combination of sensorization and the machine learning models in a real-world construction setting. Ultimately, this study comprises a significant step towards the achievement of IoT implementation from a Construction 4.0 viewpoint, especially when considering its potential for real-time and digital twins applications.

scholarly journals Timetable Design for Urban Rail Line with Capacity Constraints

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Yu-Ting Zhu ◽  
Bao-Hua Mao ◽  
Lu Liu ◽  
Ming-Gao Li
Keyword(s):  
Solution Method ◽  
Operating Cost ◽  
Capacity Constraints ◽  
Scheduling Model ◽  
Urban Rail ◽  
Proposed Model ◽  
Rail Line ◽  
First Come First Serve ◽  
Waiting Cost ◽  
Simulation Results

To design an efficient and economical timetable for a heavily congested urban rail corridor, a scheduling model is proposed in this paper. The objective of the proposed model is to find the departure time of trains at the start terminal to minimize the system cost, which includes passenger waiting cost and operating cost. To evaluate the performance of the timetable, a simulation model is developed to simulate the detailed movements of passengers and trains with strict constraints of station and train capacities. It assumes that passengers who arrive early will have more chances to access a station and board a train. The accessing and boarding processes of passengers are all based on a first-come-first-serve basis. When a station is full, passengers unable to access must wait outside until the number of waiting passengers at platform falls below a given value. When a train is full, passengers unable to board must wait at the platform for the next train to arrive. Then, based on the simulation results, a two-stage genetic algorithm is introduced to find the best timetable. Finally, a numerical example is given to demonstrate the effectiveness of the proposed model and solution method.

scholarly journals Optimization of Aircraft Climb Trajectory considering Environmental Impact under RTA Constraints

2020 ◽  
Vol 2020 ◽  
pp. 1-17
Author(s):  
Junqiang Wan ◽  
Honghai Zhang ◽  
Fangzi Liu ◽  
Wenying Lv ◽  
Yifei Zhao
Keyword(s):  
Fuel Consumption ◽  
Greenhouse Effect ◽  
Time Window ◽  
Optimization Method ◽  
Warming Trend ◽  
Weighting Factor ◽  
Pollutant Emission ◽  
Sustainable Operation ◽  
Aircraft Performance ◽  
The Impact

In order to realize the concept of air traffic sustainable operation, taking the aircraft climbing stage as an example, firstly, we establish the vertical trajectory model of aircraft climbing, analyze the change rule of aircraft performance parameters under different indicated airspeed, and establish the RTA and RHA constraint models according to the waypoint constraints. Then, considering the fuel economy and the greenhouse effect of pollutant emission, we establish a multiobjective model of aircraft flight parameter optimization, and, based on the multiobjective genetic algorithm, we establish an optimization model. Finally, we use B737-800 aircraft to carry out simulation experiments and find that, with the change of speed, fuel consumption and warming trend are different, and “objective weight, aircraft mass, flight distance, RTA time window, and wind” have different effects on the optimization results. The results show that this optimization method has a good compromise between fuel consumption and greenhouse effect by changing the weighting factor. By optimizing the flight parameters of the aircraft, it can effectively reduce the impact on the environment and provide theoretical support for the green flight of the aircraft.

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