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The purpose of this paper is to calculate the fuel consumption and emissions of carbon monoxide (CO), nitrogen oxide (NO_x) and hydrocarbons (HC) in the taxi-out period of aircraft at the International Diyarbakir Airport in 2018 and 2019.

Calculations were performed by determining the engine operating times in the taxi-out period with the flight data obtained from the airport authority. In the analyses, aircraft series and aircraft engine types were determined, and the Engine Exhaust Emission Databank of the International Civil Aviation Authority (ICAO) were used for the calculation.

Total fuel consumption in the taxi-out period in 2018 and 2019 was calculated as 525.64 and 463.69 tons, respectively. In 2018, HC, CO and NO_x emissions caused by fuel consumption were found to be 1,109, 10,668 and 2,339 kg, respectively. In 2019, the total HC, CO and NO_x emissions released to the atmosphere during the taxi-out phase are 966, 9,391 and 2,126 kg, respectively. B737 Series aircraft have the largest share in total fuel consumption and pollutant emissions.

This study explains the importance of determining fuel consumption and pollutant emissions by considering engine operating times in the taxi-out period. The study provides aviation authorities with scientific methods to follow in calculating fuel consumption and emissions from aircraft operations.

The originality of this study is the calculation of fuel consumption and pollutant emissions by determining real-time engine running times in the taxi-out period. In addition, calculations were made with real engine operating times determined in the taxi-out period using real flight data.

Performance differences between the aircraft types are natural and they inevitably cause problems in the air traffic system, particularly when slower aircraft types are followed by faster types in a climb or cruise queue. This paper presents the excess fuel consumption impact of aircraft performance differences in the air traffic environment. For this purpose, both climb and cruise phases of a flight mission are analyzed. Revision of the airworthiness regulations and air traffic procedures are suggested. The need for a flight level – cruise performance categorization is also recommended.

Reducing aircraft fuel consumption has become a paramount research area, focusing on optimizing operational parameters like speed and altitude during the cruise phase. However, the existing methods for fuel reduction often rely on complex experimental calculations and data extraction from embedded systems, making practical implementation challenging. To address this, this study aims to devise a simple and accessible approach using available information.

In this paper, a novel analytic method to estimate and optimize fuel consumption for aircraft equipped with jet engines is proposed, with a particular emphasis on speed and altitude parameters. The dynamic variations in weight caused by fuel consumption during flight are also accounted for. The derived fuel consumption equation was rigorously validated by applying it to the Boeing 737–700 and comparing the results against the fuel consumption reference tables provided in the Boeing manual. Remarkably, the equation yielded closely aligned outcomes across various altitudes studied. In the second part of this paper, a pioneering approach is introduced by leveraging the particle swarm optimization algorithm (PSO). This novel application of PSO allows us to explore the equation’s potential in finding the optimal altitude and speed for an actual flight from Algiers to Brussels.

The results demonstrate that using the main findings of this study, including the innovative equation and the application of PSO, significantly simplifies and expedites the process of determining the ideal parameters, showcasing the practical applicability of the approach.

The suggested methodology stands out for its simplicity and practicality, particularly when compared to alternative approaches, owing to the ready availability of data for utilization. Nevertheless, its applicability is limited in scenarios where zero wind effects are a prevailing factor.

The research opens up new possibilities for fuel-efficient aviation, with a particular focus on the development of a unique fuel consumption equation and the pioneering use of the PSO algorithm for optimizing flight parameters. This study’s accessible approach can pave the way for more environmentally conscious and economical flight operations.

This research is associated with the real-time parameters of wide- and narrow-body aircraft to recognize the quantitative relationship framework. This paper aims to find the superiority of aircraft design technology which triggers the reduction in specific fuel consumption (SFC) and economic competitiveness.

The real case study is performed with 22 middle-of-the-market (MoM) aircraft. This paper develops a fuel burn mathematical model for mid-size transport aircraft by a multi-linear regression approach. In addition, sensitivity analysis is performed to establish the authentication of the fuel burn model.

The study reveals that the MoM aircraft would be the future aircraft design in terms of better fuel economy and carbon footprint. From the multi-regression analysis, it is observed that the logarithmic regression model is the best fit for estimating the SFC. Moreover, fineness ratio, aspect ratio, gross weight, payload weight fraction, empty weight fraction), fuel weight fraction, payload, wing loading, thrust loading, range, take-off distance, cruise speed and rate of climb are observed as the suitable parameters which provide the best fitness value as 0.9804.

Several existing literature reveals that a few research has been performed on the MoM aircraft with wide-body configuration. Moreover, mathematical modelling on the fuel consumption was insignificantly found. This study examines several parameters which affect the fuel consumption of a wide-body aircraft. A real-case study for design configurations, propulsive systems, performance characteristics and structural integrity parameters of 22 different MoM aircraft are performed. Moreover, multi-regression modelling is developed to establish the relation between SFC and other critical parameters.

This paper aims to minimize aircraft fuel consumption during the cruise phase when the flight is subjected to a specific time of arrival for different weights and distances.

The approach adopted herein uses sequential quadratic programming algorithm from MATLAB optimization toolbox, which includes a mathematical model of a jet airliner based on the Base of Aircraft Data as a function evaluator, to find out the impact of meet-time of arrival constraints on fuel consumption. The cruising speeds at predefined segments and the altitude are defined as the design variables.

The algorithm determines the optimum cruise altitudes and speeds for minimum fuel consumption in the case of no time constraints, also, for different time constraints where the flight time shall be reduced by increasing speed and lowering the altitude in most of the investigated cases.

The algorithm computes the optimum speed and the altitude according to different flight scenarios with the meet-time of arrival constraints for minimum fuel consumption which affects the direct operating cost of the flight. The algorithm might greatly help in decision-making for the meet-time of arrival operations.

Developing an algorithm to optimize the speed and the altitude of an aircraft based on weight and range for minimization of fuel consumption. It is a pioneer study in the literature that deals with the effect of meet-time constraints on fuel consumption.

The purpose of this paper is to create a new fuel flow rate model for the descent phase of the flight using particle swarm optimization (PSO).

A new fuel flow rate model was developed for the descent phase of the B737-800 aircraft, which is frequently used in commercial air transport using PSO method. For the analysis, the actual flight data records (FDRs) data containing the fuel flow rate, speed, altitude, engine speed, time and many more data were used. In this regard, an empirical formula has been created that gives real fuel flow rate values as a function of altitude and true airspeed. In addition, in the fuel flow rate predictions made for the descent phase of the specified aircraft, a different model has been created that can be used without any optimization process when FDR data are not available for a specific aircraft take-off weight condition.

The error analysis applied to the models showed that both models predict real fuel flow rate values with high precision.

Because of the high accuracy of the PSO model, it is thought to be useful in air traffic management, decision support systems, models used for trajectory prediction, aircraft performance models, strategies used to reduce fuel consumption and emissions because of fuel consumption.

This study is the first fuel flow rate model for descent flight using PSO algorithm. The use of real FDR data in the analysis shows the originality of this study.

In this paper, with the goal of reducing the fuel consumption of UAV, the engine performance optimization is studied and on the basis of aircraft/engine integrated control, the minimum fuel consumption optimization method of engine given thrust is proposed. In the case of keeping the given thrust of the engine unchanged, the main fuel flow of the engine without being connected to the afterburner is optimally controlled so as to minimize the fuel consumption.

In this study, the reference model real-time optimization control method is adopted. The engine reference model uses a nonlinear real-time mathematical model of a certain engine component method. The quasi-Newton method is adopted in the optimization algorithm. According to the optimization variable nozzle area, the turbine drop-pressure ratio corresponding to the optimized nozzle area is calculated, which is superimposed with the difference of the drop-pressure ratio of the conventional control plan and output to the conventional nozzle controller of the engine. The nozzle area is controlled by the conventional nozzle controller.

The engine real-time minimum fuel consumption optimization control method studied in this study can significantly reduce the engine fuel consumption rate under a given thrust. At the work point, this is a low-altitude large Mach work point, which is relatively close to the edge of the flight envelope. Before turning on the optimization controller, the fuel consumption is 0.8124 kg/s. After turning on the optimization controller, you can see that the fuel supply has decreased by about 4%. At this time, the speed of the high-pressure rotor is about 94% and the temperature after the turbine can remain stable all the time.

The optimal control method of minimum fuel consumption for the given thrust of UAV is proposed in this paper and the optimal control is carried out for the nozzle area of the engine. At the same time, a method is proposed to indirectly control the nozzle area by changing the turbine pressure ratio. The relevant UAV and its power plant designers and developers may consider the results of this study to reach a feasible solution to reduce the fuel consumption of UAV.

Fuel consumption optimization can save fuel consumption during aircraft cruising, increase the economy of commercial aircraft and improve the combat radius of military aircraft. With the increasingly wide application of UAVs in military and civilian fields, the demand for energy-saving and emission reduction will promote the UAV industry to improve the awareness of environmental protection and reduce the cost of UAV use and operation.

In the aerial transportation area, fuel costs are critical to the economic viability of companies, and so urgent measures should be adopted to avoid any unnecessary increase in operational costs. In particular, this paper addresses the case of missed approach manouevres, showing that it is still possible to optimize the usual procedure.

The costs involved in a standard procedure following a missed approach are analysed through a simulation model, and they are compared with the improvements achieved with a fast reinjection scheme proposed in a prior work.

Experimental results show that, for a standard A320 aircraft, fuel savings ranging from 55% to 90% can be achieved through the reinjection method.

To the best of the authors’ knowledge, this work is the first study in the literature addressing the fuel savings benefits obtained by applying a reinjection technique for missed approach manoeuvres.

Metroplex is a system of two or more airports, in physical proximity, with highly interdependent arrival and departure operations. The purpose of this study is the construction of an efficient and effective air route model based on the point merge system (PMS) to reduce aircraft fuel consumption and CO₂ emissions for three metroplex airports in Istanbul terminal control area (TMA).

A PMS arrival route model is constructed for metroplex airports. In the proposed model, two situations are taken into consideration: for delay which can be defined as flying on sequencing legs (PMS_del) and for no delay (PMS_{no del}). An empirical model is developed using a data set including the flight data records of ten actual B737-800 domestic flights. With this empirical model, both the baseline and the PMS models (PMS_del and PMS_{no del}) are compared in terms of fuel consumption, CO₂ emissions and flight distance and time as a theoretical computation.

In the proposed PMS_{no del} arrival route model, according to different entry points for Istanbul Ataturk International Airport (LTBA), the analyses show an average reduction of 26 per cent in flight time, 24.5 per cent in flight distance, 17 per cent in fuel burned and CO₂ emissions; in addition, for Sabiha Gökcen International Airport (LTFJ) there are 34, 23 and 32 per cent average savings for flight time, flight distance and fuel burned together with CO₂ emissions obtained, respectively. Even if the PMS_del model, for LTFJ except only one entry point, for LTBA except two entry points, better results are obtained than baseline.

The point merge model for metroplex airports in this paper can be applied by airspace designers and Air Navigation Service Providers to perform efficient and effective arrival routes.

In this study, a point merge model is constructed for metroplex airports. Quantitative results, using an empirical model, are achieved in terms of fuel consumption, CO₂ emissions and flight distance and time at metroplex airports.

This paper aims to assess the impact of electrifying the environmental control system (ECS) and ice protection system (IPS), the primary pneumatic system consumers in a conventional commercial transport aircraft, on aircraft weight, range, and fuel consumption.

The case study was carried out on Airbus A321-200 aircraft. Design, modelling and analysis processes were carried out on Pacelab SysArc software. Conventional and electrical ECS and IPS architectures were modelled and analysed considering different temperature profiles.

The simulation results have shown that the aircraft model with ±270 VDC ECS and IPS architecture is lighter, has a more extended range and has less relative fuel consumption. In addition, the simulation results showed that the maximum range and relative fuel economy of all three aircraft models increased slightly as the temperature increased.

Considering the findings in this paper, it is seen that the electrification of the conventional pneumatic system in aircraft has positive contributions in terms of weight, power consumption and fuel consumption.

The positive contributions in terms of weight, power consumption and fuel consumption in aircraft will be direct environmental and economic contributions.

Apart from the conventional ECS and IPS of the aircraft, two electrical architectures, 230 VAC and ±270 VDC, were modelled and analysed. To see the effects of the three models created in different temperature profiles, analyses were done for cold day, ISA standard day and hot day temperature profiles.