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This paper is one of a series addressing the need for simple, yet accurate, methods for the estimation of cruise fuel burn and other important aircraft performance parameters. Here, a previously published, constant Reynolds number model for turbofan-powered, civil transport aircraft is extended to include Reynolds number effects. Provided the variation of temperature with pressure is known, the method is applicable to flight in any atmospheric conditions. For a given aircraft, cruising in a given atmosphere, there is a single Mach number and Flight Level pair, at which the fuel burn per unit distance travelled through the air has an absolute minimum value. Both these quantities depend upon the Reynolds number, which, in turn, depends upon the aircraft weight and the atmospheric vertical temperature profile. Simple, explicit expressions are developed for all parameters at the optimum condition. These are shown to be in close agreement with numerical solutions of the governing equations. It is found that typical operational mass and temperature profile variations can change cruise fuel burn rate by several percent. In the International Standard Atmosphere, when the speed and altitude deviate from their optimum values, the fuel burn penalty is reduced slightly relative to the constant Reynolds number case. By way of example, the method is used to estimate the minimum fuel, speed-versus-height trajectory for cruise in a realistic atmosphere. For each aircraft, cruise fuel burn is found to be governed by six independent parameters. All are constants. Two are simple, involving only size and weight, whereas four are complex and must be determined by either theoretical, or empirical, means. The estimation of these quantities will be considered in Part 2.

This paper presents a physics-guided deep neural network framework to estimate fuel consumption of an aircraft. The framework aims to improve data-driven models’ consistency in flight regimes that are not covered by data. In particular, we guide the neural network with the equations that represent fuel flow dynamics. In addition to the empirical error, we embed this physical knowledge as several extra loss terms. Results show that our proposed model accomplishes correct predictions on the labeled test set, as well as assuring physical consistency in unseen flight regimes. The results indicate that our model, while being applicable to the aircraft’s complete flight envelope, yields lower fuel consumption error measures compared to the model-based approaches and other supervised learning techniques utilizing the same training data sets. In addition, our deep learning model produces fuel consumption trends similar to the BADA4 aircraft performance model, which is widely utilized in real-world operations, in unseen and untrained flight regimes. In contrast, the other supervised learning techniques fail to produce meaningful results. Overall, the proposed methodology enhances the explainability of data-driven models without deteriorating accuracy.

Urban air mobility operations, such as flying Uncrewed Aerial Vehicles (UAVs) and small passenger aircraft in and around cities, will be inherently susceptible to the turbulent wind conditions in urban environments. Therefore, understanding UAM aircraft performance under microscale wind disturbances is critical. Gaining such insight is non-trivial due to the lack of sufficient UAM aircraft operational data and the complexities involved in flight testing UAM aircraft. A viable solution to overcome this hindrance is through simulation-based flight testing, data collection, and performance assessment. To support this effort, the present paper establishes a custom Stochastic microscale Wind Model (SWM) capable of efficiently generating high-resolution, spatio-temporally varying urban wind fields. The SWM is validated against wind tunnel test data, and subsequently, the findings are employed to guide targeted refinements of urban wake simulation. Furthermore, to incorporate realistic atmospheric conditions and demonstrate the ability to generate location-specific wind fields, the SWM is coupled with the mesoscale Weather Research and Forecasting (WRF) model. This integrated approach is demonstrated through a case study focused on a potential vertiport site in Milan, Italy, illustrating its utility for assessing operational area-specific UAM aircraft performance and vertiport emplacement.

A simulation-based approach for take-off and landing performance assessments is presented in this work. In the context of aircraft design loops, it provides a detailed and flexible formulation that can be integrated into a wider simulation methodology for a complete commercial aviation mission. As a matter of fact, conceptual and preliminary aircraft design activities require iterative calculations to quickly make performance predictions on a set of possible airplane configurations. The goal is to search for a design that best fits all top level aircraft requirements among the results of a great number of multi-disciplinary analyses, as fast as possible, and with a certain grade of accuracy. Usually, such a task is carried out using statistical or semi-empirical approaches which can give pretty accurate results in no time. However, those prediction methods may be inappropriate when dealing with innovative aircraft configurations or whenever a higher level of accuracy is necessary. Simulation-based design has become crucial to make the overall process affordable and effective in cases where higher fidelity analyses are required. A common example when flight simulations can be effectively used to support a design loop is given by aircraft mission analyses and performance predictions. These usually include take-off, climb, en route, loiter, approach, and landing simulations. This article introduces the mathematical models of aircraft take-off and landing and gives the details of how they are implemented in the software library JPAD. These features are not present in most of the currently available pieces of preliminary aircraft design software and allow one to perform high fidelity, simulation-based take-off and landing analyses within design iterations. Although much more detailed than classical semi-empirical approaches, the presented methodologies require very limited computational effort. An application of the proposed formulations is introduced in the second part of the article. The example considers the Airbus A220-300 as a reference aircraft model and includes complete take-off and landing performance studies, as well as the simulation of both take-off and landing certification noise trajectories.

The possibility of G-induced loss of consciousness (G-LOC) is a key concern when flying modern, high-performance aircraft. Currently, there are no identification methods available based on physiological data. This study aimed to determine whether specific pulse wave changes could be reliably identified using automatic computer algorithms to detect impending G-LOC. The pulse waves of 86 people who experienced G-LOC in a human centrifuge were analysed alongside an age-, gender-, nationality-, training-, and anti-G-equipment-matched control group using computer algorithm methods to analyse possible longer reductions in the G-LOC group. Based on this data, the study showed that centrifuge profiles with a gradual “onset run” using AGSM resulted in longer pulse wave flattening around the G-LOC in the G-LOC group than in the matched control group. However, this could not be verified in human centrifuge runs with active flight profiles and higher onset rates. Unfortunately, this means that the method used here would not currently be applicable in actual flight. In the future, the possibility of creating an identification method could be extended by incorporating additional physiological data.

Research on morphing aircraft that can change geometry to achieve the desired performance and stability under different flight conditions has been ongoing for many years. This study provides a conceptual-level, preliminary analysis of the impact of symmetrically changing the wing sweep angle on aircraft performance and stability. The T-37B-like aircraft is selected as a base to compare the results with T-37B’s known data. The T-37B-like aircraft is modeled in both Digital DATCOM and Open VSP software. Changes in aircraft performance and stability are demonstrated for changes in the wing sweep angle between −10° and 40°. When 0° and 40° wing sweep configurations are compared, it is observed that the 40° wing sweep configuration performs better in terms of climb and range, but worse in terms of takeoff distance, glide, approach, and radius of turn. In terms of static stability, it has a positive effect on longitudinal stability. While it does not significantly affect lateral stability overall, it contributes positively to stability around the roll axis. Changing the symmetrical wing sweep angle is expected to improve certain performance and stability parameters while degrading others. A symmetrical variable-sweep wing offers advantages by adjusting to the optimal sweep angle for each flight phase. Thus, benefits can be fully utilized, and drawbacks minimized. However, it entails design, mechanical, weight, and financial costs. Therefore, whether the performance and stability benefits outweigh these costs must be evaluated on an aircraft-specific basis.

A flight envelope for aircraft performance in the vertical plane illustrates the performance limitations on the aircraft, usually indicating the minimum and maximum airspeeds at a given altitude, the airspeeds for maximum rate of climb and maximum angle of climb at a given altitude, and the maximum altitude or absolute ceiling of the aircraft. This study outlines the procedure for constructing a vertical-plane flight performance aircraft for an aircraft with a fixed-pitch propeller, which involves additional complexities due to the variable propeller efficiency. The propeller performance, engine power, and drag polar models are described, as is the computational procedure. Envelopes for the flight performance in the vertical plane are presented for a particular remotely-piloted aircraft at different take-off weights.

Aviation emissions are continuously increasing along with the rapid development of air transportation, and results in the deterioration in regional air quality and the global climate. Accurate emission estimation is of great importance for relevant policies promotion and the sustainable development of the environment. Previous studies focused on the total emissions of a flight and lacked high precision in both spatial and temporal resolutions, especially aviation activities near ground. In this research, we propose an open-sourced emission calculation framework based on actual flight trajectories (TrajEmission), which calculates both the ground and airborne emissions simultaneously according to the configuration parameters, trajectory characteristics, and ambient conditions. We compare the emission results with five emission inventory methods. The results indicate that pollutant (nitrogen oxides, carbon monoxide, and unburned hydrocarbons) emissions in the landing and takeoff (LTO) cycle might usually be underestimated due to a lack of trajectory-based methods. In addition, in the overall results, the method based on the great circle route leads to an overestimation of 56.8% of pollutant emissions compared to the method based on actual routes. We also investigate the extent to which other factors could influence the emission results. To summarize, the TrajEmission framework can build inventories for the whole process of flight movements with high spatial–temporal resolutions and provide solid data support for environmental science and other related fields.

PurposeThe authors employed the three different versions (Charnes–Cooper–Rhodes, Banker–Charnes–Cooper and slack-based measure of efficiency) of data envelopment analysis (DEA) to evaluate the comparative efficiency/inefficiency of aircraft maintenance performance during the previous 41 months in United States Air Force (USAF). As a complimentary tool, the authors also adopted Tobit regression analysis to identify factors affecting efficiencies and inefficiencies.Design/methodology/approachThis paper aims to measure the relative efficiency of maintenance performances for a type of USAF aircraft in an effort to enhance aviation safety and combat readiness.FindingsThrough this study, the authors have two noteworthy findings. These are (1) an increased number of “cannibalization” (extracting necessary parts from the existing aircraft) practices tended to reduce maintenance efficiency; (2) The number of mission-capable aircraft turned out to be the most important factor for maintenance performance efficiency.Originality/valueThis paper is one of the first studies on aircraft maintenance that considered popular but neglected cannibalization practices as a new variable for assessing the maintenance efficiency. In addition, this paper is one of the few studies that performed a post-ad hoc analysis as a follow-up to DEA analysis.

With global warming, extreme high temperatures become more frequent and are an important factor affecting aircrafts’ takeoff performance. Using Community Earth System Model version 1 (CESM1) and Boeing Performance Software (BPS), the influence of increasing temperature on aircrafts’ maximum takeoff weight (MTOW) and takeoff distance is evaluated quantitatively in this study. The results show that the distribution of summer daily maximum temperature shifts obviously to higher temperature at all the chosen airports and the variation in temperature is larger at four airports (Jinan, Shanghai, Lhasa, and Urumqi) during 2071−2080 under the RCP8.5 scenario than that in the historical run (1991−2000). The warming air leads to the MTOW reducing and takeoff distance increasing. Taking the Boeing 737–800 aircraft as an illustration, the number of weight-restriction days increases significantly across the airports, which can influence airlines’ economic benefit and flight operations in the future. It is also found that the takeoff distance does not change linearly with temperature, but shows a stronger increase with higher temperature. The takeoff distance increases about 6.2% on average during 2071−2080 compared to 1991−2000 for the low-altitude airports, calling for an additional 113−222 m takeoff distance in future summers.