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Aerospace
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Flight Simulation
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Flight Simulation

A special issue of Aerospace (ISSN 2226-4310).

Deadline for manuscript submissions: closed (30 September 2020) | Viewed by 30098

Special Issue Editor

Dr. Agostino De Marco

E-Mail Website
Guest Editor
Department of Industrial Engineering, University of Naples Federico II, Napoli, Italy
Interests: flight dynamics modeling; aircraft stability and control; nonlinear aerodynamics modeling; aircraft design
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Flight simulation (FS) has an important role in many fields. Today, the simulation of atmospheric and space flight conditions in ground-based simulators and special-purpose aircraft is used for aircrew training as well as for design, development, and evaluation of aerospace vehicles, systems, and subsystems. FS is presently an important step in aircraft and rotorcraft design, where visions are converted into a virtual reality. The fidelity of simulation systems ranges widely; some aim to recreate an environment or system to such a high degree that it is difficult to distinguish between the simulator and the real system, while others simply aim to recreate a small part of a system, or to present the system as a whole in a more compact fashion.

The FS research community faces new technical challenges when technology and requirements change and evolve. Future generations of FS systems will involve challenges in vehicle modeling techniques and tools as well as environmental modeling, use of computing resources, avionics and instrumentation, motion base technology, and visual system technology.

In the field of Modeling and Simulation of Aircraft Dynamics, Systems, and Environments, including uninhabited aerial systems (UAS) and urban air mobility (UAM) vehicles, multidisciplinary modeling and simulation that spans across domains is becoming increasingly popular. At present, novel modeling and simulation approaches that integrate two, or more, domains are possible─for example, integrating structural dynamics and computational aerodynamics.

In the field of Modeling and Simulation for Certification and Qualification, FS has become an essential tool in the certification process of new commercial aircraft. Furthermore, the introduction of autonomous aircraft in civil airspace, such as UAS and UAM vehicles, requires novel certification approaches based on modeling and simulation. Key research approaches in this context will be those that aim at expanding the use of simulation for handling quality certification of new and derivative aircraft designs, the use of simulation for the certification of autonomous aircraft, and the design of flight tests to validate these simulations.

An important area of research is that involving all aspects in the design, development, and use of motion systems, visual systems, and other simulator hardware, as well as image generation. Novel motion configurations and hardware as well as the application of motion for research and training will exploit emerging motion and visual system technologies and will improve simulation fidelity and effectiveness.

A wide research area where FS is highly involved is that of Model-Based Development, that is, a modern approach to engineering that positions models as the core assets of systems development. Novel techniques and new tools in model-based development in the aerospace field are rapidly penetrating the modeling and simulation aerospace design community as a means of reducing cost while increasing productivity. Key research topics in this context will deal with the use of model-, software-, processor-, and hardware-in-the-loop simulations. Areas of interest span from these approaches, also called X-in-the-loop simulations, to system integration laboratories for hardware-in-the-loop testing of modern fly-by-wire systems, integration and testing of modern avionics and synthetic vision systems, and autonomous flight systems integration and testing.

Dr. Agostino De Marco
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Aerospace is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • flight dynamics modelling
  • multidisciplinary modeling and simulation
  • real-time simulation
  • human-in-the-loop vehicle simulation
  • model-in-the-loop simulation
  • software-in-the-loop simulation
  • processor-in-the-loop simulation
  • model-based design
  • handling quality certification
  • motion systems
  • visual systems
  • simulation fidelity

Published Papers (5 papers)

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32 pages, 1746 KiB  
Article
A Simulation-Based Performance Analysis Tool for Aircraft Design Workflows
by Agostino De Marco, Vittorio Trifari, Fabrizio Nicolosi and Manuela Ruocco
Aerospace 2020, 7(11), 155; https://doi.org/10.3390/aerospace7110155 - 30 Oct 2020
Cited by 12 | Viewed by 8977
Abstract
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. [...] Read more.
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. Full article
(This article belongs to the Special Issue Flight Simulation)
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19 pages, 3095 KiB  
Article
New Reliability Studies of Data-Driven Aircraft Trajectory Prediction
by Seyed Mohammad Hashemi, Ruxandra Mihaela Botez and Teodor Lucian Grigorie
Aerospace 2020, 7(10), 145; https://doi.org/10.3390/aerospace7100145 - 09 Oct 2020
Cited by 23 | Viewed by 4201
Abstract
Two main factors, including regression accuracy and adversarial attack robustness, of six trajectory prediction models are measured in this paper using the traffic flow management system (TFMS) public dataset of fixed-wing aircraft trajectories in a specific route provided by the Federal Aviation Administration. [...] Read more.
Two main factors, including regression accuracy and adversarial attack robustness, of six trajectory prediction models are measured in this paper using the traffic flow management system (TFMS) public dataset of fixed-wing aircraft trajectories in a specific route provided by the Federal Aviation Administration. Six data-driven regressors with their desired architectures, from basic conventional to advanced deep learning, are explored in terms of the accuracy and reliability of their predicted trajectories. The main contribution of the paper is that the existence of adversarial samples was characterized for an aircraft trajectory problem, which is recast as a regression task in this paper. In other words, although data-driven algorithms are currently the best regressors, it is shown that they can be attacked by adversarial samples. Adversarial samples are similar to training samples; however, they can cause finely trained regressors to make incorrect predictions, which poses a security concern for learning-based trajectory prediction algorithms. It is shown that although deep-learning-based algorithms (e.g., long short-term memory (LSTM)) have higher regression accuracy with respect to conventional classifiers (e.g., support vector regression (SVR)), they are more sensitive to crafted states, which can be carefully manipulated even to redirect their predicted states towards incorrect states. This fact poses a real security issue for aircraft as adversarial attacks can result in intentional and purposely designed collisions of built-in systems that can include any type of learning-based trajectory predictor. Full article
(This article belongs to the Special Issue Flight Simulation)
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23 pages, 1141 KiB  
Article
A Generalized Approach to Operational, Globally Optimal Aircraft Mission Performance Evaluation, with Application to Direct Lift Control
by Sam de Wringer, Carmine Varriale and Fabrizio Oliviero
Aerospace 2020, 7(9), 134; https://doi.org/10.3390/aerospace7090134 - 09 Sep 2020
Cited by 5 | Viewed by 4180
Abstract
A unified approach to aircraft mission performance assessment is presented in this work. It provides a detailed and flexible formulation to simulate a complete commercial aviation mission. Based on optimal control theory, with consistent injection of rules and procedures typical of aeronautical operations, [...] Read more.
A unified approach to aircraft mission performance assessment is presented in this work. It provides a detailed and flexible formulation to simulate a complete commercial aviation mission. Based on optimal control theory, with consistent injection of rules and procedures typical of aeronautical operations, it relies on generalized mathematical and flight mechanics models, thereby being applicable to aircraft with very distinct configurations. It is employed for an extensive evaluation of the performance of a conventional commercial aircraft, and of an unconventional box-wing aircraft, referred to as the PrandtlPlane. The PrandtlPlane features redundant control surfaces, and it is able to employ Direct Lift Control. To demonstrate the versatility of the performance evaluation approach, the mission-level benefits of using Direct Lift Control as an unconventional control technique are assessed. The PrandtlPlane is seen to be competitive in terms of its fuel consumption per passenger per kilometer. However, this beneficial fuel performance comes at the price of slower flight. The benefits of using Direct Lift are present but marginal, both in terms of fuel consumption and flight time. Nonetheless, enabling Direct Lift Control results in a broader range of viable trajectories, such that the aircraft no longer requires cruise-climb for maximum fuel economy. Full article
(This article belongs to the Special Issue Flight Simulation)
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18 pages, 1336 KiB  
Article
Multi-Axis Inputs for Identification of a Reconfigurable Fixed-Wing UAV
by Piotr Lichota
Aerospace 2020, 7(8), 113; https://doi.org/10.3390/aerospace7080113 - 05 Aug 2020
Cited by 15 | Viewed by 3445
Abstract
Designing a reconfiguration system for an aircraft requires a good mathematical model of the object. An accurate model describing the aircraft dynamics can be obtained from system identification. In this case, special maneuvers for parameter estimation must be designed, as the reconfiguration algorithm [...] Read more.
Designing a reconfiguration system for an aircraft requires a good mathematical model of the object. An accurate model describing the aircraft dynamics can be obtained from system identification. In this case, special maneuvers for parameter estimation must be designed, as the reconfiguration algorithm may require to use flight controls separately, even if they usually work in pairs. The simultaneous multi-axis multi-step input design for reconfigurable fixed-wing aircraft system identification is presented in this paper. D-optimality criterion and genetic algorithm were used to design the flight controls deflections. The aircraft model was excited with those inputs and its outputs were recorded. These data were used to estimate stability and control derivatives by using the maximum likelihood principle. Visual match between registered and identified outputs as well as relative standard deviations were used to validate the outcomes. The system was also excited with simultaneous multisine inputs and its stability and control derivatives were estimated with the same approach as earlier in order to assess the multi-step design. Full article
(This article belongs to the Special Issue Flight Simulation)
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18 pages, 5574 KiB  
Article
Conceptual Design, Flying, and Handling Qualities Assessment of a Blended Wing Body (BWB) Aircraft by Using an Engineering Flight Simulator
by Clayton Humphreys-Jennings, Ilias Lappas and Dragos Mihai Sovar
Aerospace 2020, 7(5), 51; https://doi.org/10.3390/aerospace7050051 - 28 Apr 2020
Cited by 15 | Viewed by 7605
Abstract
The Blended Wing Body (BWB) configuration is considered to have the potential of providing significant advantages when compared to conventional aircraft designs. At the same time, numerous studies have reported that technical challenges exist in many areas of its design, including stability and [...] Read more.
The Blended Wing Body (BWB) configuration is considered to have the potential of providing significant advantages when compared to conventional aircraft designs. At the same time, numerous studies have reported that technical challenges exist in many areas of its design, including stability and control. This study aims to create a novel BWB design to test its flying and handling qualities using an engineering flight simulator and as such, to identify potential design solutions which will enhance its controllability and manoeuvrability characteristics. This aircraft is aimed toward the commercial sector with a range of 3000 nautical miles, carrying 200 passengers. The BWB design was flight tested at an engineering flight simulator to first determine its static stability through a standard commercial mission profile, and then to determine its dynamic stability characteristics through standard dynamic modes. Its flying qualities suggested its stability with a static margin of 8.652% of the mean aerodynamic chord (MAC) and consistent response from the pilot input. In addition, the aircraft achieved a maximum lift-to-drag ratio of 28.1; a maximum range of 4,581 nautical miles; zero-lift drag of 0.005; while meeting all the requirements of the dynamic modes. Full article
(This article belongs to the Special Issue Flight Simulation)
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