Multi-disciplinary performance studies on propulsion system integration for military aircraft.

Military aircraft propulsion systems represent one of the most challenging sectors of jet engine design: Operating at an extremely variable environment strongly influenced by aircraft aerodynamics, these engines should pack high thrust output at the minimum possible size without compromising reliability and operating cost. In addition, the multidisciplinary nature of military aircraft operations frequently introduces contradicting performance objectives which are hard to incorporate to engine design. All the above are combined with the very high cost of engine development, necessitating proper selections early in the design phase to ensure the success of the development process and the viability of new engine concepts. Despite the significant volume of research in the field and perhaps due to the sensitivity of the data involved, studies published to date are focused on rather specific topics without addressing the full multidisciplinary aircraft-propulsion system integration problem. In order to achieve this, a new synthesis of methods needs to be established combining aspects and contributions from different areas of research. This project investigates the development of a new methodology for interconnecting engine preliminary design to aircraft operational requirements. Under this scope, a representation of a generic military airframe is constructed and combined with engine performance models and simulation tools to investigate propulsion system effects on aircraft mission performance and survivability. More specifically, the project’s contributions in the field of military aircraft propulsion system integration are focused on three domains: • A new military aircraft representation modelling critical aspects of the interaction between the aircraft and the propulsion system: Aircraft aerodynamics, airframe/propulsion system aerodynamic interference, IR and noise signature. The model has low computational requirements and is suitable for use in the context of large-scale parametric studies and trajectory optimization cases. • New simulation-based techniques for estimating climb performance and assessing the mission capabilities of aircraft/engine configurations in realistic mission scenarios. Points of novelty within the developed methods include a multi-objective formulation to the climb trajectory problem, a technique for Altitude-Mach tracking, an expansion of the Energy-Manoeuvrability (E-M) technique allowing for the concurrent optimization of the aircraft trajectory and engine schedule and the introduction of minimum noise and IR trajectories for military aircraft. • The quantification of propulsion system effects on aircraft survivability, taking into account both the aircraft’s IR signature and aircraft/missile kinematic performance. This is achieved through a combination of an aircraft IR model with kinematic simulations of missile-vs-aircraft and aircraft-vs-aircraft which are used to measure an aircraft’s susceptibility to attacks, along with its own ability to attack manoeuvring targets. The above methods are developed and validated using published data and applied to investigate aircraft performance trends in a series of test cases where the effectiveness of different propulsion system designs is evaluated in a variety of simulated mission tasks. The results successfully demonstrate the developed methods’ ability to quantify the relation between aircraft performance and engine design, providing a basis for understanding the performance trade-offs that result from the adoption of different propulsion system configurations, to maximize the efficiency of the powerplant design process.PhD in Aerospac

Effects of propulsion system operation on military aircraft survivability

The recent advances in infrared (IR) weapon technology have dramatically altered the rules of air combat, leading to a consistent departure from “traditional” energy-maneuverability philosophy in aircraft design, prioritizing stealth and sophisticated armament instead. In this modern aerial warfare environment, it is obvious that new techniques need to be applied to properly assess aircraft survivability and produce successful designs for aircraft propulsion systems. The present study focuses on the development of such a methodology, which contrary to related work in the field includes considerations for both aircraft IR signature and missile/aircraft kinematic performance. An aircraft IR signature model is constructed using a collection of methods for area and temperature estimation and exhaust plume modeling; the latter is combined with missile-vs-aircraft and aircraft-vs-aircraft simulations to quantify aircraft survivability in the form of missile and aircraft lethal zones. The proposed methodology is applied to a study on propulsion system effects on aircraft survivability, in which a comparison between different engine configurations is performed: In the scenarios examined, IR signature at cruise conditions and maximum-power thrust performance are identified as key parameters for aircraft combat performance

Multi-objective climb path optimization for aircraft/engine integration using Particle Swarm Optimization

In this article, a new multi-objective approach to the aircraft climb path optimization problem, based on the Particle Swarm Optimization algorithm, is introduced to be used for aircraft–engine integration studies. This considers a combination of a simulation with a traditional Energy approach, which incorporates, among others, the use of a proposed path-tracking scheme for guidance in the Altitude–Mach plane. The adoption of population-based solver serves to simplify case setup, allowing for direct interfaces between the optimizer and aircraft/engine performance codes. A two-level optimization scheme is employed and is shown to improve search performance compared to the basic PSO algorithm. The effectiveness of the proposed methodology is demonstrated in a hypothetic engine upgrade scenario for the F-4 aircraft considering the replacement of the aircraft’s J79 engine with the EJ200; a clear advantage of the EJ200-equipped configuration is unveiled, resulting, on average, in 15% faster climbs with 20% less fuel

Neural network based dynamic model and gust identification system for the Jetstream G-NFLA

Artificial neural networks are an established technique for constructing non-linear models of multi-input-multi-output systems based on sets of observations. In terms of aerospace vehicle modelling, however, these are currently restricted to either unmanned applications or simulations, despite the fact that large amounts of flight data are typically recorded and kept for reasons of safety and maintenance. In this paper, a methodology for constructing practical models of aerospace vehicles based on available flight data recordings from the vehicles’ operational use is proposed and applied on the Jetstream G-NFLA aircraft. This includes a data analysis procedure to assess the suitability of the available flight databases and a neural network based approach for modelling. In this context, a database of recorded landings of the Jetstream G-NFLA, normally kept as part of a routine maintenance procedure, is used to form training datasets for two separate applications. A neural network based longitudinal dynamic model and gust identification system are constructed and tested against real flight data. Results indicate that in both cases, the resulting models’ predictions achieve a level of accuracy that allows them to be used as a basis for practical real-world applications