Framework for Modelling and Simulation of Multi-Physics Aircraft Systems with Distributed Electronic Controllers

Proceedings of the Institution of Mechanical Engineers, Part G:

et al. 2019

New technologies and complex systems are being developed in commercial aviation to meet strict requirements regarding fuel consumption, emissions and noise constraints. This motivates the development of multidisciplinary environments to efficiently manage the increasing complexity of the design process. Under the Clean Sky 2 initiative, the ModellIng and Simulation tools for Systems IntegratiON on Aircraft (MISSION) project aims to develop an integrated framework to holistically support the aircraft design, development and validation processes. Within the MISSION framework, this paper proposes a methodology to handle the integration between the aircraft level and the system level in the early phase of aircraft design. The methodology is demonstrated for the case of the Landing Gear System in the rejected take-off scenario.

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Section: Aircraft-level Integrated Simulationmentioning

confidence: 99%

A modelling and simulation framework for the integrated design of aircraft systems

Cimmino

Proceedings of the Institution of Mechanical Engineers, Part G:

et al. 2019

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“…More recently, the field of aerospace design has been enhanced by a broader use of machine learning applications for a multitude of specific design problems and applications [46][47][48][49][50]. Previous work in the context of the MISSION project focuses on the integration of the system-level dynamics with the aircraft-level [51] and the design of controls for multiple aircraft systems [52]. This paper leverages the modeling framework proposed in Garcia Garriga et al [53] to enable trade-off studies among multiple power architectures in the evaluation of aircraft system architectures and proposes a principled approach to reduce the architecture design space and speed up the identification of the optimal architecture.…”

Section: Introductionmentioning

confidence: 99%

A Machine Learning Enabled Multi-Fidelity Platform for the Integrated Design of Aircraft Systems

Mainini

Journal of Mechanical Design

2019

The push toward reducing the aircraft development cycle time motivates the development of collaborative frameworks that enable the more integrated design of aircraft and their systems. The ModellIng and Simulation tools for Systems IntegratiON on Aircraft (MISSION) project aims to develop an integrated modelling and simulation framework. This paper focuses on some recent advancements in the MISSION project and presents a design framework that combines a filtering process to down-select feasible architectures, a modeling platform that simulates the power system of the aircraft, and a machine learning-based clustering and optimization module. This framework enables the designer to prioritize different designs and offers traceability on the optimal choices. In addition, it enables the integration of models at multiple levels of fidelity depending on the size of the design space and the accuracy required. It is demonstrated for the electrification of the Primary Flight Control System (PFCS) and the landing gear braking system using different electric actuation technologies. The performance of different architectures is analyzed with respect to key performance indicators (fuel burn, weight, power). The optimization process benefits from a data-driven localization step to identify sets of similar architectures. The framework demonstrates the capability of optimizing across multiple, different system architectures in an efficient way that is scalable for larger design spaces and larger dimensionality problems.

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A modelling framework to support power architecture trade-off studies for More-Electric Aircraft

Govindaraju

Transportation Research Procedia

et al. 2018