Multi-objective optimisation methods applied to aircraft techno-economic and environmental issues

Engineering methods that couple multi-objective optimisation (MOO) techniques with high fidelity computational tools are expected to minimise the environmental impact of aviation while increasing the growth, with the potential to reveal innovative solutions. In order to mitigate the compromise between computational efficiency and fidelity, these methods can be accelerated by harnessing the computational efficiency of Graphic Processor Units (GPUs). The aim of the research is to develop a family of engineering methods to support research in aviation with respect to the environmental and economic aspects. In order to reveal the non-dominated trade-o_, also known as Pareto Front(PF), among conflicting objectives, a MOO algorithm, called Multi-Objective Tabu Search 2 (MOTS2), is developed, benchmarked relative to state-of-the-art methods and accelerated by using GPUs. A prototype fluid solver based on GPU is also developed, so as to simulate the mixing capability of a microreactor that could potentially be used in fuel-saving technologies in aviation. By using the aforementioned methods, optimal aircraft trajectories in terms of flight time, fuel consumption and emissions are generated, and alternative designs of a microreactor are suggested, so as to assess the trade-offs between pressure losses and the micro-mixing capability. As a key contribution to knowledge, with reference to competitive optimisers and previous cases, the capabilities of the proposed methodology are illustrated in prototype applications of aircraft trajectory optimisation (ATO) and micromixing optimisation with 2 and 3 objectives, under operational and geometrical constraints, respectively. In the short-term, ATO ought to be applied to existing aircraft. In the long-term, improving the micro-mixing capability of a microreactor is expected to enable the use of hydrogen-based fuel. This methodology is also benchmarked and assessed relative to state-of-the-art techniques in ATO and micro-mixing optimisation with known and unknown trade-offs, whereas the former could only optimise 2 objectives and the latter could not exploit the computational efficiency of GPUs. The impact of deploying on GPUs a micro-mixing _ow solver, which accelerates the generation of trade-off against a reference study, and MOTS2, which illustrates the scalability potential, is assessed. With regard to standard analytical function test cases and verification cases in MOO, MOTS2 can handle the multi-modality of the trade-o_ of ZDT4, which is a MOO benchmark function with many local optima that presents a challenge for a state-of-the-art genetic algorithm for ATO, called NSGAMO, based on case studies in the public domain. However, MOTS2 demonstrated worse performance on ZDT3, which is a MOO benchmark function with a discontinuous trade-o_, for which NSGAMO successfully captured the target PF. Comparing their overall performance, if the shape of the PF is known, MOTS2 should be preferred in problems with multi-modal trade-offs, whereas NSGAMO should be employed in discontinuous PFs. The shape of the trade-o_ between the objectives in airfoil shape optimisation, ATO and micro-mixing optimisation was continuous. The weakness of MOTS2 to sufficiently capture the discontinuous PF of ZDT3 was not critical in the studied examples … [cont.]

Multi-objective Tabu Search 2: first technical report

The purpose of this document is to describe Multi-Objective Tabu Search 2 (MOTS2), which is a native mutli-objective optimiser. It has been developed to tackle a variety of real-world problems of engineering interest. The design and implementation are presented, followed by verification, validation and user instructions. At a glance, it involves introduction to the algorithm, explains configuration settings and structure, and results interpretation. Then, the optimiser is tested against a series of mathematical test functions in order to verify its functionality. The main goal is to demonstrate and assess the performance and applicability of the optimiser. The next step is to use MOTS2 on a real-world case, where the performance of optimising a 2D airfoil is validated and illustrated

Developing an open-source platform for the evaluation of intelligent traffic control algorithms

Intersection management is a key component of road transport systems. Envisaging a new age of road transport systems accommodating intelligent, connected, and autonomous vehicles, many novel intersection control algorithms have been proposed in the literature. These algorithms are often implemented using bespoke software and tested over custom built network models because of their complexity and the lack of freely accessible software tools. This in turn makes them difficult to evaluate and benchmark."br/"To solve this issue, in this paper, we present the Traffic Control Test Bed project, the objective of which is to develop an open source microsimulation platform for the evaluation of intersection control algorithms. The platform provides a library of road network models together with an intuitive synthetic road network generator for user-defined layouts. It facilitates and streamlines the parallel execution of simulations. Outputs and performance indicators are monitored and visualised by the platform both during runtime and at post processing stage. We demonstrate the usage of the platform with a case study evaluating two simple signal optimisation methods. As well as being an arena for traffic control algorithms, the open source property of the platform also invites contributions from the wider research community to improve execution validity and efficiency of traffic control systems

Developing an open-source platform for the evaluation of intelligent traffic control algorithms

Intersection management is a key component of road transport systems. Envisaging a new age of road transport systems accommodating intelligent, connected, and autonomous vehicles, many novel intersection control algorithms have been proposed in the literature. These algorithms are often implemented using bespoke software and tested over custom built network models because of their complexity and the lack of freely accessible software tools. This in turn makes them difficult to evaluate and benchmark.To solve this issue, in this paper, we present the Traffic Control Test Bed project, the objective of which is to develop an open source microsimulation platform for the evaluation of intersection control algorithms. The platform provides a library of road network models together with an intuitive synthetic road network generator for user-defined layouts. It facilitates and streamlines the parallel execution of simulations. Outputs and performance indicators are monitored and visualised by the platform both during runtime and at post processing stage. We demonstrate the usage of the platform with a case study evaluating two simple signal optimisation methods. As well as being an arena for traffic control algorithms, the open source property of the platform also invites contributions from the wider research community to improve execution validity and efficiency of traffic control systems

A multi-fidelity, multi-disciplinary analysis and optimization framework for the design of morphing UAV wings

© 2015 American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.A framework for the design and optimization of a morphing wing is presented. It allows the user to simplify the design process of a morphing UAV wing with a simple and effective interface with the possibility to easily switch between flight phases and morphing concepts. It consists of two main solvers: a high-fidelity CFD module for detailed RANS simulation and a fast low-fidelity module that solves the aeroelastic problem by coupling a geometrically nonlinear structural model to a potential flow aerodynamic model. The structure of the framework and the methodology used for the design of a morphing UAV wing are detailed. This wing is the focus of the European FP7 CHANGE project and serves as an example of the application of this methodology

SUMO 2016 – Traffic, Mobility, and Logistics

Dear reader, You are holding in your hands a volume of the series „Reports of the DLR-Institute of Transportation Systems“. We are publishing in this series fascinating, scientific topics from the Institute of Trans- portation Systems of the German Aerospace Center (Deutsches Zentrum für Luft- und Raumfahrt e.V. – DLR) and from his environment. We are providing libraries with a part of the circulation. Outstanding scientific contributions and dissertations are here published as well as projects reports and proceedings of conferences in our house with different contributors from science, economy and politics. With this series we are pursuing the objective to enable a broad access to scientific works and results. We are using the series as well as to promote practically young researchers by the publication of the dissertation of our staff and external doctoral candidates, too. Publications are important milestones on the academic career path. With the series „Reports of the DLR-Institute of Transportation Systems / Berichte aus dem DLR-Institut für Verkehrssystemtechnik“ we are widening the spectrum of possible publications with a building block. Beyond that we understand the communication of our scientific fields of research as a contribution to the national and international research landscape in the fields of automotive, railway systems and traffic management. With this volume we publish the proceedings of the SUMO Conference 2016 which was held from 23rd to 25th May 2016 with a focus on traffic, mobility, and logistics. SUMO is an open source tool for traffic simulation that provides a wide range of traffic planning and simulation functionalities.The conference proceedings offer an overview of the applicability of the SUMO tool suite as well as its universal extensibility due to the availability of the source code. The major topic of this fourth edition of the SUMO conference are the different facets of moving objects occurring as personal mobility and freight delivery as well as communicating networks of intelligent vehicles. Several articles cover heterogeneous traffic networks, junction control and new traffic model extensions to the simulation. Subsequent specialized issues such as disaster management aspects and applying agile development techniques to scenario building are targeted as well. At the conference the international user community exchanged their experiences in using SUMO. With this volume we provide an insight to these experiences as inspiration for further projects with the SUMO suite