A Historical Note on the Beauty Contest

Alain Ledoux, who was one of over 6,000 chess players taking part in Bühren and Frank´s (2012) online Beauty Contest experiment, turned out to be the forgotten inventor of that game. We reconstruct the birth of the Beauty Contest. In section 1 of our note, its first two authors outline the history of the game that metamorphosed into the famous guessing game experiment which was first run in the lab by Rosemarie Nagel. In section 2, Rosemarie Nagel adds further remarks and thoughts about the development of the experimental Beauty Contest.

AGILE Paradigm: The next generation collaborative MDO for the development of aeronautical systems

The research and innovation EU funded AGILE project has developed the next generation of aircraft Multidisciplinary Design and Optimization (MDO) processes, which target significant reductions in aircraft development costs and time to market, leading to more cost-effective and greener aircraft solutions. 19 industry, research and academia partners from Europe, Canada and Russia have developed solutions to cope with the challenges of collaborative design and optimization of complex aeronautical products. In order to accelerate the deployment of large-scale, collaborative multidisciplinary design and optimization, a novel approach, the so-called “AGILE Paradigm”, has been conceived. The AGILE Paradigm is defined as a “blueprint for MDO”, accelerating the deployment and the operations of collaborative “MDO systems” and enabling the development of complex products practiced by multi-site and cross-organizational design teams, having heterogeneous expertise. A set of technologies has been developed by the AGILE consortium to enable the implementation of the AGILE Paradigm principles, thus delivering not only an abstract formalization of the approach, but also an applicable framework. The collection of all the technologies constitutes the so-called “AGILE Framework”, which has been applied for the design and the optimization of multiple aircraft configurations. The ambition of the AGILE Paradigm was set to reduce the lead time of 40% with respect to the current state-of-the-art. This work reviews the evolution of the MDO systems, underlines the open challenges tackled by the AGILE project, and introduces the main architectural concepts behind the AGILE Paradigm. Thereafter, an overview of the application design cases is presented, focusing of the main challenges and achievements. The AGILE technologies enabled the consortium to formulate and to solve in 15 months 7 MDO applications in parallel for the development of 7 novel aircraft configurations, demonstrating time savings beyond the 40% goal

An Integrated Method for Determination of the Oswald Factor in a Multi-Fidelity Design Environment

Aircraft conceptual design often focuses on unconventional configurations like for example forward swept wings. Assessing the characteristics of these configurations usually requires the use of physic based analysis modules. This is due to the fact that for unconventional configurations no sucient database for historic based analysis modules is available. Nevertheless, physic based models require a lot of input data and their computational cost can be high. Generating input values in a trade study manually is work-intensive and error-prone. Conceptual design modules can be used to generate sucient input data for physic based models and their results can be re-integrated into the conceptual design phase. In this study a direct link between a conceptual design module and an aerodynamic design module is presented. Geometric information is generated by the conceptual design module and the physic based results, in form of the Oswald factor, are then fed back. Apart from the direct link, an equation for determination of the Oswald factor is derived via a Symbolic Regression Approach

Collaborative understanding of disciplinary correlations using a low-fidelity physics based aerospace toolkit

Covering all relevant physical effects and mutual influences during aircraft preliminary design at a sufficient level of fidelity necessitates simultaneous consideration of a large number of disciplines. This requires an approach in which teams of engineers apply their analysis tools and knowledge to collaboratively approach design challenges. In the current work, recent technical advancements of the German Aerospace Center (DLR) in data and workflow management are utilized for establishing a toolbox containing elementary disciplinary analysis modules. This toolbox is focussed on providing fast overall aircraft design capabilities. The incorporated empirical and physics based tools of low fidelity level can be used for setting up modular design workflows, tailored for the design cases under consideration. This allows the involved engineers to identify initial design trends at a low computational effort. Furthermore, areas of common physical affinity are identified, serving as a basis for communication and for incorporating tools of higher fidelity in later phases of the design process. Clear visualisation methods aid in efficiently translating knowledge between the involved engineers within the identified areas of common affinity. A system-of-systems approach is established by applying the elementary aircraft design toolbox for the establishment of requirement catalogues for engine preliminary design. The engine designers at their turn deliver initial performance correlations for application in the aircraft design toolbox. In this way, a clear synergy is established between the design of both the airframe and power plant. Using this approach, engineers of different technical backgrounds share their knowledge in a collaborative design approach. The use case guiding the present work involves a conventional short to medium range aircraft sent at half the design range. The wing area and aspect ratio are varied to investigate the influence on the engine requirements catalogue for this particular mission

Preliminary Design for Flexible Aircraft in a Collaborative Environment

Conclusions: - Collaborative design approach for aircraft in pre-design: Enabling physics based analysis. Focus on flexibility effects. - Integration of distributed physics based modules: Analysis starting from an initial OAD synthesis model. Disciplinary modules for aero-structural design and new synthesis. Flexibility loop influence. - Design cases: Conventional aircraft behaves as expected. Care has to be considered with the unconventional aircraft case. - Outlook: Adopt the approach for design and optimization applications

Towards a seamless simulation of the air transport system

To create revolutionary solutions answering the increasing demands on the air transport system of the future, a systematic and integrative consideration of all disciplines across the complete product lifecycle is needed. Through the development and utilization of a well-balanced mix of design process digitalization and the development of a corresponding design process methodology, actively involving the heterogeneous disciplinary specialists, the German Aerospace Center (DLR) has fostered effective collaboration between the multitude of disciplines involved over the past decade. The combined effort has led to the maturation of a framework for the seamless connection of disciplinary knowledge in a highly-scalable distributed multidisciplinary collaboration framework for air vehicle design. This paper describes the components of the developed distributed collaboration framework and provides an overview of the broad range of air vehicle design initiatives in which the framework has been successfully applied. On the basis of this, an outlook in future enhancements of the overall design methodology is presented, ultimately targeting to obtain an air vehicle architecture optimization framework capable of seamlessly covering the entire design lifecycle of revolutionary air transport systems

An MBSE Architectural Framework for the Agile Definition of System Stakeholders, Needs and Requirements

Model Based Systems Engineering (MBSE) approaches are rapidly spreading among organizations and industries due to all their claimed benefits over traditional document-based approaches. Benefits include for instance enhanced design quality of systems, clearer development of system requirements and specifications and improved communications within the design teams. Currently, MBSE methods and tools are mainly employed to successfully develop complex systems, such as aircraft or its components. However, this paper proposes to adopt MBSE also in the design of development systems, which aim to design complex systems. In particular, this paper focuses on the first activities of a typical Systems Engineering Product Development process: identification of system stakeholders, collection of their needs and development of system requirements. The main outcome delivered from this paper is an architectural framework, i.e. a guideline for the modeling of complex systems. More specifically, the architectural framework is still under development, and hence the current version focuses on the modeling of stakeholders, needs and requirements of complex systems. The focus of the proposed architectural framework is on the agility for the definition phases of complex systems. In other words, it is developed to streamline, improve and accelerate the definition and modeling of complex systems. Details of the architectural framework including the means to represent all the system information are provided. In addition, the architectural framework for the development of complex systems is supported by an MBSE development system, currently being addressed in the EU-funded research project AGILE 4.0. The MBSE development system is presented in this paper together with an example of its application for the definition of complex systems: an horizontal tail plane for a regional jet aircraft, designed and manufactured within an aeronautical supply chain consisting of different companies

SYSTEM ARCHITECTURE DESIGN SPACE MODELING AND OPTIMIZATION ELEMENTS

Optimization of complex system architectures can support the non-biased search for novel architectures in the early design phase. Four aspects needed to enable architecture optimization are discussed: formalization of the architecture design space, systematic exploration of the design space, conversion from architecture model to simulation model, and flexible simulation of architecture performance. Modeling the design space is driven by system requirements and simulation capabilities and should be based on functional decomposition. Systematic exploration can be done using enumeration, design of experiments, or optimization. Various approaches for converting architectures to simulation models are discussed. Finally, simulation environments should expose a flexible and modular interface to be used in architecture optimization. A jet engine architecting problem is presented that demonstrates various aspects of system architecture optimization

A semantic knowledge based engineering framework for the rapid generation of novel air vehicle configurations

The demands posed on modern aircraft design encourages research into new tools and methodologies that allow the rapid generation of digital prototypes which can represent fundamentally different configurations. High-level design decisions are generally made within the conceptual design phase and require a solid understanding of the technology impacts on the overall aircraft system. This paper presents a recently developed, novel knowledge-based engineering framework, which allows for the transparent digitization of conceptual design knowledge and its interconnection using semantic-web technologies. It focuses on describing an effective structure for capturing and storing the expert’s knowledge and on the procedures required to analyse and solve the resulting complex system. By flexibly recombining the knowledge patterns concerning e.g. different propulsion architectures or lifting-surface configurations, the resulting system provides a significantly reduced effort to generate fundamentally different air vehicle configuration prototypes and allows for covering the vast design space typically considered during the conceptual design phase. The discussion is supported by examples for the automated creation of multi-trapezoidal lifting surfaces and the creation of different combat air vehicles architectures starting from the same knowledge base