CEAS 2017 Conference

AGILE  is developing the next generation of aircraft Multidisciplinary Design and Optimization processes, which target significant reductions in aircraft development costs and time to market, leading to cheaper an greener aircraft solution. 

AGILE Objectives

AGILE is implementing novel design methodologies and platforms, accelerating the deployment of large scale, distributed, cross-organizational MDO processes.

AGILE ambition is to achieve the reduction of 20% in time to converge the design of an aircraft and a 40% in time needed to setup and solve the multidisciplinary problem in a team of heterogeneous specialists.

To meet the challenging objectives of the AGILE project a team of 19 industry, research and academia partners from Europe, Canada and Russia are collaborating together. The composition of the Consortium reflects the heterogeneous structure characteristic for today’s aircraft development teams.

AGILE Sessions @ CEAS 2017 Conference, 16-20 October 2017, Bucharest, Romania

AGILE current status and results will be presented in dedicated sessions hosted by the CEAS 2017 Conference.

  • The AGILE Technical sessions

    Wednesday 18 & Thursday 19, October, Iorga Hall

  • The AGILE Workshop

    Thursday 19, 12:05-12:45, Iorga Hall

 Ready to touch and play with the AGILE technologies ?
Join the AGILE Challenge !

AGILE is making the collaborative MDO technologies available! AGILE will launch the exciting AGILE Challenge. Come to meet the AGILE members and discover how you can participate.

For any information: challenge@agile-project.eu

Technical sessions detailed program

Session 27. AGILE I
Chair(s): Pier Davide Ciampa (DLR, DE)
Wednesday 18 | 10:45 - 12:45 | Iorga Hall

10:45876 AGILE Aircraft Development Process - Abstract
Pier Davide Ciampa (DLR, DE), Björn Nagel (DLR, DE)
11:05844 Methods supporting the efficient collaborative design of future aircraft - Abstract
Erik Baalbergen (Netherlands Aerospace Centre, NL), Erwin Moerland (DLR, DE) Wim Lammen (Netherlands Aerospace Centre, NL), Pier Davide Ciampa
11:25173 Graph-based algorithms and data-driven documents for formulation and visualization of large MDO systems - Abstract
Benedikt Aigner (RWTH Aachen University, DE), Imco van Gent (Delft University of Technology, NL), Gianfranco La Rocca (Delft University of Technology, NL), Eike Stumpf (RWTH Aachen University, DE), Leo L.M. Veldhuis (Delft University of Technology, NL)
11:45245 The effect of sub-systems design parameters on preliminary aircraft design in a multidisciplinary design environment - Abstract
Marco Fioriti (Politecnico di Torino, IT), Luca Boggero (Politecnico di Torino, IT), Sabrina Corpino (Politecnico di Torino, IT), Prajwal Shiva Prakasha (DLR, DE), Pier Davide Ciampa (DLR, DE), Björn Nagel (DLR, DE)
12:05254 An improved method for transport aircraft for high lift aerodynamic prediction - Abstract
Pierluigi Della Vecchia (University of Naples “Federico II”, IT), Fabrizio Nicolosi (University of Naples “Federico II”, IT), Manuela Ruocco (University of Naples “Federico II”, IT), Luca Stingo (University of Naples “Federico II”, IT), Agostino De Marco (University of Naples “Federico II”, IT)
12:25957 Robust optimization of a rudder hinge system taking into account uncertainty in airframe parameters - Abstract
Ton van der Laan (GKN Fokker Aerostructures, NL), Luc Hootsmans (GKN Fokker Aerostructures, NL), Marco Panzeri (Noesis Solutions, BE), Roberto d’Ippolito (NOESIS Solutions, BE)

Session 33. AGILE II
Chair(s): Thierry Lefebvre (ONERA, FR)
Wednesday 18 | 13:45 - 15:45 | Iorga Hall

13:45956 Overview of MDO enhancement in the AGILE project: A clustered and surrogate-based MDA use case - Abstract
Thierry Lefebvre (ONERA, FR), Nathalie Bartoli (ONERA, FR), Sylvain Dubreuil (ONERA, FR), Riccardo Lombardi (NOESIS Solutions, BE), Wim Lammen (NLR, NL), Mengmeng Zhang (AIRINNOVA, SE), Imco van Gent (Delft University of Technology, NL), Pier Davide Ciampa (DLR, DE)
14:05898 Collaborative design of aircraft systems - Multi-Level Optimization of an aircraft rudder - Abstract
Wim Lammen (NLR, NL), Bert de Wit (NLR, NL), Jos Vankan (NLR, NL), Huub Timmermans (NLR, NL), Ton van der Laan (GKN Fokker Aerostructures, NL), Pier Davide Ciampa (DLR, DE)
14:25969 CMDOWS: A proposed new standard to store and exchange MDO systems - Abstract
Imco van Gent (Delft University of Technology, NL), Gianfranco La Rocca (Delft University of Technology, NL), Maurice F. M. Hoogreef (Delft University of Technology, NL)
14:45851 MDO architectures comparison on analytical test case and aerostructural aircraft system design problem - Abstract
Francesco Torrigiani (DLR, DE), Pier Davide Ciampa (DLR, DE)
15:05953 Disciplinary data fusion for multi-fidelity aerodynamic application - Abstract
Mengmeng Zhang (Airinnova, SE), Aidan Jungo (CFS Engineering, CH), Nathalie Bartoli (ONERA, FR)
15:25271 Uncertainty quantification and robust design optimization applied to aircraft propulsion systems - Abstract
Marco Panzeri (Noesis Solutions, BE), Andrey Savelyev (TsAGI, RU), Kirill Anisimov (TsAGI, RU), Roberto d’Ippolito (Noesis Solutions, BE), Artur Mirzoyan (CIAM, RU)

Session 44. AGILE III
Chair(s): Jan Vos (CFS Engineering, CH)
Thursday 19 | 10:45 - 12:45 | Iorga Hall

10:45270 Airframe - On board system - Propulsion system optimization for civil transport aircraft: AGILE EU project - Abstract
Prajwal Shiva Prakasha (DLR, DE), Pier Davide Ciampa (DLR, DE), Luca Boggero (Politecnico di Torino, IT), Marco Fioriti (Politecnico di Torino, IT), Benedikt Aigner (RWTH Aachen University, DE), Artur Mirzoyan (CIAM, RU), Alik Isyanov (CIAM, RU), Kirill Anisimov (TsAGI, RU), Andrey Savelyev (TsAGI, RU)
11:05258 Automated selection of airliner optimal on-board systems architecture within MDO collaborative environment - Abstract
Riccardo Lombardi (Noesis Solutions, BE), Marco Fioriti (Politecnico di Torino, IT), Luca Boggero (Politecnico di Torino, IT), Luciana Lo Verde (Leonardo Aircraft, IT), Nicola Catino (Leonardo Aircraft, IT), Artur Mirzoyan (CIAM, RU), Roberto D‟Ippolito (Noesis Solutions, BE)
11:25272 Low speed take-off aerodynamic analysis - Abstract
Dominique Charbonnier (CFS Engineering, CH), Jan B. Vos (CFS Engineering, CH), Prajwal Shiva Prakasha (DLR, DE), Artur Mirzoyan (CIAM, RU), Andrey Savelyev (TsAGI, RU), Pierluigi Della Vecchia (University of Naples "Federico II", IT)
11:45852 Knowledge-based automatic airframe design using CPACS - Abstract
Jan-Niclas Walther (DLR, DE), Pier Davide Ciampa (DLR, DE)

The AGILE project targets the establishment of a collaborative MDO network. The developed methodologies and technologies in AGILE will be accessible to other research and educational activities via dedicated initiatived.

AGILE Academy

Open Day

AGILE Aircraft Development Process

Methods supporting the efficient collaborative design of future aircraft

The paper describes the need for and advantages of efficient and effective collaboration within the aircraft development supply chain. It discusses the barriers on the organisational, human and technical levels that hamper efficient collaboration. One of the focal points of the European Horizon2020 project AGILE is the creation of technical solutions for resolving the challenges that come with collaboration. In this light, the paper focuses on two methods being investigated and developed for supporting multidisciplinary teams from different organisations in collaborative aircraft design. The first method concerns the realisation of cross-organisational workflows for multidisciplinary design of aircraft. The workflows support the definition and smooth application of multiorganisation collaborative product development analyses. The second method concerns the deployment and management of surrogate models, which support efficient collaborative multidisciplinary aircraft design while dealing with intellectual property issues and computational speed limitations. After the introduction of the methods, two representative use cases which are successfully supported by the methods are highlighted. An important observation is that efficient collaboration is not straightforward when engineers from different and usually geographically dispersed organisations attempt to achieve a common design target. Once the collaboration methods are in place however, investigation of novel aircraft configurations is enabled by optimally leveraging the dedicated disciplinary knowledge of all involved experts.

Graph-based algorithms and data-driven documents for formulation and visualization of large MDO systems

A new system is presented that enables the visualization of large multidisciplinary design optimization (MDO) problems and their solution strategy. This visualization system is the result of a cooperation between RWTH Aachen University and Delft University of Technology (DUT) within the EU project AGILE. In AGILE, col- laborative MDO is performed in large, heterogeneous teams of experts by solving MDO problems using a collection of design and analysis tools. The two main phases of such a collaborative MDO project are the formulation and the execution phase. This paper focuses on the visualizations required to support the for- mulation phase of the MDO problem. In this phase three main steps have been identified: the set-up of the repository of interconnected tools, the definition of the MDO problem at hand, and the determination of the solution strategy to solve that MDO problem. KADMOS, an open-source MDO support system developed by DUT, uses graph-based analysis to formulate an MDO problem and its solution strategy, based on the disciplinary analyses available in a repository. The results of KADMOS are stored in a standardized format called CMDOWS, which is eventually used to trigger the execution phase by means of a simulation workflow platform of choice. Although based on XML, the readability of the CMDOWS file is quite poor also for MDO experts, especially for large MDO systems involving thousands of variables, thus preventing visual inspection of the formalized MDO problem. Providing visualization capabilities to thoroughly inspect the outcome of the three aforementioned formulation steps becomes a key factor to enable the specification of large MDO sys- tems in a heterogeneous team. Therefore, one of the main hurdles for using MDO as a development process can be removed. Conventional visualization methods (such as N2-charts, functional dependency tables, and design structure matrices) have major scalability limitations. Therefore VISTOMS, a dynamic visualization package based on the open-source visualization library D3.js, was developed by RWTH Aachen to enable the visualization and inspection of the different MDO system specification steps. The developed visualization capabilities are demonstrated by means of a wing design optimization problem performed at DUT. As shown in this use case, VISTOMS enables the visualization and inspection of a large MDO system containing more than ten different aircraft design tools, interlinking thousands of variables.

The effect of sub-systems design parameters on preliminary aircraft design in a multidisciplinary design environment

The remarkable complexity of the aircraft design is due to several reasons and one of these is certainly the high number of completely different design disciplines involved in the process. Many efforts are spent to harmonize and optimize the aircraft design trying to consider all disciplines together with the same level of detail. Within the ongoing H2020 AGILE research, an aircraft MDO (Multidisciplinar y Design Optimization) process is setting up linking several design tools and, above all, competences together. This paper focuses on the evaluation of the effects of the main on-board systems design parameters on the other disciplines. Starting from a baseline aircraft (A GILE DC1 regional turbofan), the effect of each parameters have been quantified in terms of variation of aircraft weight, fuel consumption and engine performance. This analysis represents a useful starting point to better understand the importance and the influence of novel On-Board Systems configurations, such as More and All Electric, to the overall aircraft design.

An improved method for transport aircraft for high lift aerodynamic prediction

The aim of this work is the development of a methodology to predict lift characteristics for transport aircraft in the whole flight envelope, useful in the preliminary aircraft design stage. The purpose is an attempt to improve the classical methodologies for wing load distribution and lift prediction, considering the airfoils aerodynamic characteristics until stall and post stall conditions during the process, and modifying 2D characteristics in case of high lift devices to take into account 3D effects introduced by the devices themselves. The method is a modification of Nasa Blackwell procedure, capable to predict wing stall aerodynamic characteristics for both clean and flapped configuration. As far the high lift devices effect is concerned, the improved method works substituting clean airfoil aerodynamic characteristics with the flapped aerodynamics ones, and introducing a correction to evaluate the 3D effects induced by high lift devices geometrical discontinuities. The results of the developed method have been compared with CFD and experimental data showing good agreement, making available a fast and reliable method, useful in preliminary aircraft design.

Robust optimization of a rudder hinge system taking into account uncertainty in airframe parameters

For a tier 1 supplier of aircraft components it is essential to develop components that can absorb changes in its requirements without having a negative influence on the supplier’s profit margin. In order to achieve this, the effect of design changes needs to be investigated early in the design process. To realize this vision the design process must be highly automated and incorporate solution finding techniques such as Design Of Experiments (DOE’s) and optimizations. In this paper a framework is presented that estimates the weight and cost of an aircraft rudder hinge system. This framework has been researched and developed within the context of the H2020 AGILE project to support 3rd generation multidisciplinary design optimization teams .The process is fully automated and packaged in the Process Integration and Design Optimization (PIDO) tool Optimus. This packaging allows the generation of DOE data with which robustness analyses can be performed. The robustness analysis presented in this paper is the response of the rudder hinge system to a change in design loads. It is shown that the best design found in a deterministic approach, so looking at one design point only, is not the best design available from a robustness point of view. In this way the value of robustness analysis in the design process of aircraft components is demonstrated.

Overview of MDO enhancement in the AGILE project: A clustered and surrogate-based MDA use case

This paper presents innovative methodological investigations performed as research activities in the field of MDO for conceptual aircraft in the ongoing EU-funded research project AGILE. The next generation of aircraft Multidisciplinary Design and Optimization processes is developed in AGILE, which targets significant reduc- tions in aircraft development costs and time to market, leading to cheaper and greener aircraft solutions. The paper introduces the AGILE project structure and recalls the achievements of the 1st year (Design Campaign 1 or DC-1) leading to a reference distributed MDO system. Design Campaign 2 (DC-2) is briefly described, investigating the ease of the optimization of complex workflows, characterized by a high degree of discipline interdependencies, high number of design variables in the context of multilevel and multipartner collaborative engineering projects. The paper focuses on an innovative approach where a complex workflow has been simplified and implemented by using surrogate models for clusters of disciplines to reduce the computational time. The paper will detail the different steps of the retained approach to set up and operate this test case, involving a team of surrogate specialists, and taking advantage of the AGILE framework.

Collaborative design of aircraft systems - Multi-Level Optimization of an aircraft rudder

The design and development of modern aircraft is a complex process involving many actors from different companies, e.g. the aircraft Original Equipment Manufacturer (OEM) and suppliers of (sub)systems and parts. The suppliers are responsible for their own system or part design, while the OEM is responsible for the overall aircraft design and the interfaces between the aircraft systems and parts. A system design that is optimal from system or part perspective may not be optimal from the global aircraft perspective. In order to avoid costly redesign iterations there is a need to optimize both the design of the overall aircraft and of its systems in an integrated way. This paper describes two methods for applying Multi-Level Optimization (MLO), in order to integrate the local system/part design optimization within the global aircraft design optimization. The design of an aircraft rudder is applied as use case. The use case addresses the coupling of a specific aircraft design analysis with a specific rudder design analysis and the global and local optimizations. First the MLO method Analytical Target Cascading (ATC) is applied to a theoretical example of fictive rudder design. Second a surrogate-based MLO approach is applied to a collaborative aircraft rudder design study involving multi-partner analysis tools. Both methods illustrate that applying MLO provides insight into the coupled design problem both for the OEM and for the supplier and reduces development time.

CMDOWS: A proposed new standard to store and exchange MDO systems

This paper proposes a new format to store and exchange multidisciplinary design optimization (MDO) sys- tems. Here, the generic term MDO system refers to the organized set of disciplinary tools, and their ex- changed data and the process connections that, all together, define an MDO computational setup. In the process leading to the formal specification of such a computational system, i.e. starting from a repository of disciplinary tools, down to the specification of the actual optimization problem and finally to the implementa- tion of a specific MDO architecture, the aforementioned set of tools, data and connections evolves, until the complete MDO system formulation (thus not yet executable) is reached. The proposed new standard, called CMDOWS (Common MDO Workflow Schema), has been developed to enable this process by providing a means to store and exchange any MDO system and its associated information in a neutral format. Further- more, CMDOWS provides the starting point to translate any MDO system formulation into an executable computational workflow, by means of a Process Integration and Design Optimization (PIDO) tool of choice. To the authors’ knowledge, such an exchange format does currently not exist, notwithstanding the enormous potential it would have for the exploitation of large-scale MDO in industry. CMDOWS is one of the outcomes of the EU project AGILE, where one of the main goals is to reduce the development time of distributed MDO workflows created by large and heterogeneous teams of experts. CMDOWS is an XML schema (XSD) that, in its set-up and structure, shows similarities with the Common Parametric Aircraft Configuration Schema (CPACS) developed by the German Aerospace Center (DLR), which is becoming a de-facto standard to store and exchange aircraft design and performance data. Whereas CPACS allows the user to store aircraft data in a standard format, CMDOWS enables the storing the specification of a full system of multidisciplinary tools, including the data and process links between its various operating blocks (e.g. disciplinary tools, objective and constraint functions, optimizers, convergers, etc.). The key aspect of this proposed format for MDO sys- tems is its neutral XML-based data representation, which is both human-readable and machine-interpretable, making any stored MDO system exchangeable between the design team members and the applications de- veloped to support the team in setting up the MDO system. The latter form of exchangeability is a key enabler for the creation of a versatile MDO framework that includes applications such as tool repositories, MDO system formulation platforms, visualization packages, and collaborative workflow execution platforms. The CMDOWS definition is available, including examples, through a publicly available software repository. Although the schema is under continuous development within the AGILE project, a case study demonstrating the use of CMDOWS version 0.6 in the AGILE MDO framework is presented in this paper. Based on this case study, it can be concluded that the current version of CMDOWS already provides a robust standard to exchange MDO systems between MDO framework applications. The schema will be extended to meet future developments and promote its adoption as a recognized standard in the broader MDO community.

MDO architectures comparison on analytical test case and aerostructural aircraft system design problem

An aircraft system design problem is intrinsically a multidisciplinary problem. If the design configuration is unconventional, sound low-fidelity analysis methods are not available. Complex hi- fidelity tools are often the only solution to obtain reliable results, and for these reasons designers are deeply interested in the interactions and organization of these tools. Inside a Multidisciplinary Design Optimization (MDO) process, different architectures are possible. Analysis and comparison of six MDO architectures is the aim of this paper. The considered architectures are All-At-Once (AAO), Simultaneous Analysis and Design (SAND), Individual Discipline Feasible (IDF), Multidisciplinary Feasible (MDF), Collaborative Optimization (CO), Bi-Level Integrated System Synthesis (BLISS). The comparison is conducted on mathematical benchmark cases and on a simplified aerostructural aircraft design problem. Results expressed in a unified nomenclature are available as open source. Further, the CMDOWS (Common MDO Workflow Schema) developed in the AGILE project is used to translate the neutral description of the MDO problem into an executable implementation and it will be released as open source too. The aim is to promote the discussion on MDO architectures within the MDO research community.

Disciplinary data fusion for multi-fidelity aerodynamic application

This paper presents some multi-fidelity activities in the field of aerodynamic in the ongoing EU-funded re- search project AGILE. Different computation tools relative to different level of fidelity are used in the project and the idea is to combine all the data in a global surrogate model to reduce the computational time in an optimization process for instance. The paper focuses on the data fusion tool embedded in the AGILE frame- work with the choice of the surrogate models, the choice of the tool’s fidelity and the choice of the sampling points via an iterative process. The paper will detail the different steps of the proposed approach to set up and operate the data fusion service proposed to the AGILE partners.

Uncertainty quantification and robust design optimization applied to aircraft propulsion systems

The standard way of formulating optimization problems applied to aircraft design is based on the assumption that the underlying system is deterministic, i.e., that the knowledge associated with the design variables and with the system dynamic is not characterized by uncertainty. However, in real conditions randomness impacts the formulation of the design process in multiple ways and the system outputs (i.e., the key performance indicators and the design constraints) are also affected by uncertainty. A system designed under deterministic assumptions may therefore have an unreliable behavior due to the fluctuations associated with the input random variables. This problem can be tackled by adopting a probabilistic approach and re-formulating the design optimization problem with an additional set of constraints associated with the robustness / reliability of the target system. This work addresses the problem of optimizing the geometry of a turbofan engine nacelle subject on reliability constraints. An advanced, machine-learning based framework is adopted in order to (a) investigate the system behavior through an adaptive design of experiments technique and (b) build accurate surrogate models of the system dynamics. These surrogate models are then employed to run a set of probabilistic studies at an affordable computational cost. The results of these investigations include (a) an extensive suite of analyses aimed at characterizing the uncertainty associated with the output quantities of interest; (b) a robust optimization of the engine nacelle geometry and (c) an assessment of the reliability of the optimized design. The improved performance and reliability of the design, together with the limited number of overall system evaluations required to run the analyses, demonstrate the effectiveness and the engineering applicability of the proposed approach.

Airframe - On board system - Propulsion system optimization for civil transport aircraft: AGILE EU project

As part of H2020 EU project “AGILE”, a Collaborative System of Systems Multidisciplinary Design Optimization research approach is presented in this paper. An approach to integrate airframe design analysis, as well as propulsion system, aircraft on-board systems, aerodynamics, structures and emission analysis in the early design process is presented. Moreover, the aim of this approach is to exploit the coupling parameters in an integrated analysis and optimization approach. Further, the disciplinary analysis modules from multiple organizations involved in the optimization are integrated within a distributed framework. The disciplinary analysis tools are not shared, but only the data is shared between partners through a secured network of framework. The collaborative design process is implemented by making use of XML based standard Common Parametric Aircraft Configuration Scheme (CPACS), which is the basis for communication within distributed framework to exchange model information between the multi-disciplinary analysis modules and between partner organizations involved in the research activity. The framework is validated with a regional jet passenger reference aircraft. The Sensitivity of varying Engine By Pass Ratio, On-Board System Architectures (Conventional/More Electric/All Electric) is performed through disciplinary modules, effects propagated and its impact on overall aircraft performance in terms of Fuel Burn, Emission and Life Cycle Cost is presented.

Automated selection of airliner optimal on-board systems architecture within MDO collaborative environment

The test case described in the paper is a multidisciplinary design optimization (MDO) aimed at the identification of the best on-board system architecture on the basis of its production and operative costs. Other researcher have focused their attention in the selection of more suitable system architecture [1], however, in the present work, one of the key objective was to develop a collaborative multidisciplinary optimization environment able to propagate the effects of the chosen architecture on engine and actuator fairings and consequently on engine performance (fuel consumption) and aerodynamic properties (total drag). The collaborative MDO has been implemented using a commercial PIDO, Optimus by Noesis Solutions; this has been used to connect four different analysis tools (developed and operated by Politecnico di Torino, Leonardo Aircraft-Alenia and CIAM) adopting the communication protocols that have been developed within AGILE.

Low speed take-off aerodynamic analysis

In the frame of the EU funded H2020 project AGILE (Aircraft 3rd Generation MDO for Innovative Collab- oration of Heterogeneous Teams of Experts) detailed CFD simulations were made to analyze the high lift system of an optimized regional aircraft. The paper presents shortly how the different components of the aircraft were obtained and integrated in a model suitable to perform the simulations. High-fidelity RANS (Reynolds-Averaged Navier-Stokes) CFD calculations were carried out, with a focus on take-off conditions, and aerodynamic coefficients as well as flow field distributions were extracted. The results are discussed, and point out in one hand the reliability of high-fidelity CFD simulations to highlight detailed flow phenomena like flow separations, and in another hand the importance to consider low speed flow regimes (take-off or landing) in an aircraft design and optimization process.

Knowledge-based automatic airframe design using CPACS

The CPACS data format [1, 2] has long been established as the primary means of data exchange in preliminary aircraft design projects within DLR. As described by Scherer et al. [3], it contains a wide range of options for describing the structural layout of a design including frames and stringers, floors, bulkheads, etc. Based on these descriptions, several finite element model generators comparable to the one described by Walther et al. [4] have been implemented, which can provide detailed computational structural models of a given design. However, all model generators require the information on the structural layout to be available in CPACS upfront. Within a larger aircraft design context, this necessitates the augmentation of the description of the structure to a given plain aircraft geometry. So far, this has been accomplished through a manual process, which not only results in an increased risk of errors, but also prohibits the exposure of parameters to a larger multidisciplinary optimization. In the presented paper, a newly developed knowledge-based airframe augmentation module will be introduced. Implemented in Python, it provides methods to automatically initialize a full structural layout on a given CPACS geometry, based on a manageable number of control parameters. In addition to an outline of the governing design rules, several application cases will also be given.