Example of a third Generation MDO framework

The 3rd Generation MDO framework described in this subsection as an example has been developed within the context of the H2020 AGILE project [180]. This European project encompasses 19 partners from universities, research centers, and industries. Each partner is specialized in a design discipline, as structural design, propulsion system analysis, costs evaluation, optimization processes, collaboration techniques, process integration. The on-board system design discipline – or rather, the subsystem design tool ASTRID – has been integrated within the hereunder described MDO framework in the context of the doctorate. The main objective of the AGILE project is to reduce the aircraft development process – and therefore the TTM – implementing a more competitive supply chain at the early stage of the design [111]. In other words, the ambition of this project is to develop an innovative multidisciplinary design framework, integrating advanced design and optimization techniques and enhancing the collaboration of several experts with different skills, backgrounds and affiliations. One of the main innovations of the AGILE 3rd Generation MDO framework is represented by the inclusion of the subsystems design. Therefore, the hereunder described framework can be also employed for the assessment of subsystem impacts on the other design disciplines since the conceptual design phase. In particular, applications of the AGILE MDO framework proposed in Chapter 4 will show some of these impacts on the OAD, mainly due to masses and power offtakes of different on-board system architectures.

The main elements of this kind of innovative MDO environment are three. The first one is an engineering framework software for the management of the development process and the optimization. This type of tool is named Process Integration and Design Optimization (PIDO) environment. In particular, two kinds of PIDO software are employed in AGILE. The first one is the “Remote Component Environment” (RCE) [181] developed by the German Aerospace Center DLR. The second commercial tool is “Optimus” framework [182], provided by NOESIS Solutions.

The second main element required for a 3rd Generation MDO framework is a common namespace for the exchange of information between the disciplinary

Step 4: Implement and verify the design framework 95 experts, hence supporting the collaboration among different experts. This central data model is represented by CPACS (see subsection 1.3.1).

The last element is represented by the disciplinary tools. This modules should be able to extract the required information from the CPACS, and then upload the obtained results. Furthermore, the disciplinary modules shall be implemented within a PIDO framework, in order to connect them together in a single design process. An example of disciplinary tool concerning the preliminary design of aircraft subsystems is presented in subsection 3.3.2.

Actually, an additional element is required to enable the interconnections among the disciplinary tools. For this purpose, a software named Brics has been coded by the Dutch Aerospace Center NLR [183]. Brics encompasses all the technologies required to support the realization of cross-organization collaborative workflows, for instance complying with companies IT security constraints.

More details concerning the MDO framework developed in the AGILE project and about the integration of the aircraft subsystems design module within this collaborative framework are presented in the following subsection.

The AGILE framework

In Figure 32 is depicted an example of a 3rd Generation MDO framework. It represents an OAD process implemented within the AGILE project [119].

From the figure it is possible to note the cross-organizational, distributed and multi-disciplinary aspects of the proposed design framework. A few design disciplines are involved within this design process. These design disciplines are analyzed by different European, Russian and Canadian partners distributed in several locations.

Among all the disciplines encompassed inside the proposed framework, in the current dissertation the attention is focused on the aircraft subsystems preliminary design. In particular, the integration of this discipline within the MDO environment is hereafter described. Case studies and results concerning the framework of Figure 32 are instead proposed and discussed in Chapter 4.

Figure 33 shows the implementation of the subsystems preliminary design tool, ASTRID, integrated within the PIDO software Optimus. This version of ASTRID is coded in Matlab language and it fulfils two prerequisites:

96 Integration of subsystems design in a collaborative MDO process

Step 4: Implement and verify the design framework 97 1) It runs without any user interaction. An MDO process might be

characterized by thousands loops and iterations. Thus, all the required tool inputs shall be provided automatically once evaluated from the other design disciplines, or must be initialized before the tool execution.

2) It is executable from command line. This command is automatically given by the workflow instead of the disciplinary expert.

Figure 33: Implementation of ASTRID within the AGILE MDO framework. The prerequisites compliant version of ASTRID implemented within the framework receives two input files. The first one is represented by the CPACS input xml file. It is updated on the basis of the results obtained during the previous disciplinary analyses. For instance, the primary surfaces hinge moment evaluated by the aerodynamic tools is employed by ASTRID for the sizing of the actuation systems. The second input file, named “Astrid_INPUT_EXT.m”, contains all the specific parameters peculiar of the subsystems design discipline, for instance types of electric voltage and hydraulic system pressure. These values are not provided by any disciplinary module of the workflow, but it is the responsibility of the on-board systems expert to define them.

Once ASTRID has completed the execution and the results from this analysis have been derived, the CPACS file is updated with the new outputs and then passed to other disciplines. Both the input and the output files are exchanged with the other disciplines by means of “Brics” software. The CPACS files are stored inside a server hosted at the DLR of Hamburg, in Germany. From the workflow of Figure 33 it can be seen that two “Brics” interfaces are integrated to download and upload the two CPACS files.

98 Integration of subsystems design in a collaborative MDO process An example of application of a workflow analogous to the one depicted in Figure 32 will be provided in Section 4.4. In particular, other than the subsystems design tool, this version of 3rd Generation MDO framework encompasses the following main disciplinary modules:

1) Aircraft synthesis: the module includes aerodynamic and structural analyses. It is implemented within the tool VAMPzero owned by the German research center DLR ( [51], [184]). The main aircraft aerodynamic characteristics (e.g. the drag polar) are computed through a VLM model based on the well-known AVL solver. Furthermore, the Aircraft Synthesis module calculates structural loads and perform FEM based structural analyses.

2) Low speed aerodynamics: both University of Naples and the Swiss company CFS Engineering provide expertise regarding the aircraft aerodynamics, focusing on the detailed design of the high lift devices. 3) Propulsion: the Russian Central Institute of Aviation Motor Development

(CIAM) is in charge of modelling the propulsion system. Preliminary results including engine sizing and performance are obtained by means of the commercial tool GasTurb v12 ( [87], [88]).

4) Nacelle and airframe integration: the aerodynamic characteristics of the nacelle and its integration with the airframe are investigated by Russian institute TsAGI [185]. Firstly, the aerodynamic analysis of the isolated nacelle is investigated according to the ambient flow, engine geometry and engine gas dynamics properties. Then, the coupling influences among the nacelle and the airframe are investigated.

5) Mission performance: the aircraft performance relative to each mission phase is computed by a module developed by DLR. This tool requires input concerning the airplane aerodynamics, the engine performance, the aircraft weights to estimate the block and reserve fuel required during a predefined mission.

6) Cost analysis: the LCC of the aircraft is assessed by means of a simulation tool developed by the Institute of Aerospace Systems of RWTH Aachen University. Semi-empirical methods described in [186] and [187] are implemented within the module for the evaluation of both recurring and non-recurring costs.

Step 5: Create and select the design solution 99