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Rule-based architecture for collaborative multidisciplinary aircraft design optimisation

Rule-based architecture for collaborative multidisciplinary aircraft design optimisation
Rule-based architecture for collaborative multidisciplinary aircraft design optimisation
In aircraft design, the jump from the conceptual to preliminary design stage introduces a level of complexity which cannot be realistically handled by a single optimiser, be that a human (chief engineer) or an algorithm. The design process is often partitioned along disciplinary lines, with each discipline given a level of autonomy. This introduces a number of challenges including, but not limited to: coupling of design variables; coordinating disciplinary teams; handling of large amounts of analysis data; reaching an acceptable design within time constraints. A number of classical Multidisciplinary Design Optimisation (MDO) architectures exist in academia specifically designed to address these challenges. Their limited use in the industrial aircraft design process has inspired the authors of this paper to develop an alternative strategy based on well established ideas from Decision Support Systems. The proposed rule based architecture sacrifices possibly elusive guarantees of convergence for an attractive return in simplicity. The method is demonstrated on analytical and aircraft design test cases and its performance is compared to a number of classical distributed MDO architectures.
Multidisciplinary design optimisation, Rule Based Architecture, Aircraft Design, Decision support system
1021-1030
Jelev, Nickolay
cb200afa-2590-41b0-99ff-8f8aa78b8517
Keane, Andy
26d7fa33-5415-4910-89d8-fb3620413def
Holden, Carren M.E.
411ab81a-6161-4eef-9d23-8ffc8972b572
Sobester, Andras
096857b0-cad6-45ae-9ae6-e66b8cc5d81b
Jelev, Nickolay
cb200afa-2590-41b0-99ff-8f8aa78b8517
Keane, Andy
26d7fa33-5415-4910-89d8-fb3620413def
Holden, Carren M.E.
411ab81a-6161-4eef-9d23-8ffc8972b572
Sobester, Andras
096857b0-cad6-45ae-9ae6-e66b8cc5d81b

Jelev, Nickolay, Keane, Andy, Holden, Carren M.E. and Sobester, Andras (2017) Rule-based architecture for collaborative multidisciplinary aircraft design optimisation. International Journal of Mechanical, Aerospace, Industrial, Mechatronic and Manufacturing Engineering, 11 (5), 1021-1030. (doi:10.1999/1307-6892/10007081).

Record type: Article

Abstract

In aircraft design, the jump from the conceptual to preliminary design stage introduces a level of complexity which cannot be realistically handled by a single optimiser, be that a human (chief engineer) or an algorithm. The design process is often partitioned along disciplinary lines, with each discipline given a level of autonomy. This introduces a number of challenges including, but not limited to: coupling of design variables; coordinating disciplinary teams; handling of large amounts of analysis data; reaching an acceptable design within time constraints. A number of classical Multidisciplinary Design Optimisation (MDO) architectures exist in academia specifically designed to address these challenges. Their limited use in the industrial aircraft design process has inspired the authors of this paper to develop an alternative strategy based on well established ideas from Decision Support Systems. The proposed rule based architecture sacrifices possibly elusive guarantees of convergence for an attractive return in simplicity. The method is demonstrated on analytical and aircraft design test cases and its performance is compared to a number of classical distributed MDO architectures.

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Rule Based Architecture for Collaborative Multidisciplinary Aircraft Design Optimisation, Jelev, Keane, Holden, Sobester, (2017) - Version of Record
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Published date: May 2017
Keywords: Multidisciplinary design optimisation, Rule Based Architecture, Aircraft Design, Decision support system

Identifiers

Local EPrints ID: 418502
URI: http://eprints.soton.ac.uk/id/eprint/418502
PURE UUID: 271fe410-d396-4134-9ca7-ee5ac0e0ecd9
ORCID for Andy Keane: ORCID iD orcid.org/0000-0001-7993-1569
ORCID for Andras Sobester: ORCID iD orcid.org/0000-0002-8997-4375

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Date deposited: 09 Mar 2018 17:30
Last modified: 16 Mar 2024 03:26

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Contributors

Author: Nickolay Jelev
Author: Andy Keane ORCID iD
Author: Carren M.E. Holden
Author: Andras Sobester ORCID iD

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