A Fully Automated Chain from MDAO Problem Formulation to Workflow Execution

A Fully Automated Chain from MDAO Problem Formulation to Workflow Execution

van Gent, I. (TU Delft Flight Performance and Propulsion)
Lombardi, R. (NOESIS Solutions)
la Rocca, G. (TU Delft Flight Performance and Propulsion)
d'Ippolito, R (NOESIS Solutions)

2017

In this paper, a methodology to connect the multidisciplinary design analysis and optimization (MDAO) problem formulation tool KADMOS and the commercial Process Integration and Design Optimization (PIDO) platform Optimus is presented. This capability has been developed in the context of the EU project AGILE. The aim of this development is to create a combined environment that gives the MDAO design team the ability to define and formalize an MDAO
problem and directly execute it with ease, without the need of the otherwise needed manual operations typically required to define the workflow in the PIDO system. The combination of problem formulation and PIDO platform execution have been tested on a small analytical MDAO problem to demonstrate its viability. Furthermore, a realistic aerostructural MDAO system of industrial relevance was also used to demonstrate the scalability of the approach for a bigger and more complex MDAO system. Results indicate that a fully automated chain is indeed possible which will make it easier for design teams to define, execute and compare different MDAO problem definitions and architectures in the time usually necessary to implement one MDAO system. Future work will focus on extending the proven capabilities of the automated chain to a wider variety of design problems and MDAO architectures.

MDO
MDAO
Design automation
PIDO
Systems Engineering
KADMOS
CMDOWS
Optimus

http://resolver.tudelft.nl/uuid:1b0841b5-f6a6-4750-8490-0e83e8347c10

EUROGEN 2017 September 13-15, 2017, Madrid, Spain

International Conference on Evolutionary and Deterministic Methods for Design Optimization and Control with Applications to Industrial and Societal Problems, 2017-09-13 → 2017-09-15, Madrid, Spain

Institutional Repository

conference paper

© 2017 I. van Gent, R. Lombardi, G. la Rocca, R d'Ippolito