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Multidisciplinary Design Optimization of Aerial Vehicles: A Review of Recent Advancements
Linköping University, Department of Management and Engineering, Machine Design. Linköping University, Faculty of Science & Engineering.
Linköping University, Department of Management and Engineering, Machine Design. Linköping University, Faculty of Science & Engineering.
Linköping University, Department of Management and Engineering, Machine Design. Linköping University, Faculty of Science & Engineering.
Linköping University, Department of Management and Engineering, Machine Design. Linköping University, Faculty of Science & Engineering.
2018 (English)In: International Journal of Aerospace Engineering, ISSN 1687-5966, E-ISSN 1687-5974, article id 4258020Article, review/survey (Refereed) Published
Abstract [en]

The aim of this paper is to present the most common practices in multidisciplinary design optimization (MDO) of aerial vehicles over the past decade. The literature sample is identified through established internet search engines, and a stringent review methodology is implemented in order to ensure the selection of the most relevant sources. In this work, the primary emphasis is on the assessment of the state-of-the-art framework development strategies, while at a secondary level, the objective is to identify the possible improvement directions by evaluating the research trends and gaps. As an additional contribution, statistical studies are also provided, and it is shown how MDO of aerial vehicles has evolved in terms of problem formulation, disciplinary modeling, analysis capabilities, tool implementation, and general applicability. Given this foundation as well as the results of the review, this work concludes by presenting a roadmap for guiding academia and industry in respect to the application of MDO on aerial vehicles. Overall, the roadmap together with the literature review is not only expected to serve as a guide for newcomers into the MDO field but also as an elementary basis which will allow researchers to conduct additional studies in this important and constantly evolving area of design.

Place, publisher, year, edition, pages
HINDAWI LTD , 2018. article id 4258020
National Category
Software Engineering
Identifiers
URN: urn:nbn:se:liu:diva-149403DOI: 10.1155/2018/4258020ISI: 000434182500001OAI: oai:DiVA.org:liu-149403DiVA, id: diva2:1229227
Note

Funding Agencies|Vinnova IMPOz project [2013-03758]

Available from: 2018-06-29 Created: 2018-06-29 Last updated: 2019-11-13
In thesis
1. Design Optimization of Unmanned Aerial Vehicles: A System of Systems Approach
Open this publication in new window or tab >>Design Optimization of Unmanned Aerial Vehicles: A System of Systems Approach
2019 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Over the last years, Unmanned Aerial Vehicles (UAVs) have gradually become a more efficient alternative to manned aircraft, and at present, they are being deployed in a broad spectrum of both military as well as civilian missions. This has led to an unprecedented market expansion with new challenges for the aeronautical industry, and as a result, it has created a need to implement the latest design tools in order to achieve faster idea-to-market times and higher product performance.

As a complex engineering product, UAVs are comprised of numerous sub-systems with intricate synergies and hidden dependencies. To this end, Multidisciplinary Design Optimization (MDO) is a method that can identify systems with better performance through the concurrent consideration of several engineering disciplines under a common framework. Nevertheless, there are still many limitations in MDO, and to this date, some of the most critical gaps can be found in the disciplinary modeling, in the analysis capabilities, and in the organizational integration of the method.

As an aeronautical product, UAVs are also expected to work together with other systems and to perform in various operating environments. In this respect, System of Systems (SoS) models enable the exploration of design interactions in various missions, and hence, they allow decision makers to identify capabilities that are beyond those of each individual system. As expected, this significantly more complex formulation raises new challenges regarding the decomposition of the problem, while at the same time, it sets further requirements in terms of analyses and mission simulation.

In this light, this thesis focuses on the design optimization of UAVs by enhancing the current MDO capabilities and by exploring the use of SoS models. Two literature reviews serve as the basis for identifying the gaps and trends in the field, and in turn, five case studies try to address them by proposing a set of expansions. On the whole, the problem is approached from a technical as well as an organizational point of view, and thus, this research aims to propose solutions that can lead to better performance and that are also meaningful to the Product Development Process (PDP).

Having established the above foundation, this work delves firstly into MDO, and more specifically, it presents a framework that has been enhanced with further system models and analysis capabilities, efficient computing solutions, and data visualization tools. At a secondary level, this work addresses the topic of SoS, and in particular, it presents a multi-level decomposition strategy, multi-fidelity disciplinary models, and a mission simulation module. Overall, this thesis presents quantitative data which aim to illustrate the benefits of design optimization on the performance of UAVs, and it concludes with a qualitative assessment of the effects that the proposed methods and tools can have on both the PDP and the organization. 

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2019. p. 81
Series
Linköping Studies in Science and Technology. Dissertations, ISSN 0345-7524 ; 2018
National Category
Production Engineering, Human Work Science and Ergonomics
Identifiers
urn:nbn:se:liu:diva-161915 (URN)10.3384/diss.diva-161915 (DOI)9789175190013 (ISBN)
Public defence
2019-12-06, Hörsal C3, C-huset, Campus Valla, Linköping, 10:15 (English)
Opponent
Supervisors
Funder
Vinnova
Available from: 2019-11-13 Created: 2019-11-13 Last updated: 2019-12-11Bibliographically approved

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