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Geometry Based Design Automation: Applied to Aircraft Modelling and Optimization
Linköping University, Department of Management and Engineering, Machine Design. Linköping University, The Institute of Technology.
2012 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Product development processes are continuously challenged by demands for increased efficiency. As engineering products become more and more complex, efficient tools and methods for integrated and automated design are needed throughout the development process. Multidisciplinary Design Optimization (MDO) is one promising technique that has the potential to drastically improve concurrent design. MDO frameworks combine several disciplinary models with the aim of gaining a holistic perspective of a system, while capturing the synergies between different subsystems. Among all disciplines, the geometric model is recognized as playing a key role, because it collects most of the data required to any other disciplinary analysis. In the present thesis, methodologies to enable multidisciplinary optimization in early aircraft design phases are studied. In particular, the research aims at putting the CAD geometric model in the loop. This requires the ability to automatically generate or update the geometric model, here referred to as geometry-based design automation.

The thesis proposes the use of Knowledge Based Engineering (KBE) techniques to achieve design reuse and automation. In particular, so called High Level CAD templates (HLCts) are suggested to automate geometry generation and updates. HLCts can be compared to parametric LEGO® blocks containing a set of design and analysis parameters. These are produced and stored in libraries, giving engineers or a computer agent the possibility to first topologically select the templates and then modify the shape of each template parametrically.

Since parameterization is central to modelling by means of HLCts, a thorough analysis of the subject is also performed. In most of the literature on MDO and KBE two recurring requirements concerning the geometrical model are expressed: the model should be flexible and robust. However, these requirements have never been properly formulated or defined. Hence, in the thesis a mathematical formulation for geometry model robustness and flexibility are proposed. These formulations ultimately allow the performance of geometric models to be precisely measured and compared.

Finally, a prototyping and validation process is presented. The aim is to quickly and cost-effectively validate analytical results from an MDO process. The proposed process adopts different manufacturing techniques depending on the size and purpose of the intended prototype. In the last part of the thesis, three application examples are presented. The examples are chosen from research projects that have been carried out at Linköping University and show how the proposed theoretical results have been successfully employed in practice.

Abstract [sv]

Kraven på ökad effektivitet utmanar ständigt  produktutvecklingsprocessen. I och med att ingenjörsprodukter blir allt mer komplexa, växer genom hela utvecklingsprocessen behovet av verktyg och metoder för integrerad och automatiserad design. Multidisciplinär Design Optimering (MDO) är en lovande teknik som kan drastiskt förbättra parallell design. I ett MDO ramverk är flera disciplinära modeller sammankopplade för att uppnå ett holistiskt systemperspektiv, men där synergierna mellan olika delsystem också kan fångas upp. Bland alla möjliga discipliner spelar geometrimodellen en central roll, eftersom den innefattar en stor del av all information som är nödvändig för andra disciplinära analyser.

I avhandlingen studeras ett flertal metoder för att möjliggöra multidisciplinär optimering i de tidigaste faserna av flygplansdesign. I synnerlighet är forskningen riktad mot att införa geometriska CAD modeller i designloopen. Det blir därmed nödvändigt att kunna automatiskt generera eller uppdatera geometriska modeller, vilket i avhandlingen kallas för ”geometribaserad design automation”.

Avhandlingen förordar att Knowledge Based Engineering (KBE) tekniker används för att konstruktioner skall kunna automatiseras och återanvändas. Så kallade Hög Nivå CAD mallar (på engelska High Level CAD templates – HLCts) föreslås för att automatiskt generera och uppdatera geometrimodeller. HLCts kan jämföras med parametriska LEGO® klossar som innehåller variabler för design och analys. Mallarna kan samlas i bibliotek; därefter har konstruktörer eller dator agenter möjligheten att först topologiskt välja en mall och sedan ändra på dess utförande genom utvalda parametrar.

Eftersom parameterisering är ett centralt begrepp för HLCt principen, föreslås även en fördjupad analys av ämnet. I stor del av MDO och KBE litteraturen ställs det två återkommande krav på geometrimodellen: modellen bör vara flexibel och robust. Eftersom dessa krav aldrig har getts en formell formulering, förordas i avhandlingen en matematisk beskrivning av modellrobusthet och - flexibilitet. Tack vore formuleringen är det möjligt att noggrant mäta och jämföra till vilken grad geometriska modeller fungerar.

Slutligen presenteras en valideringsprocess baserad på kostnadseffektiva prototyper som används för att snabbt bekräfta analytiska resultat från MDO ramverket. Den föreslagna processen nyttjar olika tillverkningsmetoder, beroende på prototypens tänkta storlek och användning. I sista delen av avhandlingen presenteras även tre applikationsexempel, valda från forskningsprojekt som har bedrivits på Linköpings universitet och som visar hur de teoretiska resultaten har kommit till användning i praktiken.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press , 2012. , 87 p.
Series
Linköping Studies in Science and Technology. Dissertations, ISSN 0345-7524 ; 1418
National Category
Mechanical Engineering
Identifiers
URN: urn:nbn:se:liu:diva-73109ISBN: 978-91-7519-986-3 (print)OAI: oai:DiVA.org:liu-73109DiVA: diva2:466519
Public defence
2012-01-27, C4, Hus C, Campus Valla, Linköpings universitet, Linköping, 10:15 (English)
Opponent
Supervisors
Available from: 2011-12-16 Created: 2011-12-16 Last updated: 2011-12-21Bibliographically approved
List of papers
1. Automated Design and Fabrication of Micro Air Vehicles
Open this publication in new window or tab >>Automated Design and Fabrication of Micro Air Vehicles
2011 (English)In: Journal of Aerospace Engineering, ISSN 0893-1321, E-ISSN 1943-5525, Vol. 226, no 10, 1271-1282 p.Article in journal (Refereed) Published
Abstract [en]

A methodology for an automated design and fabrication of micro-air vehicles (MAVs) is presented. A design optimization framework has been developed that interfaces several software systems to generate MAVs to optimally fulfil specific mission requirements. By means of amulti-objective genetic algorithm, families of MAVs are tailored with respect to objectives such as weight and endurance. The framework takes into consideration the airframe and aerodynamic design as well as the selection and positioning of internal components. The selection of propulsion system components is made from a database of off-the-shelf components. In combination with a three-dimensional printer, physical prototypes can be quickly manufactured. A validation of the framework results from flight tests of a real MAV is also presented.

Place, publisher, year, edition, pages
SAGE Journals online, 2011
Keyword
Micro Air Vehicle; multidisciplinary optimization; multi-objective optimization; genetic algorithm; CAD automation; design automation
National Category
Mechanical Engineering
Identifiers
urn:nbn:se:liu:diva-73107 (URN)10.1177/0954410011419612 (DOI)000312145300006 ()
Available from: 2011-12-16 Created: 2011-12-16 Last updated: 2017-12-08Bibliographically approved
2. Flexible and Robust CAD Models for Design Automation
Open this publication in new window or tab >>Flexible and Robust CAD Models for Design Automation
2012 (English)In: Advanced Engineering Informatics, ISSN 1474-0346, E-ISSN 1873-5320, Vol. 26, no 2, 180-195 p.Article in journal (Refereed) Published
Abstract [en]

This paper explores novel methodologies for enabling Multidisciplinary Design Optimization (MDO) of complex engineering products. To realize MDO, Knowledge Based Engineering (KBE) is adopted with the aim of achieving design reuse and automation. The aim of the on-going research at Linköping University is to shift from manual modelling of disposable geometries to Computer Aided Design (CAD) automation by introducing generic high-level geometry templates. Instead of repeatedly modelling similar instances of objects, engineers should be able to create more general models that can represent entire classes of objects. The proposed methodology enables utilization of commercial design tools, hence taking industrial feasibility into consideration. High Level CAD templates (HLCt) will be proposed and discussed as the building blocks of flexible and robust CAD models, which in turn enables high-fidelity geometry in the MDO loop. Quantification of the terms flexibility and robustness is also presented, providing a means to measure the quality of the geometry models. Finally, application examples are presented in which the outlined framework is evaluated. The applications have been chosen from three ongoing research projects aimed at automating the design of transport aircraft, industrial robots, and micro air vehicles.

Keyword
Design automation, Multidisciplinary Design Optimization, Robustness, Flexibility, Knowledge-Based Engineering
National Category
Mechanical Engineering
Identifiers
urn:nbn:se:liu:diva-73108 (URN)10.1016/j.aei.2012.01.004 (DOI)000308122400003 ()
Available from: 2011-12-16 Created: 2011-12-16 Last updated: 2017-12-08Bibliographically approved
3. Development of a subscale flight testing platform for a generic future fighter
Open this publication in new window or tab >>Development of a subscale flight testing platform for a generic future fighter
2010 (English)Conference paper, Published paper (Refereed)
Abstract [en]

One branch of the current research in aircraft design at Linköping University is focused on fast concept evaluation in early design stages. This covers multidisciplinary optimization using tools of different level of complexity and low-cost subscale flight testing. In some cases a flight test will provide more answers than several computations ever could. In order to achieve this goal a methodology is required to allow fast creation of subscale flying concepts and to obtain as much reliable information as possible from the tests. The methodology is currently being developed. One important part of it is the scaling methodology and the imposed requirements on manufacturing. The present paper presents the latest subscale demonstrator from Linköping University that has been built as part of the study initiated by the Swedish Material Board on a Generic Future Fighter aircraft.

Keyword
subscale, demonstrator, flight testing
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-62594 (URN)
Conference
27TH INTERNATIONAL CONGRESS OF THE AERONAUTICAL SCIENCES - ICAS 2010
Available from: 2011-11-10 Created: 2010-11-30 Last updated: 2011-12-16Bibliographically approved
4. Evaluation of Automatically Designed Micro Air Vehicles and Flight Testing
Open this publication in new window or tab >>Evaluation of Automatically Designed Micro Air Vehicles and Flight Testing
2010 (English)Conference paper, Published paper (Refereed)
Abstract [en]

The presented work is centered on the evaluation of Micro or Mini Air Vehicles (MAV) that have been automatically designed and manufactured. An in-house developed design framework uses several coupled computer software’s to generate the geometric design in CAD, a well as list of off the shelf components for the propulsion system, and computer code for autonomous flight ready to upload in the intended autopilot. The paper describes the experiences made so far regarding automation of the design process and of manufacturing. Furthermore, it presents results from evaluation and analysis of the optimization algorithm and flight testing, and from continuing work with the framework to achieve deeper understanding of the process and to fine-tune the design automation performance. The flight data is correlated to the predicted performances to validate the models and design process.

Keyword
Design automation, multidisciplinary optimization, MAV
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-62584 (URN)
Conference
48th AIAA Aerospace Sciences Meeting Including the New Horizons Forum and Aerospace Exposition, Orlando, Florida, Jan. 4-7, 2010
Available from: 2011-11-10 Created: 2010-11-30 Last updated: 2011-12-16Bibliographically approved
5. Use of Panel Code Modeling in a Framework for Aircraft Concept Optimization
Open this publication in new window or tab >>Use of Panel Code Modeling in a Framework for Aircraft Concept Optimization
2006 (English)In: 11th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference, 6-8 September, Portsmouth, Virginia, USA, 2006, 7084- p.Conference paper, Published paper (Other academic)
Abstract [en]

 

 

In this study the use of a high-order panel code within a framework for aircraft concept design is discussed. The framework is intended to be a multidisciplinary optimization tool to be adopted from the very beginning of the conceptual design phase in order to define and refine the aircraft design, with respect to its aerodynamic, stability and control, structure and basic aircraft systems. The presented work is aimed at developing a module for aerodynamic analysis of concepts as a basis for a direct search optimization of the concept layout. The design criterion, used in the example presented here, is to minimize the maximum take-off weight required to fulfil the mission. Classic and simple equations are used together with the data generated by the panel code solver to calculate the aircraft’s performances. Weights are calculated by means of statistical group weight equations, but the weight could also be calculated from a CAD-model. The design of an Unmanned Combat Air Vehicle is used as test case for three different optimization algorithms: one gradient method based (Fmincon), one non-gradient based (Complex) and one Genetic Algorithm (GA). Comparison of results and performances shows that the Genetic Algorithm is best fitted for the specific problem, having the by far best hit rate, even if it is at a cost of longer computing time. The Complex algorithm requires less iterations and is also able to find the optimum solution, but with a worse hit rate, while Fmincon can not reach to a global optimum. The suggested optimized configuration for the aircraft is very similar to the Boeing X-45C and Northrop Grumman X-47B.

National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-13306 (URN)
Available from: 2011-11-10 Created: 2008-05-21 Last updated: 2011-12-16Bibliographically approved

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