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  • 1.
    Papageorgiou, Athanasios
    Linköping University, Department of Management and Engineering, Machine Design. Linköping University, Faculty of Science & Engineering. 202100-3096.
    Design Optimization of Unmanned Aerial Vehicles: A System of Systems Approach2019Doctoral 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. 

    List of papers
    1. Multidisciplinary Design Optimization of Aerial Vehicles: A Review of Recent Advancements
    Open this publication in new window or tab >>Multidisciplinary Design Optimization of Aerial Vehicles: A Review of Recent Advancements
    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
    National Category
    Software Engineering
    Identifiers
    urn:nbn:se:liu:diva-149403 (URN)10.1155/2018/4258020 (DOI)000434182500001 ()
    Note

    Funding Agencies|Vinnova IMPOz project [2013-03758]

    Available from: 2018-06-29 Created: 2018-06-29 Last updated: 2019-11-13
    2. The Role of Multidisciplinary Design Optimization (MDO) in the Development Process of Complex Engineering Products
    Open this publication in new window or tab >>The Role of Multidisciplinary Design Optimization (MDO) in the Development Process of Complex Engineering Products
    2017 (English)In: DS 87 Proceedings of the 21st International Conference on Engineering Design (ICED 17): Vol 4: Design Methods and Tools, Vancouver, Canada, 21-25.08.2017 / [ed] Anja Maier, Stanko Škec, Harrison Kim, Michael Kokkolaras, Josef Oehmen, Georges Fadel, Filippo Salustri, Mike Van der Loos, Design Society , 2017, Vol. 4, p. 109-118Conference paper, Published paper (Other academic)
    Abstract [en]

    The work presented in this paper explores several concepts related to the design of complex engineering products and emphasizes on the effects of considering Multidisciplinary Design Optimization (MDO) in the development process. This paper is by no means a comprehensive literature review, but instead, the aim is to discuss some key points through theory and references to common MDO applications. In this respect, the central topics which are addressed herein are the enhancement of the generic product development process, the road towards a better integration of the organization’s functions, the methods to manage complex system architectures, and finally, the shortcomings of the MDO field. As a link to more tangible industrial applications, Unmanned Aerial Vehicles (UAVs) are chosen as an illustrative example due to their technical complexity as well as the demanding requirements of the corresponding market. Overall, the paper shows that despite the current state-of-the-art limitations, MDO can be a valuable tool within the “traditional” design process that has the potential to enable products of better quality while simultaneously reducing the total development time and effort.

    Place, publisher, year, edition, pages
    Design Society, 2017
    Series
    ICED, ISSN 2220-4342
    Keywords
    Design methods, Design process, Optimization, New product development, Multidisciplinary Design Optimization
    National Category
    Other Mechanical Engineering
    Identifiers
    urn:nbn:se:liu:diva-142278 (URN)978-1-904670-92-6 (ISBN)
    Conference
    21st International Conference on Engineering Design (ICED 17)
    Available from: 2017-10-24 Created: 2017-10-24 Last updated: 2019-11-13
    3. Development of a Multidisciplinary Design Optimization Framework Applied on UAV Design by Considering Models for Mission, Surveillance, and Stealth Performance
    Open this publication in new window or tab >>Development of a Multidisciplinary Design Optimization Framework Applied on UAV Design by Considering Models for Mission, Surveillance, and Stealth Performance
    2017 (English)In: 18th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference, 2017Conference paper, Published paper (Other academic)
    Abstract [en]

    This paper presents a Multidisciplinary Design Optimization (MDO) framework that is intended to be employed in the early design stages of Unmanned Aerial Vehicles (UAVs) when the primary focus is on the tradeoffs between the mission, stealth, and surveillance performance requirements. The proposed MDO framework takes into account the aircraft’s geometry, the aerodynamics, the trim, the stability, and the simulation of the mission, but it also includes two additional models for computing the Radar Cross Section (RCS) and the sensor performance. A multi-level solution architecture is implemented in order to tackle the increased complexity of the problem, and it is shown that this type of decomposition can be a more efficient optimization approach compared to the traditional single-level formulation. The operation of the framework is evaluated through single objective optimizations by using the weighted sum method, while it is also investigated whether or not metamodels can be a viable alternative to the computationally expensive RCS and sensor analysis models. Overall, the results show that the mission, stealth, and surveillance performance are conflicting objectives, and therefore, their concurrent consideration in an optimization framework can help increase the available knowledge early on in the design of UAV applications.

    Series
    AIAA AVIATION Forum ; 2017-4151
    National Category
    Aerospace Engineering
    Identifiers
    urn:nbn:se:liu:diva-142277 (URN)10.2514/6.2017-4151 (DOI)
    Conference
    18th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference, Denver, Colorado, USA, 2017, AIAA AVIATION Forum, (AIAA 2017-4151)
    Available from: 2017-10-24 Created: 2017-10-24 Last updated: 2019-11-13
    4. Multidisciplinary Optimization of Unmanned Aircraft Considering Radar Signature, Sensors, and Trajectory Constraints
    Open this publication in new window or tab >>Multidisciplinary Optimization of Unmanned Aircraft Considering Radar Signature, Sensors, and Trajectory Constraints
    2018 (English)In: Journal of Aircraft, ISSN 0021-8669, E-ISSN 1533-3868, Vol. 55, no 4, p. 1629-1640Article in journal (Refereed) Published
    Abstract [en]

    This paper presents a multidisciplinary design optimization framework applied to the development of unmanned aerial vehicles with a focus on radar signature and sensor performance requirements while simultaneously considering the flight trajectory. The primary emphasis herein is on the integration and development of analysis models for the calculation of the radar cross section and sensor detection probability, whereas traditional aeronautical disciplines such as aerodynamics and mission simulation are also taken into account in order to ensure a flyable concept. Furthermore, this work explores the effect of implementing trajectory constraints as a supplementary input to the multidisciplinary design optimization process and presents a method that enables the optimization of the aircraft under a three-dimensional flight scenario. To cope with the additional computational cost of the high-fidelity radar cross section and sensor calculations, the use of metamodels is also investigated and an efficient development methodology that can provide high-accuracy approximations for this particular problem is proposed. Overall, the operation and performance of the framework are evaluated against five surveillance scenarios, and the obtained results show that the implementation of trajectory constraints in the optimization has the potential to yield better designs by 12–25% when compared to the more “traditional” problem formulations.

    Place, publisher, year, edition, pages
    American Institute of Aeronautics and Astronautics, 2018
    Keywords
    UAV, MDO, RCS, Trajectory, Sensors
    National Category
    Aerospace Engineering
    Identifiers
    urn:nbn:se:liu:diva-150980 (URN)10.2514/1.C034314 (DOI)000449304100025 ()2-s2.0-85050865062 (Scopus ID)
    Funder
    VINNOVA, 2013-03758
    Note

    Funding agencies: Innovative Multidisciplinary Product Optimization (IMPOz) project of Swedens innovation agency VINNOVA [2013-03758]

    Available from: 2018-09-07 Created: 2018-09-07 Last updated: 2019-11-13Bibliographically approved
    5. A Data Management and Visualization Tool for Integrating Optimization Results in Product Development
    Open this publication in new window or tab >>A Data Management and Visualization Tool for Integrating Optimization Results in Product Development
    2018 (English)In: DS 91: Proceedings of NordDesign 2018, Linköping, Sweden, 14th - 17th August 2018: DESIGN IN THE ERA OF DIGITALIZATION / [ed] Ekströmer, Philip; Schütte, Simon and Ölvander, Johan, 2018Conference paper, Published paper (Other academic)
    Abstract [en]

    This paper presents a data management and visualization tool that was developed in parallel with a Multidisciplinary Design Optimization (MDO) framework in order to enable a more effective use of the obtained results within the Product Development Process (PDP). To this date, the main problem is that the majority of MDO case studies conclude by suggesting a small number of optimal configurations, which do not really hold any meaningful value for the decision makers since they represent only a narrow area of the design space. In this light, the proposed tool aims to provide designers with new possibilities in respect to post-processing of large data sets, and subsequently, to allow the non-technical teams to be engaged and benefit from the use of MDO in the company practices. As an example, an Unmanned Aerial Vehicle (UAV) configurator developed by using the Graphical User Interface (GUI) of MATLAB is herein presented, and it is shown that a tool for handling the results can be the logical next step towards integrating MDO in the manufacturing industry. Overall, this work aims to demonstrate the benefits of the present visualization and management tool as a complementary addition to an existing optimization framework, and also to determine if this approach can be the right strategy towards improving the MDO method for an eventual use in the PDP of complex pro-ducts like UAVs.

    Series
    NordDESIGN
    Keywords
    Big Data, Digital Design
    National Category
    Aerospace Engineering
    Identifiers
    urn:nbn:se:liu:diva-155050 (URN)978-91-7685-185-2 (ISBN)
    Conference
    NordDesign 2018, Linköping, Sweden, 14th - 17th August 2018
    Available from: 2019-03-11 Created: 2019-03-11 Last updated: 2019-11-13Bibliographically approved
    6. Multidisciplinary Optimization of Unmanned Aircraft in a System of Systems Context
    Open this publication in new window or tab >>Multidisciplinary Optimization of Unmanned Aircraft in a System of Systems Context
    2018 (English)Conference paper, Published paper (Other academic)
    Abstract [en]

    This paper explores the use of Multidisciplinary Design Optimization (MDO) in the development of Unmanned Aerial Vehicles (UAVs) when the requirements include a collaboration in a System of Systems (SoS) environment. In this work, the framework considers models that can capture the mission, stealth, and surveillance performance of each aircraft, while at the same time, a dedicated simulation module assesses the total cooperation effect on a given operational scenario. The resulting mixed continuous and integer variable problem is decomposed with a multi-level architecture, and in particular, it is treated as a fleet allocation problem that includes a nested optimization routine for sizing a “yet-to-be-designed” aircraft. Overall, the models and the framework are evaluated through a series of optimization runs, and the obtained Pareto front is compared with the results from a traditional aircraft mission planning method in order to illustrate the benefits of this SoS approach in the design of UAVs.

    Keywords
    MDO, UAV, SoS
    National Category
    Aerospace Engineering
    Identifiers
    urn:nbn:se:liu:diva-155047 (URN)978-3-932182-88-4 (ISBN)
    Conference
    31th Congress of the International Council of the Aeronautical Sciences (ICAS) 2018 - Belo Horizonte, Brazil, September 9-14, 2018
    Available from: 2019-03-11 Created: 2019-03-11 Last updated: 2019-11-13Bibliographically approved
  • 2.
    Papageorgiou, Athanasios
    Linköping University, Department of Management and Engineering, Machine Design. Linköping University, Faculty of Science & Engineering.
    Optimization of Unmanned Aerial Vehicles: Expanding the Multidisciplinary Capabilities2017Licentiate thesis, comprehensive summary (Other academic)
    Abstract [en]

    Over the last decade, Unmanned Aerial Vehicles (UAVs) have experienced an accelerated growth, and nowadays they are being deployed in a variety of missions that have traditionally been covered by manned aircraft. This unprecedented market expansion has created new and unforeseen challenges for the manufacturing industry which is now called to further reduce the idea-to-market times while simultaneously delivering designs of even higher performance. In this environment of uncertainty and risk, it is without a doubt crucial for the involved actors to find ways to secure their strategic advantage, and hence, implementing the latest design tools has become a critical consideration in every Product Development Process (PDP).

    To this end, a method that has been frequently applied in the PDP and has shown many successful results in the development of complex engineering products is Multidisciplinary Design Optimization (MDO). In general, MDO can bring additional knowledge regarding the best-suited designs much earlier in the process, and in this respect, it can lead to significant cost and time savings by reducing the total number of refinement iterations. Nevertheless, the organizational and cultural integration of MDO has been often overlooked, while at the same time, several technical aspects of the method for UAV design are still at an elementary level. On the whole, research on MDO is showing a slow progress, and to this date, there are many limitations in both the disciplinary models and the available analysis capabilities.

    In light of the above, this thesis focuses on the particulars of the MDO methodology, and more specifically, on how it can be best adapted and evolved in order to enhance the development process of UAVs. The primary objective is to study the current trends and gaps of the MDO practices in UAV applications, and subsequently to build upon that and explore how these can be included in a roadmap that will be able to serve a guide for newcomers in the field. Compared to other studies, the problem is herein approached from both a technical as well as organizational perspective, and thus, this research not only aims to propose techniques that can lead to better designs but also solutions that will be meaningful to the PDP. Having established the above foundation, this work shows that the traditional MDO frameworks for UAV design have been neglecting several important features, and it elaborates on how those novel elements can be modeled in order to enable a better integration of MDO into the organizational functions. Overall, this thesis presents quantitative and qualitative data which illustrate the effectiveness of the new framework enhancements in the development process of UAVs, and concludes with discussions on the possible improvement directions towards achieving more and better MDO capabilities.

    List of papers
    1. The Role of Multidisciplinary Design Optimization (MDO) in the Development Process of Complex Engineering Products
    Open this publication in new window or tab >>The Role of Multidisciplinary Design Optimization (MDO) in the Development Process of Complex Engineering Products
    2017 (English)In: DS 87 Proceedings of the 21st International Conference on Engineering Design (ICED 17): Vol 4: Design Methods and Tools, Vancouver, Canada, 21-25.08.2017 / [ed] Anja Maier, Stanko Škec, Harrison Kim, Michael Kokkolaras, Josef Oehmen, Georges Fadel, Filippo Salustri, Mike Van der Loos, Design Society , 2017, Vol. 4, p. 109-118Conference paper, Published paper (Other academic)
    Abstract [en]

    The work presented in this paper explores several concepts related to the design of complex engineering products and emphasizes on the effects of considering Multidisciplinary Design Optimization (MDO) in the development process. This paper is by no means a comprehensive literature review, but instead, the aim is to discuss some key points through theory and references to common MDO applications. In this respect, the central topics which are addressed herein are the enhancement of the generic product development process, the road towards a better integration of the organization’s functions, the methods to manage complex system architectures, and finally, the shortcomings of the MDO field. As a link to more tangible industrial applications, Unmanned Aerial Vehicles (UAVs) are chosen as an illustrative example due to their technical complexity as well as the demanding requirements of the corresponding market. Overall, the paper shows that despite the current state-of-the-art limitations, MDO can be a valuable tool within the “traditional” design process that has the potential to enable products of better quality while simultaneously reducing the total development time and effort.

    Place, publisher, year, edition, pages
    Design Society, 2017
    Series
    ICED, ISSN 2220-4342
    Keywords
    Design methods, Design process, Optimization, New product development, Multidisciplinary Design Optimization
    National Category
    Other Mechanical Engineering
    Identifiers
    urn:nbn:se:liu:diva-142278 (URN)978-1-904670-92-6 (ISBN)
    Conference
    21st International Conference on Engineering Design (ICED 17)
    Available from: 2017-10-24 Created: 2017-10-24 Last updated: 2019-11-13
    2. Development of a Multidisciplinary Design Optimization Framework Applied on UAV Design by Considering Models for Mission, Surveillance, and Stealth Performance
    Open this publication in new window or tab >>Development of a Multidisciplinary Design Optimization Framework Applied on UAV Design by Considering Models for Mission, Surveillance, and Stealth Performance
    2017 (English)In: 18th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference, 2017Conference paper, Published paper (Other academic)
    Abstract [en]

    This paper presents a Multidisciplinary Design Optimization (MDO) framework that is intended to be employed in the early design stages of Unmanned Aerial Vehicles (UAVs) when the primary focus is on the tradeoffs between the mission, stealth, and surveillance performance requirements. The proposed MDO framework takes into account the aircraft’s geometry, the aerodynamics, the trim, the stability, and the simulation of the mission, but it also includes two additional models for computing the Radar Cross Section (RCS) and the sensor performance. A multi-level solution architecture is implemented in order to tackle the increased complexity of the problem, and it is shown that this type of decomposition can be a more efficient optimization approach compared to the traditional single-level formulation. The operation of the framework is evaluated through single objective optimizations by using the weighted sum method, while it is also investigated whether or not metamodels can be a viable alternative to the computationally expensive RCS and sensor analysis models. Overall, the results show that the mission, stealth, and surveillance performance are conflicting objectives, and therefore, their concurrent consideration in an optimization framework can help increase the available knowledge early on in the design of UAV applications.

    Series
    AIAA AVIATION Forum ; 2017-4151
    National Category
    Aerospace Engineering
    Identifiers
    urn:nbn:se:liu:diva-142277 (URN)10.2514/6.2017-4151 (DOI)
    Conference
    18th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference, Denver, Colorado, USA, 2017, AIAA AVIATION Forum, (AIAA 2017-4151)
    Available from: 2017-10-24 Created: 2017-10-24 Last updated: 2019-11-13
  • 3.
    Papageorgiou, Athanasios
    et al.
    Linköping University, Department of Management and Engineering, Machine Design. Linköping University, Faculty of Science & Engineering.
    Amadori, Kristian
    Linköping University, Department of Management and Engineering, Machine Design. Linköping University, Faculty of Science & Engineering.
    Jouannet, Christopher
    Linköping University, Department of Management and Engineering, Fluid and Mechatronic Systems. Linköping University, Faculty of Science & Engineering.
    Ölvander, Johan
    Linköping University, Department of Management and Engineering, Machine Design. Linköping University, Faculty of Science & Engineering.
    Multidisciplinary Optimization of Unmanned Aircraft in a System of Systems Context2018Conference paper (Other academic)
    Abstract [en]

    This paper explores the use of Multidisciplinary Design Optimization (MDO) in the development of Unmanned Aerial Vehicles (UAVs) when the requirements include a collaboration in a System of Systems (SoS) environment. In this work, the framework considers models that can capture the mission, stealth, and surveillance performance of each aircraft, while at the same time, a dedicated simulation module assesses the total cooperation effect on a given operational scenario. The resulting mixed continuous and integer variable problem is decomposed with a multi-level architecture, and in particular, it is treated as a fleet allocation problem that includes a nested optimization routine for sizing a “yet-to-be-designed” aircraft. Overall, the models and the framework are evaluated through a series of optimization runs, and the obtained Pareto front is compared with the results from a traditional aircraft mission planning method in order to illustrate the benefits of this SoS approach in the design of UAVs.

  • 4.
    Papageorgiou, Athanasios
    et al.
    Linköping University, Department of Management and Engineering, Machine Design. Linköping University, Faculty of Science & Engineering.
    Tarkian, Mehdi
    Linköping University, Department of Management and Engineering, Machine Design. Linköping University, Faculty of Science & Engineering.
    Amadori, Kristian
    Linköping University, Department of Management and Engineering, Machine Design. Linköping University, Faculty of Science & Engineering.
    Andersson (Ölvander), Johan
    Linköping University, Department of Management and Engineering, Machine Design. Linköping University, Faculty of Science & Engineering.
    Multidisciplinary Optimization of Unmanned Aircraft Considering Radar Signature, Sensors, and Trajectory Constraints2018In: Journal of Aircraft, ISSN 0021-8669, E-ISSN 1533-3868, Vol. 55, no 4, p. 1629-1640Article in journal (Refereed)
    Abstract [en]

    This paper presents a multidisciplinary design optimization framework applied to the development of unmanned aerial vehicles with a focus on radar signature and sensor performance requirements while simultaneously considering the flight trajectory. The primary emphasis herein is on the integration and development of analysis models for the calculation of the radar cross section and sensor detection probability, whereas traditional aeronautical disciplines such as aerodynamics and mission simulation are also taken into account in order to ensure a flyable concept. Furthermore, this work explores the effect of implementing trajectory constraints as a supplementary input to the multidisciplinary design optimization process and presents a method that enables the optimization of the aircraft under a three-dimensional flight scenario. To cope with the additional computational cost of the high-fidelity radar cross section and sensor calculations, the use of metamodels is also investigated and an efficient development methodology that can provide high-accuracy approximations for this particular problem is proposed. Overall, the operation and performance of the framework are evaluated against five surveillance scenarios, and the obtained results show that the implementation of trajectory constraints in the optimization has the potential to yield better designs by 12–25% when compared to the more “traditional” problem formulations.

  • 5.
    Papageorgiou, Athanasios
    et al.
    Linköping University, Department of Management and Engineering, Machine Design. Linköping University, Faculty of Science & Engineering.
    Tarkian, Mehdi
    Linköping University, Department of Management and Engineering, Machine Design. Linköping University, Faculty of Science & Engineering.
    Amadori, Kristian
    Linköping University, Department of Management and Engineering, Machine Design. Linköping University, Faculty of Science & Engineering.
    Ölvander, Johan
    Linköping University, Department of Management and Engineering, Machine Design. Linköping University, Faculty of Science & Engineering.
    Multidisciplinary Design Optimization of Aerial Vehicles: A Review of Recent Advancements2018In: International Journal of Aerospace Engineering, ISSN 1687-5966, E-ISSN 1687-5974, article id 4258020Article, review/survey (Refereed)
    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.

  • 6.
    Papageorgiou, Athanasios
    et al.
    Linköping University, Department of Management and Engineering, Machine Design. Linköping University, Faculty of Science & Engineering.
    Ölvander, Johan
    Linköping University, Department of Management and Engineering, Machine Design. Linköping University, Faculty of Science & Engineering.
    A Data Management and Visualization Tool for Integrating Optimization Results in Product Development2018In: DS 91: Proceedings of NordDesign 2018, Linköping, Sweden, 14th - 17th August 2018: DESIGN IN THE ERA OF DIGITALIZATION / [ed] Ekströmer, Philip; Schütte, Simon and Ölvander, Johan, 2018Conference paper (Other academic)
    Abstract [en]

    This paper presents a data management and visualization tool that was developed in parallel with a Multidisciplinary Design Optimization (MDO) framework in order to enable a more effective use of the obtained results within the Product Development Process (PDP). To this date, the main problem is that the majority of MDO case studies conclude by suggesting a small number of optimal configurations, which do not really hold any meaningful value for the decision makers since they represent only a narrow area of the design space. In this light, the proposed tool aims to provide designers with new possibilities in respect to post-processing of large data sets, and subsequently, to allow the non-technical teams to be engaged and benefit from the use of MDO in the company practices. As an example, an Unmanned Aerial Vehicle (UAV) configurator developed by using the Graphical User Interface (GUI) of MATLAB is herein presented, and it is shown that a tool for handling the results can be the logical next step towards integrating MDO in the manufacturing industry. Overall, this work aims to demonstrate the benefits of the present visualization and management tool as a complementary addition to an existing optimization framework, and also to determine if this approach can be the right strategy towards improving the MDO method for an eventual use in the PDP of complex pro-ducts like UAVs.

  • 7.
    Papageorgiou, Athanasios
    et al.
    Linköping University, Department of Management and Engineering, Machine Design. Linköping University, Faculty of Science & Engineering.
    Ölvander, Johan
    Linköping University, Department of Management and Engineering, Machine Design. Linköping University, Faculty of Science & Engineering.
    The Role of Multidisciplinary Design Optimization (MDO) in the Development Process of Complex Engineering Products2017In: DS 87 Proceedings of the 21st International Conference on Engineering Design (ICED 17): Vol 4: Design Methods and Tools, Vancouver, Canada, 21-25.08.2017 / [ed] Anja Maier, Stanko Škec, Harrison Kim, Michael Kokkolaras, Josef Oehmen, Georges Fadel, Filippo Salustri, Mike Van der Loos, Design Society , 2017, Vol. 4, p. 109-118Conference paper (Other academic)
    Abstract [en]

    The work presented in this paper explores several concepts related to the design of complex engineering products and emphasizes on the effects of considering Multidisciplinary Design Optimization (MDO) in the development process. This paper is by no means a comprehensive literature review, but instead, the aim is to discuss some key points through theory and references to common MDO applications. In this respect, the central topics which are addressed herein are the enhancement of the generic product development process, the road towards a better integration of the organization’s functions, the methods to manage complex system architectures, and finally, the shortcomings of the MDO field. As a link to more tangible industrial applications, Unmanned Aerial Vehicles (UAVs) are chosen as an illustrative example due to their technical complexity as well as the demanding requirements of the corresponding market. Overall, the paper shows that despite the current state-of-the-art limitations, MDO can be a valuable tool within the “traditional” design process that has the potential to enable products of better quality while simultaneously reducing the total development time and effort.

  • 8.
    Papageorgiou, Athanasios
    et al.
    Linköping University, Department of Management and Engineering, Machine Design. Linköping University, Faculty of Science & Engineering.
    Ölvander, Johan
    Linköping University, Department of Management and Engineering, Machine Design. Linköping University, Faculty of Science & Engineering.
    Amadori, Kristian
    Saab Aeronautics, Sweden.
    Development of a Multidisciplinary Design Optimization Framework Applied on UAV Design by Considering Models for Mission, Surveillance, and Stealth Performance2017In: 18th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference, 2017Conference paper (Other academic)
    Abstract [en]

    This paper presents a Multidisciplinary Design Optimization (MDO) framework that is intended to be employed in the early design stages of Unmanned Aerial Vehicles (UAVs) when the primary focus is on the tradeoffs between the mission, stealth, and surveillance performance requirements. The proposed MDO framework takes into account the aircraft’s geometry, the aerodynamics, the trim, the stability, and the simulation of the mission, but it also includes two additional models for computing the Radar Cross Section (RCS) and the sensor performance. A multi-level solution architecture is implemented in order to tackle the increased complexity of the problem, and it is shown that this type of decomposition can be a more efficient optimization approach compared to the traditional single-level formulation. The operation of the framework is evaluated through single objective optimizations by using the weighted sum method, while it is also investigated whether or not metamodels can be a viable alternative to the computationally expensive RCS and sensor analysis models. Overall, the results show that the mission, stealth, and surveillance performance are conflicting objectives, and therefore, their concurrent consideration in an optimization framework can help increase the available knowledge early on in the design of UAV applications.

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