Capability-Based Quantitative Technology Evaluation for Systems-of-Systems

Biltgen, Patrick T.; Mavris, Dimitri N.

doi:10.1109/sysose.2007.4304300

Cited by 14 publications

(5 citation statements)

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“…Apart from that, a valid alternative for quantifying the potential of different technologies in SoS studies was presented in Refs. [26][27][28], where various physics-based models of aircraft system were exercised within a hierarchical objectoriented constructive simulation. In these studies, it was also shown that surrogate models can provide a fast assessment of the individual technologies, and in turn capture efficiently the complete system behavior at an SoS level.…”

Section: B System-of-systems Studiesmentioning

confidence: 99%

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Multidisciplinary and Multifidelity Framework for Evaluating System-of-Systems Capabilities of Unmanned Aircraft

Παπαγεωργίου¹,

Ölvander²,

Amadori³

et al. 2020

Journal of Aircraft

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Section: B System-of-systems Studiesmentioning

confidence: 99%

“…The solution to the above problem that is implemented, and has also been followed by Refs. [26][27][28], is to develop surrogate models.…”

Section: Efficient Computingmentioning

confidence: 99%

Multidisciplinary and Multifidelity Framework for Evaluating System-of-Systems Capabilities of Unmanned Aircraft

Παπαγεωργίου¹,

Ölvander²,

Amadori³

et al. 2020

Journal of Aircraft

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“…The framework that was presented in paper VI enables the decision-making team to explore the design interactions in a SoS context, however, its applicability is limited to case studies which aim to develop one yet-to-be-designed UAV. As stated before, it is through the exploration of the design space that value can be added to the product and reduce the risks for the organization, and thus, there is a need to define a general methodology for analyzing even larger SoS design spaces starting from the needs and reaching down to all system levels as in the examples of Biltgen and Mavris (2007) as well as Bagdatli et al (2010). On the whole, this methodology should enable to take into account problem formulations that include different types and numbers of systems, while at the same time, it should offer scalability in terms of analysis and simulation models; it should allow to consider the operational scenario and the tactical behavior; and lastly, it should enable the use of multi-fidelity tools according to the requirements of each development stage.…”

Section: Populating the Sos Design Spacementioning

confidence: 99%

Design Optimization of Unmanned Aerial Vehicles : A System of Systems Approach

Παπαγεωργίου

2019

Linköping Studies in Science and Technology. Dissertations

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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 subsystems 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. v vi This Ph.D. project was carried out at the division of Machine Design of Linköping Universi...

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“…Interoperability in military systems-of-systems architectures and capability-based quantitative technology evaluation have been addressed in (Wyatt et al, 2012) and (Biltgen & Mavris, 2007). The increasing complexity of net-centric warfare requires systems to be interoperable to achieve mission success.…”

Section: Related Workmentioning

confidence: 99%

“…The authors plan to extend their approach to examine multiple capabilities across a range of scenarios and will incorporate variable fidelity models to examine different trends and behaviours at varying levels of detail. Methods used in (Wyatt et al, 2012) and (Biltgen & Mavris, 2007) are different while the research goals and use of the results are similar. Simultaneous examination of technologies and tactics, resource allocation to new technology programs, sensitivity analysis of technology areas on top-level capability areas, system of systems' modelling and variable fidelity of systems and subsystems are common principles with our research methods.…”

Section: Related Workmentioning

confidence: 99%

Dependency of Military Capabilities on Technological Development

Kuikka

Nikkarila

Suojanen

2015

Journal of Military Studies

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Our goal is to get better understanding of different kind of dependencies behind the high-level capability areas. The models are suitable for investigating present state capabilities or future developments of capabilities in the context of technology forecasting. Three levels are necessary for a model describing effects of technologies on military capabilities. These levels are capability areas, systems and technologies. The contribution of this paper is to present one possible model for interdependencies between technologies. Modelling interdependencies between technologies is the last building block in constructing a quantitative model for technological forecasting including necessary levels of abstraction. This study supplements our previous research and as a result we present a model for the whole process of capability modelling. As in our earlier studies, capability is defined as the probability of a successful task or operation or proper functioning of a system. In order to obtain numerical data to demonstrate our model, we conducted a questionnaire to a group of defence technology researchers where interdependencies between seven representative technologies were inquired. Because of a small number of participants in questionnaires and general uncertainties concerning subjective evaluations, only rough conclusions can be made from the numerical results.

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Capability-Based Quantitative Technology Evaluation for Systems-of-Systems

Cited by 14 publications

References 0 publications

Multidisciplinary and Multifidelity Framework for Evaluating System-of-Systems Capabilities of Unmanned Aircraft

Multidisciplinary and Multifidelity Framework for Evaluating System-of-Systems Capabilities of Unmanned Aircraft

Design Optimization of Unmanned Aerial Vehicles : A System of Systems Approach

Dependency of Military Capabilities on Technological Development

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