A Systems Engineering Approach to the Application of Multidisciplinary Design, Analysis and Optimization (MDAO) for Efficient Supersonic Air-Vehicle Exploration (ESAVE)

Hurwitz, Wayne; Donovan, Shane; Camberos, José; German, Brian

doi:10.2514/6.2012-5491

Cited by 10 publications

(12 citation statements)

References 2 publications

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“…In the optimization of aerial vehicles, the most frequently used objectives are directly related to the overall operation of the design, and it can be seen that the majority of case studies often consider an objective which is directly related to weight, aerodynamics, or mission performance (see Figure 3). According to the findings of this review, weight indexes are by far the most preferred metric since they have been used in 67 case optimization studies (39%), and the main reason is that they can be a good overview of many critical design requirements, like for example, the cost and the mission efficiency [12][13][14][15][16]. Here, the most commonly used approach is to consider a single objective, but it is also possible to combine several objectives through an aggregated function or formulate a multiobjective problem which can generally be a more flexible alternative for design space exploration [13,17].…”

Section: State Of the Artmentioning

confidence: 99%

“…Overall, it has been shown that this approach has the potential to determine the design variables with the highest influence, and therefore, it can reduce the total parameters to a number that is relevant but also manageable for each specific case study [19][20][21][22]. As far as the constraints are concerned, those are usually limited to the critical case-depended features [16,23] or similarly, to common airworthiness aspects like the field performance [13,[24][25][26]. In general, constraints can add further fidelity to the design, and this has been often exemplified through the incorporation of safety regulations in the modeling of fuel systems [27], aircraft controls [28,29], and mission requirements for general aviation [25,30,31].…”

Section: Time Span January Of 2006-december Of 2016 Source Typementioning

confidence: 99%

“…In aerial vehicle design, cost calculations are commonly based on empirical equations and statistical data which generally offer fast estimations [34]; however, the main disadvantage is that they are typically valid for a limited number of configurations and they usually omit how the product will evolve over time [38,54,73]. Thus, it can be observed that many authors are enhancing the traditional MDO frameworks with supplementary financial computations, and it can be seen that aspects such as the R&D and production planning [38,54,56] as well as the direct and indirect operating costs [13,32,79,80] are crucial factors which can often drive the final design. In a similar way, additional knowledge can be obtained by modeling the behavior of the stakeholders through either a deterministic [24] or stochastic [81] market model, and overall, it has been shown that this value-driven approach can enable a better and more focused assessment of specific business risks which has not always been possible in the traditional performance-based MDO.…”

Section: Alternative Modelsmentioning

confidence: 99%

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Multidisciplinary Design Optimization of Aerial Vehicles: A Review of Recent Advancements

Παπαγεωργίου

Tarkian

Amadori

et al. 2018

International Journal of Aerospace Engineering

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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.

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Section: State Of the Artmentioning

confidence: 99%

Section: Time Span January Of 2006-december Of 2016 Source Typementioning

confidence: 99%

Section: Alternative Modelsmentioning

confidence: 99%

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Multidisciplinary Design Optimization of Aerial Vehicles: A Review of Recent Advancements

Παπαγεωργίου

Tarkian

Amadori

et al. 2018

International Journal of Aerospace Engineering

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“…According to the review that is presented in paper I, the most frequent formulation is the SOO, whereas multiple objectives can also be taken into account by using the weighted-sum method or a MOO which is a more flexible alternative for design space exploration (Hurwitz et al, 2012). Moreover, the most preferred metrics are typically design parameters which are associated with the weight of the aircraft (e.g.…”

Section: Problem Formulationmentioning

confidence: 99%

Optimization of Unmanned Aerial Vehicles: Expanding the Multidisciplinary Capabilities

Παπαγεωργίου¹

2018

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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. vi vii

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“…has developed a framework aimed at the design of Efficient Supersonic Air-Vehicle Exploration (ESAVE) [223]. The project AGILE [224], which is aimed at a 40% increase in solving speed in aircraft design MDO problems, also deserves be noted.…”

Section: Multidisciplinary Design Optimizationmentioning

confidence: 99%

RPAS Design : an MDO Approach

Aliaga-Aguilar¹

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Unmanned aircraft and, particularly, RPAS (Remotely Piloted Aircraft Systems) are nowadays experiencing great growth both in the military and civil industries. This is due to the fact that removing the need to be manned has enabled the improvement of their endurance, range, and overall performance while, at the same time, reducing the risk to which human lives were exposed. In addition, RPAS can be made much smaller. This decrease of mass and size increases the variety of missions they can perform. However, the design process to manufacture such aircraft is often long and costly, which prevents small companies from undertaking it. Multidisciplinary Design Optimization (MDO) is an engineering field whose focus is to solve highly complex problems by the means of optimization techniques. It has been used in the design of commercial aircraft for a long time, but integrating the various engineering disciplines that take part in designing an RPAS within an MDO to simplify the design process is a challenge. In addition, there is an ample variety of architectures for MDO projects and, the reasons to choose a particular one, have to be discussed on a case by case basis. During the last years, distributed architectures have become widespread, given that they can take advantage of parallel computing (even with graphical platforms) and reduce computing time. Adapting the formulation of a problem to a particular vii Dissertation Overview Chapter 1: This is the introduction to the thesis. It presents the evolution of RPAS and the current state of the art both in MDO and in RPAS design methodologies. Chapter 2 introduces the Generic Parameter Penalty Architecture (GPPA): a new, flexible MDO architecture, oriented towards the solution of engineering problems that present different levels of complexity. Chapter 3 introduces the RPAS Advanced MDO Platform (RAMP). A new MDO environment aimed at the design of small RPAS. Chapters 4-7 present RAMP's main analysis models: aerodynamics, structure, economy and pricing, propulsion, and performance. Chapter 8 presents an application case of RAMP to a real-world mission. Chapter 8 does so by limiting RAMP's configuration availability to just classical. This provides the opportunity to compare its results to most commercially available RPAS, while Chapter 9 unleashes RAMP's full capabilities to also consider Blended Wing Body (BWB) and Canard configurations. Chapter 9 presents results for the various tests and hypothesis that are presented in the thesis, while Chapter 10 serves to give shape to the conclusions of the thesis and the future lines of research.

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A Systems Engineering Approach to the Application of Multidisciplinary Design, Analysis and Optimization (MDAO) for Efficient Supersonic Air-Vehicle Exploration (ESAVE)

Cited by 10 publications

References 2 publications

Multidisciplinary Design Optimization of Aerial Vehicles: A Review of Recent Advancements

Multidisciplinary Design Optimization of Aerial Vehicles: A Review of Recent Advancements

Optimization of Unmanned Aerial Vehicles: Expanding the Multidisciplinary Capabilities

RPAS Design : an MDO Approach

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