An Overview of the Optimized Integrated Multidisciplinary Systems Program

Reuter, Robert; Iden, Steve; Snyder, Richard; Allison, Darcy L.

doi:10.2514/6.2016-0674

Cited by 11 publications

(16 citation statements)

References 10 publications

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“…Due to the fluid nature of the initial design process, it is not recommended to use high fidelity analysis design tools, such as Computational Fluid Dynamics (CFD), at this stage as they can be unnecessarily costly [4,54]. What is required is a tool that strikes a balance between sufficient accuracy and computational cost [55][56][57][58]. Piperni et al [59] and Zhang et al [60] have argued that the level of fidelity that should be delivered by the models is mostly determined at the development stage, which the design process aims to enhance.…”

Section: Particles Selection Schema On I-mopso Interfacementioning

confidence: 99%

Section: Automated Optimisation Framework (Non-interactive)mentioning

confidence: 99%

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The Interactive Design Approach for Aerodynamic Shape Design Optimisation of the Aegis UAV

2019

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In this work, an interactive optimisation framework—a combination of a low fidelity flow solver, Athena Vortex Lattice (AVL), and an interactive Multi-Objective Particle Swarm Optimisation (MOPSO)—is proposed for aerodynamic shape design optimisation of any aerial vehicle platform. This paper demonstrates the benefits of interactive optimisation—reduction of computational time with high optimality levels. Progress towards the most preferred solutions is made by having the Decision Maker (DM) periodically provide preference information once the MOPSO iterations are underway. By involving the DM within the optimisation process, the search is directed to the region of interest, which accelerates the process. The flexibility and efficiency of undertaking optimisation interactively have been demonstrated by comparing the interactive results with the non-interactive results of an optimum design case obtained using Multi-Objective Tabu Search (MOTS) for the Aegis UAV. The obtained results show the superiority of using an interactive approach for the aerodynamic shape design, compared to posteriori approaches. By carrying out the optimisation using interactive MOPSO it was shown to be possible to obtain similar results to non-interactive MOTS with only half the evaluations. Moreover, much of the usual complexity of post-data-analysis with posteriori approaches is avoided, since the DM is involved in the search process.

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Section: Particles Selection Schema On I-mopso Interfacementioning

confidence: 99%

Section: Automated Optimisation Framework (Non-interactive)mentioning

confidence: 99%

The Interactive Design Approach for Aerodynamic Shape Design Optimisation of the Aegis UAV

2019

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“…According to the review of paper I, the majority of authors abstain from specifying the development stage that they are working on, while at the same time, there is general tendency where the choice of tools is based on availability rather than suitability. Overall, it is stressed that the MDO tools should be able to capture the correct physics of the problem (Reuter et al, 2016), but also to be as computationally efficient as possible in order to enable even faster design evaluations (Henderson et al, 2012). To this end, it can be seen that a prevalent trend is to build modular frameworks that can adapt to different fidelity requirements, whereas it can be argued that the main gap herein is the lack of a complete list regarding the available software solutions (see Figure 16).…”

Section: Level Of Fidelitymentioning

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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“…In [43,44], the authors reported developing a strategy that used non-interactive and interactive techniques, respectively, to formulate the design problem and improve the optimisation speed. To deliver a sufficient level of fidelity to the DM at very fast computational times, the low fidelity flow solver Athena Vortex Lattice (AVL) was used to capture the physics of the problem [45][46][47][48]. Improving the ability of the developed method to accelerate the search while retaining all the useful information in the design space was the main area of work.…”

Section: Introductionmentioning

confidence: 99%

“…The flow solver used to evaluate worthwhile solutions is the Athena Vortex Lattice (AVL) [51,52]. Many codes utilize Vortex Lattice Method (VLM) for aerodynamic characteristics calculations, but AVL is the most well-known and provides the most accurate and efficient results when compared with other aerodynamic analysis software employing the same method [45][46][47][48]52]. In addition, AVL code is easy to use and capable of manipulating a large number of design parameters within a short computational time and limited cost.…”

Section: Introductionmentioning

confidence: 99%

Artificial Intelligence to Enhance Aerodynamic Shape Optimisation of the Aegis UAV

Azabi

Chai

Kipouros

2019

MAKE

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This article presents an optimisation framework that uses stochastic multi-objective optimisation, combined with an Artificial Neural Network (ANN), and describes its application to the aerodynamic design of aircraft shapes. The framework uses the Multi-Objective Particle Swarm Optimisation (MOPSO) algorithm and the obtained results confirm that the proposed technique provides highly optimal solutions in less computational time than other approaches to the same design problem. The main idea was to focus computational effort on worthwhile design solutions rather than exploring and evaluating all possible solutions in the design space. It is shown that the number of valid solutions obtained using ANN-MOPSO compared to MOPSO for 3000 evaluations grew from 529 to 1006 (90% improvement) with a penalty of only 8.3% (11 min) in computational time. It is demonstrated that including an ANN, the ANN-MOPSO with 3000 evaluations produced a larger number of valid solutions than the MOPSO with 5500 evaluations, and in 33% less computational time (64 min). This is taken as confirmation of the potential power of ANNs when applied to this type of design problem.

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An Overview of the Optimized Integrated Multidisciplinary Systems Program

Cited by 11 publications

References 10 publications

The Interactive Design Approach for Aerodynamic Shape Design Optimisation of the Aegis UAV

The Interactive Design Approach for Aerodynamic Shape Design Optimisation of the Aegis UAV

Optimization of Unmanned Aerial Vehicles: Expanding the Multidisciplinary Capabilities

Artificial Intelligence to Enhance Aerodynamic Shape Optimisation of the Aegis UAV

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