Multidisciplinary Design Optimization Supported by Knowledge Based Engineering

Sobieszczanski‐Sobieski, Jaroslaw; Morris, A.J.; Tooren, M.J.L. Van; Rocca, Gianfranco La; Yao, Wen

doi:10.1002/9781118897072

Cited by 70 publications

(59 citation statements)

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“…Overall, the system design and optimization process aims to support and speed up the development process, and to this end, it is essential to have a correct problem definition, adequate modeling as well as simulation capabilities, and finally a suitable optimization environment that can enable the evaluation of the various concepts (see Figure 6). Apart from the above descriptive formulation, the typical design optimization problem can also be expressed in mathematical terms, and its basic form according to Sobieszczanski-Sobieski et al (2015) that is also encountered in this thesis is presented in Equation 3. The considered problem takes into account a generic objective function which is denoted here as f(x), two sets of inequality and equality constraints that are represented by gj(x) and hj(x), and lastly a set of design variables xi with x u and x l being the upper and lower limits respectively.…”

Section: Engineering Design Optimizationmentioning

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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Section: Engineering Design Optimizationmentioning

confidence: 99%

Optimization of Unmanned Aerial Vehicles: Expanding the Multidisciplinary Capabilities

Παπαγεωργίου¹

2018

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“…An example is in the field of robotics systems (Trabelsi et al, 2015), where Chen developed a simple design principle for an untethered, entirely soft, swimming robot with the ability to achieve directional propulsion without batteries and on-board electronics. A multidisciplinary design optimization advisor system (Sobieszczanski-Sobieski et al, 2015) and the implementation of an ICAD generative model (La Rocca et al, 2002) was proposed in the design of aircraft applications. There are numerous methods to solve this kind of problems and many other methods are also studied to improve calculation time and precision in CSP problems.…”

Section: State Of the Artmentioning

confidence: 99%

Supporting Design Tasks Through Constraint Satisfaction Tools

Nardelli¹,

Cicconi²,

Raffaeli³

et al. 2018

Proceedings of the DESIGN 2018 15th International Design Conference

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Nowadays, different commercial tools are available to support engineers during optimization tasks in engineering design; however, many researches have been still studying tools and methods to improve the design process and overcome some limits related to configuration and design optimization. This paper proposes a methodological approach to highlight how a CSP analysis can support the first phase of an optimization analysis, to reduce the design space of solutions to be investigated and subsequently optimized. A test case shows a CSP study applied to steel structures for oil & gas applications.

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“…So optimizing composite structures, often leads to multi-criteria and multidisciplinary optimization (Sobieszczanksi-Sobieski et al 2015).…”

Section: Introductionmentioning

confidence: 99%

“…In Baier (1977Baier ( , 1978 and Stadler (1984) applications in the structural design have showed huge potential by simultaneously considering multiple criteria and thereby yielding optimal compromises. Sobieszczanksi-Sobieski et al (2015) covers most of the mentioned aspects as multiple objectives, multiple disciplines and knowledge engineering.…”

Section: Introductionmentioning

confidence: 99%

Multi-criteria optimization of an aircraft propeller considering manufacturing

Schatz¹,

Hermanutz²,

Baier³

2016

Struct Multidisc Optim

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Carbon-fiber-reinforced polymers are gaining ground; high mass-specific stiffness and strength properties in fiber direction are commonly identified as reasons. Nonetheless, there are great challenges unleashing the entire light-weight potential. For instance, the multitude of parameters (e.g. fiber orientations), also being linked with each other and having huge influence on, not only structural mechanics, but also onto effort in terms of manufacturing. Moreover, these parameters ideally need to be determined, such that mass and costs are minimal, while all structural and technical requirements are fulfilled. The challenge of considering manufacturing aspects along with structural mechanics are mainly addressed in this paper. It is outlining an approach for modeling manufacturing effort via expert knowledge and how to actually consider this model in a multi-criteria optimization framework. In addition, it will be shown how to incorporate these knowledge-based models into an efficient structural design optimization. For this sake, a braided propeller structure is optimized.

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Multidisciplinary Design Optimization Supported by Knowledge Based Engineering

Cited by 70 publications

References 0 publications

Optimization of Unmanned Aerial Vehicles: Expanding the Multidisciplinary Capabilities

Optimization of Unmanned Aerial Vehicles: Expanding the Multidisciplinary Capabilities

Supporting Design Tasks Through Constraint Satisfaction Tools

Multi-criteria optimization of an aircraft propeller considering manufacturing

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