Topology Optimisation of Aircraft Wing Box Ribs

Krog, L. A.; Tucker, Aaron; Uk, Airbus; Boyd, R W

doi:10.2514/6.2004-4481

Cited by 132 publications

(93 citation statements)

References 3 publications

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“…This includes successful aerospace applications during development of the new generation airliners such as A380, 350 and B787 (see, e.g., Krog et al 2004). However, the inability of taking fail-safe requirement into consideration in a computationally viable way has been seen as a significant limitation.…”

Section: Introductionmentioning

confidence: 99%

Fail-safe topology optimization

Zhou

Fleury

2016

Struct Multidisc Optim

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Fail-safe robustness of critical load carrying structures is an important design philosophy for aerospace industry. The basic idea is that a structure should be designed to survive normal loading conditions when partial damage occurred. Such damage is quantified as complete failure of a structural member, or a partial damage of a larger structural part. In the context of topology optimization fail-safe consideration was first proposed by Jansen et al. Struct Multidiscip Optim 49(4):657-666, (2014). While their approach captures the essence of fail-safe requirement, it has two major shortcomings: (1) it involves analysis of a very large number of FEA models at the scale equal to the number of elements; (2) failure was introduced in generic terms and therefore the fundamental aspects of failure test of discrete members was not discussed. This paper aims at establishing a rigorous framework for failsafe topology optimization of general 3D structures, with the goal to develop a computationally viable solution for industrial applications. We demonstrate the effectiveness of the proposed approach on several examples including a 3D example with over three hundred thousand elements.

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Section: Introductionmentioning

confidence: 99%

Fail-safe topology optimization

Zhou

Fleury

2016

Struct Multidisc Optim

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“…Topology optimisation allows a much wider search of the design domain since it is free from the limitations of a parametric definition. As such, it has been implemented in the redesign of many aerospace parts to decrease mass [7][8][9] . Ref.…”

Section: Introductionmentioning

confidence: 99%

Topology Optimisation: Increasing the Speed and Reliability of Design

Kelly

Keane

Sóbester

et al. 2014

15th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference

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In this paper, topology optimisation is applied to the design of the rear fuselage of an unmanned aerial vehicle (UAV). A comparison is drawn between the performance of a design created through evolutionary structural optimisation (ESO) and a baseline design modelled on a manually designed and successfully flow fuselage geometry, for different wing shapes. The loading for each wing shape is determined by full-potential (FP) aerodynamic analysis. A Kriging model is then employed in a multidisciplinary optimisation procedure driving a trade study between aerodynamic efficiency and aircraft structural weight. Using this procedure, a Pareto front is populated to give a set of optimal designs which satisfy maximum aerodynamic efficiency and minimum weight objectives. A wide search of the design space is achieved with little manual intervention, which makes use of the high fidelity weight estimate extracted from topology optimization results. Nomenclature= element index 0 = initial value = compliance = coefficient of lift = coefficient of drag = Young's modulus f = load vector = landing lift constant = lift force = aircraft mass = element removal rate u = displacement vector = volume * = volume fraction = relative density ̅ = mean von Mises stress Introduction NCREASINGLY, complex design systems are operated from a range of different computational platforms with a number of different design teams. The more complex these systems become, the less likely it is to see effective integration of each of these specialist activities 1 . This often results in the opportunities to change the design decreasing dramatically the further one progresses through the design process, and often this allows imperfections to remain in the design as it is too expensive to go back and correct them 2 . Better integration within the design process can facilitate smaller design organisations with shorter time to manufacture and less human interaction. By more fully exploiting the capabilities of computers in design, search and optimisation, this is an achievable objective. The increasing power of modern computer systems continues to expand the depth of computational analysis that can be afforded within the design process. 3 . The aerodynamic optimisation is carried out using an estimate for the weight of the structure based on previous models. Commonly, statistical models are used to provide weight estimates to inform optimisation decisions, some of which are reviewed in Ref.4. To manually update the internal structure in this model would take many hours of Computer Aided Design (CAD) drawing, carried out by a skilled design engineer. Automation of the internal design definition would permit a high fidelity weight estimation, allowing the designer to conduct a much more accurate search of the design space with little additional manual effort.In the literature, several authors have used higher fidelity geometry-generation methods capable of providing weight estimates and structural analysis for the multidisciplinary optimisation of aircrafts. In...

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“…These problems require the use of body-fitted finiteelement meshes, which are typically non-uniform and non-rectilinear. Such problems have been solved successfully by SIMP researchers on a number of occasions [6,7,8,9]; however, they present a unique challenge for users of the level set method. The HamiltonJacobi equation, which is at the heart of the level set method, is solved on a uniform Cartesian grid, which typically coincides with the finite-element mesh.…”

Section: Introductionmentioning

confidence: 99%