Reliability Based Multidisciplinary Optimization of Aeroelastic Systems with Structural and Aerodynamic Uncertainties

Nikbay, Melike; KURU, Muhammet Nasıf

doi:10.2514/1.c031693

Cited by 21 publications

(5 citation statements)

References 25 publications

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“…Reliability-Based Design Optimisation and Robust Design Optimisation are the two main methodologies reported in the literature for probabilistic design optimisation [23][24][25][26]40]. In this work, aleatory variations in material stiffness and ply thickness are considered.…”

Section: Second Level: Robust and Reliability-based Design Optimisationmentioning

confidence: 99%

“…These uncertainties are to be quantified accurately in order to produce realistic designs accounting for robustness and reliability. The literature reports two main methodologies for uncertaintybased design optimisation: 1) Reliability-Based Design Optimisation (RBDO) [12,[23][24][25] and 2) Robust Design Optimisation (RDO) [24,26]. RBDO aims at optimising a design whilst having a particular risk or target reliability/performance as a constraint.…”

Section: Introductionmentioning

confidence: 99%

“…The application of probabilistic optimisation approaches such as RBDO and RDO for the aeroelastic tailoring of composite structures has been reported by several authors [12,23,25]. Scarth et al [12] and Manan et al [23] used simplified analytical models for aeroelastic stability with uncertainty arising from composite material properties.…”

Section: Introductionmentioning

confidence: 99%

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A robust and reliability-based aeroelastic tailoring framework for composite aircraft wings

Othman

Silva

Cabral

et al. 2019

Composite Structures

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This paper presents a multi-level aeroelastic tailoring framework for the optimisation of composite aircraft wings. The framework is capable of structural sizing and produces detailed composite ply configurations through robust and reliability-based design optimisation, and is demonstrated on a representative regional jet airliner finite element wing box model. The optimisation procedure is divided into two levels. The first level optimises the wing structure for minimum weight subject to multiple constraints including strain, buckling, aeroelastic stability and gust response. These first level solutions are then fed into the second level to be further optimised for robustness or reliability by considering uncertainties in material properties at ply level. Both the principles of robust and reliability-based design optimisation can also be used in combination to ensure a balance between the robustness and reliability of the structural performance. In order to keep computations to an acceptable cost, the second level optimisation employs the Polynomial Chaos Expansion method to approximate the effect of probabilistic uncertainty on structural performance. In comparison to the original benchmark wing, the framework produces an overall weight reduction of 32.1%, despite a 1.5% increase from the first to the second level optimisation that accounts for stochastic design variations.

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Section: Second Level: Robust and Reliability-based Design Optimisationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A robust and reliability-based aeroelastic tailoring framework for composite aircraft wings

Othman

Silva

Cabral

et al. 2019

Composite Structures

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“…Scarth, Cooper [45] investigated the influence of material variability on stability margins in flutter characteristics. Various linear and nonlinear aeroelastic problems were formulated and solved with the aid of the reliability based design optimization methods in Refs [46][47][48][49][50][51][52][53] and even the results were compared with the results obtained with the use of deterministic optimization methods Nikbay et al [46,52,53]. The criteria considered can include probabilistic/fuzzy constraints with both structural and aerodynamic uncertainties.…”

Section: Reliability Analysismentioning

confidence: 99%

Optimal Design of Plated/Shell Structures under Flutter Constraints—A Literature Review

2019

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Aeroelastic optimization has become an indispensable component in the evaluation of divergence and flutter characteristics for plated/shell structures. The present paper intends to review the fundamental trends and dominant approaches in the optimal design of engineering constructions. A special attention is focused on the formulation of objective functions/functional and the definition of physical (material) variables, particularly in view of composite materials understood in the broader sense as not only multilayered laminates but also as sandwich structures, nanocomposites, functionally graded materials, and materials with piezoelectric actuators/sensors. Moreover, various original aspects of optimization problems of composite structures are demonstrated, discussed, and reviewed in depth.

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“…A typical design problem of such a submerged body is characterized by a number of input random parameters. For reliable prediction of the flow field and aerodynamic forces exerted on the structure, the uncertainties in several parameters such as velocity, density, and boundary conditions should be taken into account (Pettit, 2004;Najm, 2011;Nikbay & Kuru, 2013). A number of popular methods for uncertainty propagation exist such as Monte Carlo simulation (MCS; Schenk & Schuëller, 2005), perturbation, and the spectral stochastic finite element method (SSFEM;Ghanem & Spanos, 2003;Ghanem & Ghosh, 2007;Ghosh et al, 2009).…”

Section: Introductionmentioning

confidence: 99%

A semi-intrusive stochastic perturbation method for lift prediction and global sensitivity analysis

Suryawanshi¹,

Ghosh

2017

AIEDAM

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Sensitivity analysis plays an important role in finding an optimal design of a structure under uncertainty. Quantifying relative importance of random parameters, which leads to a rank ordering, helps in developing a systematic and efficient way to reach the optimal design. In this work, lift prediction and sensitivity analysis of a potential flow around a submerged body is considered. Such flow is often used in the initial design stage of structures. The flow computation is carried out using a vortex-panel method. A few parameters of the submerged body and flow are considered as random variables. To improve the accuracy in lift prediction in a computationally efficient way, a new semi-intrusive stochastic perturbation method is proposed. Accordingly, a perturbation is applied at the linear system solving level involving the inuence coefficient matrix, as opposed to using perturbation in the lift quantity itself. This proposed method, which is partially analogous to the intrusive or Galerkin projection methods in spectral stochastic finite element methods, is found to be more accurate than using perturbation directly on the lift and faster than a direct simulation. The proposed semi-intrusive stochastic perturbation method is found to yield faster estimates of the Sobol’ indices, which are used for global sensitivity analysis. From global sensitivity analysis, the flow parameters are found to be more important than the parameters of the submerged body.

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Reliability Based Multidisciplinary Optimization of Aeroelastic Systems with Structural and Aerodynamic Uncertainties

Cited by 21 publications

References 25 publications

A robust and reliability-based aeroelastic tailoring framework for composite aircraft wings

A robust and reliability-based aeroelastic tailoring framework for composite aircraft wings

Optimal Design of Plated/Shell Structures under Flutter Constraints—A Literature Review

A semi-intrusive stochastic perturbation method for lift prediction and global sensitivity analysis

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