Global optimization of benchmark aerodynamic cases using physics-based surrogate models

Iuliano, Emiliano

doi:10.1016/j.ast.2017.04.013

Cited by 46 publications

(21 citation statements)

References 13 publications

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“…SBO has been successfully applied in the aerospace engineering field [19][20][21][22][23][24][25][26][27]. In continuity with other works by the author [28][29][30][31], the present paper proposes an adaptive SBO framework for design optimization with different updating strategies and optimization algorithms. A sketch of the main building blocks is provided in Figure 1.…”

Section: Introductionmentioning

confidence: 94%

“…Finally, while previous investigations focused only on aerodynamic optimization cases, here an extensive study is carried out on analytic test functions in order to quickly assess the performance of the algorithm on known data. The paper is structured as follows: the first section is devoted to the surrogate model definition and to the training methods; then, the sequential design by means of various infill criteria is discussed and some examples on a basic test function are proposed; furthermore, having introduced all the computational pieces, the whole surrogate-based sequential optimization algorithm is described in detail and interactions between subphases are highlighted; finally, the experimental test campaign on multidimensional scalable test functions is discussed as well as the results obtained by using different setups; an example of real-world application is given in the very final section where a benchmark aerodynamic shape optimization case is faced and results are compared with a previous work by the same author [31].…”

Section: Introductionmentioning

confidence: 99%

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Efficient Design Optimization Assisted by Sequential Surrogate Models

Iuliano

2019

International Journal of Aerospace Engineering

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The paper proposes a global optimization algorithm employing surrogate modeling and adaptive infill criteria. The surrogates are exploited to screen the design space and provide lower-fidelity predictions across it; on the other hand, specific criteria are designed to suggest new points for high-fidelity evaluation so as to enrich the optimizer database. Both Kriging and radial basis function network are used as surrogates with different training strategies. Sequential design is achieved by introducing several infill criteria according to the realization of the exploration-exploitation trade-off. Optimization results are provided both for scalable and analytical test functions and for a practical aerodynamic shape optimization problem.

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Section: Introductionmentioning

confidence: 94%

Section: Introductionmentioning

confidence: 99%

Efficient Design Optimization Assisted by Sequential Surrogate Models

Iuliano

2019

International Journal of Aerospace Engineering

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“…Marco Ceze of the University of Michigan studied the characteristics of CST parameterization and found that the ill-conditioning of parameterization when fitting airfoil with high-order Bernstein polynomials [8]. Straathof et al proposed a parameterization method that used a combination of Bernstein polynomials and B-splines to allow for both the local and global control of a shape, which is an extension to the Class-Shape-Transformation Method [9].Currently, for 3D wing geometries, the CST methodology is being widely used to drive aerodynamic optimization problems by using a full potential panel code, where the Euler solver being used for 2D airfoil optimizations [10][11][12][13].Moreover, in terms of structural optimization, plenty of research has been made, and various optimization strategies have been proposed. Presently, the surrogate model technique is promising due to the excellent computational accuracy and efficiency, especially for the practical engineering system with complex mapping functions [14][15][16][17].…”

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confidence: 99%

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confidence: 99%

A General Integrated Method for Design Analysis and Optimization of Missile Structure

Wang

Yang²,

Guo

et al. 2019

Algorithms

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In the demonstration phase of a missile scheme, to obtain the optimum proposal, designers need to modify the parameters of the overall structure frequently and significantly, and perform the structural analysis repeatedly. In order to reduce the manual workload and improve the efficiency of research and development, a general integrated method of missile structure modeling, analysis and optimization was proposed. First, CST (Class and Shape transformation functions) parametric method was used to describe the general structure of the missile. The corresponding software geometric modeling and FEM (Finite Element Method) analyzing of the missile were developed in C/C++ language on the basis of the CST parametric method and UG (Unigraphics) secondary development technology. Subsequently, a novel surrogate model-based optimation strategy was proposed to obtain a relatively light mass missile structure under existing shape size. Eventually, different missile models were used to verify the validity of the method. After executing the structure modeling, analysis and optimization modules, satisfactory results can be obtained that demonstrated the stability and adaptability of the proposed method. The method presented saves plenty of time comparing to the traditional manual modeling and analysis method, which provides a valuable technique to improve the efficiency of research and development.3D modeling program based on the UG secondary development technology, which has improved the modeling efficiency. Wang et al. [4] used the technology of UG/KF secondary development for the automatic modeling of the wind turbine blades, and the aerodynamic characteristics of the impeller were analyzed by the Fluent software. Moreover, He et al. [5] implemented the parametric modeling of the blended-wing-body underwater glider structure by using UG secondary development technology and studied its structural performance with ANSYS. Therefore, UG is considered as an excellent tool that can realize the integration of modeling and simulation.Meanwhile, airfoils have been parameterized in a wide variety of ways. Among them, CST is considered to be a more effective method, which can represent the different types of geometries in a generic way with fewer parameters. Kulfan and Bussoletti [6] proposed a parameterization method that based on class and shape transformation functions, which has the advantages of high precision and fewer variables. The CST method is a powerful and versatile means to describe complex aeronautical shapes ranging from 2D airfoils to 3D geometries of aircraft using analytical functions. Since it has been introduced, this parameterization method has been the subject of several studies [7]. Marco Ceze of the University of Michigan studied the characteristics of CST parameterization and found that the ill-conditioning of parameterization when fitting airfoil with high-order Bernstein polynomials [8]. Straathof et al. proposed a parameterization method that used a combination of Bernstein polynomials and B-splines to allow...

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“…As such, the AIAA Aerodynamic Design Optimization Discussion Group (ADODG) a was formed. As part of this, a number of inviscid and viscous aerofoil and wing benchmark optimization cases were suggested, with a number of research groups presenting results; see [13][14][15][16][17][18][19][20][21] for example.…”

Section: Introductionmentioning

confidence: 99%

Global Optimization of Wing Aerodynamic Optimization Case Exhibiting Multimodality

Poole

Allen

Rendall

2018

Journal of Aircraft

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An investigation into an aerodynamic optimization benchmark case that exhibits multimodality is presented using a global optimization approach. The recently suggested case 6 of the AIAA Aerodynamic Design Optimization Discussion Group involves the drag minimization of a rectangular NACA0012 wing subject to lift and root bending moment, as well as other geometric constraints. In this paper, optimization of that case using a state-of-the-art constrained population-based global optimization framework is presented.Shape control is achieved via a hierarchical application of the radial basis function domain element approach. Three different fidelity of optimization cases are performed to investigate the multimodality of various aspects of the full problem, with four independent runs of each case being performed. When considering chord optimization, the optimizer converges to two independently identifiable minima with very similar performance. When adding dihedral and sweep variation, further multimodality is introduced, though this multimodality is reasonably well defined, with minima including forward and rearward sweep, and an upward and downward winglet. Introducing thickness variables leads to a highly multimodal problem due to the coupling between the chord and thickness variables. The theoretical minimum drag for this case is 24.7 counts, which a number of the runs get close to achieving.

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Global optimization of benchmark aerodynamic cases using physics-based surrogate models

Cited by 46 publications

References 13 publications

Efficient Design Optimization Assisted by Sequential Surrogate Models

Efficient Design Optimization Assisted by Sequential Surrogate Models

A General Integrated Method for Design Analysis and Optimization of Missile Structure

Global Optimization of Wing Aerodynamic Optimization Case Exhibiting Multimodality

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