Exploring multi-stage shape optimization strategy of multi-body geometries using Kriging-based model and adjoint method

Yim, JinWoo; Lee, Byung Joon; Kim, Chongam

doi:10.1016/j.compfluid.2012.07.015

Cited by 14 publications

(4 citation statements)

References 25 publications

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“…Step 2: The predictive models of the EF R and R a are then established in terms of the inputs using the improved Kriging models. The Kriging model is an interpolation-based correlation using the Gaussian function, which is expressed as a function of the global model u and local deviation Z(x) [25]:…”

Section: Optimization Frameworkmentioning

confidence: 99%

Sustainability-Based Optimization of the Rotary Turning of the Hardened Steel

Nguyen

Duong

Mia

2020

Metals

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The rotary turning is an effective manufacturing method to machine hardened metals due to longer tool life, higher production rate, and acceptable quality. However, sustainability-based optimization of the rotary turning has not been thoroughly considered because of the huge efforts. This study presents an optimization to enhance the energy efficiency (EFR), turning cost (CT), average roughness (Ra), and the operational safety (POS) for the rotary turning of the hardened steel. Four key process parameters considered are the inclined angle (α), depth of cut (ap), feed rate (f), and cutting speed (vc). The improved Kriging (IK) models were used to construct the relations between the parameters and performances. The optimum varied factors were obtained utilizing the neighborhood cultivation genetic algorithm (NCGA). The findings revealed that the performance models are primarily affected by the feed rate, depth of cut, speed, and inclined angle, respectively. The optimal values of the α, ap, f, and vc are 26°, 0.44 mm, 0.37 mm/rev, and 200 mm/min, respectively. The improvements in energy efficiency, average roughness, and cost are 8.91%, 20.00%, and 14.75%, as compared to the initial values. Moreover, the NCGA may perform an efficient operation to obtain the optimal outcomes, as compared to conventional algorithms.

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Section: Optimization Frameworkmentioning

confidence: 99%

Sustainability-Based Optimization of the Rotary Turning of the Hardened Steel

Nguyen

Duong

Mia

2020

Metals

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“…Kriging approximation is a type of reduced order model, which has been proved to be able to do well with complexity problem such as multiobjectives/multivariables problem and multipeaks problem [16,27,28]. It can save lots of computational time and ultimately make optimization process available.…”

Section: Doe (Design Of Experiments) and Kriging Approximationmentioning

confidence: 99%

Parametric Study of Fuel Distribution Effects on a Kerosene-Based Scramjet Combustor

Yang

Wang

2016

International Journal of Aerospace Engineering

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Generally, the overall performance of scramjet combustor is greatly impacted by the fuel distribution scheme. The current paper mainly conducted a comprehensive parametric study of the impact of fuel distribution on the overall performance of a kerosene-based scramjet combustor. Herein, a 3D supersonic combustor with a recessed cavity and four injection orifices was taken into consideration. The combustor’s performance was analyzed by 3D RANS model. The fuel equivalence ratio for each injection port was taken as the design variables. And the combustion efficiency, the total pressure recovery coefficient, and the drag coefficient were chosen as the objective functions. Some novel data mining methods including DOE technique, Kriging approximation model, interaction analysis, and main effects analysis methods were employed to conduct the parametric study. The distributed fuel injection scheme was optimized by nondominated sorting genetic algorithm. The results show that three objective functions were remarkably affected by both of the total fuel equivalence ratio and the fuel distribution scheme. The objective functions cannot reach the optimal solution at the same time, and there must be a tradeoff among the objective functions.

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“…In order to fully exploit the capabilities of the adjoint solver, the control parameters of the actuation are allowed to vary spatially in the flap region so that largest degree of freedom is taken for the optimization, thus allowing the maximum design space dimension. A similar design strategy for aerodynamic shape optimization is suggested in [25]. This paper is organized as follows.…”

Section: Introductionmentioning

confidence: 99%

A Two-Level Hybrid Approach for Optimal Active Flow Control on a Three-Element Airfoil

Nemili¹,

Özkaya²,

Gauger³

et al. 2016

Proceedings of the VII European Congress on Computational Methods in Applied Sciences and Engineering (ECCOMAS Congress 2016)

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Abstract. In this paper we present a two-level approach that combines an adjoint-based gradient search method with an evolutionary algorithm for optimal active flow control. The suggested method effectively combines the advantages of both approaches and achieves a good compromise between the computational effort and the degree of freedom used in optimization. In the first level, a global optimization is performed with few design parameters using an evolutionary algorithm. In the second level, the global optimal solution from the first level is taken as the initial setting for the adjoint based local optimization using a large number of design parameters. The unsteady discrete adjoint solver required for the second level is developed based on Algorithmic Differentiation techniques for the unsteady incompressible flowsgoverned by Unsteady Reynolds-Averaged Navier Stokes (URANS) equations. In this way, the discrete adjoint solver is robust and has exactly the same functionality with the underlying URANS flow solver. The applicability of the two-level method is demonstrated by finding the optimal parameters of the active flow control mechanism on a three element airfoil configuration at a Reynolds number of Re = 10 6 and an angle of attack of AoA = 6 • . Numerical results have shown that the hybrid approach completely suppressed the separation and very significantly increased the mean-lift coefficient by 67% compared to the un-actuated baseline flow.

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Exploring multi-stage shape optimization strategy of multi-body geometries using Kriging-based model and adjoint method

Cited by 14 publications

References 25 publications

Sustainability-Based Optimization of the Rotary Turning of the Hardened Steel

Sustainability-Based Optimization of the Rotary Turning of the Hardened Steel

Parametric Study of Fuel Distribution Effects on a Kerosene-Based Scramjet Combustor

A Two-Level Hybrid Approach for Optimal Active Flow Control on a Three-Element Airfoil

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