Design Optimization of Three-Dimensional Channel Roughened by Oblique Ribs Using Response Surface Method

2004 ◽  
Vol 28 (7) ◽  
pp. 879-886 ◽  
Author(s):  
Young-Seok Choi ◽  
Yong-In Kim ◽  
Sung Kim ◽  
Seul-Gi Lee ◽  
Hyeon-Mo Yang ◽  
...  

Abstract This paper describes the numerical optimization of an axial fan focused on the blade and guide vane (GV). For numerical analysis, three-dimensional (3D) steady-state Reynolds-averaged Navier-Stokes (RANS) equations with the shear stress transport (SST) turbulence model are discretized by the finite volume method (FVM). The objective function is enhancement of aerodynamic performance with specified total pressure. To select the design variables which have main effect to the objective function, 2k factorial design is employed as a method for design of experiment (DOE). In addition, response surface method (RSM) based on the central composite design applied to carry out the single-objective optimization. Effects on the components such as bell mouth and hub cap are considered with previous analysis. The internal flow characteristics between base and optimized model are analyzed and discussed.


Author(s):  
P. BHATTACHARJEE ◽  
K. RAMESH KUMAR ◽  
T. A. JANARDHAN REDDY

Optimization of any aerospace product results in increasing payload capacity of space vehicles. Essentially weight, volume and cost are the main constraints. Design optimization studies for aerospace system are increasingly gaining importance. The problem of optimum design under uncertainty has been formulated as reliability-based design optimization. The reliability based optimization, which includes robustness requirements leads to multi-objective optimization under uncertainty. In this paper Reliability, based design optimization study is carried out under linear constraint optimization to minimize the weight of a nitrogen gas bottle with specified target reliability. Response surface method considering full factorial experiment is used to establish multiple regression equation for induced hoop stress and maximum strain. Necessary data pertaining to design, manufacturing and operating conditions are collected systematically for variability study. Structural reliability is evaluated using Advanced First-Order Second-Moment Method (AFOSM). Finally, optimization formulation established and it has been discussed in this paper.


Author(s):  
Xiao Tang ◽  
Jiaqi Luo ◽  
Feng Liu

An adjoint-response surface method is developed to give global representation of cost function in a parametrized design space for turbomachinery blades. Radial basis function (RBF) based and quadratic polynomial (QP) based response surface models are constructed using both the values of cost function and its adjoint gradients with respect to geometry control parameters. The method is tested on a quasi-three dimensional NACA0012 blade row, then applied to the transonic Rotor 67. In preliminary design optimization stage, when the number of undetermined control parameters is large, the QP based model can provide a global image of the cost function in high dimensional design space with a small amount of sample points. In two-parameter fine optimization stage, high resolution can be achieved with the RBF based models. This gradient-enhanced response surface method is useful in guiding designers to discover the global optimum which may be missed by local gradient methods in a complicated design space. It may also be used as substitute of CFD flow solver in time consuming iterative design and optimization.


2020 ◽  
Vol 25 (3) ◽  
pp. 355-362
Author(s):  
Youn-Hwan Kim ◽  
Do-Hyeop Kim ◽  
Jae-Won Moon ◽  
Sang-Young Jung

2008 ◽  
Vol 130 (12) ◽  
Author(s):  
Chwail Kim ◽  
K. K. Choi

Since variances in the input variables of the engineering system cause subsequent variances in the product output performance, reliability-based design optimization (RBDO) is getting much attention recently. However, RBDO requires expensive computational time. Therefore, the response surface method is often used for computational efficiency in solving RBDO problems. A method to estimate the effect of the response surface error on the RBDO result is developed in this paper. The effect of the error is expressed in terms of the prediction interval, which is utilized as the error metric for the response surface used for RBDO. The prediction interval provides upper and lower bounds for the confidence level that the design engineer specified. Using the prediction interval of the response surface, the upper and lower limits of the reliability are computed. The lower limit of reliability is compared with the target reliability to obtain a conservative optimum design and thus safeguard against the inaccuracy of the response surface. On the other hand, in order to avoid obtaining a design that is too conservative, the developed method also constrains the upper limit of the reliability in the design optimization process. The proposed procedure is combined with an adaptive sampling strategy to refine the response surface. Numerical examples show the usefulness and the efficiency of the proposed method.


2021 ◽  
Author(s):  
Jacopo Iannacci ◽  
Girolamo Tagliapietra ◽  
Alessio Bucciarelli

Abstract The emerging paradigms of Beyond-5G, 6G and Super-IoT will demand for Radio Frequency (RF) passive components with pronounced performance, and RF-MEMS technology, i.e. Microsystem-based RF passives, is a good candidate to meet such a challenge. As known, RF-MEMS have a complex behavior, that crosses different physical domains (mechanical; electrical; electromagnetic), making the whole design optimization and trimming phases particularly articulated and time consuming. In this work, we propose a novel design optimization approach based on the Response Surface Method (RSM) statistical methodology, focusing the attention on a class of RF-MEMS-based programmable step power attenuators. The proposed method is validated both against physical simulations, performed with Finite Element Method (FEM) commercial software tools, as well as experimental measurements of physical devices. The case study here discussed features 3 DoFs (Degrees of Freedom), comprising both geometrical and material parameters, and aims at optimizing the RF performance of the MEMS attenuator in terms of attenuation (S21 Scattering parameter) and reflection (VSWR – Voltage Standing Wave Ratio). When validate, the proposed RSM-based method allows avoiding physical FEM simulations, thus making the design optimization considerably faster and less complex, both in terms of time and computational load.


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