scholarly journals 1114 Multidisciplinary Design Optimization of Wing Shape for a Small Jet Aircraft Using Kriging Model

2005 ◽  
Vol 2005.15 (0) ◽  
pp. 66-69
Author(s):  
Takayasu Kumano ◽  
Shinkyu Jeong ◽  
Shigeru Obayashi ◽  
Yasushi Ito ◽  
Keita Hatanaka ◽  
...  
Keyword(s):  
Design Optimization ◽  
Multidisciplinary Design Optimization ◽  
Kriging Model ◽  
Wing Shape ◽  
Multidisciplinary Design

scholarly journals An Enhanced Analytical Target Cascading and Kriging Model Combined Approach for Multidisciplinary Design Optimization

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Ping Jiang ◽  
Jianzhuang Wang ◽  
Qi Zhou ◽  
Xiaolin Zhang
Keyword(s):  
Design Optimization ◽  
Multidisciplinary Design Optimization ◽  
Kriging Model ◽  
Multidisciplinary Design ◽  
High Approximation ◽  
Engineering Systems ◽  
Analytical Target Cascading ◽  
Combined Approach ◽  
Coordination Strategy ◽  
Target Cascading

Multidisciplinary design optimization (MDO) has been applied widely in the design of complex engineering systems. To ease MDO problems, analytical target cascading (ATC) organizes MDO process into multilevels according to the components of engineering systems, which provides a promising way to deal with MDO problems. ATC adopts a coordination strategy to coordinate the couplings between two adjacent levels in the design optimization process; however, existing coordination strategies in ATC face the obstacles of complicated coordination process and heavy computation cost. In order to conquer this problem, a quadratic exterior penalty function (QEPF) based ATC (QEPF-ATC) approach is proposed, where QEPF is adopted as the coordination strategy. Moreover, approximate models are adopted widely to replace the expensive simulation models in MDO; a QEPF-ATC and Kriging model combined approach is further proposed to deal with MDO problems, owing to the comprehensive performance, high approximation accuracy, and robustness of Kriging model. Finally, the geometric programming and reducer design cases are given to validate the applicability and efficiency of the proposed approach.

Comprehensive Study of Typical Metamodel Methods Applied in Aircraft Multidisciplinary Design Optimization

2011 ◽  
Vol 110-116 ◽  
pp. 3031-3039 ◽  
Author(s):  
Teng Long ◽  
Li Liu
Keyword(s):  
Design Optimization ◽  
Multidisciplinary Design Optimization ◽  
Least Squares Method ◽  
Numerical Test ◽  
Kriging Model ◽  
Multidisciplinary Design ◽  
Test Problems ◽  
Comparison Results ◽  
Moving Least Squares Method ◽  
Comprehensive Study

—Metamodels have been widely applied in aircraft multidisciplinary design optimization (MDO) to alleviate the computation burden and improve the optimization efficiency. At present, there are various metamodel methods available, such as response surface method, Kriging model, moving least squares method, radial basis function, neural networks and so on. However, it is difficult to confirm which metamodel method is more promising, which is also an interesting question puzzled most designers. In this article, by using a series of numerical test problems with different inherent features, a comprehensive study is employed to compare five typical metamodel methods commonly applied in aircraft MDO under multiple metrics. In term of the comparison results, the conclusions are drawn and recommendations for selecting suitable metamodels in aircraft MDO practice are also summarized.

Hybrid reliability-based multidisciplinary design optimization with random and interval variables

2017 ◽  
Vol 232 (1) ◽  
pp. 52-64 ◽  
Author(s):  
Fan Yang ◽  
Zhufeng Yue ◽  
Lei Li ◽  
Dong Guan
Keyword(s):  
Design Optimization ◽  
Multidisciplinary Design Optimization ◽  
Region Of Interest ◽  
Kriging Model ◽  
Collaborative Optimization ◽  
Multidisciplinary Design ◽  
Learning Function ◽  
Design Variables ◽  
Interval Variables ◽  
Hybrid Reliability

This article presents a procedure for reliability-based multidisciplinary design optimization with both random and interval variables. The sign of performance functions is predicted by the Kriging model which is constructed by the so-called learning function in the region of interest. The Monte Carlo simulation with the Kriging model is performed to evaluate the failure probability. The sample methods for the random variables, interval variables, and design variables are discussed in detail. The multidisciplinary feasible and collaborative optimization architectures are provided with the proposed method. The method is demonstrated with three examples.

scholarly journals Metamodel-Based Multidisciplinary Design Optimization of a Deep-Sea Manganese Nodules Test Miner

2012 ◽  
Vol 2012 ◽  
pp. 1-18 ◽  
Author(s):  
Minuk Lee ◽  
Su-gil Cho ◽  
Jong-Su Choi ◽  
Hyung-Woo Kim ◽  
Sup Hong ◽  
...  
Keyword(s):  
Design Optimization ◽  
Deep Sea ◽  
Multidisciplinary Design Optimization ◽  
Deep Ocean ◽  
Kriging Model ◽  
Multidisciplinary Design ◽  
Surface Model ◽  
Manganese Nodules ◽  
Component Systems ◽  
Design Requirements

A deep-sea manganese nodules test miner has not only coupled relationship between system components but also various design requirements of each system to meet the specified multitasks. To accomplish the multiobjectives of complex systems, multidisciplinary design optimization (MDO) is performed. Metamodels such as the kriging model and the response surface model are employed to reduce computational costs for MDO and to integrate component systems in a design framework. After verifying the accuracy of each metamodel, metamodel-based MDO for a deep-ocean test miner is formulated and performed. Finally, results and advantages of the proposed design methodology are discussed.

scholarly journals Evidence-Based Multidisciplinary Design Optimization with the Active Global Kriging Model

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-13 ◽  
Author(s):  
Fan Yang ◽  
Ming Liu ◽  
Lei Li ◽  
Hu Ren ◽  
Jianbo Wu
Keyword(s):  
Design Optimization ◽  
Multidisciplinary Design Optimization ◽  
Evidence Theory ◽  
Engineering Application ◽  
Kriging Model ◽  
Collaborative Optimization ◽  
Multidisciplinary Design ◽  
Evidence Based ◽  
Kriging Method ◽  
Learning Function

This article presents an approach that combines the active global Kriging method and multidisciplinary strategy to investigate the problem of evidence-based multidisciplinary design optimization. The global Kriging model is constructed by introducing a so-called learning function and using actively selected samples in the entire optimization space. With the Kriging model, the plausibility, Pl, of failure is obtained with evidence theory. The multidisciplinary feasible and collaborative optimization strategies of multidisciplinary design optimization are combined with the evidence-based reliability analysis. Numerical examples are provided to illustrate the efficiency and accuracy of the proposed method. The numerical results show that the proposed algorithm is effective and valuable, which is valuable in engineering application.

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