An adaptive sampling strategy for construction of surrogate aerodynamic model

Wang, Xiaojun; Ni, Bowen; Zeng, Linxi; Liu, Yisi

doi:10.1016/j.ast.2021.106594

Cited by 7 publications

(3 citation statements)

References 25 publications

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“…Although traditional CFD methods can perform high-precision numerical simu-lations, the computation for data acquisition is much more expensive and time-consuming in airfoil aerodynamic optimization. Therefore, the surrogate model has emerged and gradually been developed as an essential branch and key technology of aerodynamic optimization [78].…”

Section: Aerodynamic Solving and Performance Evaluationmentioning

confidence: 99%

A Review of Intelligent Airfoil Aerodynamic Optimization Methods Based on Data-Driven Advanced Models

Wang,

Zhang,

Wang

et al. 2024

Mathematics

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With the rapid development of artificial intelligence technology, data-driven advanced models have provided new ideas and means for airfoil aerodynamic optimization. As the advanced models update and iterate, many useful explorations and attempts have been made by researchers on the integrated application of artificial intelligence and airfoil aerodynamic optimization. In this paper, many critical aerodynamic optimization steps where data-driven advanced models are employed are reviewed. These steps include geometric parameterization, aerodynamic solving and performance evaluation, and model optimization. In this way, the improvements in the airfoil aerodynamic optimization area led by data-driven advanced models are introduced. These improvements involve more accurate global description of airfoil, faster prediction of aerodynamic performance, and more intelligent optimization modeling. Finally, the challenges and prospect of applying data-driven advanced models to aerodynamic optimization are discussed.

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Section: Aerodynamic Solving and Performance Evaluationmentioning

confidence: 99%

A Review of Intelligent Airfoil Aerodynamic Optimization Methods Based on Data-Driven Advanced Models

Wang,

Zhang,

Wang

et al. 2024

Mathematics

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“…A sampling plan that is well-distributed but not regular across the design space is essential for building a surrogate model. 19 By changing propeller rotational speed and applying pitch angle variation, propeller performance is calculated and studied. Considering the working condition and the number of variables, full factorial sampling is applied to the design space, as shown in Figure 10.…”

Section: Design Of Experimentsmentioning

confidence: 99%

High-altitude airship variable-pitch propeller performance analysis at multiple altitudes

Dongchen

Song

Jiao

et al. 2023

Proceedings of the Institution of Mechanical Engineers, Part G:

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To achieve better propulsion performance for high-altitude airships, this paper proposes a variable-pitch propeller design and performance analysis. Propeller surrogate models were constructed based on an in-house fluid–structure solver and validated by a wind tunnel experiment. Based on the surrogate model, this paper studied propeller performance under the common influence of propeller pitch variation and rotational speed, and proved the positive effect of the variable-pitch propeller on maintaining relatively high efficiency in large rotational speed range. This paper compared the performance of variable-pitch propellers and fixed-pitch propellers under the constraints of the motor. The results show that introducing variable-pitch propellers to high-altitude airships can significantly improve propeller performance at multiple altitudes and laminar wind speeds. And the potential of airship weight reduction brought by the variable-pitch technique is discussed as well.

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“…The key to the success of adaptive sampling is therefore the selection of infill criteria, which determines the location of the new samples in the sample space. Wang et al 37 presented a novel adaptive sampling method based on the hyper-volume iteration (HVI) strategy for constructing surrogate aerodynamic models. Applying an adaptive sampling strategy based on expected local errors, Xu et al 38 proposed an ensemble of adaptive surrogate models.…”

Section: Introductionmentioning

confidence: 99%

Research on surrogate model of dam numerical simulation with multiple outputs based on adaptive sampling

Liang¹,

Li²,

Pan³

et al. 2023

Sci Rep

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Dam numerical simulation is an important method to research the dam structural behavior, but it often takes a lot of time for calculation when facing problems that require many simulations, such as structural parameter back analysis. The surrogate model is widely used as a technology to reduce computational cost. Although various methods have been widely investigated, there are still problems in designing the surrogate model's optimal Design of Experiments (DoE). In addition, most of the current DoE focuses on establishing a single-output problem. Designing a reasonable DoE for high-dimensional outputs is also a problem that needs to be solved. Based on the above issues, this research proposes a sequential surrogate model based on the radial basis function model (RBFM) with multi-outputs adaptive sampling. The benchmark function demonstrates the applicability of the proposed method to single-input & multi-outputs and multi-inputs & multi-outputs problems. Then, this method is applied to establishing a surrogate model for dam numerical simulation with multi-outputs. The result demonstrates that the proposed technique can be sampled adaptively and samples can be targeted based on the function form of the surrogate model, which significantly reduces the required sampling and calculation cost.

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An adaptive sampling strategy for construction of surrogate aerodynamic model

Cited by 7 publications

References 25 publications

A Review of Intelligent Airfoil Aerodynamic Optimization Methods Based on Data-Driven Advanced Models

A Review of Intelligent Airfoil Aerodynamic Optimization Methods Based on Data-Driven Advanced Models

High-altitude airship variable-pitch propeller performance analysis at multiple altitudes

Research on surrogate model of dam numerical simulation with multiple outputs based on adaptive sampling

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