Adaptive Kriging Method for Uncertainty Quantification of the Photoelectron Sheath and Dust Levitation on the Lunar Surface | Zendy

Xinpeng Wei | Zendy; Jianxun Zhao | Zendy; Xiaoming He | Zendy; Zhen Hu | Zendy; Xiaoping Du | Zendy; Daoru Han | Zendy

Open Access

Adaptive Kriging Method for Uncertainty Quantification of the Photoelectron Sheath and Dust Levitation on the Lunar Surface

Author(s) -

Xinpeng Wei,

Jianxun Zhao,

Xiaoming He,

Zhen Hu,

Xiaoping Du,

Daoru Han

Publication year - 2021

Publication title -

journal of verification validation and uncertainty quantification

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.218

H-Index - 4

eISSN - 2377-2166

pISSN - 2377-2158

DOI - 10.1115/1.4050073

Subject(s) - levitation , kriging , surface (topology) , function (biology) , computer science , mathematics , engineering , geometry , mechanical engineering , machine learning , evolutionary biology , biology , magnet

This paper presents an adaptive Kriging based method to perform uncertainty quantification (UQ) of the photoelectron sheath and dust levitation on the lunar surface. The objective of this study is to identify the upper and lower bounds of the electric potential and that of dust levitation height, given the intervals of model parameters in the one-dimensional (1D) photoelectron sheath model. To improve the calculation efficiency, we employ the widely used adaptive Kriging method (AKM). A task-oriented learning function and a stopping criterion are developed to train the Kriging model and customize the AKM. Experiment analysis shows that the proposed AKM is both accurate and efficient.

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