Abstract

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.

Department(s)

Mechanical and Aerospace Engineering

Second Department

Mathematics and Statistics

Publication Status

Available Access

Comments

National Science Foundation, Grant 1923799

International Standard Serial Number (ISSN)

2377-2166; 2377-2158

Document Type

Article - Journal

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2024 American Society of Mechanical Engineers, All rights reserved.

Publication Date

01 Mar 2021

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