Prediction of Airtightness Performance of Stratospheric Ships Based on Multivariate Environmental Time-Series Data

Yitong Bi, Wenkuan Xu (), Lin Song, Molan Yang and Xiangqiang Zhang
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Yitong Bi: Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
Wenkuan Xu: Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
Lin Song: Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
Molan Yang: Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
Xiangqiang Zhang: Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China

Forecasting, 2025, vol. 7, issue 2, 1-23

Abstract: This study addresses the challenge of predicting the airtightness of stratospheric airship envelopes, a critical factor influencing flight performance. Traditional ground-based airtightness tests often rely on limited resources and empirical formulas. To overcome these limitations, this paper explores the use of predictive models to integrate multi-source test data, enhancing the accuracy of airtightness assessments. A performance comparison of various prediction models was conducted using ground-based test data from a specific stratospheric airship. Among the models evaluated, the NeuralProphet model demonstrated superior accuracy in long-term airtightness predictions, effectively capturing time-series dependencies and spatial interactions with environmental conditions. This work introduces an innovative approach to modeling airtightness, providing both experimental and theoretical contributions to the field of stratospheric airship performance prediction.

Keywords: stratosphere airship; airtightness; time series prediction (search for similar items in EconPapers)
JEL-codes: A1 B4 C0 C1 C2 C3 C4 C5 C8 M0 Q2 Q3 Q4 (search for similar items in EconPapers)
Date: 2025
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