The Model and Data-Driven Digital Twin Technology for Ultimate Load-Bearing Capacity of the Rocket Propellant Tank Structure

HUANG Jia; TONG Jun; GUO Jian; GUO Wenjing; YANG Rong; ZHU Xiquan

doi:10.21656/1000-0887.450210

Volume 46 Issue 8

Aug. 2025

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Article Navigation > Applied Mathematics and Mechanics > 2025 > 46(8): 973-982

HUANG Jia, TONG Jun, GUO Jian, GUO Wenjing, YANG Rong, ZHU Xiquan. The Model and Data-Driven Digital Twin Technology for Ultimate Load-Bearing Capacity of the Rocket Propellant Tank Structure[J]. Applied Mathematics and Mechanics, 2025, 46(8): 973-982. doi: 10.21656/1000-0887.450210

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The Model and Data-Driven Digital Twin Technology for Ultimate Load-Bearing Capacity of the Rocket Propellant Tank Structure

doi: 10.21656/1000-0887.450210

Beijing Institute of Structure and Environment Engineering, Beijing 100076, P.R.China

Received Date: 2024-07-12
Rev Recd Date: 2024-07-31

Available Online: 2025-09-10

Abstract

Abstract

A digital twin methodology integrating physical measurements with computational modeling was proposed for predicting the ultimate load-bearing capacity of the key propellant tank structure in aerospace launch vehicles. First, a refined finite element model (FEM) was established based on the tank structural design and manufacturing process characteristics, to compute and analyze the structure strength, with results extracted specifically in positions corresponding to physical measurement points. Historical experimental data from structural strength tests were subsequently processed and analyzed. With both the test data and the simulation outputs, a comprehensive training dataset was constructed for the tank structure ultimate load-bearing capacity digital twin model. A long short-term memory (LSTM) network was then trained with this dataset to predict the structure ultimate load-bearing capacity. Finally, a dual-mode (offline and online interactive) digital twin system was implemented to predict the tank structure ultimate load-bearing performance. This proposed method significantly enhances virtual-physical testing ability and efficiency and reduces related testing costs and risks.
- tank structure,
- ultimate load-bearing capacity,
- digital twin,
- long short-term memory

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References(14)

References

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