Quantification and Sensitivity Analysis of the Model Uncertainty in the Projectile-Barrel Coupled Artillery Dynamics System Based on Random Matrix Theory
Simplifications in the engineering of artillery firing dynamics modeling introduce model uncertainty, which seriously affects the model’s predictive performance. To this end, a typical variable-section hollow cylindrical cantilever beam structure in artillery firing dynamics is investigated in this paper. The statistical approximation methods quantify parameter and model uncertainty separately, and their respective confidence intervals were calculated and compared. The results show that the traditional parameter uncertainty approach overestimates the parameter uncertainty ranges, and introducing the model uncertainty approach dramatically improves the model prediction performance. Additionally, a projectile-barrel coupled artillery dynamics model considering model uncertainty is established, and its effectiveness is validated through the actual launch experiments. The sensitivity of the dynamic responses to the system matrix, namely model uncertainty, is further analyzed. This paper provides theoretical references for the study of uncertainty in artillery launch dynamics and proposes effective methods to enhance the predictability of computational models for complex structural systems.
Authors
- Qingle Wu (ORCID: https://orcid.org/0009-0001-0844-9203)
- Guolai Yang (ORCID: https://orcid.org/0000-0003-2499-6407)
- Zongfan Wang (ORCID: https://orcid.org/0009-0000-4361-5505)
- Liqun Wang (ORCID: https://orcid.org/0000-0003-1475-8739)
- Chengyuan Guo
Institutions
- Nanjing University of Science and Technology (CN)
Publication Details
- Journal
- International Journal of Computational Methods
- Published
- 2024-08-29
- DOI
- https://doi.org/10.1142/s021987622450049x
- Citations
- 1
- Primary Topic
- Advanced Measurement and Detection Methods
- Type
- article
- Field-Weighted Citation Impact
- 0.21
Funders
- National Natural Science Foundation of China
- Natural Science Foundation of Jiangsu Province
- Intelligence Community Postdoctoral Research Fellowship Program