Experimental study and numerical model adequacy assessment of hull structure dynamic response subject to underwater explosion

ABSTRACT

The purpose of this study was to establish a model adequacy assessment method for dynamic response of hull structure subjected to underwater explosion. A numerical model is established and experiments are carried out to assess the shock response of the hull structure. Experiment data processing method suitable for this study is proposed. The numerical calculation results and the processed experimental data are first compared graphically to initially verify the accuracy of the numerical model. Subject matter expert score for qualitative analysis is obtained from the comparison of time series and the quantitative validation metric is calculated. Four validation metrics are introduced to represent the different time and frequency domain characteristics of the signals. Probabilistic neural network is used to establish the relationship between subject matter expert score and validation metric. The total probability formula is used to synthesize the overall model adequacy score of the model.

KEYWORDS:

• Underwater explosion
• model adequacy assessment
• probabilistic neural network
• validation metric
• experimental study

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes on contributors

Wenqi Zhang, PHD candidate, College of Shipbuilding Engineering, Harbin Engineering University, Harbin, China.

Xiongliang Yao, Professor, College of Shipbuilding Engineering, Harbin Engineering University, Harbin, China.

Yinan Wang, PHD candidate, College of Shipbuilding Engineering, Harbin Engineering University, Harbin, China.

Zhikai Wang, Associate professor, College of Shipbuilding Engineering, Harbin Engineering University, Harbin.

ORCID

Wenqi Zhang http://orcid.org/0000-0003-2317-7100

Additional information

Funding

The authors gratefully acknowledge the support provided by the National Natural Science Foundation of China [grant number 51779056, 11602069] and the Natural Science Foundation of Heilongjiang Province [grant number E2017026].