Rapid prediction and optimization method for protective effectiveness of flexibly supported plate structure under underwater explosive

GUO Tongtong; GUO Yu; YU Jun; CHEN Juan; WANG Haikun; ZHANG Lunping

doi:10.11883/bzycj-2024-0068

Volume 44 Issue 10

Oct. 2024

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GUO Tongtong, GUO Yu, YU Jun, CHEN Juan, WANG Haikun, ZHANG Lunping. Rapid prediction and optimization method for protective effectiveness of flexibly supported plate structure under underwater explosive[J]. Explosion And Shock Waves, 2024, 44(10): 105101. doi: 10.11883/bzycj-2024-0068

Citation:

GUO Tongtong, GUO Yu, YU Jun, CHEN Juan, WANG Haikun, ZHANG Lunping. Rapid prediction and optimization method for protective effectiveness of flexibly supported plate structure under underwater explosive[J]. Explosion And Shock Waves, 2024, 44(10): 105101. doi: 10.11883/bzycj-2024-0068

Citation:

GUO Tongtong, GUO Yu, YU Jun, CHEN Juan, WANG Haikun, ZHANG Lunping. Rapid prediction and optimization method for protective effectiveness of flexibly supported plate structure under underwater explosive[J]. Explosion And Shock Waves, 2024, 44(10): 105101. doi: 10.11883/bzycj-2024-0068

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Rapid prediction and optimization method for protective effectiveness of flexibly supported plate structure under underwater explosive

doi: 10.11883/bzycj-2024-0068

GUO Tongtong^{1, 2
,},
GUO Yu^{1, 2},
YU Jun^{1, 2},
CHEN Juan³,
WANG Haikun^{1, 2},
ZHANG Lunping^{1, 2
,
,}

1.
China Ship Scientific Research Center, Wuxi 214000, Jiangsu, China
2.
Taihu Laboratory of Deep Sea Technology Science, Wuxi 214000, Jiangsu, China
3.
China Ship Development and Design Center, Wuhan 430000, Hubei, China

Received Date: 2024-03-11
Rev Recd Date: 2024-08-21

Available Online: 2024-09-02

Publish Date: 2024-10-30

Abstract

Abstract

In order to make a rapid assessment and design optimization of the protective performance of flexibly supported plate structure subjected to underwater explosion, a high-confidence simulation method is first established for the protective performance of flexibly supported plate structure subjected to underwater explosion. Then, underwater explosion tests were conducted on the flexibly supported plate structure to validate the computational accuracy of the developed high-confidence simulation method by comparing the deformation between the simulation results and the experimental results. The thickness of the blast-facing panel, the thickness of the flexible supports, and the thickness of the stiffened web are identified as the three key characteristic parameters that affect the protective performance of the flexibly supported plate. Utilizing optimized Latin-hypercube sampling method, 15 sample conditions are extracted from the sample space. The validated high-confidence simulation method is then used to generate protective performance data for these 15 sample conditions, which is subsequently employed to construct a proxy model for rapid assessment of the protective performance of the flexibly supported plates by using a radial basis function (RBF) neural network. The accuracy of the proxy model is assessed by using 5 randomly selected conditions, and the results show that the prediction error is within 7%, indicating a high level of prediction accuracy. The multi-island genetic algorithm (MIGA) is applied to the proxy model to perform multi-objective optimization and obtain a pareto set of solutions. The condition with the maximum specific ultimate energy absorption per unit mass is selected as the optimal structural parameters for the flexibly supported plate, achieving the goals on enhancing the ultimate protective performance and reducing the total structural mass. The rapid prediction and optimization method developed in this study provides significant technical support for the design and optimization of flexibly supported plate, and ensures both effective protection and weight savings.
- underwater explosion,
- flexibly supported plate,
- protective effectiveness,
- sampling method,
- neural network,
- multi objective optimization

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References(12)

References

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