Improved Similarity Law for Scaling Dynamic Responses of Stiffened Plates with Distorted Stiffener Configurations

Author:

Zhou Hongyu1234,Okada Tetsuo5ORCID,Kawamura Yasumi5ORCID,Wang Deyu23,Hayakawa Ginga5

Affiliation:

1. Graduate School of Engineering Science, Yokohama National University, Yokohama 240-8501, Japan

2. State Key Laboratory of Ocean Engineering, Shanghai Jiao Tong University, Shanghai 200240, China

3. Institute of Marine Equipment, Shanghai Jiao Tong University, Shanghai 200240, China

4. School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai 200240, China

5. Faculty of Engineering, Yokohama National University, Yokohama 240-8501, Japan

Abstract

Experimental analysis on small-scale models is widely used to predict the dynamic responses of full-scale structures subjected to impact loads. However, due to manufacturing constraints, achieving a perfectly scaled model under a large scaling factor is challenging, leading to the use of distorted scaled models as a compromise. This paper introduces an improved similarity law that ensures distorted scaled models accurately replicate the dynamic responses of prototype stiffened plates under impact loads. The proposed similarity law meticulously considers both the distorted attached plate thickness and variations in stiffener configuration. Double input parameters involving the load case and geometry are formulated to govern the dynamic responses of integrated stiffeners. Additionally, an approximate method rooted in elastic–plastic theory is developed to assess the dominant behaviors of stiffened plates during impact. Consequently, the distorted stiffener configuration of scaled models is designed through a methodology primarily centered on capturing dominant behaviors. Comprehensive numerical simulations are conducted to evaluate the behavior of stiffened plates subjected to impact loads. The results compellingly demonstrate that the proposed similarity law adeptly compensates for geometric distortions, ensuring reliable predictions of dynamic responses in distorted scaled models.

Publisher

MDPI AG

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