Design and Optimization of Artificial Reef Materials and Structures for Intelligent Ocean Ranching: A Neural Network and CFD Approach

Qichao Yang; Liren Zhang; Zhenbo Li; Junyi Jiang; Pengye Jiang

doi:10.54691/xt7xfb25

Authors

Qichao Yang
Liren Zhang
Zhenbo Li
Junyi Jiang
Pengye Jiang

DOI:

https://doi.org/10.54691/xt7xfb25

Keywords:

Artificial reef, fly ash, BP neural network, fluid dynamics, 3D printing, fish behavior.

Abstract

This study focuses on the design and optimization of artificial reef materials and structures for ocean ranching. By incorporating fly ash, a major solid waste, into reef materials, we aim to achieve resource utilization and carbon emission reduction. BP neural network models are used to predict the composition ratio of concrete to meet expected mechanical properties. Two types of reef structures, "deflector - type" and "upwelling - type," are designed and analyzed through fluid dynamics simulations. The "deflector - type" reef is selected based on the results. Additionally, a customized cement 3D printer is developed to fabricate the reefs. Experimental studies on fish behavior responses to the reefs are also conducted. The results provide a theoretical basis and technical support for the construction of intelligent ocean ranches.

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