Gray-Box Dynamic Model for Wave Glider Driven by a Hybrid of Deep Learning and Physics-Based Models Dataset

Citation Author(s):
Yongkuang
Zhang
Submitted by:
hui wang
Last updated:
Fri, 01/17/2025 - 12:15
DOI:
10.21227/r2jd-a440
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Abstract 

The data presented is "Gray-Box Dynamic Model for Wave Glider Driven by a Hybrid of Deep Learning and Physics-Based Models". In this study, the data set utilized for training the surrogate model consists of a total of 5 columns. These columns are FX, FZ, t, velx, and velz. Specifically, FX and FZ represent the hydrodynamic forces acting on the X - axis and Z - axis of the glider respectively. The variable t stands for time, while velx and velz denote the speeds of the glider on the z - axis and x - axis. This comprehensive data set is crucial for accurately training the model and understanding the behavior of the wave glider.

Instructions: 

For the actual data setup, both irregular waves (characterized by the PM spectrum) and regular waves were configured with a wave height of 1 m, a simulation duration of 40 s, and a sampling frequency of 100 Hz.

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