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Gray-Box Dynamic Model for Wave Glider Driven by a Hybrid of Deep Learning and Physics-Based Models Dataset
- Citation Author(s):
- Submitted by:
- hui wang
- Last updated:
- Fri, 01/17/2025 - 12:15
- DOI:
- 10.21227/r2jd-a440
- License:
- Categories:
- Keywords:
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.
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.