CFD-Generated Slamming Pressure Dataset for Wedge Water-Entry Prediction Using Stacking Ensemble Learning

Description

This dataset contains CFD-derived peak slamming-pressure data used to develop and evaluate machine-learning models for rapid prediction of wedge water-entry slamming pressure. The dataset comprises 96 water-entry operating conditions. For each condition, pressure peaks are provided at six monitoring positions, resulting in 576 samples. The input variables are water-entry velocity (V), wedge mass (M), and horizontal monitoring position (X), while the output variable is the CFD-derived peak slamming pressure (P).

Institutions

• Wuhan University of Technology

  Hubei, Wuhan

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