Regime Maps for Sloshing in Horizontal Cylindrical Tanks Under Vertical Acceleration

TL;DR

This paper develops a data-driven regime map for vertical sloshing in cylindrical tanks under vertical acceleration, aiding in predicting and managing sloshing effects on vehicle stability.

Contribution

It introduces a novel regime classification method using high-speed video, mPOD, and kernel classification, avoiding interface tracking.

Findings

Identified distinct sloshing regimes including stable waves and mode shapes.

Created a dimensionless regime map for three fill ratios.

Provided a predictive tool for sloshing-induced load assessment.

Abstract

Vertical sloshing in partially filled fuel tanks can significantly impact vehicle stability and structural integrity, particularly under harmonic accelerations near twice the sloshing natural frequency. In this regime, parametric resonance may arise, with nonlinear free-surface dynamics driving large-amplitude waves, interface break-up, and severe sloshing-induced mixing. In this work, we identify and characterize the distinct sloshing regimes associated with the lowest-frequency parametric instability, specifically when the external forcing frequency approaches twice the lowest natural frequency. Experiments were conducted in a transparent cylindrical tank with diameter D = 134.5 mm and length L = 336.3 mm. This work presents a data-driven approach for regime identification and classification that relies solely on high-speed video recordings and circumvents the need for interface tracking. The method combines prototype-based data labeling with dimensionality reduction via multiscale proper orthogonal decomposition (mPOD) and automatic kernel-based classification. The results are summarized in a dimensionless regime map across three fill ratios, where stable waves, longitudinal and transverse mode shapes, and mode-competition regimes are distinguished. The developed map provides a predictive tool for assessing sloshing-induced loads, supporting structural and operational optimization of fuel systems.