Nonlinear and chaotic vessel dynamics

As military and commercial applications drive the marine industry towards innovation in hull design, particular research interest has grown from the need to reconcile speed and stealth with safety and stability. Dr. McCue’s particular research focuses have included coupling mathematical approaches, such as Lyapunov and finite-time Lyapunov exponents, with numerical simulation of ship dynamics to detect chaotic vessel behavior. Capsize and other vessel instabilites are studied using these techniques with the intent of developing real-time on-board tools of use to designers and vessel captains alike. Additionally, Dr. McCue’s research group has been working to apply Melnikov methods, traditionally limited to single degree of freedom roll models due to the requirement of small damping and forcing, to a broader range of ship phenomena. This research was supported by the Office of Naval Research and the National Science Foundation.

Smoothed particle hydrodynamics (SPH)

Smoothed particle hydrodynamics (SPH) is a meshless, Lagrangian, particle CFD method. Our research focuses upon coupling SPH and finite elements methods to understand dynamic behaviors of fluid-structure interaction in rapidly deforming conditions. The Office of Naval Research has supported this research.

Verification and Validation

This research seeks to develop novel verification and validation techniques by drawing together the fields of nonlinear time series analysis and computational fluid mechanics. Time series analysis provides qualitative and quantitative metrics for validation of ship motions numerical tools. Conversely, traditional CFD verification tools, such as the method of manufactured solutions, applied in a non-traditional manner, can be demonstrated to have great benefit in understanding and improving computation time when studying chaotic behaviors, including ship capsizing. This research has been supported by the Office of Naval Research and the National Science Foundation.

Neural networks

Our research group is studying the use of neural networks to better model and understand ship dynamic behavior. Neural networks are used both as a prediction tool, and as a tool which can produce results amenable to use in validation exercises, a mechanism for rapid incorporation of analytical results into a predictive framework, and as a means to compare different ship motion models. This work was supported by the Office of Naval Research and the National Science Foundation.

Quiescence prediction

Development of new approaches and evaluation criteria for anticipating quiescent behavior for launch and recovery operations. This research has the potential to improve the safety and/or the operating envelope for the launch and recovery of helicopters and other craft. This work has been supported by CSC, the Naval Surface Warfare Center, Carderock Division and the Office of Naval Research.

Sloshing of fluid in tanks

From liquified natural gas carriers to anti-rolling tanks, fluid sloshing in a tank, and the loads imparted on a vessel due to the sloshing of a fluid in a tank, result in interesting and complicated dynamics.

Parametric rolling

In addition to the capsize problem, Dr. McCue has conducted research on parametric rolling, a dangerous instability known to cause unexpectedly large increases in roll motions over short time periods.


When I migrated from aerospace engineering to naval architecture, I often remarked that I was the type of engineer who so long as whatever we were discussing was big enough to have a proverbial tire to kick, I am interested.  The interface of aerospace and ocean engineering has recently led me to a strong interest in exploration, exploration of Europa in particular!

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