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Facial recognition software (FRS) is a form of biometric security that detects a face, analyzes it, converts it to data, and then matches it with images in a database. This technology is currently being used in vehicles for safety and convenience features, such as detecting driver fatigue, ensuring ride share drivers are wearing a face covering, or unlocking the vehicle. Public transportation hubs can also use FRS to identify missing persons, intercept domestic terrorism, deter theft, and achieve other security initiatives. However, biometric data is sensitive and there are numerous remaining questions about how to implement and regulate FRS in a way that maximizes its safety and security potential while simultaneously ensuring individual’s right to privacy, data security, and technology-based equality.

We present an approach in which we use simulation to capture the two-way coupling between the dynamics of a vehicle and that of a fluid that sloshes in a tank attached to the vehicle. The simulation is carried out in and builds on support provided by two modules: Chrono::FSI (Fluid-Solid Interaction) and Chrono::Vehicle. The dynamics of the fluid phase is governed by the mass and momentum (Navier-Stokes) equations, which are discretized in space via a Lagrangian approach called Smoothed Particle Hydrodynamics. The vehicle dynamics is the solution of a set of differential algebraic equations of motion. All equations are discretized in time via a half-implicit symplectic Euler method. This solution approach is general - it allows for fully three dimensional (3D) motion and nonlinear transients. We demonstrate the solution in conjunction with the simulation of a vehicle model that performs a constant radius turn and double lane change maneuver.