Virtual Rainwater Management for eVTOL and Drone Applications Using PreonLab SPH Simulation

Abstract:
Rainwater accumulation and management are critical to the safety and reliability of drones and emerging eVTOL aircraft. Current industry practice relies on physical rain testing, such as RTCA DO-160, which defines rainfall conditions for environmental qualification but is costly and difficult to apply during early design stages. This work presents a virtual rainwater assessment framework using Smoothed Particle Hydrodynamics (SPH) simulation in PreonLab. Using an early-stage APELEON cargo drone as a reference case, the method predicts rain impingement, surface runoff, pooling, and ingress under representative rainfall conditions. The meshless SPH approach enables direct simulation of complex geometries and transient interactions without mesh generation, while also supporting rotating components and arbitrary orientations. Results identify key mechanisms governing water transport, including geometry-driven runoff, hinge-related ingress, and droplet deflection from nearby structures. While the total water accumulated on the aircraft can reach on the order of several hundred grams, the amount entering the cargo space remain small. Localized moisture exposure highlights potential durability risks. The framework enables early design evaluation, parametric studies, and rapid assessment of mitigation strategies, supporting simulation-driven development and certification preparation for advanced air mobility systems.

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