Sensors, Journal Year: 2025, Volume and Issue: 25(7), P. 2202 - 2202
Published: March 31, 2025
Water film depth (WFD) on runways is a key factor contributing to aircraft hydroplaning during takeoff and landing. Thus, the early measurement or prediction of WFD rain critical for reducing accidents. Most existing models are derived from experiments conducted road surfaces. However, an accurate reduced risk require precise empirical model. This study involving four parameters-rainfall intensity, pavement mean texture depth, drainage length, transverse slope-to develop dataset specific different runway conditions. The multiple linear regression method employed establish model predictions. proposed National Taiwan University (NTU) model's predictability compared with three using NTU Gallaway datasets. results clearly demonstrate superior accuracy robustness other evaluated models. offers practical predictive formula, making it highly suitable integration into contaminated warning management systems. laser displacement sensor programmable logic controller obtain high-accuracy, high-sampling-rate data. Modern automated data acquisition enables simultaneous at points captures complete curve zero stable which was previously difficult obtain.
Language: Английский