Data-Driven Modeling and Regulation of Aircraft Brakes Degradation via Antiskid Controllers

In ground vehicles, braking actuator degradation and tire consumption do not represent a significant maintenance cost as the lifespan of both components, at least in common situations, is rather long. In the aeronautical context, and for aircraft in particular, instead, braking actuator degradation and tire consumption significantly contribute to an aircraft maintenance cost due to the frequency of their replacement. This is mainly due to the fact that aircraft braking maneuvers last significantly longer than those in the automotive context. So that the antilock braking system is always active during the braking maneuver, making its impact on the consumption of the two components significant. This work proposes an innovative data-driven model of brake and tire degradation, showing how they are related to the antiskid controller parameters. The analysis is carried out in a MATLAB/Simulink environment on a single wheel rigid body model, validated experimentally, which includes all the nonlinear effects peculiar of the aeronautic context. The results show that by using an appropriate antiskid control approach, it is possible to directly regulate the consumption of these components while at the same time guaranteeing the required braking performance

Shock Absorber Leakage Impact on Aircraft Lateral Stability During Ground Handling Maneuvers

Aircraft braking maneuvers are safety-critical on-ground motions that exhibit complex dynamics and significant dependence on system operating conditions. The fundamental interface between the aircraft and the ground is the landing gear. Among the landing gear components, the shock absorbers may be subject to gas leakage during their lifetime, which is an anomaly that could compromise the lateral stability properties of the aircraft on the operating regimes found during braking maneuvers. In this paper, an explicit link is established between main landing gear shock absorber leakage and aircraft lateral stability. To investigate lateral stability, a high-fidelity multibody nonlinear aircraft simulator is developed in a MATLAB/Simulink framework and validated against experimental data. To generate insight into the problem and to quantify shock absorber leakage impact on aircraft lateral stability, two simple but descriptive analytical models are also developed, each one on a different operating mode of the system. The analysis of the models reveals that shock absorber leakage can have a significant effect on aircraft lateral stability, especially at high velocities and highly damped nose wheel steering conditions. The models developed in this work may be used by aircraft control system designers to come up with more effective lateral stability controllers in the event of main landing gear shock absorber leakage

Active and Data-driven Health and Usage Monitoring of Aircraft Brakes

Aircraft brakes are a safety-critical subsystem, and their prolonged use in each landing maneuver makes them subject to significant wear. Thus, it is crucial to devise efficient methods for monitoring their correct functioning and their health and usage status using the signals available in the Brake Control Unit. This paper proposes and validates an innovative data-driven approach to this problem. The proposed architecture is integrated with the Anti-lock Braking System algorithm providing combined health monitoring and anomaly detection for aircraft brakes in addition to an online estimate of the residual useful life of these components

GDF15 and ACE2 stratify COVID-19 patients according to severity while ACE2 mutations increase infection susceptibility

Coronavirus disease 19 (COVID-19) is a persistent global pandemic with a very heterogeneous disease presentation ranging from a mild disease to dismal prognosis. Early detection of sensitivity and severity of COVID-19 is essential for the development of new treatments. In the present study, we measured the levels of circulating growth differentiation factor 15 (GDF15) and angiotensin-converting enzyme 2 (ACE2) in plasma of severity-stratified COVID-19 patients and uninfected control patients and characterized the in vitro effects and cohort frequency of ACE2 SNPs. Our results show that while circulating GDF15 and ACE2 stratify COVID-19 patients according to disease severity, ACE2 missense SNPs constitute a risk factor linked to infection susceptibility