Runway excursion during landing is usually formed by coupled deviations in energy management, flare timing, wind disturbance, and directional control, rather than by a single exceedance. This study proposes an interpretable Quick Access Recorder (QAR)-based machine learning framework to identify operational risk boundaries for runway excursion. Using 2362 valid flights from two airports, touchdown ground speed and magnetic heading are first inferred from aircraft states one second before touchdown. CatBoost and XGBoost provide stable regression performance, with root mean square error (RMSE) values of about 1.85 kt and 0.57 deg. Shapley additive explanations (SHAP) and locally weighted scatterplot smoothing (LOWESS) are then used to extract nonlinear thresholds and link them to two process-based risk manifestations, namely long landing from 50 ft to touchdown and landing rollout directional instability within 15 s after touchdown. The results show clear probability shifts. For long landing, IVV_mean crossing −237.95 ft/min increases the event probability from 0.011 to 0.144, while PITCH_MAX_to_TD above 5.29 s increases it from 0.032 to 0.191. For directional instability, WIN_CRS_var above 5.87 kt² increases the probability from 0.008 to 0.337, and LATG_min below −0.11 g increases it from 0.028 to 0.329. These thresholds are mapped into six ordered probability intervals, which provide auditable support for FOQA monitoring, explainable flight review, and threshold based runway excursion warning.
The unwanted overpressure and combustion promotion phenomenon by perfluoro-2-methyl-3-pentanone (C6F12O) hinders its application, previous studies indicated that composite approach holds promise for optimizing the overpressure of C6F12O. However, our previous research revealed that the optimization effect of inert gases is limited for the insufficient chemical effect, therefore, it is necessary to seek more efficient optimization methods. From the view of incorporating the agents with highly efficient chemical inhibition effects, this paper explored the optimizing effect of trifluoroiodomethane (CF3I) on the overpressure C6F12O through experiments and chemical kinetic mechanism. Experimental results show C6F12O/CF3I mixtures own considerable optimization on the increase of peak pressure and laminar burning velocity induced by C6F12O. As C6F12O/CF3I in 7/3 and 5/5 ratios, the maximum overpressure was reduced by 30.08% and 63.77%, respectively, the peak value of SL is decreased from 17.1 cm/s to 13.4 cm/s and 10.6 cm/s, and the adiabatic temperature increasing ratios have been delayed. Kinetic mechanism analysis demonstrated the high-efficient optimization effect of C6F12O/CF3I mixture on adiabatic temperature, free radicals and equilibrium gas amount. More interestingly, the iodide groups in mixture agents suppressed the CO production from hydrocarbon and fluorinated groups (center dot CF3CO, center dot C2F5CO and center dot CF:O), which increased the reaction CO + OH = CO2 + H to yield more H radicals and gas amount. Besides, iodide groups could also suppress hydrocarbon and fluorinated groups yield H radicals directly, thus demonstrating an excellent optimizing effect.
To investigate the impact of rainy weather on approach operations in the terminal maneuvering area (TMA), a multi-dimensional trajectory data analysis framework is proposed. The Air Traffic Management Airport Performance (ATMAP) algorithm is combined with Meteorological Terminal Aviation Routine Weather Reports (METAR) and Automatic Dependent Surveillance-Broadcast (ADS-B) trajectory data to filter approach trajectories under no-weather and rainy-weather conditions. The density-based Ordering Points To Identify the Clustering Structure (OPTICS) clustering algorithm is employed to identify nine typical approach trajectory patterns under no weather. By integrating a multi-classifier based on Synthetic Minority Over-Sampling Technique (SMOTE) oversampling and the RUSBoost algorithm, the rainy-weather trajectories are matched with the no-weather trajectory patterns. Based on the proposed trajectory centripetal aggregation degree (TCAD) indicator, three deviation levels — low, medium, and high — are defined. Subsequently, from four analytical dimensions — flight time, trajectory efficiency, pilot-controller radio communication pressure, and air traffic control (ATC) strategy — the impacts of rainy weather are systematically quantified using statistical hypothesis testing, effect size estimation, and the introduced trajectory stretch degree (TSD) and the proposed pressure index of pilot-controller radio communication (PIRC). Taking Beijing Capital International Airport as a case study, the results show that different trajectory patterns are affected by rainy weather to significantly different degrees. Further analysis reveals that differences in the chosen deviation modes are the fundamental causes of the varying impact degrees across trajectory patterns in different analytical dimensions, and three typical ATC strategies are identified. This framework can provide quantitative decision-making support for air traffic control units in predicting approach operation situations and optimizing airspace resource allocation under rainy weather conditions.
Lithium-ion batteries (LIBs) have become the cornerstone of global clean energy transition with their superior energy density and long cycle life. However, the escalating energy density of LIBs intensifies critical thermal safety concerns, including severe heat accumulation and uncontrollable thermal runaway propagation. The organic phase change materials (PCMs) are limited by inherent flammability and low latent heat, whereas inorganic hydrated salts suffer from intractable supercooling and liquid leakage. To address these bottlenecks, this study develops a hydrated-salt composite PCM (CPCM) employing sodium sulfate decahydrate as the matrix, encapsulated within a synergistic framework of expanded graphite and porous calcium silicate. The optimized CPCM features a dual-stage heat storage mechanism by leveraging vaporization enthalpy, it delivers a phase-change enthalpy of 140.5 J g−1 and the remarkable total heat-storage density of 879.0 J g−1, while maintaining excellent cyclic stability. Notably, the optimized CPCM demonstrates superior flame retardancy, achieving a UL-94 V-0 rating. In flame-exposure tests, the material acts as an exceptional flame-insulating barrier, maintaining an impressively low back-side temperature of merely 30.2 °C even under direct burner exposure. In a module comprising five series-connected 23 Ah prismatic lithium iron phosphate (LiFePO4) cells, SPEC10 limits the maximum temperature to 57.6 °C at 2C discharge rate, representing reductions of 5.2 °C and 5.0 °C relative to the organic flame-retardant CPCM (FRCPCM) and the hydrated salt CPCM (SPE5) modules, respectively. Furthermore, it provides a robust thermal shock protection with heating plates reaching 200 °C by 8000 s. This multifunctional CPCM serves as a promising material candidate for enhancing the thermal safety of battery management systems.
A strong coupling effect exists between aircraft fuselage dynamics and landing gear shimmy, but the interaction mechanism between this coupling and structural clearance, an inevitable strong nonlinear factor of landing gear, remains unclear. This study aims to address this gap by establishing a coupled nonlinear dynamic model of the fuselage-nose landing gear with clearance, and investigating the influence of key parameters on the system’s shimmy characteristics. Based on the established coupled nonlinear dynamic model of fuselage-nose landing gear with clearance, the study adopts bifurcation theory, Poincaré sections, Lyapunov exponent spectrum analysis, and numerical simulations to explore the effects of structural clearance, forward speed, and fuselage parameters on the system’s shimmy behavior. Structural clearance excites an independent lateral vibration mode of the fuselage, induces bilateral amplitude jumps in the torsional shimmy branch, and triggers transitions of the system’s dynamic behavior from periodic attractors to chaotic attractors and invariant tori. Fuselage modal mass and natural frequency exert distinct effects on shimmy characteristics: increased modal mass suppresses fuselage vibration and torsional shimmy but expands the lateral shimmy region, while increased natural frequency only reduces the fuselage vibration region. This study reveals the response mechanism of fuselage dynamics under clearance nonlinearity, clarifies the fuselage’s key role as a dominant factor of the system’s dynamic behavior in overall coupled vibration, and provides a theoretical basis for the anti-shimmy design of clearance-containing landing gear systems.
