In view of the fact that there is no suitable measurement method for tire driving resistance during the operation of a transporter on soil pavement, this paper proposes a simple measurement and estimation method for driving resistance on a soil runway based on the Bekker settlement model. In this paper, using the driving resistance equation based on the Bekker model, a simplified equation of driving resistance related to mass is proposed. Using the principle of kinematics, a simple test device for driving resistance was developed, and the test data of the test device were used to determine the parameters of the driving resistance estimation equation of the road surface. The driving resistance of the wheel running state was tested by the simulated aircraft load loading vehicle through the mechanical sensor, and the consistency between the theoretical value and the actual value of the driving resistance value under 8T, 10T, and 12T loads was verified. This research shows that the test method and estimation method have low cost and good accuracy and are suitable for wide promotion. The results of this paper provide a new idea and method for estimating the driving resistance of a wheel when a transporter runs on a soil road and also provide a reference for designing the length of a soil runway.

Aiming at the practical difficulties (e.g., high cost of full-scale tests) in testing the rolling resistance of aircraft wheels on unpaved runways, this study establishes a theoretical calculation formula for wheel rolling resistance based on the Bekker model, following an analysis of the development and application of wheel–soil interaction models. Global sensitivity analysis using the Sobol’ method was performed on the theoretical formula to derive a simplified calculation model. Aircraft load simulation tests under 80 kN, 100 kN, and 120 kN loading conditions were conducted using a specialized loading vehicle to determine parameters for the simplified prediction model. The resistance values obtained from this model were then applied to calculate aircraft takeoff roll distance. The accuracy of resistance estimation was verified by comparing the calculated results with takeoff distances reported in relevant literature. This research provides a novel approach for estimating wheel rolling resistance of transport aircraft on unpaved runways and offers valuable reference for determining the required length of unpaved runways.

Runway excursion (RE) risk during aircraft landing emerges from the coupling of technical, environmental, human, information-related, and organizational factors, and is characterized by the coexistence of deterministic deviations and uncertain intermediate states. This study proposes an uncertainty-aware RE risk assessment framework by integrating the SHELLO model with Set Pair Analysis. A six-dimensional indicator system covering Software, Hardware, Environment, Liveware, Liveware–Organization, and Organization was established based on accident reports, regulatory and operational documents, 94 valid pilot questionnaires, and expert consultation. Indicator weights were determined through structured expert judgment, and grading thresholds were established by integrating industry standards, operational evidence, expert judgment, and simulation-supported information. A discrepancy-refined ternary SPA formulation was employed to characterize identity, discrepancy, and contrary relationships and to further resolve the discrepancy component into identity-side, residual, and contrary-side components. The principal value of connection degree and set pair potential were then used to characterize the separation of the evaluated state from the neutral position and the relative dominance between identity and contrary components. A case study of an A320-landing RE scenario indicated that the evaluated system fell within the Grade II intermediate diagnostic region. Hardware and Environment characterized the background risk conditions, whereas Software-related information deviations and Liveware–Organization coordination deficiencies showed the most prominent negative diagnostic contributions. Four additional anonymized A320-landing incident cases exhibited distinct dimensional risk profiles. Discrepancy refinement changed three-dimensional classifications relative to conventional SPA, illustrating its effect on boundary-sensitive risk diagnosis.

In view of the lack of soil bins for studying the surface interaction between aircraft wheels and soil, this study designed an indoor test bench for aircraft wheels and soil, including a soil container, loading vehicle, and intelligent measurement and control system, to test key parameters such as tire speed and wheel frictional resistance. The test system is capable of achieving speed regulation ranging from 0 to 30 km/h. The vertical load adjustment range with an adjustment interval of 10 kg spans from 90 to 140 kg. The soil type, compaction degree, and other conditions can be modified as per requirements to vary multiple test conditions, thereby enabling us to explore their influence on the driving resistance of the wheels. Moreover, the test data can be collected and processed in real time. A performance test of a wheel–soil table was carried out. The results show that the wheel–soil table test system is stable and reliable and can determine the relationship between the tire and soil, and the structural design of the test system meets the use requirements. In addition, it achieves the target test speed, data acquisition frequency, and stability. In terms of functionality and operational difficulty, the data acquisition of the entire test process is automated, and the test system achieves better informationization than previous methods. The overall operation of the wheel–soil platform is stable and powerful; thus, the model test platform design goal is achieved, and the testing requirements are met.