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Long-term preventive maintenance planning using finite annual budgets is vital for maintaining the service performance of airport runway composite pavements. Using the pavement condition index (PCI) to quantify composite pavement performance, this study investigated the PCI deterioration tendencies of middle runways, terminal runways, and taxiways and developed prediction models related to structural thickness and air traffic. Performance jump (PJ) and deterioration rate reduction (DRR) were used to measure maintenance benefits. Based on 112 composite pavement sections in the Long-term Pavement Performance Program, this study analyzed the influences of five typical preventive maintenance technologies on PJ, DRR, and PCI deterioration rates. The logarithmic regression relationship between PJ and PCI was obtained. For sections treated with crack sealing and crack filling, the DRR was nearly 0. For sections treated with fog seal, thin HMA overlay, and hot-mix recycled AC, the DRR was 0.2, 0.7, and 0.8, respectively. To solve the multi-objective maintenance problem, this study proposed a decision-making optimization method based on dynamic programming, and the solution algorithm was optimized, which was applied in a five-year maintenance plan. Considering different PCI deterioration tendencies of airport regions, as well as PJ, DRR, and costs of maintenance technologies, the preventive maintenance decision-making optimization method meets performance and financial requirements sufficiently. [ABSTRACT FROM AUTHOR]

This study was undertaken to develop a new index, the Airport Runway Roughness Index (ARRI), that considers the effect of runway space when evaluating airport runway roughness. The difference between roadway and runway roughness evaluations is analysed in detail and the spatial effect is considered for a proposed runway roughness evaluation model. The evaluation of runway roughness should fully account for the dynamic responses of different typical aircraft during taxiing at the most unfavourable speed for the full cross-section of the runway. ARRI is defined according to the normalised weighted average of the vibration responses of typical aircraft models at the most unfavourable excitation waveband, the most unfavourable taxiing speed, and the most unfavourable lateral offset position within the longitudinal distance of the runway. Using runway three-dimensional full-section unevenness data collection equipment, a runway roughness evaluation procedure that is based on ARRI is proposed. The ARRI system provides qualitative improvement in terms of its representation ability, the rationality of the evaluation criteria, and the correlation of the indicators. [ABSTRACT FROM AUTHOR]

Dynamic soil stress in the ground induced by aircraft loads can lead to excessive and differential settlements. The effect of aircraft speeds on the dynamic stress is complicated due to runway roughness, lift force and wave propagation. In this paper, a virtual prototype model of B777-300 was initially developed to investigate the aircraft loads impacted by runway roughness and lift force. Subsequently, a finite element model of the runway was established for the dynamic stress in the ground subjected to moving aircraft loads. Results show that as aircraft speed increases, the aircraft-load-induced dynamic stress in the ground first increases and then decreases. The critical speed of dynamic stress accompanied with a peak stress varies with soil depth. In the shallow soil layers, dynamic stress in the ground is mainly affected by runway roughness and lift force. The critical speed of dynamic stress is close to the sensitive speed corresponding to peak aircraft loads. With the increase of soil depth and aircraft speed, the effect of dynamic amplification due to wave propagation becomes more pronounced. In the deep soil layers, the critical speed of dynamic stress approaches the Rayleigh wave velocity of soils, especially when soft soil layers exist. [ABSTRACT FROM AUTHOR]

Fast and accurate detection of airfield pavement damage is crucial to airport flight safety and airfield pavement maintenance. An efficient and lightweight detection algorithm that can be embedded into the mobile detection device has been in urgent demand. However, traditional Convolutional Neural Networks (CNNs) usually generate redundant feature maps during feature extraction or use extra operations during feature fusion to gain better performance, which greatly challenges the efficiency of the algorithm. We approached this issue by proposing an accurate and efficient detection algorithm, the YOLOv5-APD. The algorithm improves the model performance in two ways: Speeding up training and inferencing by using cheaper operations during feature extraction; Reducing the model complexity by removing redundant nodes during feature fusion. We verified the detection performance of YOLOv5-APD on a self-made dataset and compared it with the other state-of-the-art (SOTA) models. Then ablation experiments were carried out to investigate the effects of the proposed model design and the impact of image augmentation. Results showed that the proposed YOLOv5-APD model outperformed the SOTA algorithms in model performance and efficiency, which attained the optimal performance mean average precision (mAP) of 0.924. The proposed model also achieved the fastest inference speed of 142 frame-per-second (FPS), with a model footprint of 8.3 G FLOPs and 8 MB Parameters. [ABSTRACT FROM AUTHOR]

Understanding the vibration response patterns of aircraft taxiing under runway roughness excitation is crucial for aircraft design and runway performance evaluation. In this paper, we establish pavement roughness models for both asphalt and concrete surfaces, taking into account their unique structural characteristics. We construct a six-degrees-of-freedom aircraft model using multi-rigid-body system dynamics theory and employ the pseudo-excitation method to examine the influence of pavement roughness types on the steady vibration response of aircraft taxiing at constant speeds. Furthermore, we analyze the non-stationary vibration response patterns of aircraft during takeoff and landing taxiing using the method of instantaneous frequency response function with space frequency. Lastly, we explore the effect of stochastic structural parameters on aircraft vibration response using the Monte Carlo method. Our findings reveal that the roughness power spectrum differs between asphalt and concrete pavements, and the established roughness models in this paper demonstrate a strong fit (R2 > 0.95). The type of pavement roughness has a relatively minor impact on the power spectral density distribution of the aircraft vibration response, suggesting that the same roughness model can be used for both asphalt and concrete pavements when high accuracy is not required. The power spectral density distribution of aircraft vibration response varies across different motion attitudes, with the vibration response during landing being significantly larger than that during takeoff. Among the aircraft structural parameters, the randomness of the sprung mass has the most substantial effect on the aircraft vibration response, potentially causing the variation coefficient of dynamic load on the front landing gear to exceed 0.11. Tire stiffness comes next, which can lead to the variation coefficient of dynamic load on the main landing gear reaching 0.07. The results have a guiding role in optimizing aircraft structure design and ensuring pavement performance. [ABSTRACT FROM AUTHOR]

Thickness detection of concrete pavement is a critical step in construction completion acceptance and serves as an important metric for subsequent pavement performance evaluations. The crux of thickness evaluation lies in determining the interface reflection echo propagation sound time. Based on the acoustic impedance difference between the surface layer and contact layer, pavement can be classified into two types: large-difference and small-difference. By examining the singularity of the detection signal, we employed the improved correlation coefficient method and the wavelet transform maximum value method to identify the interface reflection echo sound time. This study refines the traditional correlation coefficient method by using the surface direct wave as the reference signal, simplifying the signal analysis process. In actual detection, for the type of concrete pavement with large differences in acoustic impedance, the average relative error between the improved correlation coefficient method and the core drilling method can be reduced to 1.7%; for the type with small differences, the average relative error of the detection results obtained using the wavelet transform modulus maximum method can be reduced to 1.9%, showcasing high accuracy. [ABSTRACT FROM AUTHOR]

Airport runway roughness can be characterised by power spectral density (PSD) and two spectrum parameters, namely, the unevenness index and waviness. In order to find suitable spectrum parameters for airport runway roughness, seven runway profiles in China were measured to expand the current database of runway profiles. The statistical distributions of the spectrum parameters for runway roughness then were calculated, and the effects of the spectrum parameters on aircraft vibrations were analysed. The results show that the mode of the unevenness index is 0.13, which is a little lower than that of an A-level road, and the mode of waviness is 2.2, which is higher than the waviness recommended in ISO road classification. Moreover, as the unevenness index and the waviness increase, the aircraft vibrations become more severe. The aircraft vibration responses can be represented as a function of waviness, unevenness index, and speed, with a high correlation. At a constant speed, the relationship between the threshold values of the unevenness index and waviness can be shown as a straight line in a log plot. Finally, taking 200 km/h as the representative speed, threshold curves of the spectrum parameters, which are based on ride comfort levels and statistical analysis are proposed for the the simulation of aircraft vibration. [ABSTRACT FROM AUTHOR]

This study was undertaken to develop a new index, the Main Landing Gear Cumulative Stroke (MLGCS) index, to evaluate airport runway roughness. Using ADAMS/Aircraft software, we first developed and validated a virtual prototype model of the Boeing B737-800 aircraft and then employed the model to predict the aircraft's dynamic responses with regard to roughness. Using this prototype model and comparing it to the International Roughness Index (IRI) that is designed to evaluate roadway roughness, we established a landing gear cumulative stroke (LGCS) model to represent runway roughness. The results show that taxiing speed is an important factor using the LGCS model. According to the most unfavorable scenario, we determined the LGCS of the nose landing gear to be 100 km/h and that of the main landing gear to be 60 km/h. These results underscore that, based on correlation analysis, using the cumulative stroke of the main landing gear is more reasonable than using that of the nose landing gear to evaluate runway roughness. Furthermore, based on measured data for 37 runways, a comparison of commonly used roughness indices indicates that the MLGCS index proposed in this paper is superior to both the Boeing Bump Index and the IRI. [ABSTRACT FROM AUTHOR]

Pavement evaluation is critical for the decision-making process of pavement preservation and rehabilitation. Roughness is a key airport pavement characteristic that has been linked to impacts such as safety and service life. The Boeing Bump is one of the few roughness evaluation methods that has been developed specifically for runways. Although it is superior to the widely used International Roughness Index (IRI), it does not take into account the superposition effect of continuous runway bumps. Based on the ADAMS/Aircraft virtual prototype platform, this paper establishes and verifies five typical models (B737, B747, B757, B777, and B787) and then analyzes the most unfavorable speed (in terms of aircraft vibration) of each model and the dynamic responses caused by multiple bumps. The original Boeing Bump is improved and optimized by determining dynamic response thresholds for the various aircraft types. The results show that the revised Boeing Bump is more realistic than the original version, especially with regard to medium and long wave bands. [ABSTRACT FROM AUTHOR]

Objective. The current study sought to compare the effects of the addition of Qingshen granules to conventional Western medicine on immune function in patients with comorbid chronic renal failure and damp-heat syndrome and to explore the possible mechanisms responsible for any differences observed. Methods. Through a multicenter, randomized, controlled study, a total of 282 eligible patients were divided into experimental (n = 136) and control groups (n = 146). All of the patients were treated with conventional Western medical therapy. The experimental group also received Qingshen granules three times daily for 12 weeks. Clinical efficacy was observed in the two groups. Peripheral blood levels of CD4+ T cells, CD8+ T cells, Th17 cells, nuclear factor-κB p65 (NF-κB p65) activity, serum interleukin-17 (IL-17), serum interleukin-6 (IL-6), tumor necrosis factor-α (TNF-α), tumor necrosis factor receptor-associated factor 6 (TRAF6), fibronectin (FN), and type IV collagen (Col-IV) were detected in both groups. Results. The total clinical curative effective rate was significantly higher p < 0.05 in the experimental group (79.41%) than in the control group (67.12%). Before treatment, there were no significant differences in CD4+/CD8+ T cell ratio, Th17 cell level, NF-κB p65 activity, serum IL-17, IL-6, TNF-α, TRAF6, FN, and Col-IV between the experimental and control groups p > 0.05 ; however, all of the measures were significantly higher than those observed in a healthy comparison group (p < 0.05 or p < 0.01). After treatment, the above indexes in the experimental group were significantly lower than those before treatment (p < 0.05 or p < 0.01). Similarly, NF-κB p65 activity, serum IL-17, TNF-α, TRAF6, FN, and Col-IV in the control group were significantly lower than the levels observed prior to treatment (p < 0.05 or p < 0.01); however, while all of the other indexes were lower than those observed before treatment, the differences were not statistically significant p > 0.05 . Conclusion. Qingshen granules adjust immune dysfunction, improve immunity mediated inflammatory response, and attenuate renal fibrosis in patients with comorbid chronic renal failure and damp-heat syndrome. [ABSTRACT FROM AUTHOR]

With the rapid development of the vehicle chassis control and autonomous driving technology, it is more and more urgent to realize the active steering technology of autonomous driving stability control. Under emergency conditions, the adhesion constraints, the model uncertainty, and the strong nonlinearity of vehicle bring great challenges to active steering control. In this paper, a model predictive control method for an active steering system based on a nonlinear vehicle model is proposed to solve the problems of adhesion constraint, model uncertainty, and external disturbance in the active steering system. Based on the real-time measurement of vehicle state, a new optimization method is proposed in this paper, which has good performance in dealing with the uncertainty and nonlinearity of the model. The control method transforms the constraint problem into quadratic programming and nonlinear programming. In order to ensure the control accuracy when the vehicle enters the nonlinear area, the control model is built with the combination of the nonlinear tire model and the 2DOF model. The control model is built based on Simulink, and the effectiveness of the controller is the verified joint simulation of Simulink and CarSim. The hardware-in-the-loop (HIL) test bench based on LabVIEW RT is built and tested in order to verify the feasibility and real effect of the controller. Simulation and HIL test results demonstrate that, compared with PID controller, the model predictive controller can accomplish the driving task well and improve the vehicle handling stability. [ABSTRACT FROM AUTHOR]

Runway roughness is one of the most critical performance factors for runway evaluation, which directly impacts airport operation safety and pavement preservation cost. Properly evaluated runway roughness could optimize the decision-making process for runway preservation and therefore reduce the life cycle cost of the runway pavement asset. In this paper, the excitation effect of runway roughness is analyzed using a coupled aircraft/runway system. The coupled system is composed of a two degrees-of-freedom (2-DOF) aircraft model and a typical asphalt runway structure model established under runway roughness random excitation in this work. The dynamic differential equations for the coupled system are derived based on D'Alembert's principle. The system's vibration responses are determined via the pseudo excitation method and three response laws, i.e., the center of gravity acceleration (CGA), the dynamic load coefficient (DLC) of the landing gear, and the runway structural displacement, which are investigated under different modes. The results show that the first-order mode of the runway structure, vertical deformation, is the most significant of the four modes. Moreover, uneven excitation has a significant effect on the distribution of the aircraft's vibration response. Compared with a single aircraft system, the developed coupled aircraft/runway system has different dynamic responses, and the degree of difference depends on the taxiing speed. The coupled effect on the CGA increases significantly with an increase in speed, with up to a 7.3% percentage difference. The coupled effect on the DLC first increases and then decreases as the aircraft speed increases, reaching a maximum of about 6% percentage difference at 120 km/h. [ABSTRACT FROM AUTHOR]

To advance the development of piezoelectric energy harvesters, this study designed and manufactured bridge-unit-based and pile-unit-based piezoelectric devices. An indoor material testing system and accelerated pavement test equipment were used to test the electrical performance, mechanical performance, and electromechanical coupling performance of the devices. The results showed that the elastic modulus of the pile structure device was relatively higher than that of the bridge structure device. However, the elastic modulus of the two devices should be improved to avoid attenuation in the service performance and fatigue life caused by the stiffness difference. Furthermore, the electromechanical conversion coefficients of the two devices were smaller than 10% and insensitive to the load magnitude and load frequency. Moreover, the two devices can harvest 3.4 mW and 2.6 mW under the wheel load simulated by the one-third scale model mobile load simulator, thus meeting the supply requirements of low-power sensors. The elastic modulus, electromechanical conversion coefficients, and electric performance of the pile structure device were more reliable than those of the bridge structure device, indicating a better application prospect in road engineering. [ABSTRACT FROM AUTHOR]

Pavement roughness is a critical airport pavement characteristic that has been linked to impacts such as safety and service life. A properly defined roughness evaluation method would reduce airport operational risk, prolong the life of aircraft landing gear, and optimize the decision-making process for pavement preservation, which together positively contribute to overall airport sustainability. In this study, we optimized the parameters of the International Roughness Index (IRI) model to resolve the current poor correlation between the IRI and aircraft vibration responses in order to adapt and extend the IRI's use for airport runway roughness evaluation. We developed and validated a virtual prototype model based on ADAMS/Aircraft software for the Boeing 737–800 and then employed the model to predict the aircraft's dynamic responses to runway pavement roughness. By developing a frequency response function for the standard 1/4 vehicle model, we obtained frequency response distribution curves for the IRI. Based on runway roughness data, we used fast Fourier transform to implement the frequency response distribution of the aircraft. We then utilized Particle Swarm Optimization to determine more appropriate IRI model parameters rather than modifying the model itself. Our case study results indicate that the correlation coefficient for the optimized IRI model and aircraft vibration response shows a qualitative leap from that of the original IRI model. [ABSTRACT FROM AUTHOR]

Active steering technology is a key technology for automatic driving vehicles to achieve route tracking and obstacle avoidance and risk avoidance, and its performance will affect the stability control of the vehicle. For solving the stability control issues of vehicles, which have uncertainty in model and robustness in system, this paper proposes an active steering control method based on the receding horizon control model. It calculates the optimal control law by this method by using the real-time vehicle state so that it can compensate for the uncertainty caused by model mismatch, interference, etc. The design of the controller is implemented by using the yaw rate deviation of the vehicle as the input of the receding horizon linear quadratic controller model and then inputting the calculated superposition angle into the vehicle model in real time. We built a Simulink control model to implement co-simulation with CarSim to verify the control effect of the controller. In addition, we built a steering hardware-in-the-loop platform based on the LabVIEW RT system. The experimental results show that the active steering system adopting a receding horizon control method had better system robustness and robust stability. [ABSTRACT FROM AUTHOR]

• Extreme value distribution better represents aircraft wheel wander. • The damage caused by each load repetition is considered individually. • The load transfer effect is taken into account using finite element analysis. • The proposed method typically produces smaller CDF values. This paper proposes an approach to determine cumulative damage factors (CDFs) based on Miner's law to improve airport runway rigid pavement design. The approach uses measured aircraft wheel wander data and constructed influence surfaces. In this study, we developed an aircraft wheel wander measuring system and measured actual aircraft wheel loading locations at the Shanghai Hongqiao International Airport (SHA). We constructed influence surfaces using finite element analysis (FEA) and multivariate interpolation. We conducted FEA of a nine-slab model to simulate load transfer effects. Based on the measured wheel wander distribution and the constructed influence surface, a cumulative damage surface construction approach for CDF determination is proposed. The preliminary benefits of the proposed cumulative damage surface method are that (1) the damage caused by each load repetition is considered individually for the CDF calculation and (2) the load transfer effect is taken into account using FEA simulations. Also, the field data we collected at SHA show that, compared to normal (uniform) distribution, extreme value distribution better represents aircraft wheel wander. A comparison between the CDFs calculated using normal distribution and extreme value distribution indicates that the maximum CDF is increased by 210% using extreme value distribution. According to the several cases analyzed in this study, the proposed cumulative damage surface method typically produces smaller CDF values than those calculated using the traditional Civil Aviation Administration of China method. Traditional airport runway rigid pavement design methods could be improved and optimized in terms of accuracy and performance using the proposed cumulative damage surface method for CDF determination. [ABSTRACT FROM AUTHOR]