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The detection of Foreign Object Debris (FOD) is crucial for maintaining safety in critical areas like airport runways. This paper presents a comprehensive review of FOD detection technologies, covering traditional, radar-based, and artificial intelligence (AI)-driven methods. Manual visual inspection and optical sensors, while widely used, are limited in scalability and reliability under adverse conditions. Radar technologies, such as millimeter-wave radar and synthetic aperture radar, offer robust performance, with advancements in algorithms and sensor fusion significantly enhancing their effectiveness. AI approaches, employing supervised and unsupervised learning, demonstrate potential for automating detection and improving precision, although challenges such as limited datasets and high computational demands persist. This review consolidates the recent progress across these domains, highlighting the need for integrated systems that combine radar and AI to improve adaptability, scalability, and small-FOD detection. By addressing these limitations, the study provides insights into future research directions and the development of innovative FOD detection solutions, contributing to safer and more efficient operational environments. [ABSTRACT FROM AUTHOR]

Flights are projected to reach eight billion globally by 2037, demanding airport operators manage operations effectively, including safety on the runway due to the high number of aircraft movements. One crucial issue is any foreign object, commonly known as foreign object debris (FOD), that must be detected and cleaned immediately to ensure aircraft safety when taking off, landing, and taxing. The International Civil Aircraft Organization (ICAO) reported that FOD causes 10.08% of aviation accidents. Most airports manually monitor and detect FOD, which could be more effective and dangerous. Therefore, it is important to provide FOD detection systems with proper technologies. Radar technologies are potential FOD detection techniques that offer robustness to weather fluctuation. However, some factors must be considered properly to provide an effective FOD system. This paper reviews radar technologies for FOD detection on airport runways by considering factors, including types of debris, detection coverage, mode of radars, frequencies, and attenuation. It was found that all critical factors considered contribute to the quality of detection. This paper will provide guidelines for developing FOD detection based on radar technologies regarding airport necessities and its specific environment. [ABSTRACT FROM AUTHOR]

Airport runway drainage is one of the key factors in ensuring the safety of aircraft operation and aircraft quality, and a good drainage system can effectively remove rainwater and reduce the impact of stagnant and retained water. To explore the drainage capacity of the existing airport runway drainage system, as well as the evolution process of rainfall and drainage system, an airportrunway in southern China was taken as the research object, applied the Danish Hydraulic Institute model integrated computing(DHI MIKE) model to the airport runway, and the coupled rainfall and flooding model was constructed. According to the rainfall characteristics of the study area and the existing drainage system, four rainfall scenarios with different recurrence periods were designed, and simulation analyses were conducted from three aspects: pipe fullness, surface inundation results, and runway waterlogging evolution process. The results show that the number of full pipes is positively related to the rainfall intensity, and the spatial distribution of water depth in the study area under different recurrence periods is generally consistent, concentrates around the shallow catchment ditch. The larger the recurrence period, the higher the water depth. The time of water accumulation and runway closure are advanced. The runway drainage capacity can meet the standard of one in five years of rainfall. [ABSTRACT FROM AUTHOR]

Copyright of Acta Scientiarum Naturalium Universitatis Sunyatseni / Zhongshan Daxue Xuebao is the property of Sun-Yat-Sen University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The elevated occurrence rate of wind shear (WS) events near airport runways presents one of the major hazards to the safe and efficient operation of landing and takeoff procedures. As a consequence of this, aircraft are more likely to experience the possibility of losing control or encountering hindrances. Hence, it is crucial to assess the factors influencing wind shear occurrence. Previous studies extensively reported the susceptibility of the runways at Hong Kong International Airport (HKIA) to significant wind shear events. Therefore, in order to estimate WS magnitude near runways at HKIA and assess various contributing factors, this study presents a novel Local Cascade Ensemble (LCE) model with its hyperparameters optimized via a Tree-Structured Parzen Estimator (TPE) to estimate the wind shear magnitude. The pilot report data obtained from HKIA between 2017 and 2021 was employed for the training and evaluation of the TPE-tuned LCE model. The outcomes of the TPE-tuned LCE model were also compared to those of other contemporary machine learning (ML) models. The findings indicated that the TPE-tuned LCE model exhibited better predictive performance in comparison to other models, as assessed by a mean absolute error (MAE) of 4.38 knots, a mean squared error (MSE) of 70.28 knots, a root mean squared error (RMSE) of 8.38 knots, and coefficient of determination (R2) value of 0.79. Subsequently, model interpretation via SHapley Additive exPlanations (SHAP) technique was performed on the outcomes of TPE-tuned LCE. It indicated that that certain runways at HKIA, such as runway 07 C, 07 L, 25 C, and 25R, had a higher likelihood of experiencing elevated wind shear conditions within 1000 ft above the runway level. [ABSTRACT FROM AUTHOR]

The detection of foreign object debris (FOD) is a critical safety issue in airport operations. Nowadays, the most advanced detection systems are high frequency radars installed along the runway. In this article, the authors propose a synthetic aperture radar (SAR) aboard a small unmanned aerial system (UAS), a quadcopter, flying sideways over the runway as FOD detection system. This solution can operate during the daily airport operations and does not require permanent installations near the runways. To focus SAR images, an accurate knowledge of the platform position is needed. So, the hardest challenge in SAR imaging with UAS is an effective mitigation and compensation of uncontrolled movements. For this reason, a specific back propagation algorithm was developed. The FOD detection technique was tested in a general aviation airfield (Serristori, Arezzo, Italy) and in two Italian commercial airports: Milan Linate Airport (LIN), Olbia Costa Smeralda Airport (OLB).

Pilots commonly undergo training to effectively manage instances of wind shear (WS) during both the landing and takeoff stages. Nevertheless, in exceptional circumstances, there may be instances of severe wind shear (SWS) surpassing a magnitude of 30 knots, leading to adverse effects on the operation of taking off and landing aircraft. This phenomenon can lead to the execution of aborted landing maneuvers and deviations from the intended glide path. This study utilized the explainable boosting machine (EBM), an advanced machine learning (ML) model known for its transparency, to predict the severity of WS occurrences and analyze the underlying factors. The dataset consisted of 21,392 data points from 2018 to 2022 acquired from two Doppler light detection and ranging (LiDAR) systems installed at Hong Kong International Airport (HKIA). Initially, the Doppler LiDAR data received data treatment in order to address the issue of data imbalance. Subsequently, utilizing the processed data, the hyperparameters of EBM were optimized using the Bayesian optimization technique. The EBM model underwent subsequent training and evaluation, wherein its performance metrics were computed and compared with those of an alternative glass-box model including decision tree (DT) and counterpart black-box models, namely, random forest (RF) and extreme gradient boosting (XGBoost). The EBM model trained on synthetic minority oversampling technique (SMOTE)-treated data demonstrated superior performance in comparison with the alternative models, as indicated by its higher geometric mean (0.77), balanced accuracy (0.78), and Matthews' correlation coefficient (0.169). Furthermore, the EBM exhibited enhanced predictive performance and facilitated a comprehensive analysis of individual and pairwise factor interactions in the prediction of WS severity. This enabled the assessment of the factors that contributed to the instances of SWS in the proximity of airport runways. [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]

The assessment of airfield runway destruction effectiveness and functional recovery time is of great importance in the field of operational assessment. In this paper, the criteria and methods of damage assessment of airfield runways are studied in the context of the sub-bomb against airfield runways and the benefits of striking airfield runways as a starting point. Firstly, the main purpose of attacking airport runway is blockade, and the damage assessment criteria of runway should focus on its time benefit. Then, it is concluded that calculating the minimum lifting window can only achieve the purpose of blockade of airport, and the optimal lifting window is needed to calculate the airport function recovery time. A direction search algorithm is proposed to search the optimal lifting window on the airport runway after striking, and an example is given.

Copyright of Ordnance Industry Automation is the property of Editorial Board for Ordnance Industry Automation and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper studied the problem of ice and snow pollutants identification and freezing temperature detection under winter runway operation, and designed an active detection system for runway ice and snow pollutants and freezing temperature. The temperature change trend during the liquid freezing process was researched, and the freezing temperature detection model based on sequence segmented linear fitting and inflection point identification was proposed in combination with active cooling technology. The differences in dielectric properties of runway snow and ice cover are studied, and a multi-frequency detection-based forked-finger planar capacitive sensor was identified for snow and ice pollutants detection considering practical application scenarios. A finite element simulation model of the forked-finger planar capacitive sensor was established, to optimize the structural parameters of the sensor and verify the feasibility of the capacitor sensor. Finally, the detection device and control system were designed and fabricated, and built an experimental platform for system test. The field experimental results showed that the system has good reliability and stability, and the error of freezing temperature detection model is less than 0.3 °C. At the same time, it can identify three types of pollutants, including water, ice and ice–water mixture, with an accuracy of 89%. [ABSTRACT FROM AUTHOR]

Rising temperatures due to climate change can significantly impact the freeze–thaw condition of airport pavements in cold regions. This case study investigates the implications of warming temperatures on the freeze–thaw penetration and frost heave of pavements in critical airports across Canada. To this end, different methods were used in the quantification process through climate change simulations considering emission scenario RCP8.5 in 20 and 40 year time horizons. The results show that climate change would have different design implications for airport pavements, depending on their location. The predictions suggest a shallower frost penetration depth, and possibly less frost heave, for the airports not underlain by permafrost, while airports over permafrost areas might experience an increase in thickness of the active layer, ranging from 41 to 57 percent, by 2061. Among the different methods used in this study, it was observed that some methods performed better in predicting the frost depth of fine soils, while others worked better in the frost depth prediction of coarse soils. The results indicate the need for more mechanistic models to provide a more realistic prediction of freeze–thaw penetration, as compared to existing empirical models. [ABSTRACT FROM AUTHOR]

Copyright of Command Control & Simulation / Zhihui Kongzhi yu Fangzhen is the property of Command Control & Simulation Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

ABSTRAK Tujuan penelitian ini adalah untuk menganalisis kontrol dan monitoring arus listrik CCR pada lampu PAPI di Bandar Udara Silangit. Pengumpulan data menggunakan observasi dengan cara pengamatan dan pengukuran. Berdasarkan data yang diperoleh, minimal 2,2 Ampere dan arus maksimum yang dibutuhkan untuk intensitas besar adalah 6,5 Ampere dengan kenaikan arus 5 langkah. Intensitas dan besarnya arus yang didapat memiliki nilai stabil dari hasil perbandingan monitoring dan pengukuran dilapangan pacu bandara. Kata kunci— CCR, Intensitas Cahaya, Landasan Pacu Bandara, Sistem Penerangan ABSTRACT The purpose of this study was to analyze the control and monitoring of CCR electric current on PAPI lamps at Silangit Airport. Data collection uses observation by means of observation and measurement. Based on the data obtained, a minimum of 2.2 Ampere and the maximum current required for large intensity is 6.5 Ampere with a current increase of 5 steps. The intensity and magnitude of the flow obtained have a stable value from the comparison results of monitoring and measurement on the airport runway. Keywords— Airport Runway, CCR, Light Intensity, Lighting System

Asphalt overlays have been widely employed in airport runway maintenance in recent years due to their ability to minimize traffic disruption. However, they continue to face the challenge of reflective cracks originating from the expansion joints of the underlying cement concrete runway. To better understand the cracking behavior of asphalt overlays under the combined temperature variations and aircraft loads, this study developed a finite element (FE) model. with the model incorporate two types of landing methods and typical temperature conditions. Simulation results indicate that critical loading positions are located at the edges of original cement concrete slabs, where shear stress is identified as the primary driver of crack evolution, with the peak stress coinciding with the arrival of aircraft load. Furthermore, findings suggest that the use of asphalt overlays significantly reduces the stress intensity in crack-prone areas, particularly under rough landing conditions. Reflective cracks predominantly manifest as type II shear cracks, While aircraft loading and initial crack length exert a relatively limited impact on crack propagation compared to temperature effects, the horizontal location of the initial crack substantially influences both the direction and speed of crack propagation. To mitigate crack propagation, increasing the linear shrinkage coefficient of the overlay material and the thickness of the asphalt overlay are effective strategies for enhancing the cracking resistance of airport runways with asphalt overlays. The methodologies and findings of this study provide valuable insights for engineering practices involving similar structural configurations and materials. • The fracture modes of airport runway with asphalt overlay under temperature-load coupling factors were discussed in detail. • Factors influencing the cracking behavior of reflective cracks existing in airport runway were detailed. • The most favorable load scheme and critical load position of airport runway with asphalt overlay were determined. • A XFEM model of airport runway with initial reflective cracks under temperature-load coupling factors was established. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Zhengzhou University (Natural Science Edition) is the property of Journal of Zhengzhou University (Natural Science Edition) Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

A six-degree-of-freedom mathematical model and mechanical balance equation of a "five-point-contact" aircraft are established in this study. The model and equation are used to investigate the safety and stability of a tunnel structure under the runway of an airport, particularly when aircraft taxi or move on the runway. ABAQUS is used to construct a three-dimensional finite element model of the cooperative deformation of the airport runway–soil–tunnel structure. The analysis focuses on the response and evolution of structural safety mechanical indices from the perspective of three influencing factors: type of aircraft, road surface, and burial depth. The results show that the distribution position of the main landing gear wheel is more concentrated using the dynamic load equation of different aircraft. A rigid pavement is not easily deformed when subjected to aircraft loads, whereas a flexible pavement has an excellent attenuation effect on diffusing forces. The shear stresses on the upper and lower arches of the tunnel structure differ depending on the pavement material. The deformation of the arches under shear stress is more intense than that of other parts. With an increase in burial depth, the tunnel structure withstanding the aircraft load disturbance exhibits an attenuation trend. The disturbance caused by soil stress to the tunnel structure must not be ignored. When the burial depth of the tunnel exceeds 64 m, the tunnel structure ceases to be disturbed by aircraft loads. The research results can significantly guide airport construction and be used as a reference for investigating the safety and stability of substructures under airport runways. [ABSTRACT FROM AUTHOR]

In view of the time series update of airport runway health status detection data, the Markov chain of stochastic process theory was adopted. Considering the influence of aircraft traffic load, age, and pavement structure surface-layer thickness on the performance deterioration process of airport runways, the method of survival analysis was used. The parameter model of survival analysis was used to establish the duration function model of the four condition states of the airport runway PCI (pavement condition index). The Markov transition matrix for the performance prediction of airport runways was constructed. In order to evaluate the ability of the Markov transition matrix method to predict the trend of deterioration for PCI of the airport runway under different conditions of aircraft traffic volume and thickness of the runway pavement surface, a data set was constructed with the actual inspection data of the airport runway, and the corresponding samples were selected for analysis. The results showed that a Markov transition matrix for airport runway performance prediction, constructed based on survival analysis theory, can combine discontinuous inspection data or monitoring data with Weibull function survival curves. The method proposed in this paper can quantitatively predict the remaining service life of airport runways and provide support for cost-effective decisions about airport pavement maintenance and rehabilitation. [ABSTRACT FROM AUTHOR]

In this study, a set of numerical simulation analysis methods for studying the dynamic response of runway under the action of aircraft taxiing load are presented. An aircraft-runway coupled vibration model was established, and the runway pavement roughness was taken as the vibration excitation source; then, the aircraft taxiing dynamic load was obtained. A three-dimensional finite element model of the runway was established, and the vertical dynamic displacement (VDD) response and its variation law of the runway under different void conditions were studied under the action of the dynamic load of a taxiing aircraft. In addition, using wavelet packet transform, the acceleration signals at different positions of the pavement slab under the sliding load were decomposed into three layers. The relationship among the wavelet packet energy ratio (WPER), the wavelet packet energy entropy (WPEE) of each frequency band, and the void under the pavement slab was obtained. The results show that the established model could quickly and accurately solve the aircraft taxiing dynamic load. In the case of a slight void, the VDDs in the runway center and under the main landing gears had negative exponential and logarithmic relationships with the reduction coefficient of the dynamic elastic modulus of the base layer, respectively. When there was a severe void, the pavement slab was separated from the base layer. The VDDs in the runway center and under the main landing gears were exponentially and linearly related to the slab's void area, respectively. The vibration signals were extracted at three measuring points, and the wavelet packet energy characteristics of the signals were compared and analyzed. It was found that the WPER and WPEE of the vibration signals in the void area of the slab corner could better reflect the void state of the slab bottom. [ABSTRACT FROM AUTHOR]

Rising temperatures due to climate change can significantly impact the freeze–thaw condition of airport pavements in cold regions. This case study investigates the implications of warming temperatures on the freeze–thaw penetration and frost heave of pavements in critical airports across Canada. To this end, different methods were used in the quantification process through climate change simulations considering emission scenario RCP8.5 in 20 and 40 year time horizons. The results show that climate change would have different design implications for airport pavements, depending on their location. The predictions suggest a shallower frost penetration depth, and possibly less frost heave, for the airports not underlain by permafrost, while airports over permafrost areas might experience an increase in thickness of the active layer, ranging from 41 to 57 percent, by 2061. Among the different methods used in this study, it was observed that some methods performed better in predicting the frost depth of fine soils, while others worked better in the frost depth prediction of coarse soils. The results indicate the need for more mechanistic models to provide a more realistic prediction of freeze–thaw penetration, as compared to existing empirical models.

When the aircraft takes off or lands, the tread rubber melts and adheres to the airport runway and its embedded ground lights, forming black pavement rubber marks, affecting the smoothness of the pavement, reducing the lighting degree and friction coefficient of the pavement, and directly affecting the safety of the aircraft take-off and landing. There are many shortcomings in the standard rubber removal methods. The multi-energy field composite laser cleaning technology comprehensively utilizes the laser field and auxiliary hydrodynamic field. It leverages the high-efficiency advantages of laser processing and avoids the shortcomings of its thermal energy surplus, achieving efficient, accurate, and green material removal. Based on this, this article presents for the first time the composite energy-field laser cleaning process mechanism and related performance of rubber mud layer from the surface of cement/asphalt runway and embedded grounding light cover (aluminum alloy)/light window (tempered glass). Pulse laser single energy-field cleaning is suitable for removing rubber marks from cement runways, grounding lamp covers, and light window surfaces. The cleaning mechanism is divided into two types based on the substrate: ablation and thermal stress peeling. Composite energy-field laser cleaning is suitable for removing rubber marks from asphalt runway surfaces, and the phase explosion of the liquid film is the cleaning mechanism. Under appropriate process parameters, laser cleaning can improve the runway's skid resistance, enhance the grounding light cover's corrosion resistance, and increase the grounding light window's transparency. This study can provide a reference for the laser cleaning behavior of different materials and solve the problem of rubber removal on international civil aviation airport pavement, promoting the construction of "safe, green, and smart" airports. [Display omitted] • The laser rubber removal process mechanism of airport runways was first announced. • The laser can improve the skid resistance of the runway under wet conditions. • The corrosion resistance and transparency of grounding lamps improve after degumming. [ABSTRACT FROM AUTHOR]

Due to the small size of foreign object debris (FOD) and varied complex weather conditions, the detection of FOD on airport runways is a great challenge. Radar is an important method for detecting FOD targets. However, almost all the existing systems are based on real apertures, which have disadvantages such as low azimuth resolution and susceptibility to rain interference. Here, an innovative FOD detection radar system based on arc-scanning synthetic aperture radar (AS-SAR) technology, the AS-SAR based FOD detection system (AS-FODR), achieves omnidirectional coverage with a very high azimuth resolution and the suppression of flicker clutter, such as rain drops in severe weather. According to the radar imaging simulation of a scene under rainy conditions and the information processing analysis of field experiments, a prototype system was built, and an efficient data process flow was proposed. In short, a one centimeter FOD target was detected on the runway more than 250 m away, proving that the use of AS-FODR is feasible and effective. [ABSTRACT FROM AUTHOR]

Aiming at the frequent misdetection and omission in the detection process of airport runway foreign object debris (FOD) and the difficulty of deploying the detection algorithm to embedded devices, we propose a lightweight FOD detection method called PGDIG-YOLO based on the improvement of YOLOv8n. First, a detection layer for detecting small-size objects is added and a large target detection layer is deleted to enhance the network's ability to sense small-sized objects. Second, a dilation-wise residual module is introduced in the segmentation domain, and the C2FD module is proposed, which effectively solves the problem of misdetection and missed detection of FOD on airport runways. Third, the inner-WMPDIoUv3 is designed to replace the CIoU as a loss function to improve the regression accuracy of the detection frame. Finally, the model is pruned using the Group_sl method, which reduces the amount of computation, compresses the model size, and improves the model inference speed. The experimental results on the homemade dataset FOD-Z show that, compared with the benchmark model YOLOv8n, the model volume and computation of the PGDIG-YOLO network are only 6.6% and 44.4% of the original network, and the accuracy and recall are improved by 1.1% and 3.8%, respectively. Meanwhile, the mAP@0.5, mAP@0.75, and mAP@0.5:0.95 are increased to 99.1%, 93.7%, and 85.6%, respectively. Deploying PGDIG-YOLO to the NVIDIA Jetson Xavier NX 16 GB embedded device, the detection speed reaches 42 FPS, which can realize real-time FOD detection. [ABSTRACT FROM AUTHOR]

A six-degree-of-freedom mathematical model and mechanical balance equation of a “five-point-contact” aircraft are established in this study. The model and equation are used to investigate the safety and stability of a tunnel structure under the runway of an airport, particularly when aircraft taxi or move on the runway. ABAQUS is used to construct a three-dimensional finite element model of the cooperative deformation of the airport runway–soil–tunnel structure. The analysis focuses on the response and evolution of structural safety mechanical indices from the perspective of three influencing factors: type of aircraft, road surface, and burial depth. The results show that the distribution position of the main landing gear wheel is more concentrated using the dynamic load equation of different aircraft. A rigid pavement is not easily deformed when subjected to aircraft loads, whereas a flexible pavement has an excellent attenuation effect on diffusing forces. The shear stresses on the upper and lower arches of the tunnel structure differ depending on the pavement material. The deformation of the arches under shear stress is more intense than that of other parts. With an increase in burial depth, the tunnel structure withstanding the aircraft load disturbance exhibits an attenuation trend. The disturbance caused by soil stress to the tunnel structure must not be ignored. When the burial depth of the tunnel exceeds 64 m, the tunnel structure ceases to be disturbed by aircraft loads. The research results can significantly guide airport construction and be used as a reference for investigating the safety and stability of substructures under airport runways.

In this study, a set of numerical simulation analysis methods for studying the dynamic response of runway under the action of aircraft taxiing load are presented. An aircraft-runway coupled vibration model was established, and the runway pavement roughness was taken as the vibration excitation source; then, the aircraft taxiing dynamic load was obtained. A three-dimensional finite element model of the runway was established, and the vertical dynamic displacement (VDD) response and its variation law of the runway under different void conditions were studied under the action of the dynamic load of a taxiing aircraft. In addition, using wavelet packet transform, the acceleration signals at different positions of the pavement slab under the sliding load were decomposed into three layers. The relationship among the wavelet packet energy ratio (WPER), the wavelet packet energy entropy (WPEE) of each frequency band, and the void under the pavement slab was obtained. The results show that the established model could quickly and accurately solve the aircraft taxiing dynamic load. In the case of a slight void, the VDDs in the runway center and under the main landing gears had negative exponential and logarithmic relationships with the reduction coefficient of the dynamic elastic modulus of the base layer, respectively. When there was a severe void, the pavement slab was separated from the base layer. The VDDs in the runway center and under the main landing gears were exponentially and linearly related to the slab’s void area, respectively. The vibration signals were extracted at three measuring points, and the wavelet packet energy characteristics of the signals were compared and analyzed. It was found that the WPER and WPEE of the vibration signals in the void area of the slab corner could better reflect the void state of the slab bottom.

Icing on airport runway is an important issue that affecting the operation of the airport. The research on runway icing is of great significance for ensuring the operation and safety of the airport. Firstly, in this paper, the runway temperature and ice thickness were studied by considering the underground temperature. Then combined with industrial configuration software and ActiveX controls, the runway icing prediction system was designed and verified. Through the analysis of the temperature field inside and outside of the runway as well as the studies of the meteorological factors around the surface and the runway heat exchange, the prediction equation of the runway temperature was obtained. Based on the equation, by using the predicted values of temperature and other factors, the BP neural network was trained to predict the ice thickness of the road in future. Furthermore, this paper designed an airport runway icing prediction system which installed with ActiveX controls where embedded with temperature prediction algorithm and neural network training algorithm. The system used multisensor to collect data, and wireless data transmission via GPRS DTU device. The virtual interface software and the configuration software embedded with algorithm were installed on the industrial PC to realize the prediction. By comparing the prediction of ice thickness with or without underground temperature, the average prediction accuracy of ice thickness by considering underground temperature was 13% higher than that without considering underground temperature, which verified the accuracy and feasibility of the ice prediction system.

Pavement performance of airport runway plays a key role in the process of aircraft landing and takeoff. To predict runway pavement performance in life cycle, a novel artificial neural network (ANN) has been developed since 2011 by Civil Aviation University of China (CAUC). Evaluation data of 33 runways were used to train, validate and optimize the ANN by a series of heavy weight deflectometer (HWD) tests. By estimating the simplified pavement damage index (ξ) in ANN, investigations on the influences of service life and air traffic on runway pavement performance were analysed. The outcomes from our analysis lead to a novel method of estimating and classifying runway pavement performance in entire service life. Besides ANN analysis, in situ experiments on runway pavement from 2014 to 2018 were also conducted to verify the predicted results. It demonstrates that ANN is an efficient and alternative tool in predicting runway pavement performance. The results show that the service quality of runway pavement decreases in a linear (non-linear) way for regional (hub) airport. In the process of runway pavement deterioration, service life plays a key role in all airports, while air traffic has the greatest contributions to the hub airport. Then runway pavement performance can be classified according to the simplified pavement damage index. In this way, the runway pavement performance in life cycle can be divided into four zones from excellent, good, poor to dangerous. It is possible to help airport agencies to make scientific decisions on runway pavement maintenance, rehabilitation and reconstruction. [ABSTRACT FROM AUTHOR]

Airport runway project is the core part of the airport flight area, the quality of the construction process control has a great influence on its service life. It must be ensured that the airport runway does not appear the phenomenon of broken plate, edge off, poor flatness, and meets the requirements of durability and surface wear resistance. In this paper, through summarizing the construction experience of cement concrete airport runway project for many years, we introduced control points and testing standards of the construction process in detail from the aspects of materials, equipment, process, etc. On the basis of meeting the quality requirements, we put forward the construction technology innovation achievements and subsequent development plan of cement concrete airport runway surface, the results have certain reference significance for other similar projects. [ABSTRACT FROM AUTHOR]

As an important part of civil and military buildings, airport runway is an important research object in the field of protection. In this study, damage assessment of scaled-down target of airport runway was carried out through experiment and numerical simulation. Two experimental methods, static explosion of charge after penetration and explosion of prefabricated hole, were used to damage the target and crater size and surface acceleration of the target were measured and analyzed. The experiment proves that the damage effects of the two methods were obviously different. The crater size produced by static explosion of charge after penetration was obviously larger than that produced by explosion of prefabricated hole under the same explosion depth and explosive charge, of which the shapes were also different. The numerical calculation model was established, and static explosion of charge after penetration was realized and detonation products leakage in inward explosion were solved through restart and S-ALE numerical calculation methods. Calculation results were compared with the experimental results; state equation and parameters were verified; damage effect diagram was obtained by numerical calculation, and mechanism of damage difference was analyzed. The study noted that obvious difference in explosion pressure transmitting and structural failure modes in multi-layer medium and that in a single medium. It proved that the damage caused by penetration will affect cratering effect and the movement of detonation products. Based on the experimental and numerical results, two formulas were given for calculating the crater sizes of airport runway under static explosion of charge after penetration and under explosion of prefabricated hole. The effect of dimensionless penetration coefficient and dimensionless explosion coefficient on crater size was determined by analyzing the crater relation curve of airport runway. The study indicates that the size difference between static explosion of charge after penetration and explosion of prefabricated hole charge can reach 30%. To carry out more accurate study on the damage of the projectile to target, the experiment should adopt static explosion of charge after penetration. • Study the difference of the damage effect of static explosion of charge after penetration and explosion of prefabricated hole charge. • Point out the differences in damage pattern and damage degree between the two explosion modes. • Gave calculation formulas of crater size. [ABSTRACT FROM AUTHOR]

Deformations monitoring in airport runways and the surrounding areas is crucial, especially in cases of low-bearing capacity subgrades, such as the clayey subgrade soils. An effective monitoring of the infrastructure asset allows to secure the highest necessary standards in terms of the operational and safety requirements. Amongst the emerging remote sensing techniques for transport infrastructures monitoring, the Persistent Scatterers Interferometry (PSI) technique has proven effective for the evaluation of the ground deformations. However, its use for certain demanding applications, such as the assessment of millimetric differential deformations in airport runways, is still considered as an open issue for future developments. In this study, a time-series analysis of COSMO–SkyMed satellite images acquired from January 2015 to April 2019 is carried out by employing the PSI technique. The aim is to retrieve the mean deformation velocity and time series of the surface deformations occurring in airport runways. The technique is applied to Runway 3 at the “Leonardo da Vinci” International Airport in Rome, Italy. The proposed PSI technique is then validated by way of comparison with the deformation outcomes obtained on the runway by traditional topographic levelling over the same time span. The results of this study clearly demonstrate the efficiency and the accuracy of the applied PSI technique for the assessment of deformations in airport runways.

Grooving is widely used to improve airport runway pavement skid resistance during wet weather. However, runway grooves deteriorate over time due to the combined effects of traffic loading, climate, and weather, which brings about a potential safety risk at the time of the aircraft takeoff and landing. Accordingly, periodic measurement and evaluation of groove performance are critical for runways to maintain adequate skid resistance. Nevertheless, such evaluation is difficult to implement due to the lack of sufficient technologies to identify shallow or worn grooves and slab joints. This paper proposes a new strategy to automatically identify airport runway grooves and slab joints using high resolution laser profiling data. First, K-means clustering based filter and moving window traversal algorithm are developed to locate the deepest point of the potential dips (including noises, true grooves, and slab joints). Subsequently the improved moving average filter and traversal algorithms are used to determine the left and right endpoint positions of each identified dip. Finally, the modified heuristic method is used to separate out slab joints from the identified dips, and then the polynomial support vector machine is introduced to distinguish out noises from the candidate grooves (including noises and true grooves), so that PCC slab-based runway safety evaluation can be performed. The performance of the proposed strategy is compared with that of the other two methods, and findings indicate that the new method is more powerful in runway groove and joint identification, with the F-measure score of 0.98. This study would be beneficial in airport runway groove safety evaluation and the subsequent maintenance and rehabilitation of airport runway. [ABSTRACT FROM AUTHOR]

After the description of types of pavement for airport runway, the paper presents the principle of various modern methods used in structural design, such as French practice, United States of America practice and the Canadian one. Finally based on their performance, the French and the Canadian one are selected in order to be used for the study of new durable runway pavements in comparison with the classical ones. [ABSTRACT FROM AUTHOR]

Grooves are frequently used on airport runways to address safety concerns by improving frictional properties and drainage capacity during wet weather. Groove performance deteriorates over time mostly due to traffic loading, accordingly periodic measurement and evaluation of groove dimensions are important for runway to maintain adequate frictional properties and avoid hydroplaning risks. However, such evaluation is difficult to perform due to lack of sufficient technologies to identify shallow and abrasive or worn grooves. This paper proposes new methodologies for automatic airport groove identification, measurement, and evaluation using high resolution texture data collected by point laser based profiling equipment developed by Federal Aviation Administration (FAA). Euler-Bernoulli beam filter and geometry contour based algorithms are developed to locate dips within a profile for potential groove identification. Subsequently improved moving average filter, forward and backward traversal methods are implemented to determine the starting and ending positions of each dip. Finally groove dimensions are computed per the FAA AC No. 150/5320-12C. The algorithm performance of the proposed method is evaluated based on Precision-Recall (PR) graphs with that of the FAA ProGroove software. Results indicate that the proposed methodology is more robust and accurate in runway groove identification. With the proposed method, operators of airfield runway pavements have a robust tool set to access groove performance and provide corrective maintenance actions. [ABSTRACT FROM AUTHOR]

Rigid pavement design in airport runways is based on tension critical stress at the bottom of the concrete slab. Determination of slab's critical zones, under airplanes loading types in 3D finite element modeling is the objective of this study. Numerical study to determination main gear role in passenger, commercial and military airplanes on pavement critical stress and also critical zones determination in the runway rigid pavement by using of finite element software, ABAQUS is done. In order to this study, 148 wheels characteristic of different airplanes and in various loading positions including edge and center of the concrete slab is considered. Results show that among different airplanes, A380F, B777-300ER, C17A and Concorde impose maximum tensional stress on the solid pavement airport runway. Also in all kinds of airplanes, the maximum critical stress under concrete slab is happening when the length of wheels lie on concrete slab edge.

Combined with site investigation and monitoring data of the fifth runway in Pudong airport project, this paper demonstrates the validity of surcharge preloading with prefabricated vertical drains （PVDs） in deep soft foundation treatment, and analyzes the distribution characteristics of the differential settlement for airport runway foundation across old channel after construction. The results indicate that the settlement law of the old river region is different from the law of the normal region. And the settlement and differential settlement ratio after construction can meet the specification requirement basically. But the settlement and differential settlement in old channel area increase due to the development of thicker layer of clay. Therefore, the appropriately increased overload, PVD layout depth or cryptographic layout spacing is needed according to the distribution of the thickness of compression layer. [ABSTRACT FROM AUTHOR]

The optimisation and rationalisation of individual activities fully conditions the aplication of the newest results of science, investigation and development of the civil engineering practice. The seismic methods at present have wider aplications in all the stages of the engineering - geological and geotechnical works survey at the solution of specific problems in the geotechnical practice, as is for example the subsoils survey of airports runways and surfaces. In the paper there are given results of the determination of selected subsoils section of runways with the help of methods of refracted wawes and seismic tomography.