Search Results (7)

Effective management of airport pavements is essential for maintaining safety and operational efficiency in air travel. An airport pavement management system (APMS) operates at two levels: the network level, which monitors overall pavement performance across the airport, and the project level, which conducts detailed inspections of individual pavements. However, pavement assessments are often costly and labor intensive, necessitating the development of cost-effective and practical models. This paper introduces the Airport Pavement Integrated Risk Management (APIRM) model, which integrates pavement condition assessment criteria with safety risk management (SRM) methodologies. The model was applied at Istanbul Airport. By using APIRM, airports can prioritize high-risk areas, optimizing resource allocation and enhancing safety. The model encourages coordination among various airport departments, offering a holistic approach to pavement management that integrates maintenance requirements with safety considerations. Full article

In the airport pavement management systems (APMSs), a focus point is the decision-making process. It enables finding the optimal strategy for maintaining a flight infrastructure in adequate condition over a given period, while considering the operating conditions of the airside. In this context, the present study analyzes the factors involved in the optimization processes by investigating how much they influence the solutions. Using the analysis processes connected to the APMS, the present study also includes the identification of specific intervention areas through clustering algorithms, minimizing the fixed operating costs. More specifically, the use of K-means clustering and the heuristic algorithms connected to the choices of the maintenance activities, allow possible scenarios replicating the different needs of managers to be investigated. In this way, the research work analyzes the influence of the alternatives in terms of pavement quality and total activities duration. Through this study it is shown that there is not a unique optimal strategy, but several possible solutions that can be undertaken by the airport managers according to their needs. However, the comparison of the results obtained in this study could become a useful tool for airport managers for better planning and management of the flight infrastructures. Full article

Airport pavements should ensure regular and safe movements during their service life; the management body has to monitor the functional and structural characteristics, and schedule maintenance work, balancing the often conflicting goals of safety, economic and technical issues. This paper presents a remote monitoring system to evaluate the structural performance of a runway composed of concrete thresholds and a flexible central runway. Thermometers, strain gauges, and pressure cells will be embedded at different depths to continuously monitor the pavement’s response to traffic and environmental loads. An innovative system allows data acquisition and processing with specific calculation models, in order to inform the infrastructure manager, in real time, about the actual conditions of the pavement. In this way, the authors aim to develop a system that provides useful information for the correct implementation of an airport pavement management system (APMS) based on real-life data. Indeed, it permits comprehensive monitoring functions to be performed, based on the embedded sensing network. Full article

The conditions of airport movement-area pavements play a primary role on safety and regularity of airport operations; for this reason, the aerodrome operator needs to periodically survey their condition and provide their maintenance and rehabilitation in order to ensure the required operational characteristics. To meet these needs efficiently and effectively, the Airport Pavement-Management System (APMS) has proved to be a strategic tool to support decisions, aimed at defining a technically and economically sustainable management plan. This paper aims to investigate the theoretical elements and structure of the APMS; the appropriate methodologies to guarantee a constant updating of the system in all its aspects are presented, focusing on the specific case study of a medium-dimension Italian airport. The article describes the methods and the equipment used for the high-performance surveys and the condition indexes used for collecting and analyzing the data implemented to populate the APMS of Cagliari airport. Two major survey campaigns were carried out: the first in 2016 and the second in 2019. Both surveys were carried out using the same subdivision into sample units, following the ASTM D5340-12 criteria, to correctly compare data collected in different years. In order to sufficiently populate the APMS database, the measured and back-calculated data were stored and integrated using daily acquired pavement reports since 2009 and stored with the specific intention to develop customized decay curves for Cagliari Airport pavements. Preliminary results on the sustainable use of the APMS were reported even with data collected in a limited period and successfully applied to runway flexible pavement. Full article

Multi-Temporal Interferometric Synthetic Aperture Radar (MT-InSAR) techniques are gaining momentum in the assessment and health monitoring of infrastructure assets. Amongst others, the Persistent Scatterers Interferometry (PSI) technique has proven to be viable for the long-term evaluation of ground scatterers. However, its effectiveness as a routine tool for certain critical application areas, such as the assessment of millimetre-scale differential displacements in airport runways, is still debated. This research aims to demonstrate the viability of using medium-resolution Copernicus ESA Sentinel-1A (C-Band) SAR products and their contribution to improve current maintenance strategies in case of localised foundation settlements in airport runways. To this purpose, “Runway n.3” of the “Leonardo Da Vinci International Airport” in Fiumicino, Rome, Italy was investigated as an explanatory case study, in view of historical geotechnical settlements affecting the runway area. In this context, a geostatistical study is developed for the exploratory spatial data analysis and the interpolation of the Sentinel-1A SAR data. The geostatistical analysis provided ample information on the spatial continuity of the Sentinel 1 data in comparison with the high-resolution COSMO-SkyMed data and the ground-based topographic levelling data. Furthermore, a comparison between the PSI outcomes from the Sentinel-1A SAR data—interpolated through Ordinary Kriging—and the ground-truth topographic levelling data demonstrated the high accuracy of the Sentinel 1 data. This is proven by the high values of the correlation coefficient (r = 0.94), the multiple R-squared coefficient (R² = 0.88) and the Slope value (0.96). The results of this study clearly support the effectiveness of using Sentinel-1A SAR data as a continuous and long-term routine monitoring tool for millimetre-scale displacements in airport runways, paving the way for the development of more efficient and sustainable maintenance strategies for inclusion in next generation Airport Pavement Management Systems (APMSs). Full article

An integrated approach based on machine learning and data augmentation techniques has been developed in order to predict the stiffness modulus of the asphalt concrete layer of an airport runway, from data acquired with a heavy weight deflectometer (HWD). The predictive model relies on a shallow neural network (SNN) trained with the results of a backcalculation, by means of a data augmentation method and can produce estimations of the stiffness modulus even at runway points not yet sampled. The Bayesian regularization algorithm was used for training of the feedforward backpropagation SNN, and a k-fold cross-validation procedure was implemented for a fair performance evaluation. The testing phase result concerning the stiffness modulus prediction was characterized by a coefficient of correlation equal to 0.9864 demonstrating that the proposed neural approach is fully reliable for performance evaluation of airfield pavements or any other paved area. Such a performance prediction model can play a crucial role in airport pavement management systems (APMS), allowing the maintenance budget to be optimized. Full article

The evaluation of friction is a key factor in monitoring and controlling runway surface characteristics. For this reason, specific airport management and maintenance are required to continuously monitor the performance characteristics needed to guarantee an adequate level of safety and functionality. In this regard, the authors conducted years of experimental surveys at airports including Lamezia Terme International Airport. The surveys aimed to monitor air traffic, features of geometric infrastructure, the typological and physical/mechanical characteristics of pavement layers, and runway maintenance planning. The main objective of this study was to calibrate specific models to examine the evolution of friction decay on runways in relation to traffic loads. The reliability of the models was demonstrated in the light of the significance of the friction measurement patterns by learning algorithms and considering the traffic data by varying the geometric and performance characteristics of the aircraft. The calibrated models can be implemented into pavement management systems to predict runway friction degradation, based on aircraft loads during the lifetime of the surface layers of the pavement. It is thus possible to schedule the maintenance activities necessary to ensure the safety of landing and takeoff maneuvers. Full article