Airport Taxiway Research Articles

Research on dynamic response of vertical displacement of runway pavement slab end under aircraft taxiing using novel FBG sensors

The vertical displacement dynamic response measuring at slab joints is crucial for pavement management. In order to obtain accurate dynamic vertical displacement response of slab end, this study developed a vertical displacement sensor based on Fiber Bragg Grating (FBG) technology, featuring an accuracy of 0.15 mm and a resolution of 0.015 mm, which embedded alongside other sensors into Lukou Airport taxiway. The time-history curves of vertical displacement of slab end at both joint sides were obtained, enabling a comprehensive capture of dynamic response during taxiing. In addition, finite element method (FEM) was conducted to simulate taxiing under varying aircraft types, wheel lateral deviation, and speeds. The findings revealed close alignment between FBG sensors and FEM results, with 0.18 mm average error for the sensor, clearly demonstrating its exceptional reliability. Additionally, the influence pattern of taxiing parameters on vertical displacement of slab end including wheel load and path were revealed using FEM.

Multi-Domain Semantic Model and Real-Time Planning Approach to Safe and Efficient Airport Taxiway Operations

Multi-Domain Semantic Model and Real-Time Planning Approach to Safe and Efficient Airport Taxiway Operations

Prediction of Airport Taxiway Settlement based on CNNBiLSTM-Attention

The accurate real-time prediction of complex time series in airport runway settlement is crucial. In order to achieve precise and reliable predictions of runway surface settlement, considering the nonlinear and time-dependent characteristics of settlement data under the coupling effects of dynamic loads, water levels, and other factors, a CNN-BiLSTM-Attention approach is proposed. This method first employs Convolutional Neural Networks (CNN) to extensively extract local temporal features from the input sequences. Subsequently, the extracted local temporal features are input to BiLSTM layers to learn the features of the sequences both in the forward and reverse directions. Finally, the output of the BiLSTM layers is fed into an attention mechanism layer. By computing attention weights, crucial information in the input sequences is weighted and added to enhance the model’s focus on key information. The final settlement prediction is then generated through a fully connected layer. To validate the proposed method, field settlement monitoring data from Runway L at Hangzhou Xiaoshan Airport are utilized as an engineering case study. The results indicate that the combined model captures local features of settlement sequences more effectively with a smaller dataset, achieving higher accuracy compared to a standalone BiLSTM model.

Quick taxi route assignment via real-time intersection state prediction with a spatial-temporal graph neural network

The optimization of airport taxi routes is crucial for increasing airport capacity and resource utilization. However, existing methods for preplanning schedules are often time-consuming. To address this, we propose a new approach that reduces the problem scale by predicting the intersection state in the airport taxiway network using a spatial–temporal graph neural network (STGNN) that incorporates a graph convolutional network and recursive neural network with an attention mechanism. A mixed-integer linear problem (MILP) model for taxi route assignment is established based on a subgraph obtained from the prediction results. Our approach treats time as a continuous variable without discretization, allowing aircraft to stop and wait at any node to avoid conflict. Finally, we demonstrate the effectiveness of our approach by testing it on actual operation data from Beijing Capital International Airport (PEK). Compared with several baseline algorithms, the method developed in this study has a significant impact on improving airport transportation efficiency. The results indicate that our method not only produces high-quality solutions but also operates in real time.

The Safe Passage Redundancy Analysis of Airport Taxiway Bridge Based on Aircraft Load Fatigue Accumulation

This paper is centered around the theoretical, experimental, and simulation analysis of safe passage redundancy and the mechanical deformation of the taxiway bridge under the fatigue accumulation state, and we define the redundancy as the remaining times that the aircraft can pass safely on the taxiway bridge. Based on the principle of stress control, the entity of the taxiway bridge was scaled to establish a laboratory model. The accuracy of the simulation model was verified by the comparative analysis between the experimental and the simulation data. The fatigue–life curve (S–N curve) was introduced to overlay the material fatigue state cycle into the simulation model of the taxiway bridge, and the safe passage redundancy and mechanical deformation of the bridge under the fatigue accumulation state were analyzed. By analyzing and processing the simulation data, a calculation model for the safe passage degree of the taxiway bridge under the fatigue state and a prediction calculation model for the remaining passage life were constructed. By comparing the simulation data with the model data, the accuracy of the established model was verified to be higher than 95%, which provides an important theoretical reference for the development of research on the safety life detection and evaluation of the subsequent taxiway bridge under the fatigue state.

Multi-strategy particle swarm and ant colony hybrid optimization for airport taxiway planning problem

As the connecting hub of the airport runways and gates, the taxiway plays a very important role in the rational allocation and utilization of the airport resources. In this paper, a multi-strategy particle swarm and ant colony hybrid optimization algorithm, namely MPSACO is proposed to solve the airport runway planning problem and avoid taxiway conflicts and conflict propagation. Firstly, a reasonable mathematical model of airport taxiway planning is constructed. Secondly, the multi-strategy particle swarm optimization algorithm (CWBPSO) is employed to propose a new pheromone initialization approach for ACO. And a new pheromone allocation mechanism is designed and a new pheromone update strategy based on the principle of wolf predation is developed, which are combined to design a new pheromone hybrid strategy to enhance the pheromone influence of the optimal solution, dynamically adjust the search direction, and avoid to decline the best search ability, so as to greatly improve the optimization performance of the algorithm. Finally, an airport taxiway planning approach based on MPSACO is proposed, and a conflict adjustment strategy based on speed priority and the idea of first come and first serve (FCFS) is designed to effectively optimize the airport taxiway path. In order to prove the effectiveness of the proposed algorithm/method, 10 traveling salesman problems (TSP) with different scales and an actual airport taxiway planning problem are selected in here. The experiment results show that the proposed MPSACO can effectively solve TSP and obtain the better optimal solutions, and the proposed airport taxiway planning approach can effectively plan the airport taxiing path, avoid the airport taxiing conflicts, and improve the utilization rate of taxiway resources.

Classification of Rigid Pavement at Airport Taxiway using Shear Wave Velocity and Elastic Modulus Derived from Spectral Analysis of Surface Waves (SASW) Method

Classification of Rigid Pavement at Airport Taxiway using Shear Wave Velocity and Elastic Modulus Derived from Spectral Analysis of Surface Waves (SASW) Method

Electrification of airport taxiway operations: A simulation framework for analyzing congestion and cost

Aircraft taxiing with external electric towing could significantly reduce carbon dioxide (CO2) emissions from ground operations. We develop a discrete event simulation and cost model to investigate taxiway congestion and develop a comprehensive equivalent annual cost (EAC) estimate from using electric towing tractors (e-tractors). The model incorporates collision and conflict avoidance and towing service interruptions. Experiments identify the number of e-tractors generating the lowest EAC. A case study considers three electric taxi scenarios at Montréal-Trudeau International Airport. Our findings suggest significant potential for reducing fuel consumption and CO2 emissions with limited impact on taxi time when e-tractor capacity is aligned with demand. However, high uncertainty prevents definitive conclusions about cost effectiveness. The modeling approach can be updated based on ongoing field test data and input from airlines, airports, and handling agents and used to test novel taxi strategies, develop e-tractor implementation plans, and inform the capital budgeting process.

Study of wavelet entropy for airport pavement inspection using a multistatic ground-penetrating radar system

The multilayer nature of airport pavement structures is susceptible to the generation of voids at the bonding parts of the structure, which is also called interlayer debonding. Observations have shown that the thickness of the resulting voids is usually at the scale of millimeters, which makes it difficult to inspect. The efficient and accurate characteristics of ground penetrating radar (GPR) make it suitable for large area inspections of airport pavement. In this study, a multistatic GPR system was used to inspect the interlayer debonding of a large area of an airport pavement. A special antenna arrangement can obtain common-midpoint (CMP) gathers during a common-offset survey. The presence of interlayer debonding affects the phase of the reflection signals, and the phase disturbance can be quantified by the wavelet transform. Therefore, we have developed an advanced approach that uses the average entropy of the wavelet transform parameters in CMP gathers to detect the interlayer debonding of airport pavement. The results demonstrate that the regions with high entropy correspond to regions where tiny voids exist. The new approach introduced in this study was then evaluated by a field-base experiment at an airport taxiway model. The results show that our approach can detect interlayer debonding of the pavement model accurately and efficiently. On-site coring results confirm the performance of our approach.

Subsurface Velocity Change Estimation of Pavement with Multistatic GPR System

In this paper, we propose a cross-correlation method applied to multistatic ground penetrating radar (GPR) data sets to detect road pavement damage. Pavement cracks and delamination cause variations in electromagnetic wave propagation. The proposed method can detect velocity change using cross-correlation of data traces at different times. An artificially damaged airport taxiway model was measured, and the method captures the positions of damaged parts.

Multi-objective routing and scheduling for airport ground movement

Recent research on airport ground movement introduced an Active Routing framework to support multi-objective trajectory-based operations. This results in edges in the airport taxiway graph having multiple costs such as taxi time, fuel consumption and emissions. In such a graph, multiple edges exist between two nodes reflecting different trade-offs among the multiple costs. Aircraft will have to choose the most efficient edge from multiple edges in order to traverse from one node to another respecting various operational constraints. In this paper, we introduce a multi-objective routing and scheduling algorithm based on the enumerative approach that can be used to solve such a multi-objective multi-graph problem. Results using the proposed algorithm for a range of international airports are presented. Compared with other routing and scheduling algorithms, the proposed algorithm can find a representative set of optimal or near optimal solutions in a single run when the sequence of aircraft is fixed. In order to accelerate the search, heuristic functions and a preference-based approach are introduced. We analyse the performance of different approaches and discuss how the structure of the multi-graph affects computational complexity and quality of solutions.

The application of CAP-SASW method in determination of sub-surface profile of flexible taxiway in the airport

In Malaysia, evaluating and assessing pavement condition always require destructive method such as field-cured cylinders and drilled cores from pavement. Not only these current practices are expensive and labor intensive, they are also may not represent in-place quality of pavement due to the in-situ conditions and site irregularities. In terms of the performance of the flexible pavement, the modulus and thickness of each layer in the pavement are the primary factors that associate with it. In-situ determination of these parameters is crucial, and non-destructive seismic method successfully alleviates the dependency on the destructive method. Utilizing Rayleigh wave propagation as its core element, the technology has proven its ability to obtain important parameters in pavement assessment and delineate the subsurface profile accurately. In this study, a non-destructive seismic method called Common Array Profiling Spectral Analysis of Surface Wave (CAP-SASW) was employed on flexible taxiway at Malaysia airport, as in a new, different configuration compared to the conventional SASW method. This method produces stiffness profile of the flexible pavement at airport taxiway. The inversion procedure is performed to obtain their thickness profile and results were compared with the existing methods such as Heavy Weight Deflectometer (HWD), Ground Penetrating Radar (GPR), Dynamic Cone penetrometer (DCP) and coring data. The pavement moduli are obtained with benefit from equation of Yoder and Witzack, and as for this surface wave technique, the moduli obtained are the small strain modulus. The value of elastic modulus obtained for every layer is also being compared to the modulus obtained from HWD method, which shows good comparison.

Occupational Fine/Ultrafine Particles and Noise Exposure in Aircraft Personnel Operating in Airport Taxiway

The occupational exposure to airborne fine and ultrafine particles (UFPs) and noise in aircraft personnel employed in airport taxiway was investigated. Stationary samplings and multiple personal sampling sites and job tasks were considered. Size distribution, particle number concentrations, lung dose surface area were measured by personal particle counters and by means of an electric low pressure impactor (ELPI+TM). Morphological and chemical characterization of UFPs were performed by transmission and scanning electron microscopy, the latter together with energy dispersive X-Ray spectroscopy based spatially resolved compositional mapping. A-weighted noise exposure level A-weighted noise exposure level normalized to an 8 h working day and Peak Sound C-weighted Pressure Level was calculated for single worker and for homogeneous exposure groups. Our study provides evidence on the impact of aviation-related emissions on occupational exposure to ultrafine particles and noise exposure of workers operating in an airport taxiway. Main exposure peaks are related to pre-flight operations of engine aircrafts. Although exposure to ultrafine particles and noise appears to not be critical if compared with other occupational scenarios, the coincidence in time of high peaks of exposure to ultrafine particles and noise suggest that further investigations are warranted in order to assess possible subclinical and clinical adverse health effects in exposed workers, especially for cardiovascular apparatus.

The Rare Southern Twayblade (Neottia bifolia): Sentinel of Ecosystem Integrity For Sphagnous Swamps

Long-term monitoring of the rare southern twayblade (Neottia bifolia; Orchidaceae) and understorey of a black spruce-tamarack, swamp community was conducted after construction of an airport taxiway above the swamp edge. Succession documented over 14 years in the treed swamp edge following disturbance involved loss of the twayblade, invasion by guilds of annuals, and shifts between original and new guilds of wetland plants. Despite changes, the twayblade was the only plant extirpated from the swamp edge community although fungal richness (mainly basidiomycete) was substantially lower in the edge than the swamp interior. NMS ordination indicated that the orchid niche is an undisturbed swamp with an intact tree canopy and unbroken mat of Sphagnum which supports a diverse mycorrhizal community adapted to summer water table drawdown and low ionic groundwater chemistry (e.g. Cl<10 mg/L). Fourteen years after the disturbance, southern twayblade populations in the swamp interior, 100 m from the edge were in steady decline. The woodland orchids may be sentinels of ecosystem integrity. Loss of the twayblade signalled the onset of a post-development, disturbance-cascade: installation of an impervious surface restricted infiltration, altered run-off quantity and quality which subsequently resulted in loss of the ecosystem engineer, Sphagnum, and keystone mycorrhizal fungi.

High-Resolution Velocity Analysis Method Using the ℓ-1 Norm Regularized Least-Squares Method for Pavement Inspection

We propose a high-resolution velocity analysis method to estimate the electromagnetic wave propagation velocity in subsurface medium. The estimation is achieved by applying the l-1 norm regularized least-squares method to the conventional common-midpoint (CMP) velocity analysis algorithm. The proposed method can provide not only higher resolution than the conventional velocity analysis method, but can also be applied with a coarse sampling array system, such as our array ground penetrating radar YAKUMO, which returns eight CMP traces within a two meter width. The main purpose of this approach is for precise pavement inspection at shallow depths. We applied this method to both a simulated dataset and real data acquired by YAKUMO at a model airport taxiway to detect the slight velocity changes caused by millimeter-thin cracks filled with air or water within the 15 cm-thick asphalt pavement. In both cases slight velocity changes of about 0.005 m/ns can be detected, and the difference between air- and water-filled cracks can be distinguished. Also, this method is applied to a data acquired at airport taxi-way, the damaged parts are detected successfully and shows good agreement with the corning results. The results indicate that the proposed method is effective for pavement inspection, especially in the presence of thin cracks that cannot be seen directly with the reflected signal.

Taxiway Pavement Evaluation to Support the Operational of Terminal 2 Juanda Airport

The movement of aircraft and passengers at Juanda international airport was increasing each year. Juanda airport airside infrastructure was almost reaching the maximum capacity. So that, PT. Angkasa Pura I as the operator of Juanda airport planned to revitalize the Juanda airport terminal that located on the south side. This terminal was not already 8 years operating. The infrastructure to be evaluated was the strength of taxiway pavement. Juanda airport taxiway pavement evaluated by using software COMFAA. Data input into the software COMFAA was the existing pavement structure and movement of the aircraft that will use the terminal that in the south side of Juanda airport. The results showed that the existing taxiway pavement structure was able to hold the load of aircraft movements over 20 years. So that, to prepare a taxiway pavement in the south side of Juanda airport, PT. Angkasa Pura I need only overlay the existing taxiway pavement.

Controls on permafrost thaw in a coupled groundwater-flow and heat-transport system: Iqaluit Airport, Nunavut, Canada

Numerical simulations of groundwater flow and heat transport are used to provide insight into the interaction between shallow groundwater flow and thermal dynamics related to permafrost thaw and thaw settlement at the Iqaluit Airport taxiway, Nunavut, Canada. A conceptual model is first developed for the site and a corresponding two-dimensional numerical model is calibrated to the observed ground temperatures. Future climate-warming impacts on the thermal regime and flow system are then simulated based on climate scenarios proposed by the Intergovernmental Panel on Climate Change (IPCC). Under climate warming, surface snow cover is identified as the leading factor affecting permafrost degradation, including its role in increasing the sensitivity of permafrost degradation to changes in various hydrogeological factors. In this case, advective heat transport plays a relatively minor, but non-negligible, role compared to conductive heat transport, due to the significant extent of low-permeability soil close to surface. Conductive heat transport, which is strongly affected by the surface snow layer, controls the release of unfrozen water and the depth of the active layer as well as the magnitude of thaw settlement and frost heave. Under the warmest climate-warming scenario with an average annual temperature increase of 3.23 °C for the period of 2011–2100, the simulations suggest that the maximum depth of the active layer will increase from 2 m in 2012 to 8.8 m in 2100 and, over the same time period, thaw settlement along the airport taxiway will increase from 0.11 m to at least 0.17 m.

Airport Taxiway Head-On Conflict Prediction and Avoidance in A-SMGCS

The closed loop control architecture based on event feedback was proposed for airport taxiway head-on conflict prediction and avoidance in A-SMGCS (Advanced Surface Movement Guidance and Control System). Firstly, resource-oriented controlled colored Petri net was proposed and used to model taxiway operation process. Secondly, the controlled taxiing segment concept was proposed, and rules for generating corresponding sub-model were provided. And then, using cycles and cycle chains contained in the sub-model, the sufficient and necessary condition for head-on conflict-free operation of taxiway was provided. The corresponding avoidance control strategies and algorithm for head-on conflict control were proposed. Finally, the example demonstrated the effectiveness of the proposed algorithm.

A LiDAR application for the study of taxiway surface evenness and slope

Abstract. Pavement roughness evaluation of airport runways/taxiways and scheduling of maintenance operations should be done according to well-defined procedures. Survey of geometric features of airport pavements is performed to verify the flow of water from the surface and to assure a level of roughness that allows the airplane to maneuver in the safest and most comfortable conditions. In particular the evaluation of longitudinal and transversal evenness of the runway and taxiway is carried out through topographic survey. The tachymetric survey has been carried out according to traditional topographic technique, which allows the evaluation of geometric position of isolated points with very high accuracy, but it is not very productive. Moreover it returns the pavement surface model through only few measured points. An alternative survey method, characterized by a good accuracy, high speed of acquisition and very high surveyed point density, is Terrestrial Laser Scanning (TLS), in static mode. In this paper we describe our experience aimed to validate the use of time-of-flight (TOF) TLS, based on a survey on a 200 m length segment of an international airport taxiway. From the acquired data we extracted the parameters of interest, especially the slope, and compared them with the values obtained from the traditional topographic survey. We also developed a proprietary software package to evaluate the slope and to analyze the statistical data. The software allows users to manage the flow of a semi-automatic calculation.

Integrated Optimization of Airport Taxiway and Runway Scheduling

Capacity limitation of runway and taxiway in an airport is often the major limiting factor of air traffic operation. The congestions on the apron of an airport cause severe delay on aircraft schedule. This paper proposes an integrated algorithm to solve problems of runway scheduling and taxiway routing simultaneously for both departure and arrival aircrafts. A set partitioning model with side constraint is proposed in which each possible aircraft route in the taxiway and runway is regarded as a decision variable. Beside traditional set partitioning constraints, two types of constraints are proposed to maintain a minimum separation distance between aircrafts in the taxiway and runway. The preliminary results show that our integrated algorithm outperforms the sequential method. 