Wings of Change Angola’s new international airport becomes a symbol of high-quality cooperation under the BRI

The new Dr.Antonio Agost inho Neto International Airport(AIAAN)infrastructure project is valued at around$3 billion.The project was fully funded by the Angolan government as a public investment,with lending from the Chinese government for the airport construction.China National Aero-Technology International Engineering Corp,the key construction subsidiary of AVIC International Holding,is the contractor for the project.

OPTIMIZATION OF AIRPORT TAXIING PLANNING DURING CONGESTED HOURS BASED ON IMMUNE CLONAL SELECTION ALGORITHM

In order to ease congestion and ground delays in major hub airports, an aircraft taxiing scheduling optimization model is proposed with schedule time as the object function. In the new model, the idea of a classical job shop-schedule problem is adopted and three types of special aircraft-taxi conflicts are considered in the constraints. To solve such nondeterministic polynomial time-complex problems, the immune clonal selection algorithm（ICSA） is introduced. The simulation results in a congested hour of Beijing Capital International Airport show that, compared with the first-come-first-served（FCFS） strategy, the optimization-planning strategy reduces the total scheduling time by 13.6 min and the taxiing time per aircraft by 45.3 s, which improves the capacity of the runway and the efficiency of airport operations.

Assessing the Hazard Grade of Birdstrike in Spring at Baita Airport, Hohhot

Between March and May 2005, bird communities in four sample plots at Baita Airport were studied using strips methods in Hohhot, Inner Mongolia. A total of 59 species belonging to 10 orders and 26 families were recorded. Based on the principles of avian community ecology, the community parameters were discussed, including the comparative importance value, distribution coefficient, density and probability of interactive encounter. By analyzing these indices, combined with their flight behaviors at the airport and its neighbourhood, we identified bird species that have the potential to threaten flight security at Baita Airport; The results showed that the 23 bird species including magpie and red falcon are the most hazard to flight security and the eight bird species including sparrow Hawk and Greenfinch are the hazard. Furthermore, we assessed the bird species＇ different hazard grades to flight security.

Homogeneity Analysis of Multiairport System Based on Airport Attributed Network Representation Learning

The homogeneity analysis of multi-airport system can provide important decision-making support for the route layout and cooperative operation.Existing research seldom analyzes the homogeneity of multi-airport system from the perspective of route network analysis,and the attribute information of airport nodes in the airport route network is not appropriately integrated into the airport network.In order to solve this problem,a multi-airport system homogeneity analysis method based on airport attribute network representation learning is proposed.Firstly,the route network of a multi-airport system with attribute information is constructed.If there are flights between airports,an edge is added between airports,and regional attribute information is added for each airport node.Secondly,the airport attributes and the airport network vector are represented respectively.The airport attributes and the airport network vector are embedded into the unified airport representation vector space by the network representation learning method,and then the airport vector integrating the airport attributes and the airport network characteristics is obtained.By calculating the similarity of the airport vectors,it is convenient to calculate the degree of homogeneity between airports and the homogeneity of the multi-airport system.The experimental results on the Beijing-Tianjin-Hebei multi-airport system show that,compared with other existing algorithms,the homogeneity analysis method based on attributed network representation learning can get more consistent results with the current situation of Beijing-Tianjin-Hebei multi-airport system.

Strategic development of commercial airports in Chongqing

Civil airports in China in the last 10 years have expanded substantially, and the construction of airports has come into a period planning to build airports into large transportation hub. This article combines the new trends of commercial real estate and the airport business, and explores various business marketing and management modes for operating airports with specific reference to the case of Chongqing. The main research results are as follows: First, the introduction of products and services markets should make more focus on the structure and habits of travelers. Second, developing new commercial projects through the BOT model and practicing resource replacement mode. Third, planning the terminal surrounding functions, the layout of successful business is the key factor of the rapid increase of airport non-aeronautical revenue.

Five Typical Emotional Reactions to Airport Security Screening:A Case Study

For this study,there were two sets of data collection:face-to-face interview and on-line survey via“survey monkey”.The survey focuses on the following:feelings associated with airport security screening and impact of awareness with prohibited items.The survey was conducted from May 13 to 31,2018 for three weeks covering four terminals at the Ninoy Aquino International Airport(NAIA)in Manila.From the interviews and on-line survey conducted,it was evident that there are five typical emotional reactions to airport security screening processes.Forty-five percent of travelers felt frustrated upon undergoing a security screening process.On a positive note,26%of the respondents felt relaxed and 16%have understood the screening processes being implemented in the airports.Other negative reactions surfaced were fear(5%)and humiliation(8%).Initial reactions and questions from departing passengers,such as“will I get trouble?”“will I be treated like a criminal or terrorist?”or“will I miss my flight”,these are common responses that might be traced from a first time traveler.The results of this study will provide beneficial information to airport authorities as they determine how they can best provide a balanced-mixed of security and facilitation in managing airport security.

Designing Sustainable Airport Ground Access/Egress Systems Supported by Fast-Time Modeling

The problems of airport landside capacity assessment are of industry-wide interest. Evaluation of landside capacity enables airport operators and airport designers to identify passenger and baggage flow bottlenecks, identify the primary cause of bottlenecks formation and take measures mitigating the impact of bottlenecks on the airport terminal operation. Many studies dealing with the problems of airport landside capacity are focused mainly on the processing part of the airport terminal and consider the airport terminal to be an isolated system. Even the most of models of airport landside operations developed using various simulation （both generic and dedicated） software packages （e.g., PaxSim, SLAM, WITNESS, ARENA or EXTEND） are designed for simulating the passenger and baggage flows only between curb-side and apron. Although this approach provides valuable data concerning capacity, delays or processing bottlenecks, in some cases identified capacity constraints are only the symptoms of the actual problem. In order to discover the cause of the problem, it is necessary to consider the airport terminal as an integral part of much more complex regional, national or international transportation system. This article reflects the above mentioned requirements and introduces an innovative approach to passenger and baggage flow simulation based on the fact that airport terminal is considered as an integral part of air passenger door-to-door transportation process.

Panzhihua Airport Landslide (Oct. 3rd 2009) and an Emergency Monitoring and Warning System Based on the Internet of Things

Panzhihua city （26°O5＇-27°21＇N, 101°OS＇- 102°15＇E）, located in a mountainous area, is one of the large cities in Sichuan province, China. A landslide occurred in the filling body of the eastern part of the Panzhihua airport on October 3, 2009 （hereafter called the lo.3 landslide）. We conducted field survey on the landslide and adopted emergency monitoring and warning models based on the Internet of Things （loT） to estimate the losses from the disaster and to prevent a secondary disaster from occurring. The results showed that four major features of the airport site had contributed to the landslide, i.e, high altitude, huge amount of filling rocks, deep backfilling and great difficulty of backfilling. The deformation process of the landslide had six stages and the unstable geological structure of high fillings and an earthquake were the main causes of the landslide. We adopted relative displacement sensing technology and Global System for Mobile Communications （GSM） technology to achieve remote, real-time and unattended monitoring of ground cracks in the landslide. The monitoring system, including five extensometers with measuring ranges of 200, 450 and 7oo mm, was continuously working for 17 months and released 7 warning signals with an average warning time of about 26 hours. At 10 am on 6 December 2009, the system issued a warning and on-site workers were evacuated and equipment protected immediately. At 2：20 medium-scale collapse monitoring site, which proved the reliability pm on 7 December, a occurred at the No. 5 justified the alarm and and efficiency of the monitoring system.

Numerical study on settlement of high-fill airports in collapsible loess geomaterials:A case study of Lüliang Airport in Shanxi Province,China

Foundation settlement is of great significance for high-fill engineering in collapsible loess areas.To predict the construction settlement of Lüliang Airport located in Shanxi Province,China,a plane strain finite element method considering the linear variation in the modulus,was carried out in this paper based on the results of geotechnical tests.The stress and deformation of four typical sections caused by layered fill are simulated,and then the settlement of the high-fill airport is calculated and analyzed by inputting three sets of parameters.The relative soft parameters of loess geomaterials produce more settlement than the relatively hard parameters.The thicker the filling body is,the greater the settlement is.The filling body constrained by mountains on both sides produces less settlement than the filling body constrained by a mountain on only one side even the filling thickness is almost the same.The settlement caused by the original subbase accounts for 56%−77%of the total settlement,while the fill soils themselves accounts for 23%−44%of the total settlement,which is approximately consistent with the field monitoring results.It provides a good reference for predicting the settlement of similar high-fill engineering.

Airport automatic detection in large space-borne SAR imagery

A method to detect airports in large space-borne synthetic aperture radar（SAR） imagery is studied.First,the large SAR imagery is segmented according to amplitude characteristics using maximum a posteriori（MAP） estimator based on the heavytailed Rayleigh model.The attention is then paid on the object of interest（OOI） extracted from the large images.The minimumarea enclosing rectangle（MER） of OOI is created via a rotating calipers algorithm.The projection histogram（PH） of MER for OOI is then computed and the scale and rotation invariant feature for OOI are extracted from the statistical characteristics of PH.A support vector machine（SVM） classifier is trained using those feature parameters and the airport is detected by the SVM classifier and Hough transform.The application in space-borne SAR images demonstrates the effectiveness of the proposed method.

A new approach of drawing airport noise contours on computer based on Surfer

Noise contours are used to describe the extent of airport noise pollution and to plan land use around airports. The L WECPN(weighted equivalent continuous perceive noise level) recommended by ICAO(International Civil Aviation Organization) is adopted as airport noise rating parameter in this paper. With the help of various mathematical models in the software Surfer, noise contours can be drawn automatically by the completed program in Visual C++ Code. Corrections for thrust, velocity, atmospheric temperature, humidity and lateral ground attenuation are also considered in the new method, which can improve the efficiency of drawing contours. An example of its use for drawing noise contours of an airport in Zhejiang Province of China is proposed and the predictions and the measurements show agreements well.

A Partial Parallel Airport Gate Assignment Supported by a Knowledge－based System Combined with Mathematical Programming

The gate assignment at an airport is one of the major activities in airport operations.With the increase of passenger traffic volumes and the number of flights, the complexity of this task and the factors to be considered have increased significantly, and an efficient gate utilizationhas received considerable attention. For overcoming the shortcomings of previous gate assignmentapproaches, this paper presents a partial parallel gate assignment approach, by which more factorsconcerning aircraft and gates can be collsidered at the same time. This paper also presents themethod of using a knowledge-based system combined with a mathematical programming method forgetting an optimized feasible assignment solution. By this way, it is more easily to get the solutionthat satisfies both the static and dynamic situations,and thus it may adapt well to meet the needsof actual use to rea-time operations. An experimental prototype has been implemented, and a casestudy is presented at the end of the paper.

A Bilevel Programming Approach for Optimization of Airport Ground Movement

This paper proposes an optimization model for the airport ground movement problem(GMP)based on bilevel programming to address taxi conflicts on the airport ground and to improve the operating safety and efficiency.To solve GMP,an iterative heuristic algorithm is designed.Instead of separately investigating each problem,this model simultaneously coordinates and optimizes the aircraft routing and scheduling.A simulation test is conducted on Nanjing Lukou International Airport(NKG)and the results show that the bilevel programming model can clearly outperform the widely used first-come-first-service(FCFS)scheduling scheme in terms of aircraft operational time under the precondition of none conflict.The research effort demonstrates that with the reduced operating cost and the improved overall efficiency,the proposed model can assist operations of the airports that are facing increasing traffic demand and working at almost maximum capacity.

The Application of Deep Learning in Airport Visibility Forecast

This paper uses Urumqi International Airport’s hourly observation from 2007 to 2016 and builds regression prediction model for airport visibility with deep learning method. From the results we can see: the absolute error of hourly visibility is 706 m. When the visibility ≤ 1000 m, the absolute error is 325 m, and this method can predict visibility’s trend. So we can use this method to provide the airport visibility’s objective forecast guidance products for aviation meteorological services in the future. In this paper, the Urumqi area is as the research object, to explore the depth of learning in the field of weather forecasting applications, providing a new visibility return forecast for weather forecast personnel so as to improve the visibility of the level of visibility to ensure the safe and stable operation of the airport.

Collaboration Optimization of Flight Schedule in Beijing⁃Tianjin⁃Hebei Airport Group

The coordinated and integrated development of regional airport group system has been identified as an important research topic in the field of air traffic management in China.However,due to the clear limitation on airspace resources and severe traffic congestion,it is necessary to further study the problem of flight schedule coordination optimization for airport clusters.We take the Beijing-Tianjin-Hebei airport Group as an example and construct an optimization model of flight schedule with the minimum adjustment and delay.The design of the implementation algorithm is proposed.As demonstrated by the simulation results,the flight delay in the Beijing-Tianjin-Hebei multi-airport system is noticeably reduced by applying both the optimization model and the algorithm proposed in this paper.

Airport gate assignment problem with deep reinforcement learning

With the rapid development of air transportation in recent years,airport operations have attracted a lot of attention.Among them,airport gate assignment problem(AGAP)has become a research hotspot.However,the real-time AGAP algorithm is still an open issue.In this study,a deep reinforcement learning based AGAP(DRL-AGAP)is proposed.The optimization object is to maximize the rate of flights assigned to fixed gates.The real-time AGAP is modeled as a Markov decision process(MDP).The state space,action space,value and rewards have been defined.The DRL-AGAP algorithm is evaluated via simulation and it is compared with the flight pre-assignment results of the optimization software Gurobiand Greedy.Simulation results show that the performance of the proposed DRL-AGAP algorithm is close to that of pre-assignment obtained by the Gurobi optimization solver.Meanwhile,the real-time assignment ability is ensured by the proposed DRL-AGAP algorithm due to the dynamic modeling and lower complexity.

Impact of the Sanya new airport artificial islands project on tidal dynamics of the Hongtang Bay

By establishing a 3-dimensional hydrodynamic model of the Hongtang Bay and the validation tests,tidal currents of the area before and after the construction of the Sanya new airport project,which include two artificial islands built respectively to accommodate the airport and its connected technology park,are simulated.The hydrodynamic impacts of the islands on the Hongtang Bay and surrounding waters were analyzed by comparing flow fields and velocities of tidal currents under the two conditions.

Improved Ant Colony Algorithm for Vehicle Scheduling Problem in Airport Ground Service Support

Support vehicles are part of the main body of airport ground operations,and their scheduling efficiency directly impacts flight delays.A mathematical model is constructed and the responsiveness of support vehicles for current operational demands is proposed to study optimization algorithms for vehicle scheduling.The model is based on the constraint relationship of the initial operation time,time window,and gate position distribution,which gives an improvement to the ant colony algorithm(ACO).The impacts of the improved ACO as used for support vehicle optimization are compared and analyzed.The results show that the scheduling scheme of refueling trucks based on the improved ACO can reduce flight delays caused by refueling operations by 56.87%,indicating the improved ACO can improve support vehicle scheduling.Besides,the improved ACO can jump out of local optima,which can balance the working time of refueling trucks.This research optimizes the scheduling scheme of support vehicles under the existing conditions of airports,which has practical significance to fully utilize ground service resources,improve the efficiency of airport ground operations,and effectively reduce flight delays caused by ground service support.

SA-FRCNN:An Improved Object Detection Method for Airport Apron Scenes

The airport apron scene contains rich contextual information about the spatial position relationship.Traditional object detectors only considered visual appearance and ignored the contextual information.In addition,the detection accuracy of some categories in the apron dataset was low.Therefore,an improved object detection method using spatial-aware features in apron scenes called SA-FRCNN is presented.The method uses graph convolutional networks to capture the relative spatial relationship between objects in the apron scene,incorporating this spatial context into feature learning.Moreover,an attention mechanism is introduced into the feature extraction process,with the goal to focus on the spatial position and key features,and distance-IoU loss is used to achieve a more accurate regression.The experimental results show that the mean average precision of the apron object detection based on SAFRCNN can reach 95.75%,and the detection effect of some hard-to-detect categories has been significantly improved.The proposed method effectively improves the detection accuracy on the apron dataset,which has a leading advantage over other methods.

Interpretation of EC Fine Grid Numerical Prediction Products in the Forecast of Frozen Fog in Urumqi Airport

In this paper, Urumqi Airport time-lapse ground man-made observation data from November 2015 to February 2017, European fine grid (0.25 × 0.25) initial field (20 o’clock) and the forecast field within 24 hours were utilized. From November 2015 to February 2016, the relevant materials were used as research samples (a total of 948 times), and from November 2016 to February 2017 as test samples (a total of 922 times), statistical methods were used to establish the scoring standards. And each relevant element was scored. After the score, the score level range was delineated, and the visibility forecast was performed according to the scope. The conclusions are as follows: 1) European fine grid forecast products are with good correspondence with the visibility of this field are 850 hPa and 2 m high temperature inversion, 850 hPa relative humidity and 850 hPa wind field over the field. 2) Through the statistical analysis of scores, it is defined that the score below 400 is level 4, the score above 1000 is level 1, the difference is significant, and the forecast indication is strong. Level 2 and level 3 are more evenly distributed, with no more concentrated fractions. 3) Applying the test sample to test the above indicators. The forecast accuracy of level 1 is 61.2%, and the forecast accuracy of level 4 is 97.2%, so level 1 and level 4 are expected to obtain better forecast results, which is of practical application value.