Table of Content

08 April 2025, Volume 42 Issue 6

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Safety and airworthiness of civil aircraft

Vertical crash response of typical fuselage frame section and analysis of

occupant lumbar injury

XIE Jiang a , XIE Weiwei b , CUI Shurui c , MOU Haolei a

2024, 42(6):  1-8. 

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To analyze the crash response, structural energy absorption, and occupant injury of a large aircraft fuselage frame

section in the vertical crash test, firstly, the finite element model of typical fuselage frame section-seat-occupant of

a large aircraft is established. Secondly, the failure mode of fuselage frame section and occupant response of the test

piece and this finite element model are compared and analyzed. Finally, the crash energy absorption is analyzed on

different components of the fuselage frame section, and the occupant injury situation is analyzed from the perspectives of lumbar compression load and pelvic acceleration. The simulation results show that the finite element model

of fuselage frame section-seat-occupant can effectively simulate the failure mode of fuselage frame section, one

plastic hinge at the middle support area of the the lower structure of the cargo floor and two plastic hinges at the

connections between cabin floor support columns and fuselage frames, and occupant response is effectively validated. From the perspective of energy absorption, at the vertical crash velocity of 6.02 m/s, the fuselage frame, skin

and connecting corner pieces are the main energy absorbing components, and from the perspective of occupant injuries, simulation results show that the lumbar compression load of occupant is less than 6 672 N and the pelvic acceleration is within the acceptable range of human injury. Furthermore, the dynamic response index (DRI) value

obtained from floor acceleration is lower compared with that of pelvic acceleration. The survival space in the cabin area of the fuselage frame section is maintained, and the injury risk of the occupant lumbar compression load and

pelvic acceleration is relatively small for a certain type of aircraft at a crash speed of 6.02 m/s. The research conclusion of this article can provide reference for the design of large civil aircraft fuselage structure.

Security risk assessment of airborne entertainment system based on

multidimensional cloud model and entropy theory

WANG Jinga, b , QI Shufanc , LI Guoc

2024, 42(6):  9-16. 

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In response to the certain uncertainty, randomness, and fuzziness of existing risk assessment methods of airborne

entertainment system, as well as the strong subjectivity of their evaluation indicators, which leads to inaccurate and

non-objective evaluation results, this paper proposes a risk assessment method of airborne entertainment system

based on multidimensional cloud model and entropy theory. Firstly, more comprehensive, fine-grained, and objective system vulnerabilities are used as evaluation indicators, and based on this indicator data, a multidimensional

cloud model graph is generated to visually display the membership degree of different risks. Then, the risk value of

the entire core component is calculated based on the probability of security events occurring and the probability of

security events losses. And compared with the risk comparison table, the risk assessment result of the entire system

is obtained. Multiple experimental results have shown that the evaluation results of the proposed method in this paper have better stability, accuracy, and objectivity.

Air Transportation Management

A data-driven peak-valley configuration method of flight slot coordination

parameter at busy airport

WANG Yilong, , YANG Lei , , WANG Mengfei , , ZHAO Zheng,

2024, 42(6):  17-26. 

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Scientifically establishing diversified peak-valley configuration schemes of flight slot coordination parameter represents a potent strategy for enhancing the flexibility of flight slot scheduling and alleviating planned primary delays

at busy airport. This paper proposes a general method for the generic peak-valley configuration of flight slot coordination parameter. Firstly, the structure of airport slot fire -break is defined, and the determination process of a

generic peak-valley configuration scheme of flight slot coordination parameter is introduced. Secondly, a schedule based prediction model for airport primary delay is developed, along with the design of rules generating peak-valley

feature parameters of flight slot and expected delay datasets. Finally, the synthetic minority oversampling technique

(SMOTE) and edited nearest neighbors(ENN) algorithm are then employed to addressthe issue of imbalanced dataset

category, and various decision tree classification algorithms are applied to summarize the generic peak-valley configuration pattern set of airport tree-structured slot coordination parameters under a certain level of delay. Taking

Shanghai Pudong International Airport as an example, the prediction accuracy of the primary delay model for airport

arrival and departure, as well as the accuracy of extracting the airport peak-valley configuration combination of

flight slot coordination parameter are verified, and the pattern set of tree-structured peak-valley configuration combination under certain delay level is established. This paper can offer novel insights and methods for the refined setting of airport slot coordination parameter, and providing theoretical support for the optimization and configuration

of flight slot.

Multi-Time prediction model of flight transit key nodes time based on GBDT

DING Jianli, FENG Hao

2024, 42(6):  27-33. 

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To accurately predict the flight transit key nodes time such as departure and takeoff, and improve the operational

efficiency of busy airports, a multi-time prediction model of flight transit key nodes time based on gradient boosting

decision tree (GBDT) is proposed in this paper. Firstly, the flight information data items are classified according to

the generation time. Secondly, based on the GBDT algorithm and Spark platform, the prediction models of flight

transit key nodes time at different transit times are constructed respectively. Finally, flight data is obtained and processed in real-time computing manner, enabling dynamic prediction of flight departure time and take-off time at

multiple times. The experimental results show that the proposed model has good predictive performance and has the

best predictive performance compared to other algorithms, with a prediction accuracy of 95.6% within ± 15 minutes.

Research on flight alternate landing model in emergency situation

XIE Chunsheng, HANG Yu, ZHAO Xiangling

2024, 42(6):  34-38. 

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Aiming at the problem of how to transfer a large number of flights to the appropriate alternate airport when the target

airport is temporarily closed in emergency situation, a linear programming model is established in this paper based

on the idea of collaborative decision-making, which can decrease the total flight time of flight diversion while

meeting the airline's expectations for alternate airports to the greatest extent. Combined with the actual operation

characteristics, this model considers the maximum available flight time, the expectation of airlines to the alternate

airport, the substitution ability of the airport, the acceptable aircraft category, the time slot of the alternate airport,

the aircraft cruise speed, route wind, air congestion and other objective conditions, and adds a penalty function to

the model to consider the extremely unconstrained situation. The example calculation results show that the optimized alternate results can meet the expectations of airlines while reducing the alternate time, and the total alternate time is reduced by 14.1%.

Departure flight scheduling method under the condition of flight delay disturbance

XU Dongxu, ZHANG Rong

2024, 42(6):  39-45. 

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The takeoff process of a flight is affected by various uncertain factors, such as flight delay, scheduling delay and taxi

time, etc. A reliable and robust departure sequence is essential to the safe and efficient operation of the airport.

Firstly, the kernel probability density curve of flight delay is obtained by estimating the kernel density of flight delay historical data, and then the random number of flight delay is obtained by linear interpolation. Taking the random number of flight delay as input, a multi-runway departure flight scheduling model under the uncertain flight

delay is established, and a genetic algorithm for encoding flight number is designed to solve this model. On this basis, a multi-objective dynamic scheduling model under uncertain flight delay is further established, and a hybrid

algorithm is designed to solve this model. Monte Carlo simulation is performed on the results of the two models to

explore the impact of flight delay uncertainty on departure scheduling. Finally, taking the historical data of

Guangzhou Baiyun International Airport as an example, the model validation is conducted.

Analysis of the influence degree of major public health emergencies on

civil aviation transportation volume in China

LIANG Zhixinga , MA Xinjieb , CAO Jie

2024, 42(6):  46-51. 

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In order to scientifically measure the influence level of major public health emergencies on China′s civil aviation

transportation volume and predict the future development trend of China′s civil aviation transportation volume, the

concepts of influence value and influence degree of major public health emergencies were introduced to quantitatively analyze the index such as passenger throughput and cargo throughput, etc. of Beijing Capital International

Airport, Dalian Zhoushuizi International Airport, and China′s civil aviation from 2018 to 2019. The cubic exponential smoothing method was used to calculate the predicted values for 2020 and 2021. The difference between the

predicted values and the actual values was set as the influence value, and the ratio of the influence value of the current month to the influence value of the previous month was defined as the influence degree. The results showed

that the influence degree of public health emergencies on civil aviation transportation volume was about 1.0. From

2022 to 2025, civil aviation transportation volume in China will steadily recover. The introduction of the concept

and method of influence degree provides new ideas for predicting the civil aviation transportation volume in the

context of emergencies.

Short-term forecast of airport flow based on twice decomposition integration

WANG Fei , HAN Xiangyu

2024, 42(6):  52-60. 

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In order to achieve accurate short-term forecast of airport flow, a decomposition integration forecast model based on

twice decomposition method is established in this paper. Firstly, the seasonal and trend decomposition procedure

based on Loess (STL) algorithm is applied to decompose the original time series into three components, including

trend term, seasonal term and residual term, and their sample entropy are calculated. Secondly, genetic algorithm

(GA) is applied to optimize the parameters of variational mode decomposition (VMD), and the components with

larger entropy values are subjected to twice decomposition. Thirdly, extreme gradient boosting (XGBoost) is applied

to predict all components after twice decomposition, and the final predicted value is obtained by adding and integrating. Finally, the actual operation data of domestic typical airports are collected for case analysis. For the 60 min

arrival and departure flow time series of Beijing Capital International Airport, the equal coefficient (EC) values predicted in this paper are 0.970 3 and 0.995 9 respectively, which has an improvement compared to other common

models. In addition, for the three large international airports of Shanghai Pudong, Shanghai Hongqiao, and

Guangzhou Baiyun, the EC values predicted by the proposed model are all above 0.970 0 for arrival and departure

flow at 60 min and 30 min scales, and the predicted EC values at the 15 min scale are all above 0.950 0. The results

indicate that the twice decomposition integration forecast model established in this paper has good accuracy and universality, and is feasible and effective for short-term forecast of airport flow.

Future airports and smart equipment

Terminal operation resilience evaluation based on extension cloud model

CHENG Guoyong, CHEN Shi

2024, 42(6):  61-66. 

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In order to improve the ability of terminal to respond to emergencies and ensure the continuous safe and stable operation of the airport, it is necessary to introduce the concept of terminal operation resilience and conduct resilience

evaluation. This paper is aiming at the problems of randomness and fuzziness in the existing terminal operation resilience evaluation process and the difficulty of quantitative expression of evaluation indicators. Firstly, starting

from the four basic attributes of resilience, including robustness, rapidity, redundancy and strategicity, 18 indicators are selected to construct an evaluation index system of terminal operation resilience. Secondly, the analytic hierarchy process (AHP) is used to assign weights to indicators, and then the comprehensive evaluation model of terminal operation resilience is constructed based on the extension cloud model. Finally, taking the terminal of a

northern airport as an example for verification, the results show that the comprehensive score of terminal operation

resilience of the airport was 4.362 3 points, which is medium to high resilience. The comprehensive evaluation

model of terminal operation resilience proposed in this article can provide reference for the evaluation of terminal

operation resilience.

Prediction of gear remaining useful life based on attention LSTM

GUO Runxia, NI Zhigao

2024, 42(6):  67-73. 

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Aiming at the problem of predicting the gear remaining useful life (RUL) in rotating machinery, using the unique

advantages of long short- term memory (LSTM) network in processing time series data, a gear remaining useful life

prediction algorithm combining attention mechanism and LSTM is proposed in this paper. Firstly, four kinds of

time domain features (root mean square value, kurtosis, variance, and margin index) that can better reflect

the health status are decomposed from gear vibration signal and taken as inputs to the RUL prediction network.

Secondly, with the goal of improving the accuracy of RUL prediction results, a novel RUL prediction network is

designed by combining LSTM and attention mechanism. Finally, the model was validated using real data generated from gear full-life accelerated fatigue test bench of the laboratory. The results show that the attention LSTM

algorithm proposed in this paper has high prediction accuracy in predicting the gear RUL.

Extended layerwise method research of the transient problem of piezoelectric

composite material structure

XU Jianxin, SUN Ziming, WU Yaogang, LI Dinghe

2024, 42(6):  74-81. 

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The mass matrix and time integration method were introduced into the piezoelectric extended layerwise method

(XLWM). According to the displacement and internal force balance conditions of the connection area between

piezoelectric sheet and composite material laminated structure, the overall control equation of piezoelectric composite material laminates was established, and the transient response analysis of structures containing damage was

achieved. Firstly, in the numerical example, the convergence analysis was conducted using non-destructive structures, and the converged results were compared with the three-dimensional elastic model simulated by ANSYS

software to verify the correctness of the proposed method. Secondly, in the condition of containing single damage,

the influence law of different damage parameters on the transient response of piezoelectric composite material laminates was studied. Finally, under multiple damage conditions, the variation law of transient response of piezoelectric composite material laminates under different damage parameters was studied, and the influence of the coupling

position between piezoelectric sheet and composite material on the transient response was analyzed.

General aviation and drones

Optimization of 3D reconstruction algorithm for UAV aerial survey based on

deep learning

YANG Yonggang , LI Simeng

2024, 42(6):  82-90. 

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When the traditional struct from motion (SFM) algorithm is used to realize 3D reconstruction from the perspective of

unmanned aerial vehicle (UAV), in order to reduce the mismatching of feature points and the impact of moving targets on the overall sparse point cloud, the random sample consensus (Ransac) algorithm is mainly relied on. However, these problems can lead to a decrease in the accuracy and an increase in the number of iterations of Ransac

when solving camera poses. This article conducts target detection based on a deep learning single shot multibox detector (SSD) network. Firstly, feature points within the range of dynamic target categories are removed after scaleinvariant feature transform (SIFT) extraction of feature points. Then, mismatches are removed after K-nearest neighbor (KNN) violent matching to reduce feature points within the range of invalid moving targets and mismatching

between different categories. So that when the confidence is the same, the number of iterations of Ransac when

solving camera pose is reduced, and the time of feature point violence matching and SFM algorithm calculation of

3D points are also reduced. Finally, the feasibility of the 3D reconstruction algorithm optimized by deep learning

was verified through 12 images of 2 scenes.

Damping vibration absorber analysis and improved design of a certain UAV

LIU Yanhong, LI Haofeng

2024, 42(6):  91-96. 

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Considering the control requirements of fuselage vibration for a certain type of oil-electric hybrid unmanned aerial

vehicle (UAV) during cruise phase, the damping vibration absorbers with 4-point and 6-point layout at the connection between the engine and the fuselage are designed in this paper based on the passive vibration reduction principle. After installing the two types of vibration absorbers, the flight state of the UAV are simulated on the ground, The

experimental test result is compared with original vibration absorber. The results indicate that both types of vibration absorbers can effectively control the fuselage vibration, and the damping vibration absorbers with the 6-point

layout having a better effect of vibration reduction, which ensuring each indicator of the fuselage vibration meet the

requirements. At the same time, the weight of the UAV has been reduced by reducing the weight of the vibration

absorbers.