Fluid-chemical modeling of the near-cathode sheath formation process in a high current broken in DC air circuit breaker

When the contacts of a medium-voltage DC air circuit breaker(DCCB) are separated, the energy distribution of the arc is determined by the formation process of the near-electrode sheath. Therefore, the voltage drop through the near-electrode sheath is an important means to build up the arc voltage, which directly determines the current-limiting performance of the DCCB. A numerical model to describe the near-electrode sheath formation process can provide insight into the physical mechanism of the arc formation, and thus provide a method for arc energy regulation. In this work, we establish a two-dimensional axisymmetric time-varying model of a medium-voltage DCCB arc when interrupted by high current based on a fluid-chemical model involving 16 kinds of species and 46 collision reactions. The transient distributions of electron number density, positive and negative ion number density, net space charge density, axial electric field, axial potential between electrodes, and near-cathode sheath are obtained from the numerical model. The computational results show that the electron density in the arc column increases, then decreases, and then stabilizes during the near-cathode sheath formation process, and the arc column's diameter gradually becomes wider. The 11.14 V–12.33 V drops along the17 μm space charge layer away from the cathode(65.5 k V/m–72.5 k V/m) when the current varies from 20 k A–80 k A.The homogeneous external magnetic field has little effect on the distribution of particles in the near-cathode sheath core,but the electron number density at the near-cathode sheath periphery can increase as the magnetic field increases and the homogeneous external magnetic field will lead to arc diffusion. The validity of the numerical model can be proven by comparison with the experiment.

Microstructure design of advanced magnesium-air battery anodes

Metal-air battery is an environmental friendly energy storage system with unique open structure.Magnesium(Mg)and its alloys have been extensively attempted as anodes for air batteries due to high theoretical energy density,low cost,and recyclability.However,the study on Mg-air battery(MAB)is still at the laboratory level currently,mainly owing to the low anodic efficiency caused by the poor corrosion resistance.In order to reduce corrosion losses and achieve optimal utilization efficiency of Mg anode,the design strategies are reviewed from microstructure perspectives.Firstly,the corrosion behaviors have been discussed,especially the negative difference effect derived by hydrogen evolution.Special attention is given to the effect of anode micro-structures on the MAB,which includes grain size,grain orientation,second phases,crystal structure,twins,and dislocations.For further improvement,the discharge performance,long period stacking ordered phase and its enhancing effect are considered.Meanwhile,given the current debates over Mg dendrites,the potential risk,the impact on discharge,and the elimination strategies are discussed.Microstructure control and single crystal would be promising ways for MAB anode.

Mapping Air Quality Using Remote Sensing Technology: A Case Study of Nairobi County

Nairobi County experiences rapid industrialization and urbanization that contributes to the deteriorating state of air quality, posing a potential health risk to its growing population. Currently, in Nairobi County, most air quality monitoring stations use low-cost, inaccurate monitors prone to defects. The study’s objective was to map Nairobi County’s air quality using freely available remotely sensed imagery. The Air Pollution Index (API) formula was used to characterize the air quality from cloud-free Landsat satellite images i.e., Landsat 5 TM, Landsat 7 ETM+, and Landsat 8 OLI from Google Earth Engine. The API values were computed based on vegetation indices namely NDVI, TVI, DVI, and the SWIR1 and NIR bands on the QGIS platform. Qualitative accuracy assessment was done using sample points drawn from residential, industrial, green spaces, and traffic hotspot categories, based on a passive-random sampling technique. In this study, Landsat 5 API imagery for 2010 provided a reliable representation of local conditions but indicated significant pollution in green spaces, with recorded values ranging from -143 to 334. The study found that Landsat 7 API imagery in 2002 showed expected results with the range of values being -55 to 287, while Landsat 8 indicated high pollution levels in Nairobi. The results emphasized the importance of air quality factors in API calibration and the unmatched spatial coverage of satellite observations over ground-based monitoring techniques. The study recommends the recalibration of the API formula for characteristic regions, exploring newer satellite sensors like those onboard Landsat 9 and Sentinel 2, and involving key stakeholders in a discourse to develop a suitable Kenyan air quality index.

Mastering air combat game with deep reinforcement learning

Reinforcement learning has been applied to air combat problems in recent years,and the idea of curriculum learning is often used for reinforcement learning,but traditional curriculum learning suffers from the problem of plasticity loss in neural networks.Plasticity loss is the difficulty of learning new knowledge after the network has converged.To this end,we propose a motivational curriculum learning distributed proximal policy optimization(MCLDPPO)algorithm,through which trained agents can significantly outperform the predictive game tree and mainstream reinforcement learning methods.The motivational curriculum learning is designed to help the agent gradually improve its combat ability by observing the agent's unsatisfactory performance and providing appropriate rewards as a guide.Furthermore,a complete tactical maneuver is encapsulated based on the existing air combat knowledge,and through the flexible use of these maneuvers,some tactics beyond human knowledge can be realized.In addition,we designed an interruption mechanism for the agent to increase the frequency of decisionmaking when the agent faces an emergency.When the number of threats received by the agent changes,the current action is interrupted in order to reacquire observations and make decisions again.Using the interruption mechanism can significantly improve the performance of the agent.To simulate actual air combat better,we use digital twin technology to simulate real air battles and propose a parallel battlefield mechanism that can run multiple simulation environments simultaneously,effectively improving data throughput.The experimental results demonstrate that the agent can fully utilize the situational information to make reasonable decisions and provide tactical adaptation in the air combat,verifying the effectiveness of the algorithmic framework proposed in this paper.

Influences of the Fresh Air Volume on the Removal of Cough-Released Droplets in a Passenger Car of a High-Speed Train Using CFD

The spread and removal of pollution sources,namely,cough-released droplets in three different areas(front,middle,and rear areas)of a fully-loaded passenger car in a high-speed train under different fresh air flow volume were studied using computational fluid dynamics(CFD)method.In addition,the structure of indoor flow fields was also analysed.The results show that the large eddies are more stable and flow faster in the air supply under Mode 2(fresh air volume:2200m3/h)compared to Mode 1(fresh air volume:1100m3/h).By analysing the spreading process of droplets sprayed at different locations in the passenger car and with different particle sizes,the removal trends for droplets are found to be similar under the two air supply modes.However,when increasing the fresh air flow volume,the droplets in the middle and front areas of the passenger car are removed faster.When the droplets had dispersed for 60s,Mode 2 exhibited a removal rate approximately 1%–3%higher than Mode 1 for small and medium-sized droplets with diameters of 10 and 50μm.While those in the rear area,the situation is reversed,with Mode 1 slightly surpassing Mode 2 by 1%–3%.For large droplets with a diameter of 100μm,both modes achieved a removal rate of over 96%in all three regions at the 60 s.The results can provide guidance for air supply modes of passenger cars of high-speed trains,thus suppressing the spread of virus-carrying droplets and reducing the risk of viral infection among passengers.

Dynamic propagation velocity of a positive streamer in a 3 m air gap under lightning impulse voltage

Streamers represent an important stage in the initiation of gap discharge. In this work, we used an eight-frame intensified charge-coupled device camera to capture the streamer development process when a lightning impulse voltage of 95%–100% U50% was applied in a 3 m rod–plate gap and the streamer velocity was analyzed. Analysis of the observations shows that streamer velocity can be defined by three stages: rapid velocity decline(stage 1), rapid velocity rise(stage 2)and slow velocity decline(stage 3). The effects of electrode shape, applied voltage and gap breakdown or withstanding on streamer velocity were analyzed. The electrode with a larger radius of curvature will result in a higher initial velocity, and a higher voltage amplitude will cause the streamer to propagate faster at stage 3. Gap withstanding or breakdown has no obvious effect on streamer velocity. In addition, the experimental results are compared with previous results and the statistical characteristics of the primary streamer discharge are discussed.

Different bactericidal abilities of plasma-activated saline with various reactive species prepared by surface plasma-activated air and plasma jet combinations

Plasma-activated water(PAW),as an extended form of cold atmospheric-pressure plasma,greatly expands the application of plasma-based technology.The biological effects of PAW are closely related to the aqueous reactive species,which can be regulated by the activation process.In this study,surface plasma-activated air(SAA)and a He+O_(2)plasma jet(Jet)were parallelly combined(the SAA+Jet combination)or sequentially combined(the SAA→Jet combination and the Jet→SAA combination)to prepare plasma-activated saline(PAS).The PAS activated by the combinations exhibited stronger bactericidal effects than that activated by the SAA or the Jet alone.The concentrations of H_(2)O_(2)and NO_(2)^(-)were higher in the PAS activated by the Jet→SAA combination,while ONOO^(-)concentrations were close in the three kinds of PAS and^(1)O_(2)concentrations were higher in the PAS activated by the SAA+Jet combination.The analysis of scavengers also demonstrated that H_(2)O_(2),^(1)O_(2),and ONOO^(-)in the PAS activated by the SAA+Jet combination,and^(1)O_(2)in the PAS activated by the Jet→SAA combination played critical roles in bactericidal effects.Further,the effective placement time of the three PAS varied,and the PAS activated by the Jet→SAA combination could also inactivate 2.6-log_(10)of MRSA cells after placement for more than 60 min.The regulation of reactive species in plasma-activated water via different combinations of plasma devices could improve the directional application of plasma-activated water in the biomedical field.

Air pressure law of a reservoir constructed in karst sinkholes

Karst sinkholes with natural negative landform provide favorable conditions for the pumped storage reservoir construction for less excavation work.However,the construction of the reservoir would plug the natural karst channels for water and air,which would cause remarkable air pressure in karst channels when the groundwater level fluctuates.A large laboratory simulation test was carried out to study the air pressure variation of a reservoir built on the karst sinkhole.The air pressure in the karst channel and inside the model was monitored during the groundwater rising and falling process.Result showed that the variation of air pressure in the karst channel and the surrounding rock exhibited a high degree of similarity.The air pressure increased rapidly at the initial stage of water level rising,followed by a slight decrease,then the air pressure increased sharply when the water level approached the top of the karst cave.The initial peak of air pressure and the final peak of air pressure were defined,and both air pressure peaks were linearly increasing with the water level rising rate.The negative air pressure was also analyzed during the drainage process,which was linearly correlated with the water level falling rate.The causes of air pressure variation in karst channels of a pumped storage reservoir built on the karst sinkhole were discussed.The initial rapid increase,then slight decrease and final sudden increase of air pressure were controlled by the combined effects of air compression in karst channel and air seepage into the surrounding rock.For the drainage process,the instant negative air pressure and gradual recovering of air pressure were controlled by the combined effects of negative air pressure induced by water level falling and air supply from surrounding rock.This work could provide valuable reference for the reservoir construction in karst area.

Analysis of the Erosion-Corrosion Mechanism of the Air Cooler in a Hydrocracking Unit:A Numerical and Experimental Study

Corrosion leakages often occur in the air cooler of a hydrocracking unit,with the failure sites mainly located in the entrance area of the tubes.An analysis of the macroscopic morphology and corrosion products confirmed that the damage was caused by erosion-corrosion(E-C).Numerical and experimental methods were applied to investigate the E-C mechanism in the air cooler.Computational fluid dynamics(CFD)was used to calculate the hydrodynamic parameters of the air cooler.The results showed that there was a biased flow in the air cooler,which led to a significant increase in velocity,turbulent kinetic energy and wall shear within 0.2 m of the tube entrance.A visualization experiment was then performed to determine the principles of migration and transformation of multiphase flow in the air cooler tubes.Various flow patterns(pure droplet flow,mist flow,and annular flow)and their evolutionary processes were clearly depicted experimentally.The initiation mechanism and processes leading to the development of E-C in the air cooler were also determined.This study provided a comprehensive explanation for the E-C failures that occur in air coolers during operation.

Block Incremental Dense Tucker Decomposition with Application to Spatial and Temporal Analysis of Air Quality Data

How can we efficiently store and mine dynamically generated dense tensors for modeling the behavior of multidimensional dynamic data?Much of the multidimensional dynamic data in the real world is generated in the form of time-growing tensors.For example,air quality tensor data consists of multiple sensory values gathered from wide locations for a long time.Such data,accumulated over time,is redundant and consumes a lot ofmemory in its raw form.We need a way to efficiently store dynamically generated tensor data that increase over time and to model their behavior on demand between arbitrary time blocks.To this end,we propose a Block IncrementalDense Tucker Decomposition(BID-Tucker)method for efficient storage and on-demand modeling ofmultidimensional spatiotemporal data.Assuming that tensors come in unit blocks where only the time domain changes,our proposed BID-Tucker first slices the blocks into matrices and decomposes them via singular value decomposition(SVD).The SVDs of the time×space sliced matrices are stored instead of the raw tensor blocks to save space.When modeling from data is required at particular time blocks,the SVDs of corresponding time blocks are retrieved and incremented to be used for Tucker decomposition.The factor matrices and core tensor of the decomposed results can then be used for further data analysis.We compared our proposed BID-Tucker with D-Tucker,which our method extends,and vanilla Tucker decomposition.We show that our BID-Tucker is faster than both D-Tucker and vanilla Tucker decomposition and uses less memory for storage with a comparable reconstruction error.We applied our proposed BID-Tucker to model the spatial and temporal trends of air quality data collected in South Korea from 2018 to 2022.We were able to model the spatial and temporal air quality trends.We were also able to verify unusual events,such as chronic ozone alerts and large fire events.

Factors Influencing the Spatial Variability of Air Temperature Urban Heat Island Intensity in Chinese Cities

Few studies have investigated the spatial patterns of the air temperature urban heat island(AUHI)and its controlling factors.In this study,the data generated by an urban climate model were used to investigate the spatial variations of the AUHI across China and the underlying climate and ecological drivers.A total of 355 urban clusters were used.We performed an attribution analysis of the AUHI to elucidate the mechanisms underlying its formation.The results show that the midday AUHI is negatively correlated with climate wetness(humid:0.34 K;semi-humid:0.50 K;semi-arid:0.73 K).The annual mean midnight AUHI does not show discernible spatial patterns,but is generally stronger than the midday AUHI.The urban–rural difference in convection efficiency is the largest contributor to the midday AUHI in the humid(0.32±0.09 K)and the semi-arid(0.36±0.11 K)climate zones.The release of anthropogenic heat from urban land is the dominant contributor to the midnight AUHI in all three climate zones.The rural vegetation density is the most important driver of the daytime and nighttime AUHI spatial variations.A spatial covariance analysis revealed that this vegetation influence is manifested mainly through its regulation of heat storage in rural land.

Comparative analysis of thermodynamic and mechanical responses between underground hydrogen storage and compressed air energy storage in lined rock caverns

Underground hydrogen storage(UHS)and compressed air energy storage(CAES)are two viable largescale energy storage technologies for mitigating the intermittency of wind and solar power.Therefore,it is meaningful to compare the properties of hydrogen and air with typical thermodynamic storage processes.This study employs a multi-physical coupling model to compare the operations of CAES and UHS,integrating gas thermodynamics within caverns,thermal conduction,and mechanical deformation around rock caverns.Gas thermodynamic responses are validated using additional simulations and the field test data.Temperature and pressure variations of air and hydrogen within rock caverns exhibit similarities under both adiabatic and diabatic simulation modes.Hydrogen reaches higher temperature and pressure following gas charging stage compared to air,and the ideal gas assumption may lead to overestimation of gas temperature and pressure.Unlike steel lining of CAES,the sealing layer(fibre-reinforced plastic FRP)in UHS is prone to deformation but can effectively mitigates stress in the sealing layer.In CAES,the first principal stress on the surface of the sealing layer and concrete lining is tensile stress,whereas UHS exhibits compressive stress in the same areas.Our present research can provide references for the selection of energy storage methods.

Surface air temperature change in the Wuyi Mountains,southeast China

Detecting changes in surface air temperature in mid-and low-altitude mountainous regions is essential for a comprehensive understanding of warming trend with altitude.We use daily surface air temperature data from 64 meteorological stations in Wuyi Mountains and its adjacent regions to analyze the spatio-temporal patterns of temperature change.The results show that Wuyi Mountains have experienced significant warming from 1961 to 2018.The warming trend of the mean temperature is 0.20℃/decade,the maximum temperature is 0.17℃/decade,and the minimum temperature is 0.26℃/decade.In 1961-1990,more than 63%of the stations showed a decreasing trend in annual mean temperature,mainly because the maximum temperature decreased during this period.However,in 1971-2000,1981-2010 and 1991-2018,the maximum,minimum and mean temperatures increased.The fastest increasing trend of mean temperature occurred in the southeastern coastal plains,the quickest increasing trend of maximum temperature occurred in the northwestern mountainous region,and the increase of minimum temperature occurred faster in the southeastern coastal and northwestern mountainous regions than that in the central area.Meanwhile,this study suggests that elevation does not affect warming in the Wuyi Mountains.These results are beneficial for understanding climate change in humid subtropical middle and low mountains.

Recent progress of self-supported air electrodes for flexible Zn-air batteries

Smart wearable devices are regarded to be the next prevailing technology product after smartphones and smart homes,and thus there has recently been rapid development in flexible electronic energy storage devices.Among them,flexible solid-state zinc-air batteries have received widespread attention because of their high energy density,good safety,and stability.Efficient bifunctional oxygen electrocatalysts are the primary consideration in the development of flexible solid-state zinc-air batteries,and self-supported air cathodes are strong candidates because of their advantages including simplified fabrication process,reduced interfacial resistance,accelerated electron transfer,and good flexibility.This review outlines the research progress in the design and construction of nanoarray bifunctional oxygen electrocatalysts.Starting from the configuration and basic principles of zinc-air batteries and the strategies for the design of bifunctional oxygen electrocatalysts,a detailed discussion of self-supported air cathodes on carbon and metal substrates and their uses in flexible zinc-air batteries will follow.Finally,the challenges and opportunities in the development of flexible zinc-air batteries will be discussed.

Audio-Text Multimodal Speech Recognition via Dual-Tower Architecture for Mandarin Air Traffic Control Communications

In air traffic control communications (ATCC), misunderstandings between pilots and controllers could result in fatal aviation accidents. Fortunately, advanced automatic speech recognition technology has emerged as a promising means of preventing miscommunications and enhancing aviation safety. However, most existing speech recognition methods merely incorporate external language models on the decoder side, leading to insufficient semantic alignment between speech and text modalities during the encoding phase. Furthermore, it is challenging to model acoustic context dependencies over long distances due to the longer speech sequences than text, especially for the extended ATCC data. To address these issues, we propose a speech-text multimodal dual-tower architecture for speech recognition. It employs cross-modal interactions to achieve close semantic alignment during the encoding stage and strengthen its capabilities in modeling auditory long-distance context dependencies. In addition, a two-stage training strategy is elaborately devised to derive semantics-aware acoustic representations effectively. The first stage focuses on pre-training the speech-text multimodal encoding module to enhance inter-modal semantic alignment and aural long-distance context dependencies. The second stage fine-tunes the entire network to bridge the input modality variation gap between the training and inference phases and boost generalization performance. Extensive experiments demonstrate the effectiveness of the proposed speech-text multimodal speech recognition method on the ATCC and AISHELL-1 datasets. It reduces the character error rate to 6.54% and 8.73%, respectively, and exhibits substantial performance gains of 28.76% and 23.82% compared with the best baseline model. The case studies indicate that the obtained semantics-aware acoustic representations aid in accurately recognizing terms with similar pronunciations but distinctive semantics. The research provides a novel modeling paradigm for semantics-aware speech recognition in air traffic control communications, which could contribute to the advancement of intelligent and efficient aviation safety management.

Optimal confrontation position selecting games model and its application to one-on-one air combat

In the air combat process,confrontation position is the critical factor to determine the confrontation situation,attack effect and escape probability of UAVs.Therefore,selecting the optimal confrontation position becomes the primary goal of maneuver decision-making.By taking the position as the UAV’s maneuver strategy,this paper constructs the optimal confrontation position selecting games(OCPSGs)model.In the OCPSGs model,the payoff function of each UAV is defined by the difference between the comprehensive advantages of both sides,and the strategy space of each UAV at every step is defined by its accessible space determined by the maneuverability.Then we design the limit approximation of mixed strategy Nash equilibrium(LAMSNQ)algorithm,which provides a method to determine the optimal probability distribution of positions in the strategy space.In the simulation phase,we assume the motions on three directions are independent and the strategy space is a cuboid to simplify the model.Several simulations are performed to verify the feasibility,effectiveness and stability of the algorithm.

An Analysis of Specific Categories of Birth Defects and Developmental Disabilities for Children of Participants of the Air Force Health Study

Background: The Air Force Health Study collected reproductive outcomes for live-born children of male Air Force veterans of the Vietnam War. Methods: Dioxin values for participants were obtained from blood samples. Analyses were conducted of occurrence of 16 specific categories of birth defects and developmental disabilities. Children were categorized as conceived before and after the start of participants’ Vietnam War service. Children conceived before the start of Vietnam War service were treated as being conceived when their fathers had unquantifiable dioxin values. Children conceived after the start of Vietnam War service for participants with missing dioxin values were excluded from primary analyses, but were used to assess the impact of their exclusion on conclusions. Correlation between values for specific categories for multiple children fathered by the same participant was accounted for. The dose-response relationship was treated as a step function increasing for dioxin values larger than adaptively identified individual thresholds changing with the specific category. Results: For 15 of 16 specific categories, the probability of occurrence increased substantially for a sufficiently high dioxin level above identified thresholds. Exclusion of children due to missing dioxin likely did not affect these results. Conclusions: Results supported the conclusion of substantial adverse effects on a wide variety of specific categories of birth defects and developmental disabilities due to sufficiently high exposures to dioxin, a toxic contaminant of Agent Orange used for herbicide spraying in the Vietnam War. Results may hold more generally, but might also have been affected by a variety of limitations.

A novel nano-grade organosilicon polymer:Improving airtightness of compressed air energy storage in hard rock formations

Enhancing cavern sealing is crucial for improving the efficiency of compressed air energy storage(CAES)in hard rock formations.This study introduced a novel approach using a nano-grade organosilicon polymer(NOSP)as a sealant,coupled with an air seepage evaluation model that incorporates Knudsen diffusion.Moreover,the initial coating application methods were outlined,and the advantages of using NOSP compared to other sealing materials,particularly regarding cost and construction techniques,were also examined and discussed.Experimental results indicated a significant reduction in permeability of rock specimens coated with a 7–10μm thick NOSP layer.Specifically,under a 0.5 MPa pulse pressure,the permeability decreased to less than 1 n D,and under a 4 MPa pulse pressure,it ranged between4.5×10^(-6)–5.5×10^(-6)m D,marking a 75%–80%decrease in granite permeability.The sealing efficacy of NOSP surpasses concrete and is comparable to rubber materials.The optimal viscosity for application lies between 95 and 105 KU,and the coating thickness should ideally range from 7 to 10μm,applied to substrates with less than 3%porosity.This study provides new insights into air transport and sealing mechanisms at the pore level,proposing NOSP as a cost-effective and simplified solution for CAES applications.

The Influence of Air Pollution Concentrations on Solar Irradiance Forecasting Using CNN-LSTM-mRMR Feature Extraction

Maintaining a steady power supply requires accurate forecasting of solar irradiance,since clean energy resources do not provide steady power.The existing forecasting studies have examined the limited effects of weather conditions on solar radiation such as temperature and precipitation utilizing convolutional neural network(CNN),but no comprehensive study has been conducted on concentrations of air pollutants along with weather conditions.This paper proposes a hybrid approach based on deep learning,expanding the feature set by adding new air pollution concentrations,and ranking these features to select and reduce their size to improve efficiency.In order to improve the accuracy of feature selection,a maximum-dependency and minimum-redundancy(mRMR)criterion is applied to the constructed feature space to identify and rank the features.The combination of air pollution data with weather conditions data has enabled the prediction of solar irradiance with a higher accuracy.An evaluation of the proposed approach is conducted in Istanbul over 12 months for 43791 discrete times,with the main purpose of analyzing air data,including particular matter(PM10 and PM25),carbon monoxide(CO),nitric oxide(NOX),nitrogen dioxide(NO_(2)),ozone(O₃),sulfur dioxide(SO_(2))using a CNN,a long short-term memory network(LSTM),and MRMR feature extraction.Compared with the benchmark models with root mean square error(RMSE)results of 76.2,60.3,41.3,32.4,there is a significant improvement with the RMSE result of 5.536.This hybrid model presented here offers high prediction accuracy,a wider feature set,and a novel approach based on air concentrations combined with weather conditions for solar irradiance prediction.

Cluster DetectionMethod of Endogenous Security Abnormal Attack Behavior in Air Traffic Control Network

In order to enhance the accuracy of Air Traffic Control(ATC)cybersecurity attack detection,in this paper,a new clustering detection method is designed for air traffic control network security attacks.The feature set for ATC cybersecurity attacks is constructed by setting the feature states,adding recursive features,and determining the feature criticality.The expected information gain and entropy of the feature data are computed to determine the information gain of the feature data and reduce the interference of similar feature data.An autoencoder is introduced into the AI(artificial intelligence)algorithm to encode and decode the characteristics of ATC network security attack behavior to reduce the dimensionality of the ATC network security attack behavior data.Based on the above processing,an unsupervised learning algorithm for clustering detection of ATC network security attacks is designed.First,determine the distance between the clustering clusters of ATC network security attack behavior characteristics,calculate the clustering threshold,and construct the initial clustering center.Then,the new average value of all feature objects in each cluster is recalculated as the new cluster center.Second,it traverses all objects in a cluster of ATC network security attack behavior feature data.Finally,the cluster detection of ATC network security attack behavior is completed by the computation of objective functions.The experiment took three groups of experimental attack behavior data sets as the test object,and took the detection rate,false detection rate and recall rate as the test indicators,and selected three similar methods for comparative test.The experimental results show that the detection rate of this method is about 98%,the false positive rate is below 1%,and the recall rate is above 97%.Research shows that this method can improve the detection performance of security attacks in air traffic control network.