The key parameters that characterize the morphological quality of multi-layer and multi-pass metal laser deposited parts are the surface roughness and the error between the actual printing height and the theoretical m...The key parameters that characterize the morphological quality of multi-layer and multi-pass metal laser deposited parts are the surface roughness and the error between the actual printing height and the theoretical model height.The Taguchi method was employed to establish the correlations between process parameter combinations and multi-objective characterization of metal deposition morphology(height error and roughness).Results show that using the signal-to-noise ratio and grey relational analysis,the optimal parameter combination for multi-layer and multi-pass deposition is determined as follows:laser power of 800 W,powder feeding rate of 0.3 r/min,step distance of 1.6 mm,and scanning speed of 20 mm/s.Subsequently,a Genetic Bayesian-back propagation(GB-BP)network is constructed to predict multi-objective responses.Compared with the traditional back propagation network,the GB-back propagation network improves the prediction accuracy of height error and surface roughness by 43.14%and 71.43%,respectively.This network can accurately predict the multi-objective characterization of morphological quality of multi-layer and multi-pass metal deposited parts.展开更多
To ensure an uninterrupted power supply,mobile power sources(MPS)are widely deployed in power grids during emergencies.Comprising mobile emergency generators(MEGs)and mobile energy storage systems(MESS),MPS are capabl...To ensure an uninterrupted power supply,mobile power sources(MPS)are widely deployed in power grids during emergencies.Comprising mobile emergency generators(MEGs)and mobile energy storage systems(MESS),MPS are capable of supplying power to critical loads and serving as backup sources during grid contingencies,offering advantages such as flexibility and high resilience through electricity delivery via transportation networks.This paper proposes a design method for a 400 V–10 kV Dual-Winding Induction Generator(DWIG)intended for MEG applications,employing an improved particle swarmoptimization(PSO)algorithmbased on a back-propagation neural network(BPNN).A parameterized finite element(FE)model of the DWIG is established to derive constraints on its dimensional parameters,thereby simplifying the optimization space.Through sensitivity analysis between temperature rise and electromagnetic loss of the DWIG,the main factors influencing the machine’s temperature are identified,and electromagnetic loss is determined as the optimization objective.To obtain an accurate fitting function between electromagnetic loss and dimensional parameters,the BPNN is employed to predict the nonlinear relationship between the optimization objective and the parameters.The Latin hypercube sampling(LHS)method is used for random sampling in the FE model analysis for training,testing,and validation,which is then applied to compute the cost function in the PSO.Based on the relationships obtained by the BPNN,the PSO algorithm evaluates the fitness and cost functions to determine the optimal design point.The proposed optimization method is validated by comparing simulation results between the initial design and the optimized design.展开更多
Unmanned combat aerial vehicles require lightweight,stealth-capable exhaust systems.However,traditional metallic nozzles increase radar detectability and reduce range,while advanced composites offer high performance b...Unmanned combat aerial vehicles require lightweight,stealth-capable exhaust systems.However,traditional metallic nozzles increase radar detectability and reduce range,while advanced composites offer high performance but are expensive.Therefore,to improve the operational range and survivability of unmanned combat aerial vehicles,a lightweight,high-temperature-resistant,oxidation-resistant,and low-observable composite exhaust nozzle is developed to replace conventional metallic straight-type nozzles.The nozzle features a double serpentine shape to reduce radar and infrared signatures and is manufactured as a monolithic structure using the filament winding process,accommodating the complex geometry and large size(length:1.8 m,width:0.8 m).The exhaust nozzle consists of a ceramic matrix composite made of silicon carbide fibers and a silicon oxycarbide matrix,which absorbs and scatters radio frequency signals while withstanding prolonged exposure to high-temperature(700℃)oxidizing environments typical of engine exhaust gases.The polysiloxane resin used to produce the silicon oxycarbide matrix poses significant challenges owing to its low tackiness and high viscosity variations depending on the presence of nanoparticles,making filament winding difficult.These challenges are addressed by optimizing resin viscosity and winding pattern design.As a result,the tensile strength of the composite specimens fabricated with the optimized viscosity increases by 228.03% before pyrolysis and 97.68%after pyrolysis,compared with that of the non-optimized specimens.In addition,the density and tensile strength of the composite processed via three cycles of polymer infiltration and pyrolysis increased by 13.08% and 80.37%,respectively,compared to those of the non-densified composite.High-temperature oxidation and flame tests demonstrate exceptional thermal and oxidative stability.Furthermore,when compared with carbon fiber-reinforced ceramic matrix composites,the developed composite exhibits a permittivity at least two levels lower and a reflection loss below7 dB within the frequency range of 9.3-10.9 GHz,underscoring its superior electromagnetic stealth performance.展开更多
At present,the emerging solid-phase friction-based additive manufacturing technology,including friction rolling additive man-ufacturing(FRAM),can only manufacture simple single-pass components.In this study,multi-laye...At present,the emerging solid-phase friction-based additive manufacturing technology,including friction rolling additive man-ufacturing(FRAM),can only manufacture simple single-pass components.In this study,multi-layer multi-pass FRAM-deposited alumin-um alloy samples were successfully prepared using a non-shoulder tool head.The material flow behavior and microstructure of the over-lapped zone between adjacent layers and passes during multi-layer multi-pass FRAM deposition were studied using the hybrid 6061 and 5052 aluminum alloys.The results showed that a mechanical interlocking structure was formed between the adjacent layers and the adja-cent passes in the overlapped center area.Repeated friction and rolling of the tool head led to different degrees of lateral flow and plastic deformation of the materials in the overlapped zone,which made the recrystallization degree in the left and right edge zones of the over-lapped zone the highest,followed by the overlapped center zone and the non-overlapped zone.The tensile strength of the overlapped zone exceeded 90%of that of the single-pass deposition sample.It is proved that although there are uneven grooves on the surface of the over-lapping area during multi-layer and multi-pass deposition,they can be filled by the flow of materials during the deposition of the next lay-er,thus ensuring the dense microstructure and excellent mechanical properties of the overlapping area.The multi-layer multi-pass FRAM deposition overcomes the limitation of deposition width and lays the foundation for the future deposition of large-scale high-performance components.展开更多
With the development of high-frequency and highvoltagetraction machines(TM)incorporating hairpin windings(HW)and SiC inverters for electric vehicles(EV),both theinterturn voltage stress and temperature within HW are r...With the development of high-frequency and highvoltagetraction machines(TM)incorporating hairpin windings(HW)and SiC inverters for electric vehicles(EV),both theinterturn voltage stress and temperature within HW are rising,increasing the risk of partial discharge(PD),and presentingsignificant challenges to insulation safety.Therefore,this paperaddresses this issue and proposes potential solutions.Firstly,thepaper examines an 8-pole,48-slot,6-layer HW TM to highlightthe unique characteristics of this winding structure,and explainsthe uneven distribution of interturn voltage stress andtemperature.Subsequently,a high-frequency equivalent circuitmodel of the HW TM prototype is developed.The error ofsimulation and experiment is only 5.7%,which proves theaccuracy of the model.Then,an improved HW scheme isproposed to lower the maximum voltage stress by 29.3%.Furthermore,the temperature distribution of HW TM isanalyzed to facilitate a detailed examination of the impact oftemperature on insulation PD.Finally,the partial dischargeinception voltage(PDIV)of interturn insulation,consideringtemperature effects,is calculated and verified throughexperiment.The paper proposes a reliability-oriented designmethod and process for HW TM.It demonstrates that thereliability-oriented design can achieve PD-free performance inthe design stage of HW.展开更多
High-speed permanent magnet synchronous motors(PMSMs)have recently been widely applied in various applications.However,due to the increased rotor speed and operating frequency increase,the winding AC losses rise subst...High-speed permanent magnet synchronous motors(PMSMs)have recently been widely applied in various applications.However,due to the increased rotor speed and operating frequency increase,the winding AC losses rise substantially,posing risks to the safety operation.Accurate modeling of the AC losses has therefore become critical at the motor initial design stage.This paper reviews the main modeling methods for AC copper losses in PMSMs,including analytical methods,finite element methods,and hybrid modeling methods.The advantages and disadvantages of each method are analyzed in detail,and key issues in the modeling process are discussed.Finally,future research directions in AC copper loss modeling are explored,providing new insights for motor design and performance optimization.展开更多
The huge impact kinetic energy cannot be quickly dissipated by the energy-absorbing structure and transferred to the other vehicle through the car body structure,which will cause structural damage and threaten the liv...The huge impact kinetic energy cannot be quickly dissipated by the energy-absorbing structure and transferred to the other vehicle through the car body structure,which will cause structural damage and threaten the lives of the occupants.Therefore,it is necessary to understand the laws of energy conversion,dissipation and transfer during train collisions.This study proposes a multi-layer progressive analysis method of energy flow during train collisions,considering the characteristics of the train.In this method,the train collision system is divided into conversion,dissipation,and transfer layers from the perspective of the train,collision interface,and car body structure to analyze the energy conversion,dissipation and transfer characteristics.Taking the collision process of a rail train as an example,a train collision energy transfer path analysis model was established based on power flow theory.The results show that when the maximum mean acceleration of the vehicle meets the standard requirements,the jerk may exceed the allowable limit of the human body,and there is a risk of injury to the occupants of a secondary collision.The decay rate of the collision energy along the direction of train operation reaches 79%.As the collision progresses,the collision energy gradually converges in the structure with holes,and the structure deforms when the gathered energy is greater than the maximum energy the structure can withstand.The proposed method helps to understand the train collision energy flow law and provides theoretical support for the train crashworthiness design in the future.展开更多
The growing incidence of cyberattacks necessitates a robust and effective Intrusion Detection Systems(IDS)for enhanced network security.While conventional IDSs can be unsuitable for detecting different and emerging at...The growing incidence of cyberattacks necessitates a robust and effective Intrusion Detection Systems(IDS)for enhanced network security.While conventional IDSs can be unsuitable for detecting different and emerging attacks,there is a demand for better techniques to improve detection reliability.This study introduces a new method,the Deep Adaptive Multi-Layer Attention Network(DAMLAN),to boost the result of intrusion detection on network data.Due to its multi-scale attention mechanisms and graph features,DAMLAN aims to address both known and unknown intrusions.The real-world NSL-KDD dataset,a popular choice among IDS researchers,is used to assess the proposed model.There are 67,343 normal samples and 58,630 intrusion attacks in the training set,12,833 normal samples,and 9711 intrusion attacks in the test set.Thus,the proposed DAMLAN method is more effective than the standard models due to the consideration of patterns by the attention layers.The experimental performance of the proposed model demonstrates that it achieves 99.26%training accuracy and 90.68%testing accuracy,with precision reaching 98.54%on the training set and 96.64%on the testing set.The recall and F1 scores again support the model with training set values of 99.90%and 99.21%and testing set values of 86.65%and 91.37%.These results provide a strong basis for the claims made regarding the model’s potential to identify intrusion attacks and affirm its relatively strong overall performance,irrespective of type.Future work would employ more attempts to extend the scalability and applicability of DAMLAN for real-time use in intrusion detection systems.展开更多
In practical engineering construction,multi-layered barriers containing geomembranes are extensively applied to retard the migration of pollutants.However,the associated analytical theory on pollutants diffusion still...In practical engineering construction,multi-layered barriers containing geomembranes are extensively applied to retard the migration of pollutants.However,the associated analytical theory on pollutants diffusion still needs to be further improved.In this work,general analytical solutions are derived for one-dimensional diffusion of degradable organic contaminant(DOC)in the multi-layered media containing geomembranes under a time-varying concentration boundary condition,where the variable substitution and separated variable approaches are employed.These analytical solutions with clear expressions can be used not only to study the diffusion behaviors of DOC in bottom and vertical composite barrier systems,but also to verify other complex numerical models.The proposed general analytical solutions are then fully validated via three comparative analyses,including comparisons with the experimental measurements,an existing analytical solution,and a finite-difference solution.Ultimately,the influences of different factors on the composite cutoff wall’s(CCW,which consists of two soil-bentonite layers and a geomembrane)service performance are investigated through a composite vertical barrier system as the application example.The findings obtained from this investigation can provide scientific guidance for the barrier performance evaluation and the engineering design of CCWs.This application example also exhibits the necessity and effectiveness of the developed analytical solutions.展开更多
Transportation structures such as composite pavements and railway foundations typically consist of multi-layered media designed to withstand high bearing capacity.A theoretical understanding of load transfer mechanism...Transportation structures such as composite pavements and railway foundations typically consist of multi-layered media designed to withstand high bearing capacity.A theoretical understanding of load transfer mechanisms in these multi-layer composites is essential,as it offers intuitive insights into parametric influences and facilitates enhanced structural performance.This paper employs an improved transfer matrix method to address the limitations of existing theoretical approaches for analyzing multi-layer composite structures.By establishing a twodimensional composite pavement model,it investigates load transfer characteristics and validates the accuracy through finite element simulation.The proposed method offers a straightforward analytical approach for examining internal interactions between structural layers.Case studies indicate that the concrete surface layer is the main load-bearing layer for most vertical normal and shear stresses.The soil base layer reduces the overall mechanical response of the substructure,while horizontal actions increase the risk of interfacial slip and cracking.Structural optimization analysis demonstrates that increasing the thickness of the concrete surface layer,enhancing the thickness and stiffness of the soil base layer,or incorporating gradient layers can significantly mitigate these risks of interfacial slip and cracking.The findings of this study can guide the optimization design,parameter analysis,and damage prevention of multi-layer composite structures.展开更多
This study proposes a general imperfect thermal contact model to predict the thermal contact resistance at the interface among multi-layered composite structures.Based on the Green-Lindsay(GL)thermoelastic theory,semi...This study proposes a general imperfect thermal contact model to predict the thermal contact resistance at the interface among multi-layered composite structures.Based on the Green-Lindsay(GL)thermoelastic theory,semi analytical solutions of temperature increment and displacement of multi-layered composite structures are obtained by using the Laplace transform method,upon which the effects of thermal resistance coefficient,partition coefficient,thermal conductivity ratio and heat capacity ratio on the responses are studied.The results show that the generalized imperfect thermal contact model can realistically describe the imperfect thermal contact problem.Accordingly,it may degenerate into other thermal contact models by adjusting the thermal resistance coefficient and partition coefficient.展开更多
Low Earth Orbit(LEO)mega-constellation networks,exemplified by Starlink,are poised to play a pivotal role in future mobile communication networks,due to their low latency and high capacity.With the massively deployed ...Low Earth Orbit(LEO)mega-constellation networks,exemplified by Starlink,are poised to play a pivotal role in future mobile communication networks,due to their low latency and high capacity.With the massively deployed satellites,ground users now can be covered by multiple visible satellites,but also face complex handover issues with such massive high-mobility satellites in multi-layer.The end-to-end routing is also affected by the handover behavior.In this paper,we propose an intelligent handover strategy dedicated to multi-layer LEO mega-constellation networks.Firstly,an analytic model is utilized to rapidly estimate the end-to-end propagation latency as a key handover factor to construct a multi-objective optimization model.Subsequently,an intelligent handover strategy is proposed by employing the Dueling Double Deep Q Network(D3QN)-based deep reinforcement learning algorithm for single-layer constellations.Moreover,an optimal crosslayer handover scheme is proposed by predicting the latency-jitter and minimizing the cross-layer overhead.Simulation results demonstrate the superior performance of the proposed method in the multi-layer LEO mega-constellation,showcasing reductions of up to 8.2%and 59.5%in end-to-end latency and jitter respectively,when compared to the existing handover strategies.展开更多
A numerical method to predict the bursting strength of filament wound composite rocket motor case is proposed here.This method can evaluate the longitudinal stress evolution of each composite layer as impregnated fila...A numerical method to predict the bursting strength of filament wound composite rocket motor case is proposed here.This method can evaluate the longitudinal stress evolution of each composite layer as impregnated filaments with fiber tension are wound layer by layer,and consider the effects of accumulated stress and deformation during filament winding on the bursting strength of composite case.Taking∅520 mm composite cases as a case study,the filament-winding-process-induced stress and deformation as well as progressive damage behavior are numerically predicted,followed by a comparison with experimental results.The numerical results show that the predicted bursting pressures for composite cases manufactured on the mandrels with and without a flexible component are 14.20 MPa and 21.40 MPa,respectively.These values exhibit slight deviation from the measured pressures of 13.50 MPa and 21.57 MPa.Moreover,the predicted damage locations,situated respectively in the dome and cylinder,agree well with the experimental observation.These observations indicate that use of flexible component reduces the load-bearing capacity of the domes.Furthermore,it validates the reliability and accuracy of the proposed numerical method in predicting the bursting strength of composite cases.展开更多
Stab-resistant textiles play a critical role in personal protection,necessitating a deeper understanding of how structural and layering factors influence their performance.The current study experimentally examines the...Stab-resistant textiles play a critical role in personal protection,necessitating a deeper understanding of how structural and layering factors influence their performance.The current study experimentally examines the effects of textile structure,layering,and ply orientation on the stab resistance of multi-layer textiles.Three 3D warp interlock(3DWI)structures({f1},{f2},{f3})and a 2D woven fabric({f4}),all made of high-performance p-aramid yarns,were engineered and manufactured.Multi-layer specimens were prepared and subjected to drop-weight stabbing tests following HOSBD standards.Stabbing performance metrics,including Depth of Trauma(DoT),Depth of Penetration(DoP),and trauma deformation(Ymax,Xmax),were investigated and analyzed.Statistical analyses(Two-and One-Way ANOVA)indicated that fabric type and layer number significantly impacted DoP(P<0.05),while ply orientation significantly affected DoP(P<0.05)but not DoT(P>0.05).Further detailed analysis revealed that 2D woven fabrics exhibited greater trauma deformation than 3D WIF structures.Increasing the number of layers reduced both DoP and DoT across all fabric structures,with f3 demonstrating the best performance in multi-layer configurations.Aligned ply orientations also enhanced stab resistance,underscoring the importance of alignment in dissipating impact energy.展开更多
The world’s most powerful offshore wind turbine has begun feeding electricity into the grid off the coast of southeast China,marking a major technological leap in the country’s wind power industry.The colossal turbi...The world’s most powerful offshore wind turbine has begun feeding electricity into the grid off the coast of southeast China,marking a major technological leap in the country’s wind power industry.The colossal turbine,developed and installed by China Three Gorges Corp.(CTG),is located in the Phase II Liuao offshore wind farm,more than 30 km off the coast of Fujian in waters deeper than 40 metres.The 20-mw unit successfully completed commissioning and started operation on 5 February,CTG announced.展开更多
In permanent magnet synchronous machine(PMSM) drives, temperature information is critical to achieve reliable and high-performance control. The popular model-based estimation methods are based on extracting temperatur...In permanent magnet synchronous machine(PMSM) drives, temperature information is critical to achieve reliable and high-performance control. The popular model-based estimation methods are based on extracting temperature dependent terms from the voltages using the machine model. The estimation accuracy under low speed or load can be greatly affected by the model uncertainty and noise due to low signal-tonoise ratio. This paper presents a high frequency(HF) position offset injection-based winding and permanent magnet(PM) temperature decoupled estimation approach for PMSMs to achieve accurate and robust temperature estimation among a wide speed range especially under low-speed conditions. In the proposed approach, a small HF position offset is injected into the machine to construct a decoupled winding and PM temperature estimation model, in which the winding and PM temperatures are independently estimated from HF excitations. The temperature estimation is independent from the fundamental model and parameter variation, and it achieves high signal-tonoise ratio under low-speed conditions. Moreover, the temperature estimation is also not affected by magnetic saturation and inverter distortion, which can improve the accuracy and robustness of temperature estimation. The proposed approach is validated with experiments and comparisons on a laboratory machine under various operating conditions.展开更多
Wind turbine blade defect detection faces persistent challenges in separating small,low-contrast surface faults from complex backgrounds while maintaining reliability under variable illumination and viewpoints.Conven-...Wind turbine blade defect detection faces persistent challenges in separating small,low-contrast surface faults from complex backgrounds while maintaining reliability under variable illumination and viewpoints.Conven-tional image-processing pipelines struggle with scalability and robustness,and recent deep learning methods remain sensitive to class imbalance and acquisition variability.This paper introduces TurbineBladeDetNet,a convolutional architecture combining dual-attention mechanisms with multi-path feature extraction for detecting five distinct blade fault types.Our approach employs both channel-wise and spatial attention modules alongside an Albumentations-driven augmentation strategy to handle dataset imbalance and capture condition variability.The model achieves 97.14%accuracy,98.65%precision,and 98.68%recall,yielding a 98.66%F1-score with 0.0110 s inference time.Class-specific analysis shows uniformly high sensitivity and specificity;lightning damage reaches 99.80%for sensitivity,precision,and F1-score,and crack achieves perfect precision and specificity with a 98.94%F1-score.Comparative evaluation against recent wind-turbine inspection approaches indicates higher performance in both accuracy and F1-score.The resulting balance of sensitivity and specificity limits both missed defects and false alarms,supporting reliable deployment in routine unmanned aerial vehicle(UAV)inspection.展开更多
Paying an additional RMB 2 could have your next milk tea delivered by drone to your balcony in just five minutes.This small fee represents the vast potential of the trillion-yuan lowaltitude economy.
Although wind energy is volatile,the output of a wind-storage plant is partially dispatchable,making it a promising paradigm on the generation side.A grid-friendly wind-storage plant ought to be able to continuously o...Although wind energy is volatile,the output of a wind-storage plant is partially dispatchable,making it a promising paradigm on the generation side.A grid-friendly wind-storage plant ought to be able to continuously output the desired power over a certain period of time.This paper proposes a dependable dynamic capacity provision scheme of a wind-storage plant over a daily horizon.It stipulates a minimum number of periods during which the committed capacity must be fulfilled and a maximum mismatch during the remaining periods when the desired power output is not achievable.In the general case,the day-ahead piecewise constant capacity provision results in a two-stage stochastic program formulated as a mixed-integer linear program.Specifically,for constant capacity provision,a decomposition algorithm is developed to determine the global optimal solution,and the complexity grows linearly with the number of scenarios.Given the committed capacity trajectory,the real-time operation problem is modeled as a four-state stochastic dynamic program.The discrete state-action values are derived recursively via the principle of optimality.Real-time dispatch actions are generated by using the action-value tabular leveraging inexact ultra-short-term forecasts.Numerical tests over one year demonstrate that the proposed method successfully fulfills reliable operation on 355 days and achieve an optimality gap of 9.47%compared with the ex-post optimum,which is comparable to model predictive control using exact 2–3-hour-ahead wind power forecasts.展开更多
Cyperus esculentus(C.esculentus),a desert-adapted plant species with both ecological and economic value,has been widely cultivated in northern China's sandy regions.However,limited studies have investigated the pe...Cyperus esculentus(C.esculentus),a desert-adapted plant species with both ecological and economic value,has been widely cultivated in northern China's sandy regions.However,limited studies have investigated the performance of composite shelterbelts that integrate C.esculentus.This study systematically evaluated five shelterbelt models—Populus euphratica(P.euphratica),P.euphratica–C.esculentus composite,P.euphratica–nylon net–C.esculentus composite,Tamarix chinensis(T.chinensis),and T.chinensis–C.esculentus composite—using wind tunnel experiments and field observations.Sediment flux was measured at a normalized downwind distance(x/h)of 5,where x refers to the distance from the front edge(upwind side)of the shelterbelt for upwind measurements,and the distance from the rear edge(downwind side)for downwind measurements,and h represents the canopy height.Wind velocity was measured at x/h of–2,–1,1,2,3,5,and 7,and sand flux was measured at x/h=5,under initial wind velocities of 8.0 and 12.0 m/s.The results indicated that the P.euphratica–nylon net–C.esculentus composite was the most effective in reducing wind velocity,followed by the P.euphratica–C.esculentus composite.In contrast,the P.euphratica and T.chinensis exhibited relatively weaker wind reduction capabilities.Regarding sand flux,under moderate wind velocity(8.0 m/s),both the P.euphratica–C.esculentus composite and P.euphratica–nylon net–C.esculentus composite demonstrated the lowest sand flux values.However,under high wind velocity(12.0 m/s),the P.euphratica–nylon net–C.esculentus composite significantly outperformed the other shelterbelt models in sand retention,highlighting its superior windbreak and sand fixation efficacy.Field observations further validated the windbreak and sand fixation effects of C.esculentus.Comparisons between the bare sand plot and C.esculentus plot within protective forests demonstrated that planting C.esculentus can provide substantial ecological benefits in windbreak and sand-fixation.These findings,reinforced by field observations,strengthen the wind tunnel experiment results and highlight the critical role of C.esculentus in enhancing the performance of composite shelterbelts for desert ecological restoration.展开更多
基金National Natural Science Foundation of China(52175237)。
文摘The key parameters that characterize the morphological quality of multi-layer and multi-pass metal laser deposited parts are the surface roughness and the error between the actual printing height and the theoretical model height.The Taguchi method was employed to establish the correlations between process parameter combinations and multi-objective characterization of metal deposition morphology(height error and roughness).Results show that using the signal-to-noise ratio and grey relational analysis,the optimal parameter combination for multi-layer and multi-pass deposition is determined as follows:laser power of 800 W,powder feeding rate of 0.3 r/min,step distance of 1.6 mm,and scanning speed of 20 mm/s.Subsequently,a Genetic Bayesian-back propagation(GB-BP)network is constructed to predict multi-objective responses.Compared with the traditional back propagation network,the GB-back propagation network improves the prediction accuracy of height error and surface roughness by 43.14%and 71.43%,respectively.This network can accurately predict the multi-objective characterization of morphological quality of multi-layer and multi-pass metal deposited parts.
基金funded by the Science and Technology Projects of State Grid Corporation of China(Project No.J2024136).
文摘To ensure an uninterrupted power supply,mobile power sources(MPS)are widely deployed in power grids during emergencies.Comprising mobile emergency generators(MEGs)and mobile energy storage systems(MESS),MPS are capable of supplying power to critical loads and serving as backup sources during grid contingencies,offering advantages such as flexibility and high resilience through electricity delivery via transportation networks.This paper proposes a design method for a 400 V–10 kV Dual-Winding Induction Generator(DWIG)intended for MEG applications,employing an improved particle swarmoptimization(PSO)algorithmbased on a back-propagation neural network(BPNN).A parameterized finite element(FE)model of the DWIG is established to derive constraints on its dimensional parameters,thereby simplifying the optimization space.Through sensitivity analysis between temperature rise and electromagnetic loss of the DWIG,the main factors influencing the machine’s temperature are identified,and electromagnetic loss is determined as the optimization objective.To obtain an accurate fitting function between electromagnetic loss and dimensional parameters,the BPNN is employed to predict the nonlinear relationship between the optimization objective and the parameters.The Latin hypercube sampling(LHS)method is used for random sampling in the FE model analysis for training,testing,and validation,which is then applied to compute the cost function in the PSO.Based on the relationships obtained by the BPNN,the PSO algorithm evaluates the fitness and cost functions to determine the optimal design point.The proposed optimization method is validated by comparing simulation results between the initial design and the optimized design.
基金supported by the Agency for Defense Development Grant Funded by the Korean Government(Grant No.912822501).
文摘Unmanned combat aerial vehicles require lightweight,stealth-capable exhaust systems.However,traditional metallic nozzles increase radar detectability and reduce range,while advanced composites offer high performance but are expensive.Therefore,to improve the operational range and survivability of unmanned combat aerial vehicles,a lightweight,high-temperature-resistant,oxidation-resistant,and low-observable composite exhaust nozzle is developed to replace conventional metallic straight-type nozzles.The nozzle features a double serpentine shape to reduce radar and infrared signatures and is manufactured as a monolithic structure using the filament winding process,accommodating the complex geometry and large size(length:1.8 m,width:0.8 m).The exhaust nozzle consists of a ceramic matrix composite made of silicon carbide fibers and a silicon oxycarbide matrix,which absorbs and scatters radio frequency signals while withstanding prolonged exposure to high-temperature(700℃)oxidizing environments typical of engine exhaust gases.The polysiloxane resin used to produce the silicon oxycarbide matrix poses significant challenges owing to its low tackiness and high viscosity variations depending on the presence of nanoparticles,making filament winding difficult.These challenges are addressed by optimizing resin viscosity and winding pattern design.As a result,the tensile strength of the composite specimens fabricated with the optimized viscosity increases by 228.03% before pyrolysis and 97.68%after pyrolysis,compared with that of the non-optimized specimens.In addition,the density and tensile strength of the composite processed via three cycles of polymer infiltration and pyrolysis increased by 13.08% and 80.37%,respectively,compared to those of the non-densified composite.High-temperature oxidation and flame tests demonstrate exceptional thermal and oxidative stability.Furthermore,when compared with carbon fiber-reinforced ceramic matrix composites,the developed composite exhibits a permittivity at least two levels lower and a reflection loss below7 dB within the frequency range of 9.3-10.9 GHz,underscoring its superior electromagnetic stealth performance.
基金supported by the National Key Research and Development Program of China(No.2022YFB3404700)the National Natural Science Foundation of China(Nos.52105313 and 52275299)+2 种基金the Research and Development Program of Beijing Municipal Education Commission,China(No.KM202210005036)the Natural Science Foundation of Chongqing,China(No.CSTB2023NSCQ-MSX0701)the National Defense Basic Research Projects of China(No.JCKY2022405C002).
文摘At present,the emerging solid-phase friction-based additive manufacturing technology,including friction rolling additive man-ufacturing(FRAM),can only manufacture simple single-pass components.In this study,multi-layer multi-pass FRAM-deposited alumin-um alloy samples were successfully prepared using a non-shoulder tool head.The material flow behavior and microstructure of the over-lapped zone between adjacent layers and passes during multi-layer multi-pass FRAM deposition were studied using the hybrid 6061 and 5052 aluminum alloys.The results showed that a mechanical interlocking structure was formed between the adjacent layers and the adja-cent passes in the overlapped center area.Repeated friction and rolling of the tool head led to different degrees of lateral flow and plastic deformation of the materials in the overlapped zone,which made the recrystallization degree in the left and right edge zones of the over-lapped zone the highest,followed by the overlapped center zone and the non-overlapped zone.The tensile strength of the overlapped zone exceeded 90%of that of the single-pass deposition sample.It is proved that although there are uneven grooves on the surface of the over-lapping area during multi-layer and multi-pass deposition,they can be filled by the flow of materials during the deposition of the next lay-er,thus ensuring the dense microstructure and excellent mechanical properties of the overlapping area.The multi-layer multi-pass FRAM deposition overcomes the limitation of deposition width and lays the foundation for the future deposition of large-scale high-performance components.
基金supported by the Project of National Natural Science Foundation of China under Grant 52407060 and 52422704supported by Liaoning Province science and technology plan doctoral project under Grant 2023-BSBA-255.
文摘With the development of high-frequency and highvoltagetraction machines(TM)incorporating hairpin windings(HW)and SiC inverters for electric vehicles(EV),both theinterturn voltage stress and temperature within HW are rising,increasing the risk of partial discharge(PD),and presentingsignificant challenges to insulation safety.Therefore,this paperaddresses this issue and proposes potential solutions.Firstly,thepaper examines an 8-pole,48-slot,6-layer HW TM to highlightthe unique characteristics of this winding structure,and explainsthe uneven distribution of interturn voltage stress andtemperature.Subsequently,a high-frequency equivalent circuitmodel of the HW TM prototype is developed.The error ofsimulation and experiment is only 5.7%,which proves theaccuracy of the model.Then,an improved HW scheme isproposed to lower the maximum voltage stress by 29.3%.Furthermore,the temperature distribution of HW TM isanalyzed to facilitate a detailed examination of the impact oftemperature on insulation PD.Finally,the partial dischargeinception voltage(PDIV)of interturn insulation,consideringtemperature effects,is calculated and verified throughexperiment.The paper proposes a reliability-oriented designmethod and process for HW TM.It demonstrates that thereliability-oriented design can achieve PD-free performance inthe design stage of HW.
基金supported in part by the National Natural Science Foundation of China under Grants 52025073 and 52377055。
文摘High-speed permanent magnet synchronous motors(PMSMs)have recently been widely applied in various applications.However,due to the increased rotor speed and operating frequency increase,the winding AC losses rise substantially,posing risks to the safety operation.Accurate modeling of the AC losses has therefore become critical at the motor initial design stage.This paper reviews the main modeling methods for AC copper losses in PMSMs,including analytical methods,finite element methods,and hybrid modeling methods.The advantages and disadvantages of each method are analyzed in detail,and key issues in the modeling process are discussed.Finally,future research directions in AC copper loss modeling are explored,providing new insights for motor design and performance optimization.
基金Supported by the National Natural Science Foundation of China(Grant No.52172409)Postdoctoral Innovation Talents Support Program(Grant No.BX20240298)+1 种基金the Fundamental Research Funds for the Central Universities(Grant No.2682024GF023)Heilongjiang Province Postdoctoral Foundation Project(Grant No.LBH-Z23041).
文摘The huge impact kinetic energy cannot be quickly dissipated by the energy-absorbing structure and transferred to the other vehicle through the car body structure,which will cause structural damage and threaten the lives of the occupants.Therefore,it is necessary to understand the laws of energy conversion,dissipation and transfer during train collisions.This study proposes a multi-layer progressive analysis method of energy flow during train collisions,considering the characteristics of the train.In this method,the train collision system is divided into conversion,dissipation,and transfer layers from the perspective of the train,collision interface,and car body structure to analyze the energy conversion,dissipation and transfer characteristics.Taking the collision process of a rail train as an example,a train collision energy transfer path analysis model was established based on power flow theory.The results show that when the maximum mean acceleration of the vehicle meets the standard requirements,the jerk may exceed the allowable limit of the human body,and there is a risk of injury to the occupants of a secondary collision.The decay rate of the collision energy along the direction of train operation reaches 79%.As the collision progresses,the collision energy gradually converges in the structure with holes,and the structure deforms when the gathered energy is greater than the maximum energy the structure can withstand.The proposed method helps to understand the train collision energy flow law and provides theoretical support for the train crashworthiness design in the future.
基金Nourah bint Abdulrahman University for funding this project through the Researchers Supporting Project(PNURSP2025R319)Riyadh,Saudi Arabia and Prince Sultan University for covering the article processing charges(APC)associated with this publication.Special acknowledgement to Automated Systems&Soft Computing Lab(ASSCL),Prince Sultan University,Riyadh,Saudi Arabia.
文摘The growing incidence of cyberattacks necessitates a robust and effective Intrusion Detection Systems(IDS)for enhanced network security.While conventional IDSs can be unsuitable for detecting different and emerging attacks,there is a demand for better techniques to improve detection reliability.This study introduces a new method,the Deep Adaptive Multi-Layer Attention Network(DAMLAN),to boost the result of intrusion detection on network data.Due to its multi-scale attention mechanisms and graph features,DAMLAN aims to address both known and unknown intrusions.The real-world NSL-KDD dataset,a popular choice among IDS researchers,is used to assess the proposed model.There are 67,343 normal samples and 58,630 intrusion attacks in the training set,12,833 normal samples,and 9711 intrusion attacks in the test set.Thus,the proposed DAMLAN method is more effective than the standard models due to the consideration of patterns by the attention layers.The experimental performance of the proposed model demonstrates that it achieves 99.26%training accuracy and 90.68%testing accuracy,with precision reaching 98.54%on the training set and 96.64%on the testing set.The recall and F1 scores again support the model with training set values of 99.90%and 99.21%and testing set values of 86.65%and 91.37%.These results provide a strong basis for the claims made regarding the model’s potential to identify intrusion attacks and affirm its relatively strong overall performance,irrespective of type.Future work would employ more attempts to extend the scalability and applicability of DAMLAN for real-time use in intrusion detection systems.
基金Project(2023YFC3707800)supported by the National Key Research and Development Program of China。
文摘In practical engineering construction,multi-layered barriers containing geomembranes are extensively applied to retard the migration of pollutants.However,the associated analytical theory on pollutants diffusion still needs to be further improved.In this work,general analytical solutions are derived for one-dimensional diffusion of degradable organic contaminant(DOC)in the multi-layered media containing geomembranes under a time-varying concentration boundary condition,where the variable substitution and separated variable approaches are employed.These analytical solutions with clear expressions can be used not only to study the diffusion behaviors of DOC in bottom and vertical composite barrier systems,but also to verify other complex numerical models.The proposed general analytical solutions are then fully validated via three comparative analyses,including comparisons with the experimental measurements,an existing analytical solution,and a finite-difference solution.Ultimately,the influences of different factors on the composite cutoff wall’s(CCW,which consists of two soil-bentonite layers and a geomembrane)service performance are investigated through a composite vertical barrier system as the application example.The findings obtained from this investigation can provide scientific guidance for the barrier performance evaluation and the engineering design of CCWs.This application example also exhibits the necessity and effectiveness of the developed analytical solutions.
基金supported by Fundamental Research Funds for the Central Universities(No.lzujbky-2024-05)Innovation Foundation of Provincial Education Department of Gansu(2024B-005)+2 种基金Scientific Department of Gansu(24CXGA083,24CXGA024,JK2024-28,JK2024-32 and 23CXJA0007)Industrial Support Plan Project of Provincial Education Department of Gansu(2025CYZC-003 and CYZC-2024-10)the Hunan Natural Science Foundation Science and Education Joint Fund Project(2022JJ60109).
文摘Transportation structures such as composite pavements and railway foundations typically consist of multi-layered media designed to withstand high bearing capacity.A theoretical understanding of load transfer mechanisms in these multi-layer composites is essential,as it offers intuitive insights into parametric influences and facilitates enhanced structural performance.This paper employs an improved transfer matrix method to address the limitations of existing theoretical approaches for analyzing multi-layer composite structures.By establishing a twodimensional composite pavement model,it investigates load transfer characteristics and validates the accuracy through finite element simulation.The proposed method offers a straightforward analytical approach for examining internal interactions between structural layers.Case studies indicate that the concrete surface layer is the main load-bearing layer for most vertical normal and shear stresses.The soil base layer reduces the overall mechanical response of the substructure,while horizontal actions increase the risk of interfacial slip and cracking.Structural optimization analysis demonstrates that increasing the thickness of the concrete surface layer,enhancing the thickness and stiffness of the soil base layer,or incorporating gradient layers can significantly mitigate these risks of interfacial slip and cracking.The findings of this study can guide the optimization design,parameter analysis,and damage prevention of multi-layer composite structures.
基金Projects(42477162,52108347,52178371,52168046,52178321,52308383)supported by the National Natural Science Foundation of ChinaProjects(2023C03143,2022C01099,2024C01219,2022C03151)supported by the Zhejiang Key Research and Development Plan,China+6 种基金Project(LQ22E080010)supported by the Exploring Youth Project of Zhejiang Natural Science Foundation,ChinaProject(LR21E080005)supported by the Outstanding Youth Project of Natural Science Foundation of Zhejiang Province,ChinaProject(2022M712964)supported by the Postdoctoral Science Foundation of ChinaProject(2023AFB008)supported by the Natural Science Foundation of Hubei Province for Youth,ChinaProject(202203)supported by Engineering Research Centre of Rock-Soil Drilling&Excavation and Protection,Ministry of Education,ChinaProject(202305-2)supported by the Science and Technology Project of Zhejiang Provincial Communication Department,ChinaProject(2021K256)supported by the Construction Research Founds of Department of Housing and Urban-Rural Development of Zhejiang Province,China。
文摘This study proposes a general imperfect thermal contact model to predict the thermal contact resistance at the interface among multi-layered composite structures.Based on the Green-Lindsay(GL)thermoelastic theory,semi analytical solutions of temperature increment and displacement of multi-layered composite structures are obtained by using the Laplace transform method,upon which the effects of thermal resistance coefficient,partition coefficient,thermal conductivity ratio and heat capacity ratio on the responses are studied.The results show that the generalized imperfect thermal contact model can realistically describe the imperfect thermal contact problem.Accordingly,it may degenerate into other thermal contact models by adjusting the thermal resistance coefficient and partition coefficient.
基金supported by the National Natural Science Foundation of China(No.62401597)Natural Science Foundation of Hunan Province,China(No.2024JJ6469)the Research Project of National University of Defense Technology,China(No.ZK22-02).
文摘Low Earth Orbit(LEO)mega-constellation networks,exemplified by Starlink,are poised to play a pivotal role in future mobile communication networks,due to their low latency and high capacity.With the massively deployed satellites,ground users now can be covered by multiple visible satellites,but also face complex handover issues with such massive high-mobility satellites in multi-layer.The end-to-end routing is also affected by the handover behavior.In this paper,we propose an intelligent handover strategy dedicated to multi-layer LEO mega-constellation networks.Firstly,an analytic model is utilized to rapidly estimate the end-to-end propagation latency as a key handover factor to construct a multi-objective optimization model.Subsequently,an intelligent handover strategy is proposed by employing the Dueling Double Deep Q Network(D3QN)-based deep reinforcement learning algorithm for single-layer constellations.Moreover,an optimal crosslayer handover scheme is proposed by predicting the latency-jitter and minimizing the cross-layer overhead.Simulation results demonstrate the superior performance of the proposed method in the multi-layer LEO mega-constellation,showcasing reductions of up to 8.2%and 59.5%in end-to-end latency and jitter respectively,when compared to the existing handover strategies.
基金supported by the National Natural Science Foundation of China(No.11902231)the Major Program(JD)of Hubei Province,China(No.2023BAA004).
文摘A numerical method to predict the bursting strength of filament wound composite rocket motor case is proposed here.This method can evaluate the longitudinal stress evolution of each composite layer as impregnated filaments with fiber tension are wound layer by layer,and consider the effects of accumulated stress and deformation during filament winding on the bursting strength of composite case.Taking∅520 mm composite cases as a case study,the filament-winding-process-induced stress and deformation as well as progressive damage behavior are numerically predicted,followed by a comparison with experimental results.The numerical results show that the predicted bursting pressures for composite cases manufactured on the mandrels with and without a flexible component are 14.20 MPa and 21.40 MPa,respectively.These values exhibit slight deviation from the measured pressures of 13.50 MPa and 21.57 MPa.Moreover,the predicted damage locations,situated respectively in the dome and cylinder,agree well with the experimental observation.These observations indicate that use of flexible component reduces the load-bearing capacity of the domes.Furthermore,it validates the reliability and accuracy of the proposed numerical method in predicting the bursting strength of composite cases.
文摘Stab-resistant textiles play a critical role in personal protection,necessitating a deeper understanding of how structural and layering factors influence their performance.The current study experimentally examines the effects of textile structure,layering,and ply orientation on the stab resistance of multi-layer textiles.Three 3D warp interlock(3DWI)structures({f1},{f2},{f3})and a 2D woven fabric({f4}),all made of high-performance p-aramid yarns,were engineered and manufactured.Multi-layer specimens were prepared and subjected to drop-weight stabbing tests following HOSBD standards.Stabbing performance metrics,including Depth of Trauma(DoT),Depth of Penetration(DoP),and trauma deformation(Ymax,Xmax),were investigated and analyzed.Statistical analyses(Two-and One-Way ANOVA)indicated that fabric type and layer number significantly impacted DoP(P<0.05),while ply orientation significantly affected DoP(P<0.05)but not DoT(P>0.05).Further detailed analysis revealed that 2D woven fabrics exhibited greater trauma deformation than 3D WIF structures.Increasing the number of layers reduced both DoP and DoT across all fabric structures,with f3 demonstrating the best performance in multi-layer configurations.Aligned ply orientations also enhanced stab resistance,underscoring the importance of alignment in dissipating impact energy.
文摘The world’s most powerful offshore wind turbine has begun feeding electricity into the grid off the coast of southeast China,marking a major technological leap in the country’s wind power industry.The colossal turbine,developed and installed by China Three Gorges Corp.(CTG),is located in the Phase II Liuao offshore wind farm,more than 30 km off the coast of Fujian in waters deeper than 40 metres.The 20-mw unit successfully completed commissioning and started operation on 5 February,CTG announced.
基金supported by Shenzhen Science and Technology Program under Grant JCYJ20250604175412017the National Natural Science Foundation of China under Grant 62473387+1 种基金the Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai) under Grant SML2024SP007in part by the Department of Science and Technology of Guangdong Province under Grant. 2021QN020085。
文摘In permanent magnet synchronous machine(PMSM) drives, temperature information is critical to achieve reliable and high-performance control. The popular model-based estimation methods are based on extracting temperature dependent terms from the voltages using the machine model. The estimation accuracy under low speed or load can be greatly affected by the model uncertainty and noise due to low signal-tonoise ratio. This paper presents a high frequency(HF) position offset injection-based winding and permanent magnet(PM) temperature decoupled estimation approach for PMSMs to achieve accurate and robust temperature estimation among a wide speed range especially under low-speed conditions. In the proposed approach, a small HF position offset is injected into the machine to construct a decoupled winding and PM temperature estimation model, in which the winding and PM temperatures are independently estimated from HF excitations. The temperature estimation is independent from the fundamental model and parameter variation, and it achieves high signal-tonoise ratio under low-speed conditions. Moreover, the temperature estimation is also not affected by magnetic saturation and inverter distortion, which can improve the accuracy and robustness of temperature estimation. The proposed approach is validated with experiments and comparisons on a laboratory machine under various operating conditions.
文摘Wind turbine blade defect detection faces persistent challenges in separating small,low-contrast surface faults from complex backgrounds while maintaining reliability under variable illumination and viewpoints.Conven-tional image-processing pipelines struggle with scalability and robustness,and recent deep learning methods remain sensitive to class imbalance and acquisition variability.This paper introduces TurbineBladeDetNet,a convolutional architecture combining dual-attention mechanisms with multi-path feature extraction for detecting five distinct blade fault types.Our approach employs both channel-wise and spatial attention modules alongside an Albumentations-driven augmentation strategy to handle dataset imbalance and capture condition variability.The model achieves 97.14%accuracy,98.65%precision,and 98.68%recall,yielding a 98.66%F1-score with 0.0110 s inference time.Class-specific analysis shows uniformly high sensitivity and specificity;lightning damage reaches 99.80%for sensitivity,precision,and F1-score,and crack achieves perfect precision and specificity with a 98.94%F1-score.Comparative evaluation against recent wind-turbine inspection approaches indicates higher performance in both accuracy and F1-score.The resulting balance of sensitivity and specificity limits both missed defects and false alarms,supporting reliable deployment in routine unmanned aerial vehicle(UAV)inspection.
文摘Paying an additional RMB 2 could have your next milk tea delivered by drone to your balcony in just five minutes.This small fee represents the vast potential of the trillion-yuan lowaltitude economy.
基金supported by the Smart Grid-National Science and Technology Major Project of China(2024ZD0802000).
文摘Although wind energy is volatile,the output of a wind-storage plant is partially dispatchable,making it a promising paradigm on the generation side.A grid-friendly wind-storage plant ought to be able to continuously output the desired power over a certain period of time.This paper proposes a dependable dynamic capacity provision scheme of a wind-storage plant over a daily horizon.It stipulates a minimum number of periods during which the committed capacity must be fulfilled and a maximum mismatch during the remaining periods when the desired power output is not achievable.In the general case,the day-ahead piecewise constant capacity provision results in a two-stage stochastic program formulated as a mixed-integer linear program.Specifically,for constant capacity provision,a decomposition algorithm is developed to determine the global optimal solution,and the complexity grows linearly with the number of scenarios.Given the committed capacity trajectory,the real-time operation problem is modeled as a four-state stochastic dynamic program.The discrete state-action values are derived recursively via the principle of optimality.Real-time dispatch actions are generated by using the action-value tabular leveraging inexact ultra-short-term forecasts.Numerical tests over one year demonstrate that the proposed method successfully fulfills reliable operation on 355 days and achieve an optimality gap of 9.47%compared with the ex-post optimum,which is comparable to model predictive control using exact 2–3-hour-ahead wind power forecasts.
基金supported by the Xinjiang Key Research and Development Programme Project(2022B02040-2)the Tianshan Yingcai Program of Xinjiang Uygur Autonomous Region(2024TSYCLJ0028).
文摘Cyperus esculentus(C.esculentus),a desert-adapted plant species with both ecological and economic value,has been widely cultivated in northern China's sandy regions.However,limited studies have investigated the performance of composite shelterbelts that integrate C.esculentus.This study systematically evaluated five shelterbelt models—Populus euphratica(P.euphratica),P.euphratica–C.esculentus composite,P.euphratica–nylon net–C.esculentus composite,Tamarix chinensis(T.chinensis),and T.chinensis–C.esculentus composite—using wind tunnel experiments and field observations.Sediment flux was measured at a normalized downwind distance(x/h)of 5,where x refers to the distance from the front edge(upwind side)of the shelterbelt for upwind measurements,and the distance from the rear edge(downwind side)for downwind measurements,and h represents the canopy height.Wind velocity was measured at x/h of–2,–1,1,2,3,5,and 7,and sand flux was measured at x/h=5,under initial wind velocities of 8.0 and 12.0 m/s.The results indicated that the P.euphratica–nylon net–C.esculentus composite was the most effective in reducing wind velocity,followed by the P.euphratica–C.esculentus composite.In contrast,the P.euphratica and T.chinensis exhibited relatively weaker wind reduction capabilities.Regarding sand flux,under moderate wind velocity(8.0 m/s),both the P.euphratica–C.esculentus composite and P.euphratica–nylon net–C.esculentus composite demonstrated the lowest sand flux values.However,under high wind velocity(12.0 m/s),the P.euphratica–nylon net–C.esculentus composite significantly outperformed the other shelterbelt models in sand retention,highlighting its superior windbreak and sand fixation efficacy.Field observations further validated the windbreak and sand fixation effects of C.esculentus.Comparisons between the bare sand plot and C.esculentus plot within protective forests demonstrated that planting C.esculentus can provide substantial ecological benefits in windbreak and sand-fixation.These findings,reinforced by field observations,strengthen the wind tunnel experiment results and highlight the critical role of C.esculentus in enhancing the performance of composite shelterbelts for desert ecological restoration.
