The forming of textile reinforcements is an important stage in the manufacturing of textile composite parts with Liquid Composite Molding process.Fiber orientations and part geometry obtained from this stage have sign...The forming of textile reinforcements is an important stage in the manufacturing of textile composite parts with Liquid Composite Molding process.Fiber orientations and part geometry obtained from this stage have significant impact on the subsequent resin injection and final mechanical properties of composite part.Numerical simulation of textile reinforcement forming is in strong demand as it can greatly reduce the time and cost in the determination of the optimized processing parameters,which is the foundation of the low-cost application of composite materials.This review presents the state of the art of forming modeling methods for textile reinforcement and the corresponding experimental characterization methods developed in this field.The microscopic,mesoscopic and macroscopic models are discussed.Studies concerning the simulation of wrinkling are also presented since it is the most common defect occurred in the textile reinforcement forming.Finally,challenges and recommendations on the future research directions for textile reinforcement modeling and experimental characterization are provided.展开更多
The alumina composite coatings reinforced with 25% ZrO2 （denoted as AZ-25） and 3% TiO2 （denoted as AT-3） were deposited on low carbon steel using a thermal flame spraying. The microstructure, phase composition, mi...The alumina composite coatings reinforced with 25% ZrO2 （denoted as AZ-25） and 3% TiO2 （denoted as AT-3） were deposited on low carbon steel using a thermal flame spraying. The microstructure, phase composition, microhardness and tribological properties of the coatings were investigated. The XRD results of the coatings reinforced by TiO2 （AT-3） revealed the presence of α-Al2O3 phase as matrix and new metastable phases of α-Al2O3 and α-Al2O3. However, the coatings reinforced by ZrO2 （AZ-25） consist of α-Al2O3 as matrix, q-ZrO2 and m-ZrO2. In most studied conditions, the AT-3 coating displays a better tribological performance, i.e., lower coefficient of frictions and wear rates, than the AZ-25 coating. It was also found that the microhardness of the coatings was decreased with the reinforcement of ZrO2 and increased with TiO2.展开更多
3D numerical simulations of dynamical tensile response of hybrid carbon nanotube(CNT)and SiC nanoparticle reinforced AZ91D magnesium(Mg)based composites considering interface cohesion over a temperature range from 25 ...3D numerical simulations of dynamical tensile response of hybrid carbon nanotube(CNT)and SiC nanoparticle reinforced AZ91D magnesium(Mg)based composites considering interface cohesion over a temperature range from 25 to 300℃ were carried out using a 3D representative volume element(RVE)approach.The simulation predictions were compared with the experimental results.It is clearly shown that the overall dynamic tensile properties of the nanocomposites at different temperatures are improved when the total volume fraction and volume fraction ratio of hybrid CNTs to SiC nanoparticles increase.The overall maximum hybrid effect is achieved when the hybrid volume fraction ratio of CNTs to SiC nanoparticles is in the range from 7:3 to 8:2 under the condition of total volume fraction of 1.0%.The composites present positive strain rate hardening and temperature softening effects under dynamic loading at high temperatures.The simulation results are in good agreement with the experimental data.展开更多
Ultra-high performance cement-based composites (UHPCC) is promising in construction of concrete structures that suffer impact and explosive loads.In this study,a reference UHPCC mixture with no fiber reinforcement and...Ultra-high performance cement-based composites (UHPCC) is promising in construction of concrete structures that suffer impact and explosive loads.In this study,a reference UHPCC mixture with no fiber reinforcement and four mixtures with a single type of fiber reinforcement or hybrid fiber reinforcements of straight smooth and end hook type of steel fibers were prepared.Split Hopkinson pressure bar (SHPB) was performed to investigate the dynamic compression behavior of UHPCC and X-CT test and 3D reconstruction technology were used to indicate the failure process of UHPCC under impact loading.Results show that UHPCC with 1% straight smooth fiber and 2% end hook fiber reinforcements demonstrated the best static and dynamic mechanical properties.When the hybrid steel fiber reinforcements are added in the concrete,it may need more impact energy to break the matrix and to pull out the fiber reinforcements,thus,the mixture with hybrid steel fiber reinforcements demonstrates excellent dynamic compressive performance.展开更多
To improve the comprehensive mechanical properties of Al-Si-Cu alloy,it was treated by a high-pressure torsion process,and the effect of the deformation degree on the microstructure and properties of the Al-Si-Cu allo...To improve the comprehensive mechanical properties of Al-Si-Cu alloy,it was treated by a high-pressure torsion process,and the effect of the deformation degree on the microstructure and properties of the Al-Si-Cu alloy was studied.The results show that the reinforcements(β-Si andθ-CuAl_(2)phases)of the Al-Si-Cu alloy are dispersed in theα-Al matrix phase with finer phase size after the treatment.The processed samples exhibit grain sizes in the submicron or even nanometer range,which effectively improves the mechanical properties of the material.The hardness and strength of the deformed alloy are both significantly raised to 268 HV and 390.04 MPa by 10 turns HPT process,and the fracture morphology shows that the material gradually transits from brittle to plastic before and after deformation.The elements interdiffusion at the interface between the phases has also been effectively enhanced.In addition,it is found that the severe plastic deformation at room temperature induces a ternary eutectic reaction,resulting in the formation of ternary Al+Si+CuAl_(2)eutectic.展开更多
The full-range behavior of partially bonded, together with partially prestressed concrete beams containing fiber reinforced polymer （FRP） tendons and stainless steel reinforcing bars was simulated using a simplified...The full-range behavior of partially bonded, together with partially prestressed concrete beams containing fiber reinforced polymer （FRP） tendons and stainless steel reinforcing bars was simulated using a simplified theoretical model. The model assumes that a section in the beam has a trilinear moment--curvature relationship characterized by three particular points, initial cracking of concrete, yielding of non-prestressed steel, and crushing of concrete or rupturing of prestressing tendons. Predictions from the model were compared with the limited available test data, and a reasonable agreement was obtained. A detailed parametric study of the behavior of the prestressed concrete beams with hybrid FRP and stainless steel reinforcements was conducted. It can be concluded that the deformability of the beam can be enhanced by increasing the ultimate compressive strain of concrete, unhonded length of tendon, percentage of compressive reinforcement and partial prestress ratio, and decreasing the effective prestress in tendons, and increasing in ultimate compressive strain of concrete is the most efficient one. The deformability of the beam is almost directly proportional to the concrete ultimate strain provided the failure mode is concrete crushing, even though the concrete ultimate strain has less influence on the load-carrying capacity.展开更多
We quantitatively study magnetic anomalies of reinforcement rods in bored insitu concrete piles for the first time and summarized their magnetic anomaly character. Key factors such as measuring borehole orientation, b...We quantitatively study magnetic anomalies of reinforcement rods in bored insitu concrete piles for the first time and summarized their magnetic anomaly character. Key factors such as measuring borehole orientation, borehole-reinforcement distance, and multiple-section reinforcement rods are discussed which contributes valid and quantitative reference for using the magnetic method to detect reinforcement rods. Through tests with model piles, we confirm the accuracy of theoretical computations and then utilize the law discovered in theoretical computations to explain the characteristics of the actual testing curves. The results show that the Za curves of the reinforcement rod reflect important factors regarding the reinforcement rods, such as rod length, change of reinforcement ratio, length of overlap, and etc. This research perfects the magnetic method for detecting reinforcement rods in bored in-situ concrete piles and the method has great importance for preventing building contractor fraud.展开更多
Copper matrix composites reinforced by in situ-formed hybrid titanium boride whiskers(TiB_(w))and titanium diboride particles(TiB_(2p))were fabricated by powder metallurgy.Microstructural observations showed competiti...Copper matrix composites reinforced by in situ-formed hybrid titanium boride whiskers(TiB_(w))and titanium diboride particles(TiB_(2p))were fabricated by powder metallurgy.Microstructural observations showed competitive precipitation behavior between TiB_(w) and TiB_(2p),where the relative contents of the two reinforcements varied with sintering temperature.Based on thermodynamic and kinetic assessments,the precipitation mechanisms of the hybrid reinforcements were discussed,and the formation of both TiB_(w) and TiB_(2p) from the local melting zone was thermodynamically favored.The precipitation kinetics were mainly controlled by a solid-state diffusion of B atoms.By forming a compact compound layer,in situ reactions were divided into two stages,where Zener growth and Dybkov growth prevailed,respectively.Accordingly,the competitive precipitation behavior was attributed to the transition of the growth model during the reaction process.展开更多
To examine the protection against reinforcement corrosion due to the combined action of CO2 and chlorides, experimental results of the evaluation of a study with three types of cement are presented. The study was perf...To examine the protection against reinforcement corrosion due to the combined action of CO2 and chlorides, experimental results of the evaluation of a study with three types of cement are presented. The study was performed observing the behavior of reinforcements which were put in samples submitted to accelerated carbonatation tests and accelerated tests under the effect of chlorides. For the evaluation, intensity corrosion measurements were used using the Pr （polarization resistance） technique, employing these measures as a deterioration indicator. Three types of cement available in the national market were used. The obtained results enabled the classification of the used cements, comparing their profile behaviors in the conditions of the proposed tests.展开更多
In recent years,researchers have leveraged single-agent reinforcement learning to boost educational outcomes and deliver personalized interventions;yet this paradigm provides no capacity for inter-agent interaction.Mu...In recent years,researchers have leveraged single-agent reinforcement learning to boost educational outcomes and deliver personalized interventions;yet this paradigm provides no capacity for inter-agent interaction.Multi-agent reinforcement learning(MARL)overcomes this limitation by allowing several agents to learn simultaneously within a shared environment,each choosing actions that maximize its own or the group's rewards.By explicitly modeling and exploiting agent-to-agent dynamics,MARL can align those interactions with pedagogical goals such as peer tutoring,collaborative problem-solving,or gamified competition,thus opening richer avenues for adaptive and socially informed learning experiences.This survey investigates the impact of MARL on educational outcomes by examining evidence of its effectiveness in enhancing learner performance,engagement,equity,and reducing teacher workload compared to single agent or traditional approaches.It explores the educational domains and pedagogical problems addressed by MARL,identifies the algorithmic families used,and analyzes their influence on learning.The review also assesses experimental settings and evaluation metrics to determine ecological validity,and outlines current challenges and future research directions in applying MARL to education.展开更多
A novel method that combines reinforced enzyme-induced carbonate precipitation(REICP)was proposed to improve the mechanical properties of dispersive soil.Dispersive soils,which are highly susceptible to erosion caused...A novel method that combines reinforced enzyme-induced carbonate precipitation(REICP)was proposed to improve the mechanical properties of dispersive soil.Dispersive soils,which are highly susceptible to erosion caused by rainfall or seepage,pose significantenvironmental challenges.It is essential to focus on modifying dispersive soil using environmentally friendly methods.This study investigated the cohesion,internal friction angle,permeability,hydrostability test,and microstructure of dispersive soil treated with enzyme-induced carbonate precipitation(EICP)-MgCl2-xanthan gum(REICP),using statistical analysis.A series of laboratory experiments was conducted,including direct shear tests,permeability experiments,mud ball tests,simulated rainfall tests,Fourier transform infrared spectroscopy(FTIR),X-ray diffraction(XRD),and scanning electron microscopy(SEM).The results showed that the combined treatment significantly enhanced the mechanical properties of dispersive soil.At the optimal ratio,cohesion increased by a factor of 2,and the permeability coefficientdecreased by approximately 1.7×10^(7)times.Additionally,the strength parameters gradually increased with curing time.Microstructural analyses indicated that calcite precipitation,pore filling,and ionic redistribution significantlyimproved the mechanical properties and hydrostability of the soil.Statistical analyses showed that EICP materials and xanthan gum increased soil cohesion,while magnesium chloride enhanced the internal friction angle and reduced porosity.This study integrates mechanical testing,statistical analysis,and microstructural evaluation to propose a sustainable and environmentally friendly method for improving dispersive soils.This approach reduces the use of chemical modifiers,minimizes environmental impacts,and demonstrates application potential in the stabilization of dispersive soils.展开更多
Unmanned Aerial Vehicles(UAVs)have become integral components in smart city infrastructures,supporting applications such as emergency response,surveillance,and data collection.However,the high mobility and dynamic top...Unmanned Aerial Vehicles(UAVs)have become integral components in smart city infrastructures,supporting applications such as emergency response,surveillance,and data collection.However,the high mobility and dynamic topology of Flying Ad Hoc Networks(FANETs)present significant challenges for maintaining reliable,low-latency communication.Conventional geographic routing protocols often struggle in situations where link quality varies and mobility patterns are unpredictable.To overcome these limitations,this paper proposes an improved routing protocol based on reinforcement learning.This new approach integrates Q-learning with mechanisms that are both link-aware and mobility-aware.The proposed method optimizes the selection of relay nodes by using an adaptive reward function that takes into account energy consumption,delay,and link quality.Additionally,a Kalman filter is integrated to predict UAV mobility,improving the stability of communication links under dynamic network conditions.Simulation experiments were conducted using realistic scenarios,varying the number of UAVs to assess scalability.An analysis was conducted on key performance metrics,including the packet delivery ratio,end-to-end delay,and total energy consumption.The results demonstrate that the proposed approach significantly improves the packet delivery ratio by 12%–15%and reduces delay by up to 25.5%when compared to conventional GEO and QGEO protocols.However,this improvement comes at the cost of higher energy consumption due to additional computations and control overhead.Despite this trade-off,the proposed solution ensures reliable and efficient communication,making it well-suited for large-scale UAV networks operating in complex urban environments.展开更多
Biobased biodegradable plastics have gained increasing attention as sustainable alternatives to petroleum-based materials in food packaging,offering biodegradability,renewability,and reduced environmental impact.This ...Biobased biodegradable plastics have gained increasing attention as sustainable alternatives to petroleum-based materials in food packaging,offering biodegradability,renewability,and reduced environmental impact.This review adopts a narrative review approach,integrating studies published between 2015 and 2025 from major databases to critically evaluate the recent advances,feasibility,and limitations of biobased biodegradable plastics in food packaging.Literature was thematically analyzed by material type and functional enhancement to assess their feasibility and limitations for sustainable packaging applications.Recent advances have focused on enhancing their mechanical,barrier,and functional properties through polymer blending,nanoparticle reinforcement,and incorporation of natural bioactive agents.Starch-based bioplastics,derived from renewable sources such as corn and cassava,have been improved by blending with polylactic acid(PLA)or polybutylene succinate(PBS)and reinforcing with nanocellulose or silica to enhance flexibility,strength,and thermal stability.Incorporating plant extracts and polyphenols has added antioxidant and antimicrobial functions.PLA-based films have benefited from nanoparticle fillers like zinc oxide and lignin nanoparticles,and the integration of bioactive compounds such as tea polyphenols and hop extract has enabled multifunctional,intelligent packaging with controlled release and UV protection.Polyhydroxyalkanoates(PHAs),producedmicrobially,have been functionalizedwith tannins,ferulic acid,and other natural agents to achieve high antioxidant,antibacterial,and UV-blocking performance,while multilayer coatings have improved moisture and gas resistance.PBS composites have been enhanced using nanofillers like silver or magnesium oxide and natural additives such as quercetin and essential oils,thereby improving durability and bioactivity.Emerging materials,including chitosan-,protein-,and polysaccharide-based films,show excellent film-forming ability and compatibility with natural antimicrobials;smart systems with pH-sensing and UV-shielding functions further extend food shelf life.Despite remaining challenges such as cost,moisture sensitivity,limited scalability,and potential competition with food resources,recent progress demonstrates that biobased biodegradable plastics hold strong potential to advance sustainable,high-performance food packaging,particularly when waste is valorized.Future research should focus on improving the cost-effectiveness,scalability,and moisture resistance of biobased biodegradable plastics,while advancing waste-derived feedstocks,multifunctional smart packaging,and comprehensive life cycle assessments to ensure sustainable and practical food packaging solutions.展开更多
Frequency hopping(FH)communication has good anti-fading,anti-jamming and anti-eavesdropping capabilities,so it is one of the main ways to combat electronic jamming.In order to further improve the anti-jamming capabili...Frequency hopping(FH)communication has good anti-fading,anti-jamming and anti-eavesdropping capabilities,so it is one of the main ways to combat electronic jamming.In order to further improve the anti-jamming capability of FH communication,the parameters such as fixed frequency interval,hopping rate and hopping frequency in conventional FH can be assigned with time-varying characteristics.In order to set appropriate hopping parameters to improve the performance of the system in the electromagnetic environment with various types of jamming,a heuristically accelerated Q-learning(HAQL)method is proposed in this paper.Firstly,a theoretical model for the parameter decision-making of FH system is made,and the key parameters affecting the energy efficiency of the system are analyzed.Secondly,a Q-learning model in complex electromagnetic environment is proposed,which includes setting states,actions and rewards,as well as a HAQL-based decisionmaking algorithm is put forward.Lastly,simulations are carried out under different jamming environments,and simulation results show that the average energy efficiency of HAQL algorithm is higher than that of the SARSA algorithm,the e-greedy QL algorithm and the HQL-OSGM algorithm,respectively.展开更多
Cooperative pursuit poses challenges across natural,social,and technical systems,particularly when decentralized,slow-speed pursuers attempt to capture a high-speed evader with limited observation.Most existing contri...Cooperative pursuit poses challenges across natural,social,and technical systems,particularly when decentralized,slow-speed pursuers attempt to capture a high-speed evader with limited observation.Most existing contributions place the focus on the greedy pursuit of the evader,overlooking potential collaborations among pursuers.To tackle this issue,a decisionmaking framework of multi-agent coordinated reciprocity formation pursuit(MACRFP)via deep reinforcement learning is introduced.This framework integrates the actor-critic algorithm with the coordinated reciprocity mechanism to enhance the capability of capturing a faster evader.Initially,a local perception model is created by utilizing a cellular network to simulate limitations caused by obstacles.Next,the formation coalition of pursuit is guided by the Cartesian Oval,enabling dispersed pursuers to create a siege against the faster evader.Furthermore,a coordinated reciprocity model based on the coordination graph and the attention-based graph neural networks is developed,addressing the global coordination problem by estimating a reciprocity coefficient to adjust agents'rewards.Numerical simulations demonstrate the emergence of cooperative behaviors in cooperative besiegement,target tracking,and intelligent interception during the pursuit,indicating that the proposed algorithm enhances the feasibility and effectiveness of capturing a fast-escaping target by integrating coordinated reciprocity and coalition formation.展开更多
Muon scattering tomography(MST) is a powerful noninvasive imaging technique with significant applications in nuclear material detection and security screening.Traditional MST usually relies on the point of closest app...Muon scattering tomography(MST) is a powerful noninvasive imaging technique with significant applications in nuclear material detection and security screening.Traditional MST usually relies on the point of closest approach(PoCA) algorithm to reconstruct images from muon scattering data;however,PoCA often suffers from suboptimal image clarity and resolution.To overcome these challenges,we propose a novel approach that leverages reinforcement learning(RL) to enhance MST reconstruction,termed the μRL-enhanced method.By framing the MST optimization task as an RL problem,we developed an intelligent agent capable of dynamically adjusting the key PoCA parameters.The agent is trained using a multi-objective reward function that guides the optimization toward higher-quality reconstructions.Our experimental results show that theμRL-enhanced method significantly outperforms the traditional PoCA baseline acros s multiple benchmark metrics.Specifically,the proposed approach on average attains a 307% improvement in the intersection over union(IoU),a 79% increase in the structural similarity index measure(SSIM),and a 8.4% enhancement in the peak signal-to-noise ratio(PSNR) across four experiments.Furthermore,when benchmarked against the maximum likelihood scattering and displacement(MLSD)algorithm,the μRL-enhanced method offers modest gains in PS NR and IoU,together with a one-third increase in SSIM.These improvements demonstrate the enhanced reconstruction accuracy and structural fidelity of the μRL-enhanced method,highlighting its potential to advance MST technologies and their applications.展开更多
Cellulose,the dominant natural polymer on Earth,features a distinct molecular structure with extraordinary mechanical properties and tunable characteristics,making it attractive for gel systems.Although significant pr...Cellulose,the dominant natural polymer on Earth,features a distinct molecular structure with extraordinary mechanical properties and tunable characteristics,making it attractive for gel systems.Although significant progress has been made,challenges remain in fully leveraging their functional potential and broadening practical applications.This review systematically examines the properties of cellulose and cellulose gels,exploring novel reinforcement strategies—across molecular,supramolecular network,and macroscale structure levels—to enhance mechanical,electrical,and thermal performance,while coordinating these properties for practical implementations.These advancements are exemplified in emerging fields such as flexible robotics,electronic skins,flexible energy storage devices,and human-machine interaction systems.This article thoroughly investigates the fundamental characteristics,multi-scale design approaches,performance enhancement mechanisms,and cutting-edge implementations of cellulose-based gels across diverse domains.It provides a comprehensive overview of these advanced materials and offers strategic insights and recommendations for future research and innovation.展开更多
Wireless Sensor Networks(WSNs)play a crucial role in numerous Internet of Things(IoT)applications and next-generation communication systems,yet they continue to face challenges in balancing energy efficiency and relia...Wireless Sensor Networks(WSNs)play a crucial role in numerous Internet of Things(IoT)applications and next-generation communication systems,yet they continue to face challenges in balancing energy efficiency and reliable connectivity.This study proposes SAC-HTC(Soft Actor-Critic-based High-performance Topology Control),a deep reinforcement learning(DRL)method based on the Actor-Critic framework,implemented within a Software Defined Wireless Sensor Network(SDWSN)architecture.In this approach,sensor nodes periodically transmit state information,including coordinates,node degree,transmission power,and neighbor lists,to a centralized controller.The controller acts as the reinforcement learning(RL)agent,with the Actor generating decisions to adjust transmission ranges,while the Critic evaluates action values to reflect the overall network performance.The bidirectional Node-Controller feedback mechanism enables the controller to issue appropriate control commands to each node,ensuring the maintenance of the desired node degree,reducing energy consumption,and preserving network connectivity.The algorithmfurther incorporates soft entropy adjustment to balance exploration and exploitation,alongwith an off-policy mechanism for efficient data reuse,making it well-suited to the resource-constrained conditions ofWSNs.Simulation results demonstrate that SAC-HTC not only outperforms traditional methods and several existing RL algorithms but also achieves faster convergence,optimized communication range control,global connectivity maintenance,and extended network lifetime.The key novelty of this research lies in the integration of the SAC method with the SDWSN architecture forWSNs topology control,providing an adaptive,efficient,and highly promisingmechanism for large-scale,dynamic,and high-performance sensor networks.展开更多
This paper investigates the traffic offloading optimization challenge in Space-Air-Ground Integrated Networks(SAGIN)through a novel Recursive Multi-Agent Proximal Policy Optimization(RMAPPO)algorithm.The exponential g...This paper investigates the traffic offloading optimization challenge in Space-Air-Ground Integrated Networks(SAGIN)through a novel Recursive Multi-Agent Proximal Policy Optimization(RMAPPO)algorithm.The exponential growth of mobile devices and data traffic has substantially increased network congestion,particularly in urban areas and regions with limited terrestrial infrastructure.Our approach jointly optimizes unmanned aerial vehicle(UAV)trajectories and satellite-assisted offloading strategies to simultaneously maximize data throughput,minimize energy consumption,and maintain equitable resource distribution.The proposed RMAPPO framework incorporates recurrent neural networks(RNNs)to model temporal dependencies in UAV mobility patterns and utilizes a decentralized multi-agent reinforcement learning architecture to reduce communication overhead while improving system robustness.The proposed RMAPPO algorithm was evaluated through simulation experiments,with the results indicating that it significantly enhances the cumulative traffic offloading rate of nodes and reduces the energy consumption of UAVs.展开更多
The increasing occurrence of corrosion-related damage in steel pipelines has led to the growing use of composite-based repair techniques as an efficient alternative to traditional replacement methods.Computer modeling...The increasing occurrence of corrosion-related damage in steel pipelines has led to the growing use of composite-based repair techniques as an efficient alternative to traditional replacement methods.Computer modeling and structural analysis were performed for the repair reinforcement of a steel pipeline with a composite bandage.A preliminary analysis of possible contact interaction schemes was implemented based on the theory of cylindrical shells,taking into account transverse shear deformations.The finite element method was used for a detailed study of the stress state of the composite bandage and the reinforced section of the pipeline.The limit state of the reinforced section was assessed based on the von Mises criterion for steel and the Tsai-Wu criterion for composites.The effectiveness of the repair was demonstrated on a pipeline whose wall thickness had decreased by 20%as a result of corrosion damage.At a nominal pressure of P=6 MPa,the maximum normal stress in the weakened area reached 381 MPa.The installation of a composite bandage reduced this stress to 312 MPa,making the repaired section virtually as strong as the undamaged pipeline.Due to the linearity of the problem,the results obtained can be easily used to find critical internal pressure values.展开更多
基金funding support from the Young Fund of Natural Science Foundation of Shaanxi province,China(No.2020JQ-121)Fundamental Research Funds for the Central Universities,China(No.31020190502002)。
文摘The forming of textile reinforcements is an important stage in the manufacturing of textile composite parts with Liquid Composite Molding process.Fiber orientations and part geometry obtained from this stage have significant impact on the subsequent resin injection and final mechanical properties of composite part.Numerical simulation of textile reinforcement forming is in strong demand as it can greatly reduce the time and cost in the determination of the optimized processing parameters,which is the foundation of the low-cost application of composite materials.This review presents the state of the art of forming modeling methods for textile reinforcement and the corresponding experimental characterization methods developed in this field.The microscopic,mesoscopic and macroscopic models are discussed.Studies concerning the simulation of wrinkling are also presented since it is the most common defect occurred in the textile reinforcement forming.Finally,challenges and recommendations on the future research directions for textile reinforcement modeling and experimental characterization are provided.
文摘The alumina composite coatings reinforced with 25% ZrO2 （denoted as AZ-25） and 3% TiO2 （denoted as AT-3） were deposited on low carbon steel using a thermal flame spraying. The microstructure, phase composition, microhardness and tribological properties of the coatings were investigated. The XRD results of the coatings reinforced by TiO2 （AT-3） revealed the presence of α-Al2O3 phase as matrix and new metastable phases of α-Al2O3 and α-Al2O3. However, the coatings reinforced by ZrO2 （AZ-25） consist of α-Al2O3 as matrix, q-ZrO2 and m-ZrO2. In most studied conditions, the AT-3 coating displays a better tribological performance, i.e., lower coefficient of frictions and wear rates, than the AZ-25 coating. It was also found that the microhardness of the coatings was decreased with the reinforcement of ZrO2 and increased with TiO2.
基金The authors are grateful for the financial supports from the National Natural Science Foundation of China(11672055,11272072).
文摘3D numerical simulations of dynamical tensile response of hybrid carbon nanotube(CNT)and SiC nanoparticle reinforced AZ91D magnesium(Mg)based composites considering interface cohesion over a temperature range from 25 to 300℃ were carried out using a 3D representative volume element(RVE)approach.The simulation predictions were compared with the experimental results.It is clearly shown that the overall dynamic tensile properties of the nanocomposites at different temperatures are improved when the total volume fraction and volume fraction ratio of hybrid CNTs to SiC nanoparticles increase.The overall maximum hybrid effect is achieved when the hybrid volume fraction ratio of CNTs to SiC nanoparticles is in the range from 7:3 to 8:2 under the condition of total volume fraction of 1.0%.The composites present positive strain rate hardening and temperature softening effects under dynamic loading at high temperatures.The simulation results are in good agreement with the experimental data.
基金Funded by the National Key Research and Development Program of China(No.2018YFC0705400)National Natural Science Foundation of China(No.51678142)the Fundamental Research Funds for the Central Universities。
文摘Ultra-high performance cement-based composites (UHPCC) is promising in construction of concrete structures that suffer impact and explosive loads.In this study,a reference UHPCC mixture with no fiber reinforcement and four mixtures with a single type of fiber reinforcement or hybrid fiber reinforcements of straight smooth and end hook type of steel fibers were prepared.Split Hopkinson pressure bar (SHPB) was performed to investigate the dynamic compression behavior of UHPCC and X-CT test and 3D reconstruction technology were used to indicate the failure process of UHPCC under impact loading.Results show that UHPCC with 1% straight smooth fiber and 2% end hook fiber reinforcements demonstrated the best static and dynamic mechanical properties.When the hybrid steel fiber reinforcements are added in the concrete,it may need more impact energy to break the matrix and to pull out the fiber reinforcements,thus,the mixture with hybrid steel fiber reinforcements demonstrates excellent dynamic compressive performance.
基金Funded by the National Natural Science Foundation of China(No.51905215)Postgraduate Research&Practice Innovation Program of Jiangsu Province(No.SJCX23_1233)+1 种基金Major Scientific and Technological Innovation Project of Shandong Province of China(No.2019JZZY020111)the National College Students Innovation and Entrepreneurship Training Program of China(No.CX2022415)。
文摘To improve the comprehensive mechanical properties of Al-Si-Cu alloy,it was treated by a high-pressure torsion process,and the effect of the deformation degree on the microstructure and properties of the Al-Si-Cu alloy was studied.The results show that the reinforcements(β-Si andθ-CuAl_(2)phases)of the Al-Si-Cu alloy are dispersed in theα-Al matrix phase with finer phase size after the treatment.The processed samples exhibit grain sizes in the submicron or even nanometer range,which effectively improves the mechanical properties of the material.The hardness and strength of the deformed alloy are both significantly raised to 268 HV and 390.04 MPa by 10 turns HPT process,and the fracture morphology shows that the material gradually transits from brittle to plastic before and after deformation.The elements interdiffusion at the interface between the phases has also been effectively enhanced.In addition,it is found that the severe plastic deformation at room temperature induces a ternary eutectic reaction,resulting in the formation of ternary Al+Si+CuAl_(2)eutectic.
基金Project (50478502) supported by the National Natural Science Foundation of China
文摘The full-range behavior of partially bonded, together with partially prestressed concrete beams containing fiber reinforced polymer （FRP） tendons and stainless steel reinforcing bars was simulated using a simplified theoretical model. The model assumes that a section in the beam has a trilinear moment--curvature relationship characterized by three particular points, initial cracking of concrete, yielding of non-prestressed steel, and crushing of concrete or rupturing of prestressing tendons. Predictions from the model were compared with the limited available test data, and a reasonable agreement was obtained. A detailed parametric study of the behavior of the prestressed concrete beams with hybrid FRP and stainless steel reinforcements was conducted. It can be concluded that the deformability of the beam can be enhanced by increasing the ultimate compressive strain of concrete, unhonded length of tendon, percentage of compressive reinforcement and partial prestress ratio, and decreasing the effective prestress in tendons, and increasing in ultimate compressive strain of concrete is the most efficient one. The deformability of the beam is almost directly proportional to the concrete ultimate strain provided the failure mode is concrete crushing, even though the concrete ultimate strain has less influence on the load-carrying capacity.
基金supported by Transportation Research Project of Jiangsu Province (05Y015),China
文摘We quantitatively study magnetic anomalies of reinforcement rods in bored insitu concrete piles for the first time and summarized their magnetic anomaly character. Key factors such as measuring borehole orientation, borehole-reinforcement distance, and multiple-section reinforcement rods are discussed which contributes valid and quantitative reference for using the magnetic method to detect reinforcement rods. Through tests with model piles, we confirm the accuracy of theoretical computations and then utilize the law discovered in theoretical computations to explain the characteristics of the actual testing curves. The results show that the Za curves of the reinforcement rod reflect important factors regarding the reinforcement rods, such as rod length, change of reinforcement ratio, length of overlap, and etc. This research perfects the magnetic method for detecting reinforcement rods in bored in-situ concrete piles and the method has great importance for preventing building contractor fraud.
基金This work was financially supported by the National Natural Science Foundation of China(Nos.U1502274,51834009,and 51974244).
文摘Copper matrix composites reinforced by in situ-formed hybrid titanium boride whiskers(TiB_(w))and titanium diboride particles(TiB_(2p))were fabricated by powder metallurgy.Microstructural observations showed competitive precipitation behavior between TiB_(w) and TiB_(2p),where the relative contents of the two reinforcements varied with sintering temperature.Based on thermodynamic and kinetic assessments,the precipitation mechanisms of the hybrid reinforcements were discussed,and the formation of both TiB_(w) and TiB_(2p) from the local melting zone was thermodynamically favored.The precipitation kinetics were mainly controlled by a solid-state diffusion of B atoms.By forming a compact compound layer,in situ reactions were divided into two stages,where Zener growth and Dybkov growth prevailed,respectively.Accordingly,the competitive precipitation behavior was attributed to the transition of the growth model during the reaction process.
文摘To examine the protection against reinforcement corrosion due to the combined action of CO2 and chlorides, experimental results of the evaluation of a study with three types of cement are presented. The study was performed observing the behavior of reinforcements which were put in samples submitted to accelerated carbonatation tests and accelerated tests under the effect of chlorides. For the evaluation, intensity corrosion measurements were used using the Pr （polarization resistance） technique, employing these measures as a deterioration indicator. Three types of cement available in the national market were used. The obtained results enabled the classification of the used cements, comparing their profile behaviors in the conditions of the proposed tests.
文摘In recent years,researchers have leveraged single-agent reinforcement learning to boost educational outcomes and deliver personalized interventions;yet this paradigm provides no capacity for inter-agent interaction.Multi-agent reinforcement learning(MARL)overcomes this limitation by allowing several agents to learn simultaneously within a shared environment,each choosing actions that maximize its own or the group's rewards.By explicitly modeling and exploiting agent-to-agent dynamics,MARL can align those interactions with pedagogical goals such as peer tutoring,collaborative problem-solving,or gamified competition,thus opening richer avenues for adaptive and socially informed learning experiences.This survey investigates the impact of MARL on educational outcomes by examining evidence of its effectiveness in enhancing learner performance,engagement,equity,and reducing teacher workload compared to single agent or traditional approaches.It explores the educational domains and pedagogical problems addressed by MARL,identifies the algorithmic families used,and analyzes their influence on learning.The review also assesses experimental settings and evaluation metrics to determine ecological validity,and outlines current challenges and future research directions in applying MARL to education.
基金supported by the National Natural Science Foundation of China(Grant No.42407199)Heilongjiang Provincial Natural Science Foundation of China(Grant No.PL2024D003)the Fundamental Research Funds for the Central Universities(Grant No.2572023CT17).
文摘A novel method that combines reinforced enzyme-induced carbonate precipitation(REICP)was proposed to improve the mechanical properties of dispersive soil.Dispersive soils,which are highly susceptible to erosion caused by rainfall or seepage,pose significantenvironmental challenges.It is essential to focus on modifying dispersive soil using environmentally friendly methods.This study investigated the cohesion,internal friction angle,permeability,hydrostability test,and microstructure of dispersive soil treated with enzyme-induced carbonate precipitation(EICP)-MgCl2-xanthan gum(REICP),using statistical analysis.A series of laboratory experiments was conducted,including direct shear tests,permeability experiments,mud ball tests,simulated rainfall tests,Fourier transform infrared spectroscopy(FTIR),X-ray diffraction(XRD),and scanning electron microscopy(SEM).The results showed that the combined treatment significantly enhanced the mechanical properties of dispersive soil.At the optimal ratio,cohesion increased by a factor of 2,and the permeability coefficientdecreased by approximately 1.7×10^(7)times.Additionally,the strength parameters gradually increased with curing time.Microstructural analyses indicated that calcite precipitation,pore filling,and ionic redistribution significantlyimproved the mechanical properties and hydrostability of the soil.Statistical analyses showed that EICP materials and xanthan gum increased soil cohesion,while magnesium chloride enhanced the internal friction angle and reduced porosity.This study integrates mechanical testing,statistical analysis,and microstructural evaluation to propose a sustainable and environmentally friendly method for improving dispersive soils.This approach reduces the use of chemical modifiers,minimizes environmental impacts,and demonstrates application potential in the stabilization of dispersive soils.
基金funded by Hung Yen University of Technology and Education under grand number UTEHY.L.2025.62.
文摘Unmanned Aerial Vehicles(UAVs)have become integral components in smart city infrastructures,supporting applications such as emergency response,surveillance,and data collection.However,the high mobility and dynamic topology of Flying Ad Hoc Networks(FANETs)present significant challenges for maintaining reliable,low-latency communication.Conventional geographic routing protocols often struggle in situations where link quality varies and mobility patterns are unpredictable.To overcome these limitations,this paper proposes an improved routing protocol based on reinforcement learning.This new approach integrates Q-learning with mechanisms that are both link-aware and mobility-aware.The proposed method optimizes the selection of relay nodes by using an adaptive reward function that takes into account energy consumption,delay,and link quality.Additionally,a Kalman filter is integrated to predict UAV mobility,improving the stability of communication links under dynamic network conditions.Simulation experiments were conducted using realistic scenarios,varying the number of UAVs to assess scalability.An analysis was conducted on key performance metrics,including the packet delivery ratio,end-to-end delay,and total energy consumption.The results demonstrate that the proposed approach significantly improves the packet delivery ratio by 12%–15%and reduces delay by up to 25.5%when compared to conventional GEO and QGEO protocols.However,this improvement comes at the cost of higher energy consumption due to additional computations and control overhead.Despite this trade-off,the proposed solution ensures reliable and efficient communication,making it well-suited for large-scale UAV networks operating in complex urban environments.
文摘Biobased biodegradable plastics have gained increasing attention as sustainable alternatives to petroleum-based materials in food packaging,offering biodegradability,renewability,and reduced environmental impact.This review adopts a narrative review approach,integrating studies published between 2015 and 2025 from major databases to critically evaluate the recent advances,feasibility,and limitations of biobased biodegradable plastics in food packaging.Literature was thematically analyzed by material type and functional enhancement to assess their feasibility and limitations for sustainable packaging applications.Recent advances have focused on enhancing their mechanical,barrier,and functional properties through polymer blending,nanoparticle reinforcement,and incorporation of natural bioactive agents.Starch-based bioplastics,derived from renewable sources such as corn and cassava,have been improved by blending with polylactic acid(PLA)or polybutylene succinate(PBS)and reinforcing with nanocellulose or silica to enhance flexibility,strength,and thermal stability.Incorporating plant extracts and polyphenols has added antioxidant and antimicrobial functions.PLA-based films have benefited from nanoparticle fillers like zinc oxide and lignin nanoparticles,and the integration of bioactive compounds such as tea polyphenols and hop extract has enabled multifunctional,intelligent packaging with controlled release and UV protection.Polyhydroxyalkanoates(PHAs),producedmicrobially,have been functionalizedwith tannins,ferulic acid,and other natural agents to achieve high antioxidant,antibacterial,and UV-blocking performance,while multilayer coatings have improved moisture and gas resistance.PBS composites have been enhanced using nanofillers like silver or magnesium oxide and natural additives such as quercetin and essential oils,thereby improving durability and bioactivity.Emerging materials,including chitosan-,protein-,and polysaccharide-based films,show excellent film-forming ability and compatibility with natural antimicrobials;smart systems with pH-sensing and UV-shielding functions further extend food shelf life.Despite remaining challenges such as cost,moisture sensitivity,limited scalability,and potential competition with food resources,recent progress demonstrates that biobased biodegradable plastics hold strong potential to advance sustainable,high-performance food packaging,particularly when waste is valorized.Future research should focus on improving the cost-effectiveness,scalability,and moisture resistance of biobased biodegradable plastics,while advancing waste-derived feedstocks,multifunctional smart packaging,and comprehensive life cycle assessments to ensure sustainable and practical food packaging solutions.
基金State Key Program of National Natural Science of China under grant nos.U19B2016。
文摘Frequency hopping(FH)communication has good anti-fading,anti-jamming and anti-eavesdropping capabilities,so it is one of the main ways to combat electronic jamming.In order to further improve the anti-jamming capability of FH communication,the parameters such as fixed frequency interval,hopping rate and hopping frequency in conventional FH can be assigned with time-varying characteristics.In order to set appropriate hopping parameters to improve the performance of the system in the electromagnetic environment with various types of jamming,a heuristically accelerated Q-learning(HAQL)method is proposed in this paper.Firstly,a theoretical model for the parameter decision-making of FH system is made,and the key parameters affecting the energy efficiency of the system are analyzed.Secondly,a Q-learning model in complex electromagnetic environment is proposed,which includes setting states,actions and rewards,as well as a HAQL-based decisionmaking algorithm is put forward.Lastly,simulations are carried out under different jamming environments,and simulation results show that the average energy efficiency of HAQL algorithm is higher than that of the SARSA algorithm,the e-greedy QL algorithm and the HQL-OSGM algorithm,respectively.
基金supported by the National Natural Science Foundation of China(72371052,71871042)。
文摘Cooperative pursuit poses challenges across natural,social,and technical systems,particularly when decentralized,slow-speed pursuers attempt to capture a high-speed evader with limited observation.Most existing contributions place the focus on the greedy pursuit of the evader,overlooking potential collaborations among pursuers.To tackle this issue,a decisionmaking framework of multi-agent coordinated reciprocity formation pursuit(MACRFP)via deep reinforcement learning is introduced.This framework integrates the actor-critic algorithm with the coordinated reciprocity mechanism to enhance the capability of capturing a faster evader.Initially,a local perception model is created by utilizing a cellular network to simulate limitations caused by obstacles.Next,the formation coalition of pursuit is guided by the Cartesian Oval,enabling dispersed pursuers to create a siege against the faster evader.Furthermore,a coordinated reciprocity model based on the coordination graph and the attention-based graph neural networks is developed,addressing the global coordination problem by estimating a reciprocity coefficient to adjust agents'rewards.Numerical simulations demonstrate the emergence of cooperative behaviors in cooperative besiegement,target tracking,and intelligent interception during the pursuit,indicating that the proposed algorithm enhances the feasibility and effectiveness of capturing a fast-escaping target by integrating coordinated reciprocity and coalition formation.
基金supported by the National Natural Science Foundation of China (No.12222502)。
文摘Muon scattering tomography(MST) is a powerful noninvasive imaging technique with significant applications in nuclear material detection and security screening.Traditional MST usually relies on the point of closest approach(PoCA) algorithm to reconstruct images from muon scattering data;however,PoCA often suffers from suboptimal image clarity and resolution.To overcome these challenges,we propose a novel approach that leverages reinforcement learning(RL) to enhance MST reconstruction,termed the μRL-enhanced method.By framing the MST optimization task as an RL problem,we developed an intelligent agent capable of dynamically adjusting the key PoCA parameters.The agent is trained using a multi-objective reward function that guides the optimization toward higher-quality reconstructions.Our experimental results show that theμRL-enhanced method significantly outperforms the traditional PoCA baseline acros s multiple benchmark metrics.Specifically,the proposed approach on average attains a 307% improvement in the intersection over union(IoU),a 79% increase in the structural similarity index measure(SSIM),and a 8.4% enhancement in the peak signal-to-noise ratio(PSNR) across four experiments.Furthermore,when benchmarked against the maximum likelihood scattering and displacement(MLSD)algorithm,the μRL-enhanced method offers modest gains in PS NR and IoU,together with a one-third increase in SSIM.These improvements demonstrate the enhanced reconstruction accuracy and structural fidelity of the μRL-enhanced method,highlighting its potential to advance MST technologies and their applications.
基金the National Natural Science Foundation of China(Grant No.32371823)the Liaoning Province Xingliao Talents Leading Talent Program(Grant No.XLYC2402043)the Open Foundation of State Key Laboratory of Woody Oil Resources Utilization(Grant No.SKLN EFU202517).
文摘Cellulose,the dominant natural polymer on Earth,features a distinct molecular structure with extraordinary mechanical properties and tunable characteristics,making it attractive for gel systems.Although significant progress has been made,challenges remain in fully leveraging their functional potential and broadening practical applications.This review systematically examines the properties of cellulose and cellulose gels,exploring novel reinforcement strategies—across molecular,supramolecular network,and macroscale structure levels—to enhance mechanical,electrical,and thermal performance,while coordinating these properties for practical implementations.These advancements are exemplified in emerging fields such as flexible robotics,electronic skins,flexible energy storage devices,and human-machine interaction systems.This article thoroughly investigates the fundamental characteristics,multi-scale design approaches,performance enhancement mechanisms,and cutting-edge implementations of cellulose-based gels across diverse domains.It provides a comprehensive overview of these advanced materials and offers strategic insights and recommendations for future research and innovation.
文摘Wireless Sensor Networks(WSNs)play a crucial role in numerous Internet of Things(IoT)applications and next-generation communication systems,yet they continue to face challenges in balancing energy efficiency and reliable connectivity.This study proposes SAC-HTC(Soft Actor-Critic-based High-performance Topology Control),a deep reinforcement learning(DRL)method based on the Actor-Critic framework,implemented within a Software Defined Wireless Sensor Network(SDWSN)architecture.In this approach,sensor nodes periodically transmit state information,including coordinates,node degree,transmission power,and neighbor lists,to a centralized controller.The controller acts as the reinforcement learning(RL)agent,with the Actor generating decisions to adjust transmission ranges,while the Critic evaluates action values to reflect the overall network performance.The bidirectional Node-Controller feedback mechanism enables the controller to issue appropriate control commands to each node,ensuring the maintenance of the desired node degree,reducing energy consumption,and preserving network connectivity.The algorithmfurther incorporates soft entropy adjustment to balance exploration and exploitation,alongwith an off-policy mechanism for efficient data reuse,making it well-suited to the resource-constrained conditions ofWSNs.Simulation results demonstrate that SAC-HTC not only outperforms traditional methods and several existing RL algorithms but also achieves faster convergence,optimized communication range control,global connectivity maintenance,and extended network lifetime.The key novelty of this research lies in the integration of the SAC method with the SDWSN architecture forWSNs topology control,providing an adaptive,efficient,and highly promisingmechanism for large-scale,dynamic,and high-performance sensor networks.
文摘This paper investigates the traffic offloading optimization challenge in Space-Air-Ground Integrated Networks(SAGIN)through a novel Recursive Multi-Agent Proximal Policy Optimization(RMAPPO)algorithm.The exponential growth of mobile devices and data traffic has substantially increased network congestion,particularly in urban areas and regions with limited terrestrial infrastructure.Our approach jointly optimizes unmanned aerial vehicle(UAV)trajectories and satellite-assisted offloading strategies to simultaneously maximize data throughput,minimize energy consumption,and maintain equitable resource distribution.The proposed RMAPPO framework incorporates recurrent neural networks(RNNs)to model temporal dependencies in UAV mobility patterns and utilizes a decentralized multi-agent reinforcement learning architecture to reduce communication overhead while improving system robustness.The proposed RMAPPO algorithm was evaluated through simulation experiments,with the results indicating that it significantly enhances the cumulative traffic offloading rate of nodes and reduces the energy consumption of UAVs.
文摘The increasing occurrence of corrosion-related damage in steel pipelines has led to the growing use of composite-based repair techniques as an efficient alternative to traditional replacement methods.Computer modeling and structural analysis were performed for the repair reinforcement of a steel pipeline with a composite bandage.A preliminary analysis of possible contact interaction schemes was implemented based on the theory of cylindrical shells,taking into account transverse shear deformations.The finite element method was used for a detailed study of the stress state of the composite bandage and the reinforced section of the pipeline.The limit state of the reinforced section was assessed based on the von Mises criterion for steel and the Tsai-Wu criterion for composites.The effectiveness of the repair was demonstrated on a pipeline whose wall thickness had decreased by 20%as a result of corrosion damage.At a nominal pressure of P=6 MPa,the maximum normal stress in the weakened area reached 381 MPa.The installation of a composite bandage reduced this stress to 312 MPa,making the repaired section virtually as strong as the undamaged pipeline.Due to the linearity of the problem,the results obtained can be easily used to find critical internal pressure values.
