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
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
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
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
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
This study investigates the performance of high-strength cable bolts under impact loading conditions representative of rock bursts in underground environments.Although widely used,the dynamic behaviour of these cable ...This study investigates the performance of high-strength cable bolts under impact loading conditions representative of rock bursts in underground environments.Although widely used,the dynamic behaviour of these cable bolts has received limited experimental attention,and their effectiveness in seismically active zones remains a subject of ongoing debate.To address this gap,a reverse pull-out test machine integrated with a drop hammer rig was employed.Tests were conducted on 70-t SUMO bulbed and non-bulbed cable bolts with encapsulation lengths of 300 and 450 mm,subjected to an impact energy of 14.52 k J.Results indicate that non-bulbed cables,despite showing lower initial peak loads(average 218 vs.328 k N for bulbed cables at 300 mm encapsulation),demonstrated superior energy absorption(average 11.26 vs.8.75 k J)and displacement capacity(average 48.40 vs.36.25 mm).Increasing the encapsulation length for bulbed cables led to a reduction in initial peak load but improved displacement and energy absorption.The dominant failure mechanism was debonding at the cable-grout interface,characterised by frictional sliding and cable rotation.These findings provide new insights into the energy dissipation mechanisms of cables and support the development of more resilient ground support systems for dynamically active conditions.展开更多
To address the poor mechanical performance and improve the tribological properties of self-lubricating polyphenylene sulfide/irradiation treated polytetrafluoroethylene(PPS/i-PTFE)blends,different aspect ratio carbon ...To address the poor mechanical performance and improve the tribological properties of self-lubricating polyphenylene sulfide/irradiation treated polytetrafluoroethylene(PPS/i-PTFE)blends,different aspect ratio carbon fibers(i.e.,PSCF:50,SCF:about 429)were introduced as reinforcement fillers.The results showed that the hybriding of PSCF and SCF at certain mass ratios exhibited simultaneous enhancement of mechanical and tribological performance for PPS/i-PTFE blend through the construction of synergistic lubrication and mechanical interlocking network.Specifically,the flexural strength and modulus of PPS/i-PTFE were increased by 125.6% and 389.3%,the friction coefficient and specific wear rate were decreased by 13.9% and 95%,respectively.It was worth noting that PPS composites possessed excellent integrated performance which were able to withstand sliding action under high PV(≥10 MPa·m/s)conditions,as assessed by a customized pin-on-disc tester.This work demonstrated that the formation of intact lubricating film combined with the enhanced thermal and mechanical properties were favorable for improving the tribological properties of PPS-based composites,which makes them suitable for advanced engineering applications.展开更多
Aircraft assembly is characterized by stringent precedence constraints,limited resource availability,spatial restrictions,and a high degree of manual intervention.These factors lead to considerable variability in oper...Aircraft assembly is characterized by stringent precedence constraints,limited resource availability,spatial restrictions,and a high degree of manual intervention.These factors lead to considerable variability in operator workloads and significantly increase the complexity of scheduling.To address this challenge,this study investigates the Aircraft Pulsating Assembly Line Scheduling Problem(APALSP)under skilled operator allocation,with the objective of minimizing assembly completion time.A mathematical model considering skilled operator allocation is developed,and a Q-Learning improved Particle Swarm Optimization algorithm(QLPSO)is proposed.In the algorithm design,a reverse scheduling strategy is adopted to effectively manage large-scale precedence constraints.Moreover,a reverse sequence encoding method is introduced to generate operation sequences,while a time decoding mechanism is employed to determine completion times.The problem is further reformulated as a Markov Decision Process(MDP)with explicitly defined state and action spaces.Within QLPSO,the Q-learning mechanism adaptively adjusts inertia weights and learning factors,thereby achieving a balance between exploration capability and convergence performance.To validate the effectiveness of the proposed approach,extensive computational experiments are conducted on benchmark instances of different scales,including small,medium,large,and ultra-large cases.The results demonstrate that QLPSO consistently delivers stable and high-quality solutions across all scenarios.In ultra-large-scale instances,it improves the best solution by 25.2%compared with the Genetic Algorithm(GA)and enhances the average solution by 16.9%over the Q-learning algorithm,showing clear advantages over the comparative methods.These findings not only confirm the effectiveness of the proposed algorithm but also provide valuable theoretical references and practical guidance for the intelligent scheduling optimization of aircraft pulsating assembly lines.展开更多
Bolting steel angles at the bottom ends of columns provides a rapid and efficient method for repairing damaged structures,while also offering a viable approach to restore their potential bearing capacity.To validate t...Bolting steel angles at the bottom ends of columns provides a rapid and efficient method for repairing damaged structures,while also offering a viable approach to restore their potential bearing capacity.To validate the suitability of specific strengthening strategies,particularly the utilization of bolted steel angles,three reinforced concrete frame specimens were subjected to hysteresis testing.These specimens all featured RC columns strengthened with steel angle ends.Additionally,one control specimen without steel angle ends was included in the testing.The hysteresis effects of bolting steel angles were discussed in terms of typical failure mode,hysteresis and skeleton curves,stiffness degradation and energy dissipation.The experimental results revealed that the three specimens that had bolted steel angles exhibited ductile failure behavior.Through analysis of hysteresis and skeleton curves,it was observed that the frame demonstrated distinct plasticity,maintaining sufficient load-bearing capacity even after yielding and exhibiting superior displacement ductility performance.Considering equivalent viscous damping,the energy dissipation capacity of the RC frame increased linearly with drift and remained largely unaffected by structural damage.Therefore,bolting steel angles at specified cross-sections proved to be a viable technique for structural repair and restoration.展开更多
Nonlinear static procedures are widely adopted in structural engineering practice for seismic performance assessment due to their simplicity and computational efficiency.However,their reliability depends heavily on ho...Nonlinear static procedures are widely adopted in structural engineering practice for seismic performance assessment due to their simplicity and computational efficiency.However,their reliability depends heavily on how the nonlinear behaviour of structural components is represented.The recent earthquakes in Albania(2019)and Türkiye(2023)have underscored the need for accurate assessment techniques,particularly for older reinforced concrete buildings with poor detailing.This study quantifies the discrepancies between default and user-defined component modelling in pushover analysis of pre-modern reinforced concrete structures,analysing two representative low-and mid-rise reinforced concrete frame buildings.The lumped plasticity approach incorporates moment-rotation relationships derived from actual member properties and reinforcement configurations,while the distributed plasticity approach uses software-generated default properties based on modern codes.Results show that the distributed plasticity models systematically overestimate both the strength and the deformation capacity by up to 35%compared to lumped plasticity models,especially in buildings with poor detailing and low concrete strength.These findings demonstrate that default software procedures,widely used in practice but not validated for pre-modern structures,produce dangerously unconservative seismic performance estimates.The study provides quantitative evidence of the critical need for tailored modelling strategies that reflect the actual conditions of the existing building stock.展开更多
Effective partitioning is crucial for enabling parallel restoration of power systems after blackouts.This paper proposes a novel partitioning method based on deep reinforcement learning.First,the partitioning decision...Effective partitioning is crucial for enabling parallel restoration of power systems after blackouts.This paper proposes a novel partitioning method based on deep reinforcement learning.First,the partitioning decision process is formulated as a Markov decision process(MDP)model to maximize the modularity.Corresponding key partitioning constraints on parallel restoration are considered.Second,based on the partitioning objective and constraints,the reward function of the partitioning MDP model is set by adopting a relative deviation normalization scheme to reduce mutual interference between the reward and penalty in the reward function.The soft bonus scaling mechanism is introduced to mitigate overestimation caused by abrupt jumps in the reward.Then,the deep Q network method is applied to solve the partitioning MDP model and generate partitioning schemes.Two experience replay buffers are employed to speed up the training process of the method.Finally,case studies on the IEEE 39-bus test system demonstrate that the proposed method can generate a high-modularity partitioning result that meets all key partitioning constraints,thereby improving the parallelism and reliability of the restoration process.Moreover,simulation results demonstrate that an appropriate discount factor is crucial for ensuring both the convergence speed and the stability of the partitioning training.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.
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.
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.
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.
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This study investigates the performance of high-strength cable bolts under impact loading conditions representative of rock bursts in underground environments.Although widely used,the dynamic behaviour of these cable bolts has received limited experimental attention,and their effectiveness in seismically active zones remains a subject of ongoing debate.To address this gap,a reverse pull-out test machine integrated with a drop hammer rig was employed.Tests were conducted on 70-t SUMO bulbed and non-bulbed cable bolts with encapsulation lengths of 300 and 450 mm,subjected to an impact energy of 14.52 k J.Results indicate that non-bulbed cables,despite showing lower initial peak loads(average 218 vs.328 k N for bulbed cables at 300 mm encapsulation),demonstrated superior energy absorption(average 11.26 vs.8.75 k J)and displacement capacity(average 48.40 vs.36.25 mm).Increasing the encapsulation length for bulbed cables led to a reduction in initial peak load but improved displacement and energy absorption.The dominant failure mechanism was debonding at the cable-grout interface,characterised by frictional sliding and cable rotation.These findings provide new insights into the energy dissipation mechanisms of cables and support the development of more resilient ground support systems for dynamically active conditions.
基金financially supported by the National Natural Science Foundation of China(No.52103040)China Postdoctoral Science Foundation(No.2020M673217)the Fundamental Research Funds for the Central Universities(No.2023SCU12022)。
文摘To address the poor mechanical performance and improve the tribological properties of self-lubricating polyphenylene sulfide/irradiation treated polytetrafluoroethylene(PPS/i-PTFE)blends,different aspect ratio carbon fibers(i.e.,PSCF:50,SCF:about 429)were introduced as reinforcement fillers.The results showed that the hybriding of PSCF and SCF at certain mass ratios exhibited simultaneous enhancement of mechanical and tribological performance for PPS/i-PTFE blend through the construction of synergistic lubrication and mechanical interlocking network.Specifically,the flexural strength and modulus of PPS/i-PTFE were increased by 125.6% and 389.3%,the friction coefficient and specific wear rate were decreased by 13.9% and 95%,respectively.It was worth noting that PPS composites possessed excellent integrated performance which were able to withstand sliding action under high PV(≥10 MPa·m/s)conditions,as assessed by a customized pin-on-disc tester.This work demonstrated that the formation of intact lubricating film combined with the enhanced thermal and mechanical properties were favorable for improving the tribological properties of PPS-based composites,which makes them suitable for advanced engineering applications.
基金supported by the National Natural Science Foundation of China(Grant No.52475543)Natural Science Foundation of Henan(Grant No.252300421101)+1 种基金Henan Province University Science and Technology Innovation Talent Support Plan(Grant No.24HASTIT048)Science and Technology Innovation Team Project of Zhengzhou University of Light Industry(Grant No.23XNKJTD0101).
文摘Aircraft assembly is characterized by stringent precedence constraints,limited resource availability,spatial restrictions,and a high degree of manual intervention.These factors lead to considerable variability in operator workloads and significantly increase the complexity of scheduling.To address this challenge,this study investigates the Aircraft Pulsating Assembly Line Scheduling Problem(APALSP)under skilled operator allocation,with the objective of minimizing assembly completion time.A mathematical model considering skilled operator allocation is developed,and a Q-Learning improved Particle Swarm Optimization algorithm(QLPSO)is proposed.In the algorithm design,a reverse scheduling strategy is adopted to effectively manage large-scale precedence constraints.Moreover,a reverse sequence encoding method is introduced to generate operation sequences,while a time decoding mechanism is employed to determine completion times.The problem is further reformulated as a Markov Decision Process(MDP)with explicitly defined state and action spaces.Within QLPSO,the Q-learning mechanism adaptively adjusts inertia weights and learning factors,thereby achieving a balance between exploration capability and convergence performance.To validate the effectiveness of the proposed approach,extensive computational experiments are conducted on benchmark instances of different scales,including small,medium,large,and ultra-large cases.The results demonstrate that QLPSO consistently delivers stable and high-quality solutions across all scenarios.In ultra-large-scale instances,it improves the best solution by 25.2%compared with the Genetic Algorithm(GA)and enhances the average solution by 16.9%over the Q-learning algorithm,showing clear advantages over the comparative methods.These findings not only confirm the effectiveness of the proposed algorithm but also provide valuable theoretical references and practical guidance for the intelligent scheduling optimization of aircraft pulsating assembly lines.
基金National Key R&D Program of China under Grant No.2023YFC3805100Technologies R&D Project of China Construction First Group Corporation Limited under Grant No.PT-2022-09National Natural Science Foundation of China under Grant No.52178126。
文摘Bolting steel angles at the bottom ends of columns provides a rapid and efficient method for repairing damaged structures,while also offering a viable approach to restore their potential bearing capacity.To validate the suitability of specific strengthening strategies,particularly the utilization of bolted steel angles,three reinforced concrete frame specimens were subjected to hysteresis testing.These specimens all featured RC columns strengthened with steel angle ends.Additionally,one control specimen without steel angle ends was included in the testing.The hysteresis effects of bolting steel angles were discussed in terms of typical failure mode,hysteresis and skeleton curves,stiffness degradation and energy dissipation.The experimental results revealed that the three specimens that had bolted steel angles exhibited ductile failure behavior.Through analysis of hysteresis and skeleton curves,it was observed that the frame demonstrated distinct plasticity,maintaining sufficient load-bearing capacity even after yielding and exhibiting superior displacement ductility performance.Considering equivalent viscous damping,the energy dissipation capacity of the RC frame increased linearly with drift and remained largely unaffected by structural damage.Therefore,bolting steel angles at specified cross-sections proved to be a viable technique for structural repair and restoration.
文摘Nonlinear static procedures are widely adopted in structural engineering practice for seismic performance assessment due to their simplicity and computational efficiency.However,their reliability depends heavily on how the nonlinear behaviour of structural components is represented.The recent earthquakes in Albania(2019)and Türkiye(2023)have underscored the need for accurate assessment techniques,particularly for older reinforced concrete buildings with poor detailing.This study quantifies the discrepancies between default and user-defined component modelling in pushover analysis of pre-modern reinforced concrete structures,analysing two representative low-and mid-rise reinforced concrete frame buildings.The lumped plasticity approach incorporates moment-rotation relationships derived from actual member properties and reinforcement configurations,while the distributed plasticity approach uses software-generated default properties based on modern codes.Results show that the distributed plasticity models systematically overestimate both the strength and the deformation capacity by up to 35%compared to lumped plasticity models,especially in buildings with poor detailing and low concrete strength.These findings demonstrate that default software procedures,widely used in practice but not validated for pre-modern structures,produce dangerously unconservative seismic performance estimates.The study provides quantitative evidence of the critical need for tailored modelling strategies that reflect the actual conditions of the existing building stock.
基金funded by the Beijing Engineering Research Center of Electric Rail Transportation.
文摘Effective partitioning is crucial for enabling parallel restoration of power systems after blackouts.This paper proposes a novel partitioning method based on deep reinforcement learning.First,the partitioning decision process is formulated as a Markov decision process(MDP)model to maximize the modularity.Corresponding key partitioning constraints on parallel restoration are considered.Second,based on the partitioning objective and constraints,the reward function of the partitioning MDP model is set by adopting a relative deviation normalization scheme to reduce mutual interference between the reward and penalty in the reward function.The soft bonus scaling mechanism is introduced to mitigate overestimation caused by abrupt jumps in the reward.Then,the deep Q network method is applied to solve the partitioning MDP model and generate partitioning schemes.Two experience replay buffers are employed to speed up the training process of the method.Finally,case studies on the IEEE 39-bus test system demonstrate that the proposed method can generate a high-modularity partitioning result that meets all key partitioning constraints,thereby improving the parallelism and reliability of the restoration process.Moreover,simulation results demonstrate that an appropriate discount factor is crucial for ensuring both the convergence speed and the stability of the partitioning training.
