Conventional ignition methods are proving to be ineffective for low-sensitivity energetic materials,highlighting the need to investigate alternative ignition systems,such as laser-based techniques.Over the past decade...Conventional ignition methods are proving to be ineffective for low-sensitivity energetic materials,highlighting the need to investigate alternative ignition systems,such as laser-based techniques.Over the past decade,lasers have emerged as a promising solution,providing focused energy beams for controllable,efficient,and reliable ignition in the field of energetic materials.This study presents a comparative analysis of two state-of-the-art ignition approaches:direct laser ignition and laser-driven flyer ignition.Experiments were performed using a Neodymium-doped Yttrium Aluminum Garnet(Nd:YAG)laser at different energy beam levels to systematically evaluate ignition onset.In the direct laser ignition test setup,the laser beam was applied directly to the energetic tested material,while laserdriven flyer ignition utilized 40 and 100μm aluminum foils,propelled at velocities ranging from 300 to 1250 m/s.Comparative analysis with the Lawrence and Trott model substantiated the velocity data and provided insight into the ignition mechanisms.Experimental results indicate that the ignition time for the laser-driven flyer method was significantly shorter,with the pyrotechnic composition achieving complete combustion faster compared to direct laser ignition.Moreover,precise ignition thresholds were determined for both methods,providing critical parameters for optimizing ignition systems in energetic materials.This work elucidates the advantages and limitations of each technique while advancing next-generation ignition technology,enhancing the reliability and safety of propulsion systems.展开更多
Microstructures and mechanical properties of LZ83?xY alloys containingI-phase andW-phase were investigated by XRD, OM, SEM and EDS. The experimental results show that the content ofI-phase andW-phase changes by varyin...Microstructures and mechanical properties of LZ83?xY alloys containingI-phase andW-phase were investigated by XRD, OM, SEM and EDS. The experimental results show that the content ofI-phase andW-phase changes by varying Zn/Y mass ratio in the LZ83?xY alloys. The cohesion ofI-phase/α-Mg eutectic pockets can enhance the strength in the as-cast LZ83?0.5Y and LZ83?1.0Y alloys, while theW-phase has no obvious strengthening effect on the LZ83?1.5Y alloy. In the extruded alloys, the I-phase andW-phase were extruded into the particles with nanoscale size in theβ-Li matrix phase. The dispersion strengthening of W-phase was more obvious because of the higher volume fraction. The ultimate tensile strength of extruded LZ83?1.5Y alloy is up to 238 MPa while the elongation is up to 20%.展开更多
Dissimilar welding of NiTi and stainless steel(SS)for multifunctional device fabrication is challenging due to the brittle nature of intermetallic compounds(IMCs)that are formed in the weld zone.In this work,Ni and Nb...Dissimilar welding of NiTi and stainless steel(SS)for multifunctional device fabrication is challenging due to the brittle nature of intermetallic compounds(IMCs)that are formed in the weld zone.In this work,Ni and Nb interlayers were applied for the resistance spot welding(RSW)of NiTi and SS to replace the harmful Fe_(2)Ti phase and to restrict the mixing of dissimilar molten metals,respectively.Microstructural evolution and mechanical properties of the joints were investigated.It was shown that a conventional weld nugget was created in the absence of any interlayer in the welded joint suffering from traversed cracks due to the formation of brittle IMCs network in the fusion zone(FZ).By the addition of Ni from the interlayer,Fe_(2)Ti dominated weld nugget was efficaciously replaced by Ni_(3)Ti phase;however,the presence of the large pore and cracks reduced the effective joining area.The use of a Nb interlayer resulted in a fundamentally different joint,in which FZs at NiTi and SS sides separated by the unmolten Nb would suppress the mixing of dissimilar molten metals.Nb-containing eutectic structures with low brittleness formed at the interfaces,contributing to the enhancement of joint strength(increased by 38%on fracture load and 460%on energy absorption).A high-melting-point interlayer showed great potential to realize a reliable and high-performing RSWed NiTi-SS joint.展开更多
Cu-Zn alloy (Brass) is widely used as an industrial material because of its excellent characteristics such as high corrosion resistance, non-magnetism and good forging ability. This paper evaluates the mechanical and ...Cu-Zn alloy (Brass) is widely used as an industrial material because of its excellent characteristics such as high corrosion resistance, non-magnetism and good forging ability. This paper evaluates the mechanical and microstructure properties of α-brass alloy gotten from scrap copper and zinc metal, and compares the properties with normal α-brass billets. Five different compositions of the α-brass alloy (Cu-5%Zn, Cu-10%Zn, Cu-15%Zn, Cu-20%Zn, Cu-30%Zn) were produced from scraps of copper wire and zinc batteries casing respectively by method of sand casting. The parts of the cast rods were machined to a specification of 60 mm × 100 mm × 300 mm on a lathe to obtain tensile test specimens. After homogenization annealing, the samples were heated in an electric furnace at 500℃ for 3 hours. The samples were etched with ferric chloride solution for 20 seconds and sent for metallographic examination. The result of the hardness test shows variation in hardness of the cast Cu-Zn alloys with increasing zinc content. The ductility and elongation of the α-brass decrease with increasing zinc content. The colouration of the α-brass changed from red to yellow as the zinc content increases. In conclusion, hard brass can be obtained from recycled Cu and Zn as compared to normal brass billets.展开更多
Recent advancements in machine learning and computer vision enable direct prediction of mechanical properties from microstructure images.The feasibility of this process hinges on the material structure-property relati...Recent advancements in machine learning and computer vision enable direct prediction of mechanical properties from microstructure images.The feasibility of this process hinges on the material structure-property relationship,richness of the dataset,and the choice of machine learning approach.This study investigates the application of a deep learning model to directly predict the yield strength(YS),ultimate tensile strength(UTS),and true stress-strain curve of the cast-forged AZ80 alloys from SEM microstructure images.We manufactured 27 cast-forged AZ80 magnesium alloy components using varied process parameters,creating a diverse dataset of AZ80 microstructures and mechanical properties through their characterization.In addition to predicting magnesium alloy properties,we address challenges related to data imbalance,brightness and contrast variability,and microstructure long-range heterogeneity.We demonstrate that synthetic data oversampling using a denoising diffusion probabilistic model effectively improves the model’s prediction accuracy via balancing the minority classes.A rigorous analysis of the model’s performance shows that the model accurately predicts the YS,UTS,and Ramberg-Osgood equation’s parameters(K and n).In image-out validation,the model achieves average percentage errors of 2.10%(YS),2.15%(UTS),1.50%(K),and 5.47%(n).In class-out validation,the errors are 6.27%,9.58%,4.69%,and 10.24%,respectively.展开更多
Dual atomic catalysts(DAC),particularly copper(Cu_(2))-based nitrogen(N)doped graphene,show great potential to effectively convert CO_(2)and nitrate(NO_(3)-)into important industrial chemicals such as ethylene,glycol,...Dual atomic catalysts(DAC),particularly copper(Cu_(2))-based nitrogen(N)doped graphene,show great potential to effectively convert CO_(2)and nitrate(NO_(3)-)into important industrial chemicals such as ethylene,glycol,acetamide,and urea through an efficient catalytical process that involves C–C and C–N coupling.However,the origin of the coupling activity remained unclear,which substantially hinders the rational design of Cu-based catalysts for the N-integrated CO_(2)reduction reaction(CO_(2)RR).To address this challenge,this work performed advanced density functional theory calculations incorporating explicit solvation based on a Cu_(2)-based N-doped carbon(Cu_(2)N_(6)C_(10))catalyst for CO_(2)RR.These calculations are aimed to gain insight into the reaction mechanisms for the synthesis of ethylene,acetamide,and urea via coupling in the interfacial reaction micro-environment.Due to the sluggishness of CO_(2),the formation of a solvation electric layer by anions(F^(-),Cl^(-),Br^(-),and I^(-))and cations(Na+,Mg^(2+),K+,and Ca^(2+))leads to electron transfer towards the Cu surface.This process significantly accelerates the reduction of CO_(2).These results reveal that*CO intermediates play a pivotal role in N-integrated CO_(2)RR.Remarkably,the Cu_(2)-based N-doped carbon catalyst examined in this study has demonstrated the most potential for C–N coupling to date.Our findings reveal that through the process of a condensation reaction between*CO and NH_(2)OH for urea synthesis,*NO_(3)-is reduced to*NH_(3),and*CO_(2)to*CCO at dual Cu atom sites.This dual-site reduction facilitates the synthesis of acetamide through a nucleophilic reaction between NH_(3)and the ketene intermediate.Furthermore,we found that the I-and Mg^(2+)ions,influenced by pH,were highly effective for acetamide and ammonia synthesis,except when F-and Ca^(2+)were present.Furthermore,the mechanisms of C–N bond formation were investigated via ab-initio molecular dynamics simulations,and we found that adjusting the micro-environment can change the dominant side reaction,shifting from hydrogen production in acidic conditions to water reduction in alkaline ones.This study introduces a novel approach using ion-H_(2)O cages to significantly enhance the efficiency of C–N coupling reactions.展开更多
An effective energy management strategy(EMS)is essential to optimize the energy efficiency of electric vehicles(EVs).With the advent of advanced machine learning techniques,the focus on developing sophisticated EMS fo...An effective energy management strategy(EMS)is essential to optimize the energy efficiency of electric vehicles(EVs).With the advent of advanced machine learning techniques,the focus on developing sophisticated EMS for EVs is increasing.Here,we introduce LearningEMS:a unified framework and open-source benchmark designed to facilitate rapid development and assessment of EMS.LearningEMS is distinguished by its ability to support a variety of EV configurations,including hybrid EVs,fuel cell EVs,and plug-in EVs,offering a general platform for the development of EMS.The framework enables detailed comparisons of several EMS algorithms,encompassing imitation learning,deep reinforcement learning(RL),offline RL,model predictive control,and dynamic programming.We rigorously evaluated these algorithms across multiple perspectives:energy efficiency,consistency,adaptability,and practicability.Furthermore,we discuss state,reward,and action settings for RL in EV energy management,introduce a policy extraction and reconstruction method for learning-based EMS deployment,and conduct hardware-in-the-loop experiments.In summary,we offer a unified and comprehensive framework that comes with three distinct EV platforms,over 10000 km of EMS policy data set,ten state-of-the-art algorithms,and over 160 benchmark tasks,along with three learning libraries.Its flexible design allows easy expansion for additional tasks and applications.The open-source algorithms,models,data sets,and deployment processes foster additional research and innovation in EV and broader engineering domains.展开更多
The management of agricultural wastes is essential for resource conservation and environmental sustainability.Due to escalating worries regarding plastic pollution and the surging expenses linked to petroleum-based pl...The management of agricultural wastes is essential for resource conservation and environmental sustainability.Due to escalating worries regarding plastic pollution and the surging expenses linked to petroleum-based plastics,there has been a notable transition towards the creation of biodegradable alternatives sourced from natural materials.Biofibres and bioplastics,especially those derived from agricultural waste,have garnered significant attention for their prospective uses in food packaging,biomedical sciences,and sustainable manufacturing.This study examines the viability of employing banana peel as a natural and environmentally sustainable raw material for the production of biodegradable bioplastic sheets.Due to its abundant polysaccharides and lignocellulosic fibers,banana peel presents advantageous structural and mechanical characteristics for bioplastic manufacturing.Experimental findings demonstrate that bioplastic derived from banana peels has enhanced biodegradability and environmental compatibility relative to traditional synthetic plastics,positioning it as a feasible alternative to mitigate the worldwide plastic waste epidemic.An optimal formulation was constructed using Design Expert software,comprising 55.38 g of banana peel,27.63 g of fish scales,and 20 g of chitosan powder.This formulation improves the film’s tensile strength,flexibility,and degradation rate,ensuring its efficacy in industrial applications including food packaging and molding.The study’s results highlight the promise of bioplastics made from banana peels as an economical and sustainable alternative,decreasing dependence on petroleum-based plastics and alleviating environmental pollution.展开更多
In order to study the deformation behavior and evaluate the workability of the dual-phase Mg-9Li-3Al-2Sr alloy, isothermal hot compression tests were conducted using the Gleeble-3500 thermal-mechanical simulator, in r...In order to study the deformation behavior and evaluate the workability of the dual-phase Mg-9Li-3Al-2Sr alloy, isothermal hot compression tests were conducted using the Gleeble-3500 thermal-mechanical simulator, in ranges of elevated temperatures （423-573 K） and strain rates （0.001-1 s^-1）. Plastic instability is evident during the deformation which is in the form of serrated flow; serrated yielding is attributed to the locking of mobile dislocations by the Mg and Li atoms which diffuse during the deformation. The relationships between flow stress, strain rate and deformation temperature were analyzed and the deformation activation energy and some basic material factors at different strains were calculated using the Arrhenius equation. The effects of temperature and strain rate on deformation behavior were represented using the Zener–Hollomon parameter in an exponent-type equation. To verify the validity of the constitutive model, the predicted values and experimental flow curves under different deformation conditions were compared, the correlation coefficient （0.9970） and average absolute relative error （AARE=4.41%） were calculated. The results indicate that the constitutive model can be used to accurately predict the flow behavior of dual-phase Mg-9Li-3Al-2Sr alloy during high temperature deformation.展开更多
Lane detection is a fundamental aspect of most current advanced driver assistance systems(ADASs). A large number of existing results focus on the study of vision-based lane detection methods due to the extensive knowl...Lane detection is a fundamental aspect of most current advanced driver assistance systems(ADASs). A large number of existing results focus on the study of vision-based lane detection methods due to the extensive knowledge background and the low-cost of camera devices. In this paper, previous visionbased lane detection studies are reviewed in terms of three aspects, which are lane detection algorithms, integration, and evaluation methods. Next, considering the inevitable limitations that exist in the camera-based lane detection system, the system integration methodologies for constructing more robust detection systems are reviewed and analyzed. The integration methods are further divided into three levels, namely, algorithm, system,and sensor. Algorithm level combines different lane detection algorithms while system level integrates other object detection systems to comprehensively detect lane positions. Sensor level uses multi-modal sensors to build a robust lane recognition system. In view of the complexity of evaluating the detection system, and the lack of common evaluation procedure and uniform metrics in past studies, the existing evaluation methods and metrics are analyzed and classified to propose a better evaluation of the lane detection system. Next, a comparison of representative studies is performed. Finally, a discussion on the limitations of current lane detection systems and the future developing trends toward an Artificial Society, Computational experiment-based parallel lane detection framework is proposed.展开更多
Next-generation vehicle control and future autonomous driving require further advances in vehicle dynamic state estimation. This article provides a concise review, along with the perspectives, of the recent developmen...Next-generation vehicle control and future autonomous driving require further advances in vehicle dynamic state estimation. This article provides a concise review, along with the perspectives, of the recent developments in the estimation of vehicle dynamic states. The definitions used in vehicle dynamic state estimation are first introduced, and alternative estimation structures are presented. Then, the sensor configuration schemes used to estimate vehicle velocity, sideslip angle, yaw rate and roll angle are presented. The vehicle models used for vehicle dynamic state estimation are further summarized, and representative estimation approaches are discussed. Future concerns and perspectives for vehicle dynamic state estimation are also discussed.展开更多
Since the discovery of graphene, many efforts have been done to modify the graphene structure for integrating this novel material to nanoelectronics, fuel cells, energy storage devices and in many other applications. ...Since the discovery of graphene, many efforts have been done to modify the graphene structure for integrating this novel material to nanoelectronics, fuel cells, energy storage devices and in many other applications. This leads to the production of different types of graphene-based materials, which possess properties different from those of pure graphene. Porous graphene is an example of this type of materials. It can be considered as a graphene sheet with some holes/pores within the atomic plane. Due to its spongy structure, porous graphene can have potential applications as membranes for molecular sieving, energy storage components and in nanoelectronics. In this review, we present the recent progress in the synthesis of porous graphene. The properties and the potential applications of this new material are also discussed.展开更多
Shared control schemes allow a human driver to work with an automated driving agent in driver-vehicle systems while retaining the driver’s abilities to control.The human driver,as an essential agent in the driver-veh...Shared control schemes allow a human driver to work with an automated driving agent in driver-vehicle systems while retaining the driver’s abilities to control.The human driver,as an essential agent in the driver-vehicle shared control systems,should be precisely modeled regarding their cognitive processes,control strategies,and decision-making processes.The interactive strategy design between drivers and automated driving agents brings an excellent challenge for human-centric driver assistance systems due to the inherent characteristics of humans.Many open-ended questions arise,such as what proper role of human drivers should act in a shared control scheme?How to make an intelligent decision capable of balancing the benefits of agents in shared control systems?Due to the advent of these attentions and questions,it is desirable to present a survey on the decision making between human drivers and highly automated vehicles,to understand their architectures,human driver modeling,and interaction strategies under the driver-vehicle shared schemes.Finally,we give a further discussion on the key future challenges and opportunities.They are likely to shape new potential research directions.展开更多
Di erential braking and active steering have already been integrated to overcome their shortcomings. However, existing research mainly focuses on two-axle vehicles and controllers are mostly designed to use one contro...Di erential braking and active steering have already been integrated to overcome their shortcomings. However, existing research mainly focuses on two-axle vehicles and controllers are mostly designed to use one control method to improve the other. Moreover, many experiments are needed to improve the robustness; therefore, these control methods are underutilized. This paper proposes an integrated control system specially designed for multi-axle vehicles, in which the desired lateral force and yaw moment of vehicles are determined by the sliding mode control algorithm. The output of the sliding mode control is distributed to the suitable wheels based on the abilities and potentials of the two control methods. Moreover, in this method, fewer experiments are needed, and the robustness and simultaneity are both guaranteed. To simplify the optimization system and to improve the computation speed, seven simple optimization subsystems are designed for the determination of control outputs on each wheel. The simulation results show that the proposed controller obviously enhances the stability of multi-axle trucks. The system improves 68% of the safe velocity, and its performance is much better than both di erential braking and active steering. This research proposes an integrated control system that can simultaneously invoke di erential braking and active steering of multi-axle vehicles to fully utilize the abilities and potentials of the two control methods.展开更多
Planning and decision-making technology at intersections is a comprehensive research problem in intelligent transportation systems due to the uncertainties caused by a variety of traffic participants.As wireless commu...Planning and decision-making technology at intersections is a comprehensive research problem in intelligent transportation systems due to the uncertainties caused by a variety of traffic participants.As wireless communication advances,vehicle infrastructure integrated algorithms designed for intersection planning and decision-making have received increasing attention.In this paper,the recent studies on the planning and decision-making technologies at intersections are primarily overviewed.The general planning and decision-making approaches are presented,which include graph-based approach,prediction base approach,optimization-based approach and machine learning based approach.Since connected autonomous vehicles(CAVs)is the future direction for the automated driving area,we summarized the evolving planning and decision-making methods based on vehicle infrastructure cooperative technologies.Both four-way signalized and unsignalized intersection(s)are investigated under purely automated driving traffic and mixed traffic.The study benefit from current strategies,protocols,and simulation tools to help researchers identify the presented approaches’challenges and determine the research gaps,and several remaining possible research problems that need to be solved in the future.展开更多
The effect of set-back distance on the thermo-mechanical behavior of the strip during twin roll casting(TRC)of an AZ31 magnesium alloy was modeled using finite element method(FEM).Model validation was done by comparin...The effect of set-back distance on the thermo-mechanical behavior of the strip during twin roll casting(TRC)of an AZ31 magnesium alloy was modeled using finite element method(FEM).Model validation was done by comparing the predicted and measured exit strip surface temperature as well as the secondary dendrite arm spacing(SDAS)through the thickness of the sheet to those measured during experiments.Model results showed as the set-back distance increases,the strip exit temperature decreases and the solidification front moves toward the entry of the roll gap.The cast strip also experiences more plastic deformation and consequently,the normal stress on the strip surface and effective strain at the strip center-line increase.Moreover,higher separating forces were predicted for longer set-back distances.Model predictions showed that changing the set-back distance by varying the final thickness has a more significant effect on the temperature and stress-strain fields than altering the nozzle opening height.展开更多
The accumulative roll-bonding(ARB)process was applied on the strips of aluminum alloy 1050 in two processing conditions:cold ARB and warm ARB.The results of tensile tests and microhardness measurement show that the wa...The accumulative roll-bonding(ARB)process was applied on the strips of aluminum alloy 1050 in two processing conditions:cold ARB and warm ARB.The results of tensile tests and microhardness measurement show that the warm ARB process exhibits the lower tensile strength and microhardness,more homogeneous distribution of the microhardness,higher elongation,and especially superior planar isotropy of the tensile properties in comparison to the cold ARB,because of the intermediate heat treatment as well as the elevated temperature rolling in the warm ARB process.Furthermore,with increasing the cycles of both processes,the planar isotropy decreases progressively.展开更多
To improve the safety and driving stability of the autonomous heavy truck, it is necessary to consider the differences of driving behavior and drivable trajectories between the heavy trucks and passenger cars. This st...To improve the safety and driving stability of the autonomous heavy truck, it is necessary to consider the differences of driving behavior and drivable trajectories between the heavy trucks and passenger cars. This study proposes a probabilistic decision-making and trajectory planning framework for the autonomous heavy trucks. Firstly, the driving decision process is divided into intention generation and feasibility evaluations, which are realized using the utility theory and risk assessment, respectively. Subsequently the driving decision is made and sent to the trajectory planning module. In order to reflect the greater risks of the truck to other surrounding vehicles, the aggressiveness index(AI) is proposed and quantified to infer the asymmetrical risk level of lane-change maneuver. In the planning stage, the lateral and roll dynamics stability domains are developed as the constraints to exclude the candidate trajectories that would cause vehicle instability. Finally, the simulation results are compared between the proposed model and the artificial potential filed model in the scenarios extracted from the naturalistic driving data. It is shown that the proposed framework can provide the human-like lane-change decisions and truck-friendly trajectories, and performs well in dynamic driving environments.展开更多
To overcome the limitation in formability at room temperature,manufacturers have developed magnesium alloys with remarkable properties by adding rare-earth elements.The rare-earth magnesium alloys behave differently f...To overcome the limitation in formability at room temperature,manufacturers have developed magnesium alloys with remarkable properties by adding rare-earth elements.The rare-earth magnesium alloys behave differently from the conventional alloys,especially with respect to their coupled anisotropic and strain rate sensitive behavior.In the current work,such behavior of the rare-earth Mg alloy ZEK100 sheet at room temperature is investigated with the aid of the elastic viscoplastic self-consistent polycrystal plasticity model.Different strain rate sensitivities(SRSs)for various deformation modes are employed by the model to simulate the strain rate sensitive behaviors under different loading directions and loading rates.Good agreement between the experiments and simulations reveals the importance and necessity of using different SRSs for each deformation mode in hexagonal close-packed metals.Furthermore,the relative activities of each deformation mode and the texture evolution during different loadings are discussed.The anisotropic and strain rate sensitive behavior is ascribed to the various operating deformation modes with different SRSs during loading along different directions.展开更多
The cooperation between an autonomous vehicle and a nearby vehicle is critical to ensure driving safety in the laneexchanging scenario.The nearby vehicle trajectory needs to be predicted,from which the autonomous vehi...The cooperation between an autonomous vehicle and a nearby vehicle is critical to ensure driving safety in the laneexchanging scenario.The nearby vehicle trajectory needs to be predicted,from which the autonomous vehicle is controlled to prevent possible collisions.This paper proposes a lane-exchanging driving strategy for the autonomous vehicle to cooperate with the nearby vehicle by integrating vehicle trajectory prediction and motion control.A trajectory prediction method is developed to anticipate the nearby vehicle trajectory.The Gaussian mixture model(GMM),together with the vehicle kinematic model,are synthesized to predict the nearby vehicle trajectory.A potential-feldbased model predictive control(MPC)approach is utilized by the autonomous vehicle to conduct the lane-exchanging maneuver.The potential feld of the nearby vehicle is considered in the controller design for collision avoidance.On-road driving data verifcation shows that the nearby vehicle trajectory can be predicted by the proposed method.CarSim®simulations validate that the autonomous vehicle can perform the lane-exchanging maneuver and avoid the nearby vehicle using the proposed driving strategy.The autonomous vehicle can thus safely perform the laneexchanging maneuver and avoid the nearby vehicle.展开更多
文摘Conventional ignition methods are proving to be ineffective for low-sensitivity energetic materials,highlighting the need to investigate alternative ignition systems,such as laser-based techniques.Over the past decade,lasers have emerged as a promising solution,providing focused energy beams for controllable,efficient,and reliable ignition in the field of energetic materials.This study presents a comparative analysis of two state-of-the-art ignition approaches:direct laser ignition and laser-driven flyer ignition.Experiments were performed using a Neodymium-doped Yttrium Aluminum Garnet(Nd:YAG)laser at different energy beam levels to systematically evaluate ignition onset.In the direct laser ignition test setup,the laser beam was applied directly to the energetic tested material,while laserdriven flyer ignition utilized 40 and 100μm aluminum foils,propelled at velocities ranging from 300 to 1250 m/s.Comparative analysis with the Lawrence and Trott model substantiated the velocity data and provided insight into the ignition mechanisms.Experimental results indicate that the ignition time for the laser-driven flyer method was significantly shorter,with the pyrotechnic composition achieving complete combustion faster compared to direct laser ignition.Moreover,precise ignition thresholds were determined for both methods,providing critical parameters for optimizing ignition systems in energetic materials.This work elucidates the advantages and limitations of each technique while advancing next-generation ignition technology,enhancing the reliability and safety of propulsion systems.
基金Project(2007CB613702)supported by the National Basic Research Program of ChinaProject(CDJZR14130007)supported by the Fundamental Research Funds for the Central Universities,China
文摘Microstructures and mechanical properties of LZ83?xY alloys containingI-phase andW-phase were investigated by XRD, OM, SEM and EDS. The experimental results show that the content ofI-phase andW-phase changes by varying Zn/Y mass ratio in the LZ83?xY alloys. The cohesion ofI-phase/α-Mg eutectic pockets can enhance the strength in the as-cast LZ83?0.5Y and LZ83?1.0Y alloys, while theW-phase has no obvious strengthening effect on the LZ83?1.5Y alloy. In the extruded alloys, the I-phase andW-phase were extruded into the particles with nanoscale size in theβ-Li matrix phase. The dispersion strengthening of W-phase was more obvious because of the higher volume fraction. The ultimate tensile strength of extruded LZ83?1.5Y alloy is up to 238 MPa while the elongation is up to 20%.
基金Natural Sciences and Engineering Research Council of Canada(NSERC)Canada Research Chairs(CRC)+1 种基金K.Z.acknowledges support from China Scholarship Council(CSC)J.P.O.acknowledges funding by national funds from FCT-Fundação para a Ciência e a Tecnologia,I.P.,in the scope of the projects LA/P/0037/2020,UIDP/50025/2020 and UIDB/50025/2020 of the Associate Laboratory Institute of Nanostructures,Nanomodelling and Nanofabrication–i3N.
文摘Dissimilar welding of NiTi and stainless steel(SS)for multifunctional device fabrication is challenging due to the brittle nature of intermetallic compounds(IMCs)that are formed in the weld zone.In this work,Ni and Nb interlayers were applied for the resistance spot welding(RSW)of NiTi and SS to replace the harmful Fe_(2)Ti phase and to restrict the mixing of dissimilar molten metals,respectively.Microstructural evolution and mechanical properties of the joints were investigated.It was shown that a conventional weld nugget was created in the absence of any interlayer in the welded joint suffering from traversed cracks due to the formation of brittle IMCs network in the fusion zone(FZ).By the addition of Ni from the interlayer,Fe_(2)Ti dominated weld nugget was efficaciously replaced by Ni_(3)Ti phase;however,the presence of the large pore and cracks reduced the effective joining area.The use of a Nb interlayer resulted in a fundamentally different joint,in which FZs at NiTi and SS sides separated by the unmolten Nb would suppress the mixing of dissimilar molten metals.Nb-containing eutectic structures with low brittleness formed at the interfaces,contributing to the enhancement of joint strength(increased by 38%on fracture load and 460%on energy absorption).A high-melting-point interlayer showed great potential to realize a reliable and high-performing RSWed NiTi-SS joint.
文摘Cu-Zn alloy (Brass) is widely used as an industrial material because of its excellent characteristics such as high corrosion resistance, non-magnetism and good forging ability. This paper evaluates the mechanical and microstructure properties of α-brass alloy gotten from scrap copper and zinc metal, and compares the properties with normal α-brass billets. Five different compositions of the α-brass alloy (Cu-5%Zn, Cu-10%Zn, Cu-15%Zn, Cu-20%Zn, Cu-30%Zn) were produced from scraps of copper wire and zinc batteries casing respectively by method of sand casting. The parts of the cast rods were machined to a specification of 60 mm × 100 mm × 300 mm on a lathe to obtain tensile test specimens. After homogenization annealing, the samples were heated in an electric furnace at 500℃ for 3 hours. The samples were etched with ferric chloride solution for 20 seconds and sent for metallographic examination. The result of the hardness test shows variation in hardness of the cast Cu-Zn alloys with increasing zinc content. The ductility and elongation of the α-brass decrease with increasing zinc content. The colouration of the α-brass changed from red to yellow as the zinc content increases. In conclusion, hard brass can be obtained from recycled Cu and Zn as compared to normal brass billets.
基金the financial contribution from the Natural Sciences and Engineering Research Council of Canada (NSERC), through their Strategic Partnership Grant STPGP 521551in part by support provided by the Digital Research Alliance of Canada (alliance can.ca)
文摘Recent advancements in machine learning and computer vision enable direct prediction of mechanical properties from microstructure images.The feasibility of this process hinges on the material structure-property relationship,richness of the dataset,and the choice of machine learning approach.This study investigates the application of a deep learning model to directly predict the yield strength(YS),ultimate tensile strength(UTS),and true stress-strain curve of the cast-forged AZ80 alloys from SEM microstructure images.We manufactured 27 cast-forged AZ80 magnesium alloy components using varied process parameters,creating a diverse dataset of AZ80 microstructures and mechanical properties through their characterization.In addition to predicting magnesium alloy properties,we address challenges related to data imbalance,brightness and contrast variability,and microstructure long-range heterogeneity.We demonstrate that synthetic data oversampling using a denoising diffusion probabilistic model effectively improves the model’s prediction accuracy via balancing the minority classes.A rigorous analysis of the model’s performance shows that the model accurately predicts the YS,UTS,and Ramberg-Osgood equation’s parameters(K and n).In image-out validation,the model achieves average percentage errors of 2.10%(YS),2.15%(UTS),1.50%(K),and 5.47%(n).In class-out validation,the errors are 6.27%,9.58%,4.69%,and 10.24%,respectively.
基金National Natural Science Foundation of China(U22B20149,22308376)Outstanding Young Scholars Foundation of China University of Petroleum(Beijing)(2462023BJRC015)Foundation of United Institute for Carbon Neutrality(CNIF20230209)。
文摘Dual atomic catalysts(DAC),particularly copper(Cu_(2))-based nitrogen(N)doped graphene,show great potential to effectively convert CO_(2)and nitrate(NO_(3)-)into important industrial chemicals such as ethylene,glycol,acetamide,and urea through an efficient catalytical process that involves C–C and C–N coupling.However,the origin of the coupling activity remained unclear,which substantially hinders the rational design of Cu-based catalysts for the N-integrated CO_(2)reduction reaction(CO_(2)RR).To address this challenge,this work performed advanced density functional theory calculations incorporating explicit solvation based on a Cu_(2)-based N-doped carbon(Cu_(2)N_(6)C_(10))catalyst for CO_(2)RR.These calculations are aimed to gain insight into the reaction mechanisms for the synthesis of ethylene,acetamide,and urea via coupling in the interfacial reaction micro-environment.Due to the sluggishness of CO_(2),the formation of a solvation electric layer by anions(F^(-),Cl^(-),Br^(-),and I^(-))and cations(Na+,Mg^(2+),K+,and Ca^(2+))leads to electron transfer towards the Cu surface.This process significantly accelerates the reduction of CO_(2).These results reveal that*CO intermediates play a pivotal role in N-integrated CO_(2)RR.Remarkably,the Cu_(2)-based N-doped carbon catalyst examined in this study has demonstrated the most potential for C–N coupling to date.Our findings reveal that through the process of a condensation reaction between*CO and NH_(2)OH for urea synthesis,*NO_(3)-is reduced to*NH_(3),and*CO_(2)to*CCO at dual Cu atom sites.This dual-site reduction facilitates the synthesis of acetamide through a nucleophilic reaction between NH_(3)and the ketene intermediate.Furthermore,we found that the I-and Mg^(2+)ions,influenced by pH,were highly effective for acetamide and ammonia synthesis,except when F-and Ca^(2+)were present.Furthermore,the mechanisms of C–N bond formation were investigated via ab-initio molecular dynamics simulations,and we found that adjusting the micro-environment can change the dominant side reaction,shifting from hydrogen production in acidic conditions to water reduction in alkaline ones.This study introduces a novel approach using ion-H_(2)O cages to significantly enhance the efficiency of C–N coupling reactions.
基金supported in part by the National Natural Science Foundation of China(52172377).
文摘An effective energy management strategy(EMS)is essential to optimize the energy efficiency of electric vehicles(EVs).With the advent of advanced machine learning techniques,the focus on developing sophisticated EMS for EVs is increasing.Here,we introduce LearningEMS:a unified framework and open-source benchmark designed to facilitate rapid development and assessment of EMS.LearningEMS is distinguished by its ability to support a variety of EV configurations,including hybrid EVs,fuel cell EVs,and plug-in EVs,offering a general platform for the development of EMS.The framework enables detailed comparisons of several EMS algorithms,encompassing imitation learning,deep reinforcement learning(RL),offline RL,model predictive control,and dynamic programming.We rigorously evaluated these algorithms across multiple perspectives:energy efficiency,consistency,adaptability,and practicability.Furthermore,we discuss state,reward,and action settings for RL in EV energy management,introduce a policy extraction and reconstruction method for learning-based EMS deployment,and conduct hardware-in-the-loop experiments.In summary,we offer a unified and comprehensive framework that comes with three distinct EV platforms,over 10000 km of EMS policy data set,ten state-of-the-art algorithms,and over 160 benchmark tasks,along with three learning libraries.Its flexible design allows easy expansion for additional tasks and applications.The open-source algorithms,models,data sets,and deployment processes foster additional research and innovation in EV and broader engineering domains.
文摘The management of agricultural wastes is essential for resource conservation and environmental sustainability.Due to escalating worries regarding plastic pollution and the surging expenses linked to petroleum-based plastics,there has been a notable transition towards the creation of biodegradable alternatives sourced from natural materials.Biofibres and bioplastics,especially those derived from agricultural waste,have garnered significant attention for their prospective uses in food packaging,biomedical sciences,and sustainable manufacturing.This study examines the viability of employing banana peel as a natural and environmentally sustainable raw material for the production of biodegradable bioplastic sheets.Due to its abundant polysaccharides and lignocellulosic fibers,banana peel presents advantageous structural and mechanical characteristics for bioplastic manufacturing.Experimental findings demonstrate that bioplastic derived from banana peels has enhanced biodegradability and environmental compatibility relative to traditional synthetic plastics,positioning it as a feasible alternative to mitigate the worldwide plastic waste epidemic.An optimal formulation was constructed using Design Expert software,comprising 55.38 g of banana peel,27.63 g of fish scales,and 20 g of chitosan powder.This formulation improves the film’s tensile strength,flexibility,and degradation rate,ensuring its efficacy in industrial applications including food packaging and molding.The study’s results highlight the promise of bioplastics made from banana peels as an economical and sustainable alternative,decreasing dependence on petroleum-based plastics and alleviating environmental pollution.
基金Projects(CDJZR14130007106112015CDJXY130011)supported by Fundamental Research Funds for the Central Universities,China
文摘In order to study the deformation behavior and evaluate the workability of the dual-phase Mg-9Li-3Al-2Sr alloy, isothermal hot compression tests were conducted using the Gleeble-3500 thermal-mechanical simulator, in ranges of elevated temperatures （423-573 K） and strain rates （0.001-1 s^-1）. Plastic instability is evident during the deformation which is in the form of serrated flow; serrated yielding is attributed to the locking of mobile dislocations by the Mg and Li atoms which diffuse during the deformation. The relationships between flow stress, strain rate and deformation temperature were analyzed and the deformation activation energy and some basic material factors at different strains were calculated using the Arrhenius equation. The effects of temperature and strain rate on deformation behavior were represented using the Zener–Hollomon parameter in an exponent-type equation. To verify the validity of the constitutive model, the predicted values and experimental flow curves under different deformation conditions were compared, the correlation coefficient （0.9970） and average absolute relative error （AARE=4.41%） were calculated. The results indicate that the constitutive model can be used to accurately predict the flow behavior of dual-phase Mg-9Li-3Al-2Sr alloy during high temperature deformation.
文摘Lane detection is a fundamental aspect of most current advanced driver assistance systems(ADASs). A large number of existing results focus on the study of vision-based lane detection methods due to the extensive knowledge background and the low-cost of camera devices. In this paper, previous visionbased lane detection studies are reviewed in terms of three aspects, which are lane detection algorithms, integration, and evaluation methods. Next, considering the inevitable limitations that exist in the camera-based lane detection system, the system integration methodologies for constructing more robust detection systems are reviewed and analyzed. The integration methods are further divided into three levels, namely, algorithm, system,and sensor. Algorithm level combines different lane detection algorithms while system level integrates other object detection systems to comprehensively detect lane positions. Sensor level uses multi-modal sensors to build a robust lane recognition system. In view of the complexity of evaluating the detection system, and the lack of common evaluation procedure and uniform metrics in past studies, the existing evaluation methods and metrics are analyzed and classified to propose a better evaluation of the lane detection system. Next, a comparison of representative studies is performed. Finally, a discussion on the limitations of current lane detection systems and the future developing trends toward an Artificial Society, Computational experiment-based parallel lane detection framework is proposed.
基金supported by the National Natural Science Foundation of China(61403158,61520106008)the Project of the Education Department of Jilin Province(2016-429)
文摘Next-generation vehicle control and future autonomous driving require further advances in vehicle dynamic state estimation. This article provides a concise review, along with the perspectives, of the recent developments in the estimation of vehicle dynamic states. The definitions used in vehicle dynamic state estimation are first introduced, and alternative estimation structures are presented. Then, the sensor configuration schemes used to estimate vehicle velocity, sideslip angle, yaw rate and roll angle are presented. The vehicle models used for vehicle dynamic state estimation are further summarized, and representative estimation approaches are discussed. Future concerns and perspectives for vehicle dynamic state estimation are also discussed.
基金partially supported by the Natural Science and Engineering Council of Canada (NSERC, Canada)the financial support from the high level overseas talent project of Beijing, P. R. China
文摘Since the discovery of graphene, many efforts have been done to modify the graphene structure for integrating this novel material to nanoelectronics, fuel cells, energy storage devices and in many other applications. This leads to the production of different types of graphene-based materials, which possess properties different from those of pure graphene. Porous graphene is an example of this type of materials. It can be considered as a graphene sheet with some holes/pores within the atomic plane. Due to its spongy structure, porous graphene can have potential applications as membranes for molecular sieving, energy storage components and in nanoelectronics. In this review, we present the recent progress in the synthesis of porous graphene. The properties and the potential applications of this new material are also discussed.
文摘Shared control schemes allow a human driver to work with an automated driving agent in driver-vehicle systems while retaining the driver’s abilities to control.The human driver,as an essential agent in the driver-vehicle shared control systems,should be precisely modeled regarding their cognitive processes,control strategies,and decision-making processes.The interactive strategy design between drivers and automated driving agents brings an excellent challenge for human-centric driver assistance systems due to the inherent characteristics of humans.Many open-ended questions arise,such as what proper role of human drivers should act in a shared control scheme?How to make an intelligent decision capable of balancing the benefits of agents in shared control systems?Due to the advent of these attentions and questions,it is desirable to present a survey on the decision making between human drivers and highly automated vehicles,to understand their architectures,human driver modeling,and interaction strategies under the driver-vehicle shared schemes.Finally,we give a further discussion on the key future challenges and opportunities.They are likely to shape new potential research directions.
基金National Natural Science Foundation of China(Grant No.51505178)China Postdoctoral Science Foundation(Grant No.2014M561289)
文摘Di erential braking and active steering have already been integrated to overcome their shortcomings. However, existing research mainly focuses on two-axle vehicles and controllers are mostly designed to use one control method to improve the other. Moreover, many experiments are needed to improve the robustness; therefore, these control methods are underutilized. This paper proposes an integrated control system specially designed for multi-axle vehicles, in which the desired lateral force and yaw moment of vehicles are determined by the sliding mode control algorithm. The output of the sliding mode control is distributed to the suitable wheels based on the abilities and potentials of the two control methods. Moreover, in this method, fewer experiments are needed, and the robustness and simultaneity are both guaranteed. To simplify the optimization system and to improve the computation speed, seven simple optimization subsystems are designed for the determination of control outputs on each wheel. The simulation results show that the proposed controller obviously enhances the stability of multi-axle trucks. The system improves 68% of the safe velocity, and its performance is much better than both di erential braking and active steering. This research proposes an integrated control system that can simultaneously invoke di erential braking and active steering of multi-axle vehicles to fully utilize the abilities and potentials of the two control methods.
文摘Planning and decision-making technology at intersections is a comprehensive research problem in intelligent transportation systems due to the uncertainties caused by a variety of traffic participants.As wireless communication advances,vehicle infrastructure integrated algorithms designed for intersection planning and decision-making have received increasing attention.In this paper,the recent studies on the planning and decision-making technologies at intersections are primarily overviewed.The general planning and decision-making approaches are presented,which include graph-based approach,prediction base approach,optimization-based approach and machine learning based approach.Since connected autonomous vehicles(CAVs)is the future direction for the automated driving area,we summarized the evolving planning and decision-making methods based on vehicle infrastructure cooperative technologies.Both four-way signalized and unsignalized intersection(s)are investigated under purely automated driving traffic and mixed traffic.The study benefit from current strategies,protocols,and simulation tools to help researchers identify the presented approaches’challenges and determine the research gaps,and several remaining possible research problems that need to be solved in the future.
基金The authors of this work would like to appreciate the NSERC(Natural Sciences and Engineering Research Council of Canada)Magnesium Strategic Research Network(MagNET)for the financial support of this work and the Natural Resources Canada Government Materials Laboratory,CanmetMATERIALS located in Hamilton,Ontario for providing the opportunity to perform the experimental parts of the work.The assistance of Dr.M.Kozdras,Dr.A.Javaid,Dr.E.Essadiqi and Mr.G.Birsan and P.Newcombe(from CanmetMATERIALS)in processing the experimental data is gratefully acknowledged.
文摘The effect of set-back distance on the thermo-mechanical behavior of the strip during twin roll casting(TRC)of an AZ31 magnesium alloy was modeled using finite element method(FEM).Model validation was done by comparing the predicted and measured exit strip surface temperature as well as the secondary dendrite arm spacing(SDAS)through the thickness of the sheet to those measured during experiments.Model results showed as the set-back distance increases,the strip exit temperature decreases and the solidification front moves toward the entry of the roll gap.The cast strip also experiences more plastic deformation and consequently,the normal stress on the strip surface and effective strain at the strip center-line increase.Moreover,higher separating forces were predicted for longer set-back distances.Model predictions showed that changing the set-back distance by varying the final thickness has a more significant effect on the temperature and stress-strain fields than altering the nozzle opening height.
文摘The accumulative roll-bonding(ARB)process was applied on the strips of aluminum alloy 1050 in two processing conditions:cold ARB and warm ARB.The results of tensile tests and microhardness measurement show that the warm ARB process exhibits the lower tensile strength and microhardness,more homogeneous distribution of the microhardness,higher elongation,and especially superior planar isotropy of the tensile properties in comparison to the cold ARB,because of the intermediate heat treatment as well as the elevated temperature rolling in the warm ARB process.Furthermore,with increasing the cycles of both processes,the planar isotropy decreases progressively.
基金supported by the National Natural Science Foundation of China(5187051675)。
文摘To improve the safety and driving stability of the autonomous heavy truck, it is necessary to consider the differences of driving behavior and drivable trajectories between the heavy trucks and passenger cars. This study proposes a probabilistic decision-making and trajectory planning framework for the autonomous heavy trucks. Firstly, the driving decision process is divided into intention generation and feasibility evaluations, which are realized using the utility theory and risk assessment, respectively. Subsequently the driving decision is made and sent to the trajectory planning module. In order to reflect the greater risks of the truck to other surrounding vehicles, the aggressiveness index(AI) is proposed and quantified to infer the asymmetrical risk level of lane-change maneuver. In the planning stage, the lateral and roll dynamics stability domains are developed as the constraints to exclude the candidate trajectories that would cause vehicle instability. Finally, the simulation results are compared between the proposed model and the artificial potential filed model in the scenarios extracted from the naturalistic driving data. It is shown that the proposed framework can provide the human-like lane-change decisions and truck-friendly trajectories, and performs well in dynamic driving environments.
基金supported by the National Natural Science Foundation of China(No.51975365)the Shanghai Pujiang Program(18PJ1405000)+1 种基金supported by the Natural Sciences and Engineering Research Council of Canada(NSERC)the Province of Ontario
文摘To overcome the limitation in formability at room temperature,manufacturers have developed magnesium alloys with remarkable properties by adding rare-earth elements.The rare-earth magnesium alloys behave differently from the conventional alloys,especially with respect to their coupled anisotropic and strain rate sensitive behavior.In the current work,such behavior of the rare-earth Mg alloy ZEK100 sheet at room temperature is investigated with the aid of the elastic viscoplastic self-consistent polycrystal plasticity model.Different strain rate sensitivities(SRSs)for various deformation modes are employed by the model to simulate the strain rate sensitive behaviors under different loading directions and loading rates.Good agreement between the experiments and simulations reveals the importance and necessity of using different SRSs for each deformation mode in hexagonal close-packed metals.Furthermore,the relative activities of each deformation mode and the texture evolution during different loadings are discussed.The anisotropic and strain rate sensitive behavior is ascribed to the various operating deformation modes with different SRSs during loading along different directions.
基金Supported by Project of National Natural Science Foundation of China(Grand No.52102469)Science and Technology Major Project of Guangxi(Grant Nos.AB21196029 and AA18242033)State Key Laboratory of Automotive Safety and Energy(Grant No.KF2014).
文摘The cooperation between an autonomous vehicle and a nearby vehicle is critical to ensure driving safety in the laneexchanging scenario.The nearby vehicle trajectory needs to be predicted,from which the autonomous vehicle is controlled to prevent possible collisions.This paper proposes a lane-exchanging driving strategy for the autonomous vehicle to cooperate with the nearby vehicle by integrating vehicle trajectory prediction and motion control.A trajectory prediction method is developed to anticipate the nearby vehicle trajectory.The Gaussian mixture model(GMM),together with the vehicle kinematic model,are synthesized to predict the nearby vehicle trajectory.A potential-feldbased model predictive control(MPC)approach is utilized by the autonomous vehicle to conduct the lane-exchanging maneuver.The potential feld of the nearby vehicle is considered in the controller design for collision avoidance.On-road driving data verifcation shows that the nearby vehicle trajectory can be predicted by the proposed method.CarSim®simulations validate that the autonomous vehicle can perform the lane-exchanging maneuver and avoid the nearby vehicle using the proposed driving strategy.The autonomous vehicle can thus safely perform the laneexchanging maneuver and avoid the nearby vehicle.
