In the aerospace field,hole burnishing enhancement plays an essential role in improving the service performance of load-bearing holes.To satisfy the assembly accuracy and strength requirements,the structure shape and ...In the aerospace field,hole burnishing enhancement plays an essential role in improving the service performance of load-bearing holes.To satisfy the assembly accuracy and strength requirements,the structure shape and surface integrity must be considered simultaneously during the enhancement process.The current manufacturing process of hole burnishing has a relatively weak balance between the structure shape and surface integrity;therefore,it is necessary to analyze the mechanism and optimize the parameters to improve the strengthening effect of the holes.In this study,a two-dimensional longitudinal simplified model for the hole burnishing process was established,and the reasons for the surface roughness improvement of the hole wall and material accumulation on the upper surface were analyzed.Experiments were conducted to determine the influence of the burnishing parameters on the structure shape(material accumulation,shape contour,and roundness)and surface integrity(surface roughness,residual stress,and surface hardness),based on the opposite requirements of improving the structure shape and surface integrity for the burnishing depth(BD).The results showed that with an increase in the BD,the structure shape deteriorated,whereas the surface integrity improved.Fatigue behavior verification experiments were conducted,and parameter selection schemes for the collaborative improvement of the structure shape and surface integrity were discussed.For the holes of titanium alloy TB6(Ti-10V-2Fe-3Al),the fatigue life can be increased by 162%when the BD,spindle speed,and feed rate were 0.20 mm,200 r/min,and 0.2 mm/r,respectively.展开更多
Burrs generated during the machining of Aramid-Fiber-Reinforced Composites(AFRPs)pose a challenge for the production efficiency of aircraft and helicopter housing parts.Existing studies have generally attempted to sup...Burrs generated during the machining of Aramid-Fiber-Reinforced Composites(AFRPs)pose a challenge for the production efficiency of aircraft and helicopter housing parts.Existing studies have generally attempted to suppress burrs by referring to delamination suppression methods.In contrast to stratification,burrs are remediable machining defects.As such,a mechanochemical method with burrs trimming technological strategy are implemented to effectively combat burrs.Herein,we clarify the mechanism by which aramid fibers cannot be cut off using analytical and numerical models.In addition,the mechanism of fiber fracture with Modified Polyurethane Reactive Polymer(M-PUR),and development of anti-burr devices(thermostatic adhesive sealed generator)are discussed.Finally,the experimental results show that the reduction rate in burr length is 87%-91%through the mechanochemical method.The method not only opens a new avenue to solve the burr problem of aramid fibers but also builds an interdisciplinary bridge between polymer science and composite machining.展开更多
High-aspect-ratio metallic surface microstructures are increasingly demanded in breakthrough applications,such as high-performance heat transfer enhancement and surface plasmon devices.However,the fast and cost-effect...High-aspect-ratio metallic surface microstructures are increasingly demanded in breakthrough applications,such as high-performance heat transfer enhancement and surface plasmon devices.However,the fast and cost-effective fabrication of high-aspect-ratio microstructures on metallic surfaces remains challenging for existing techniques.This study proposes a novel cutting-based process,namely elliptical vibration chiseling(EV-chiseling),for the high-efficiency texturing of surface microstructures with an ultrahigh aspect ratio.Unlike conventional cutting,EV-chiseling superimposes a microscale EV on a backward-moving tool.The tool chisels into the material in each vibration cycle to generate an upright chip with a high aspect ratio through material deformation.Thanks to the tool’s backward movement,the chip is left on the material surface to form a microstructure rather than falling off.Since one microstructure is generated in one vibration cycle,the process can be highly efficient using ultrafast(>1 kHz)tool vibration.A finite element analysis model is established to explore the process mechanics of EV-chiseling.Next,a mechanistic model of the microstructured surface generation is developed to describe the microstructures’aspect ratio dependency on the process parameters.Then,surface texturing tests are performed on copper to verify the efficacy of EV-chiseling.Uniformed micro ribs with a spacing of 1–10μm and an aspect ratio of 2–5 have been successfully textured on copper.Compared with the conventional EV-cutting that uses a forward-moving tool,EV-chiseling can improve the aspect ratio of textured microstructure by up to 40 times.The experimental results also verify the accuracy of the developed surface generation model of microstructures.Finally,the effects of elliptical trajectory,depth of cut,tool shape,and tool edge radius on the surface generation of micro ribs have been discussed.展开更多
Cemented carbide tools are widely utilized in titanium alloy machining.However,severe tool wear usually occurs during machining;thus,the wear process has attracted widespread attention.Electromagnetic treatment was ap...Cemented carbide tools are widely utilized in titanium alloy machining.However,severe tool wear usually occurs during machining;thus,the wear process has attracted widespread attention.Electromagnetic treatment was applied in our previous study to significantly improve the tool life of cemented carbide tools in Ti6Al4V machining.To investigate the effect of electromagnetic treatment on wear performance,a multiscale analysis of the wear process of cemented carbide tools in the turning process,including microdefects and wear topography at various scales,was conducted in the present study.The distribution of dislocations in the tool material was measured through electron backscatter diffraction,and the surface topographies in the wear area during the Ti6Al4V cutting process were recorded via white light interferometry.Fractal analysis based on the scaling property of surface roughness was carried out to further quantify the wear performance of the tools.The results revealed that the wear mechanism of the cutting tools was mainly adhesion and diffusion,and the diffusion wear of the electromagnetically treated tools was less than that of the untreated tools.Based on the multiscale analysis of flank wear,the effect of electromagnetic treatment on the enhancement of the wear resistance of cemented carbide cutting tools was demonstrated.The multiscale analysis of the wear performance of cutting tools in this study effectively revealed the mechanism by which electromagnetic treatment enhances wear resistance,thus contributing to filling the research gap of traditional studies on tool wear that generally employ single scales.展开更多
As the proliferation and development of automated container terminal continue,the issues of efficiency and safety become increasingly significant.The container yard is one of the most crucial cargo distribution center...As the proliferation and development of automated container terminal continue,the issues of efficiency and safety become increasingly significant.The container yard is one of the most crucial cargo distribution centers in a terminal.Automated Guided Vehicles(AGVs)that carry materials of varying hazard levels through these yards without compromising on the safe transportation of hazardous materials,while also maximizing efficiency,is a complex challenge.This research introduces an algorithm that integrates Long Short-Term Memory(LSTM)neural network with reinforcement learning techniques,specifically Deep Q-Network(DQN),for routing an AGV carrying hazardous materials within a container yard.The objective is to ensure that the AGV carrying hazardous materials efficiently reaches its destination while effectively avoiding AGVs carrying non-hazardous materials.Utilizing real data from the Meishan Port in Ningbo,Zhejiang,China,the actual yard is first abstracted into an undirected graph.Since LSTM neural network can efficiently conveys and represents information in long time sequences and do not causes useful information before long time to be ignored,a two-layer LSTM neural network with 64 neurons per layer was constructed for predicting the motion trajectory of AGVs carrying non-hazardous materials,which are incorporated into the map as background AGVs.Subsequently,DQN is employed to plan the route for an AGV transporting hazardous materials,aiming to reach its destination swiftly while avoiding encounters with other AGVs.Experimental tests have shown that the route planning algorithm proposed in this study improves the level of avoidance of hazardous material AGV in relation to non-hazardous material AGVs.Compared to the method where hazardous material AGV follow the shortest path to their destination,the avoidance efficiency was enhanced by 3.11%.This improvement demonstrates potential strategies for balancing efficiency and safety in automated terminals.Additionally,it provides insights for designing avoidance schemes for autonomous driving AGVs,offering solutions for complex operational environments where safety and efficient navigation are paramount.展开更多
文摘In the aerospace field,hole burnishing enhancement plays an essential role in improving the service performance of load-bearing holes.To satisfy the assembly accuracy and strength requirements,the structure shape and surface integrity must be considered simultaneously during the enhancement process.The current manufacturing process of hole burnishing has a relatively weak balance between the structure shape and surface integrity;therefore,it is necessary to analyze the mechanism and optimize the parameters to improve the strengthening effect of the holes.In this study,a two-dimensional longitudinal simplified model for the hole burnishing process was established,and the reasons for the surface roughness improvement of the hole wall and material accumulation on the upper surface were analyzed.Experiments were conducted to determine the influence of the burnishing parameters on the structure shape(material accumulation,shape contour,and roundness)and surface integrity(surface roughness,residual stress,and surface hardness),based on the opposite requirements of improving the structure shape and surface integrity for the burnishing depth(BD).The results showed that with an increase in the BD,the structure shape deteriorated,whereas the surface integrity improved.Fatigue behavior verification experiments were conducted,and parameter selection schemes for the collaborative improvement of the structure shape and surface integrity were discussed.For the holes of titanium alloy TB6(Ti-10V-2Fe-3Al),the fatigue life can be increased by 162%when the BD,spindle speed,and feed rate were 0.20 mm,200 r/min,and 0.2 mm/r,respectively.
基金supported by the National Natural Science Foundation of China(No.52275441)Shenzhen Science and Technology Program,China(No.WDZC20231129101903002).
文摘Burrs generated during the machining of Aramid-Fiber-Reinforced Composites(AFRPs)pose a challenge for the production efficiency of aircraft and helicopter housing parts.Existing studies have generally attempted to suppress burrs by referring to delamination suppression methods.In contrast to stratification,burrs are remediable machining defects.As such,a mechanochemical method with burrs trimming technological strategy are implemented to effectively combat burrs.Herein,we clarify the mechanism by which aramid fibers cannot be cut off using analytical and numerical models.In addition,the mechanism of fiber fracture with Modified Polyurethane Reactive Polymer(M-PUR),and development of anti-burr devices(thermostatic adhesive sealed generator)are discussed.Finally,the experimental results show that the reduction rate in burr length is 87%-91%through the mechanochemical method.The method not only opens a new avenue to solve the burr problem of aramid fibers but also builds an interdisciplinary bridge between polymer science and composite machining.
基金support for this research provided by the National Natural Science Foundation of China(Grant No.52105458)Beijing Natural Science Foundation(Grant No.3222009)+1 种基金Huaneng Group Science and Technology Research Project(No:HNKJ22-H105)China Postdoctoral Science Foundation(Grant No.2022M711807)。
文摘High-aspect-ratio metallic surface microstructures are increasingly demanded in breakthrough applications,such as high-performance heat transfer enhancement and surface plasmon devices.However,the fast and cost-effective fabrication of high-aspect-ratio microstructures on metallic surfaces remains challenging for existing techniques.This study proposes a novel cutting-based process,namely elliptical vibration chiseling(EV-chiseling),for the high-efficiency texturing of surface microstructures with an ultrahigh aspect ratio.Unlike conventional cutting,EV-chiseling superimposes a microscale EV on a backward-moving tool.The tool chisels into the material in each vibration cycle to generate an upright chip with a high aspect ratio through material deformation.Thanks to the tool’s backward movement,the chip is left on the material surface to form a microstructure rather than falling off.Since one microstructure is generated in one vibration cycle,the process can be highly efficient using ultrafast(>1 kHz)tool vibration.A finite element analysis model is established to explore the process mechanics of EV-chiseling.Next,a mechanistic model of the microstructured surface generation is developed to describe the microstructures’aspect ratio dependency on the process parameters.Then,surface texturing tests are performed on copper to verify the efficacy of EV-chiseling.Uniformed micro ribs with a spacing of 1–10μm and an aspect ratio of 2–5 have been successfully textured on copper.Compared with the conventional EV-cutting that uses a forward-moving tool,EV-chiseling can improve the aspect ratio of textured microstructure by up to 40 times.The experimental results also verify the accuracy of the developed surface generation model of microstructures.Finally,the effects of elliptical trajectory,depth of cut,tool shape,and tool edge radius on the surface generation of micro ribs have been discussed.
基金supported by the National Natural Science Foundation of China(No.52275441)the Shenzhen Science and Technology Program(No.KJZD20230923114606013).
文摘Cemented carbide tools are widely utilized in titanium alloy machining.However,severe tool wear usually occurs during machining;thus,the wear process has attracted widespread attention.Electromagnetic treatment was applied in our previous study to significantly improve the tool life of cemented carbide tools in Ti6Al4V machining.To investigate the effect of electromagnetic treatment on wear performance,a multiscale analysis of the wear process of cemented carbide tools in the turning process,including microdefects and wear topography at various scales,was conducted in the present study.The distribution of dislocations in the tool material was measured through electron backscatter diffraction,and the surface topographies in the wear area during the Ti6Al4V cutting process were recorded via white light interferometry.Fractal analysis based on the scaling property of surface roughness was carried out to further quantify the wear performance of the tools.The results revealed that the wear mechanism of the cutting tools was mainly adhesion and diffusion,and the diffusion wear of the electromagnetically treated tools was less than that of the untreated tools.Based on the multiscale analysis of flank wear,the effect of electromagnetic treatment on the enhancement of the wear resistance of cemented carbide cutting tools was demonstrated.The multiscale analysis of the wear performance of cutting tools in this study effectively revealed the mechanism by which electromagnetic treatment enhances wear resistance,thus contributing to filling the research gap of traditional studies on tool wear that generally employ single scales.
文摘As the proliferation and development of automated container terminal continue,the issues of efficiency and safety become increasingly significant.The container yard is one of the most crucial cargo distribution centers in a terminal.Automated Guided Vehicles(AGVs)that carry materials of varying hazard levels through these yards without compromising on the safe transportation of hazardous materials,while also maximizing efficiency,is a complex challenge.This research introduces an algorithm that integrates Long Short-Term Memory(LSTM)neural network with reinforcement learning techniques,specifically Deep Q-Network(DQN),for routing an AGV carrying hazardous materials within a container yard.The objective is to ensure that the AGV carrying hazardous materials efficiently reaches its destination while effectively avoiding AGVs carrying non-hazardous materials.Utilizing real data from the Meishan Port in Ningbo,Zhejiang,China,the actual yard is first abstracted into an undirected graph.Since LSTM neural network can efficiently conveys and represents information in long time sequences and do not causes useful information before long time to be ignored,a two-layer LSTM neural network with 64 neurons per layer was constructed for predicting the motion trajectory of AGVs carrying non-hazardous materials,which are incorporated into the map as background AGVs.Subsequently,DQN is employed to plan the route for an AGV transporting hazardous materials,aiming to reach its destination swiftly while avoiding encounters with other AGVs.Experimental tests have shown that the route planning algorithm proposed in this study improves the level of avoidance of hazardous material AGV in relation to non-hazardous material AGVs.Compared to the method where hazardous material AGV follow the shortest path to their destination,the avoidance efficiency was enhanced by 3.11%.This improvement demonstrates potential strategies for balancing efficiency and safety in automated terminals.Additionally,it provides insights for designing avoidance schemes for autonomous driving AGVs,offering solutions for complex operational environments where safety and efficient navigation are paramount.
