Search Results (124)

Molecular dynamics simulations were performed to investigate the nanometric cutting of polycrystalline oxygen-free copper using a single-crystal diamond tool. The effects of grain size, tool geometry (rake angle and edge radius), cutting speed, and ambient temperature on atomic migration, dislocation activity, and tool wear were systematically analyzed. The results indicate that material removal is dominated by cutting-induced amorphization and the formation of hcp-coordinated defect structures, while dislocation activity governs plastic deformation and cutting force fluctuations. A damaged subsurface layer, composed of amorphous structures, hcp-coordinated defects, and residual dislocations, is formed beneath the machined surface. Increasing grain size reduces grain-boundary-induced stress concentration and suppresses subsurface damage. A larger rake angle facilitates chip removal and reduces damage, whereas a larger edge radius intensifies dislocation activity and amorphization. Higher cutting speeds reduce lattice distortion and subsurface damage but increase stress concentration on the tool. Elevated temperature enhances atomic mobility, promoting amorphization and subsurface deformation while accelerating tool wear. These findings provide insight into the nanometric cutting behavior of polycrystalline copper and offer guidance for optimizing process parameters to improve surface integrity and tool life. Full article

Aramid fiber reinforced polymers (AFRPs) are widely used in aerospace and defense structures because of their high specific strength, impact resistance, and damage tolerance. However, severe burr formation during machining remains a major obstacle to achieving high surface integrity and dimensional accuracy. In particular, the mechanism by which tool edge radius affects burr formation in AFRP cutting has not yet been clarified quantitatively. To address this issue, this study develops an analytical model for the orthogonal cutting of AFRPs to reveal the burr formation mechanism associated with tool edge radius. The model, established on the basis of contact mechanics and fracture theory, predicts fiber deflection, cutting force evolution, fracture behavior, and burr length under different contact and boundary conditions. The results show that tool edge radius governs burr formation through a contact–state transition mechanism. When the edge radius is below a critical threshold, localized point-contact-like interaction promotes stress concentration and fiber fracture, leading to relatively clean material removal. When the edge radius exceeds this threshold, the interaction evolves toward extended contact and sliding, which suppresses complete fiber fracture and results in pronounced burr retention. Experimentally, increasing the edge radius from 5.6 μm to 110.3 μm increased the maximum burr height from 3.19 μm to 83.58 μm, corresponding to an increase of approximately 2520%. The predicted burr evolution agrees well with the experimental observations in both trend and characteristic magnitude. This study provides a mechanistic and predictive understanding of burr formation in AFRP machining and offers practical guidance for cutting edge preparation, tool wear control, and process optimization in high-quality composite machining. Full article

In this study, the material removal behavior of abrasive brushing tools on zirconia-toughened alumina cutting edges is experimentally investigated. Three different brushing tool specifications with bonded diamond grains are tested, varying in filament diameter, filament length, and grain size. Using an industrial robot setup, structured brushing experiments are performed on the cutting edges of indexable inserts under controlled variations of key process parameters, such as brushing velocity v_b, axial feed rate v_fa, infeed a_e, and contact angle φ. The resulting edge rounding is quantified using three-dimensional optical scanning. Key metrics, such as edge radius r_β and form factor K, are evaluated to assess the suitability of abrasive brushing processes for the preparation of ceramic cutting edges. The results showed that the edge radius ranged from r_β = 20 to 80 µm, while the form factor varied from K = 1 to 3. The brushing velocity v_b and axial feed rate v_fa were identified as the primary parameters influencing the rounding radius r_β, whereas the infeed a_e was the dominant parameter affecting the form factor K. While cutting edge preparation of metal and carbide tools is well studied, little research exists on abrasive brushing of zirconia-toughened alumina (ZTA) cutting inserts. Because ZTA behaves differently from metals, this study systematically investigates robot-assisted abrasive brushing of ZTA, analyzing how key process parameters affect edge radius, shape, and uniformity along the cutting edge. Full article

Grinding wheel conditioning is critical for maintaining cutting efficiency and surface quality, yet conventional mechanical dressers struggle with metal-bonded superabrasive wheels. In this study, wire electrical discharge machining (WEDM) dressing was evaluated on metal-bond diamond wheels of two grit sizes (D54 and D91) and compared to standard mechanical dressing. Dressing was performed on a WEDM machine using varied discharge currents, open-circuit voltages, and duty factors; subsequently, each wheel ground twelve grooves in tungsten carbide under identical parameters. Performance was assessed via maximum spindle power, tangential and normal forces, surface roughness (Ra), radial wheel wear, and edge radius. WEDM-dressed wheels exhibited up to 56% lower peak spindle power and 40–50% lower forces than mechanically dressed wheels. Compared to mechanically dressed wheels, WEDM-conditioned wheels exhibited markedly lower radial wear and maintained substantially sharper, more stable edge radii throughout the grinding cycles. Surface roughness converged after an initial break-in, matching mechanical methods. By selectively eroding the bond without damaging grains, WEDM dressing extends dressing intervals by approximately fivefold and reduces maintenance. Full article

The micro-geometry of the cutting edge plays a crucial role in material flow ahead of the cutting edge and chip formation, primarily influencing chip formation mechanisms and the minimum cutting thickness. In the context of turning 304 stainless steel, however, existing research still lacks a unified quantitative framework linking “cutting edge micro-geometry—material separation behavior (separation point/minimum uncut chip thickness)—microstructural evolution of the machined surface.” This gap hampers mechanistic optimization design aimed at enhancing machining quality. This study examines the turning of 304 stainless steel by integrating analytical modeling, finite element simulation, and experimental validation to develop a predictive model for minimum cutting thickness. It analyzes the effects of tool nose radius and asymmetric edge morphology, and a microstructure evolution prediction subroutine is developed based on dislocation density theory. The results indicate that the minimum cutting thickness exhibits a positive correlation with the tool nose radius, and their ratio remains stable within the range of 0.25 to 0.30. Under asymmetric edge conditions, the minimum cutting thickness initially increases and then decreases as the K-factor varies. The developed subroutine, based on the dislocation density model, enables accurate prediction of dislocation density, grain size, and microhardness in the machined surface layer. Among the factors considered, the tool nose radius demonstrates the most pronounced influence on microstructure evolution. This research provides theoretical support and a technical reference for optimizing cutting-edge design and enhancing the machining quality of 304 stainless steel. Full article

In this study, a model was developed to calculate the power required for the circumferential cutting of solid wood in the longitudinal direction, considering the relevant technological parameters and mechanical properties of the wood. Based on measurements of different combinations and using the Response surface method (RSM) and Central composite design (CCD), a model was created that, in its derived version, considers the cutting width and depth, the diameter and speed of the tool, the number of cutting edges and sharpness of the cutting edge, the feed rate of the workpiece, and the density and moisture content of the wood. The model can be used to calculate the cutting power of various tree species with densities ranging from 400 to 700 kg/m³, moisture contents from 8 to 16%, and a wide range of cutting-edge sharpness, from a sharp cutting edge with a tip radius of 5 µm to a blunt cutting edge with a tip radius of 35 µm. The model is designed for a rake angle of 20°, the value most frequently used in practise. ANOVA analysis was used to determine the suitability of the model, which is highly significant with an R² value of 0.93 and an average deviation of the calculated values from the measured values of 8.8%. The model is robust and therefore useful in the wood industry for predicting energy consumption in the processing of solid wood. Full article

To address the challenges of wear resistance for shield cutterheads and cutters in high-abrasion sandy cobble strata, this study uses the Beijing Metro Line 19 tunnel Niujie–Jinrongjie section as an engineering case study. It employs the DEM to develop a crushable sandy cobble model, evaluate the stress characteristics of fishtail cutters, rippers, and scrapers, and analyze load distribution in the cutterhead and cutters—including underlying causes. Based on simulations, the study proposes and implements targeted wear-resistant designs for field application. The results indicate that the stress variation patterns of fishtail cutters, rippers, and scrapers with respect to time and installation radius are similar. The cutterhead’s opening distribution significantly influences the intensity of normal and lateral stresses. Caused by cutting resistance, high-stress loads in cutters accumulate at the cutting edge, while those in the cutterhead localize to the soil-facing side of its spokes. Meanwhile, hindered muck flow and cutting failure of gauge cutters also cause stress concentration in the cutterhead’s transition zones and outer side of the large ring. Adopting a DEM-based method that characterizes the stress of the cutterhead and cutters to develop targeted wear-resistant designs can effectively control the wear of cutters and cutterheads in in situ engineering. The rate of abnormal cutter damage was limited to merely 5.84%, while the observed wear of the ripper cutters remained consistently below the values predicted by the IHI empirical model. This study provides a scientific basis for wear-resistant design of cutterheads in similar high-abrasion strata. Full article

It is difficult to achieve ultra-precision machining (UPM) on semiconductor materials like single-crystal silicon because of their hardness and brittleness. To solve this issue, numerous field-assisted machining systems and their combinations have been suggested and developed. However, the difficulty in directly observing the physical variables limits our comprehension of the in-depth machining mechanisms of field-assisted machining. In this work, we investigated the machining mechanism of single-crystal silicon under the combination of laser heating and tool vibration using molecular dynamics (MD) simulations. The effect of tool vibration trajectory determined by different tool edge radii is discussed under the condition of raising temperature. The simulation results indicate that the surface morphology is closely related to vibration and heating parameters. Raising the cutting temperature causes a reversed relation between tool edge radius and surface roughness. While the subsurface damage and internal stress are also determined by the tool edge radius and cutting temperature. The findings in this simulation could help to improve the understanding of machining mechanics in multi-field-assisted machining. Full article

Multi-Unmanned Aerial Vehicle (Multi-UAV) cooperative search represents a cutting-edge research direction in the field of unmanned aerial vehicle applications. The use of multi-UAV systems for low-altitude target search and area surveillance has become an effective means of enhancing security capabilities. In practical scenarios, UAVs rely on onboard sensors to acquire environmental information; however, due to the limited perceptual range of these sensors, their observation capabilities are inherently local and constrained. This paper investigates the problem of multi-UAV cooperative search in partially observable low-altitude environments, where each UAV possesses a circular sensing range with a finite radius. Target location information is only obtained when a target enters the field of view of any UAV. The objective is to achieve cooperative search and sustain continuous surveillance while ensuring safety among UAVs and with the environment. To address this challenge, we propose a novel multi-agent deep reinforcement learning (MADRL) algorithm named Normalizing Graph Attention Soft Actor-Critic (NGASAC). This algorithm integrates a normalizing flow (NL) layer and a multi-head graph attention network (MHGAT). The normalizing flow technique maps traditional Gaussian sampling to a more complex action distribution, thereby enhancing the expressiveness and flexibility of the policy. Simultaneously, by constructing a multi-head graph attention network that captures “obstacle–target” relationships, the algorithm improves the UAVs’ ability to learn and reason about complex spatial topologies, leading to significantly better performance in cooperative search and stable surveillance of hidden targets. Simulation results demonstrate that the NGASAC algorithm markedly outperforms baseline methods such as Multi-Agent Soft Actor-Critic (MASAC), Multi-Agent Proximal Policy Optimization (MAPPO), and Multi-Agent Deep Deterministic Policy Gradient (MADDPG) across multiple evaluation metrics, including success rate, task time, and obstacle avoidance capability. Furthermore, it exhibits strong generalization performance and robustness. Full article

This paper deals with the consumption of energy during the turning of low-alloyed steel 16MnCr5. The study employs the earlier reported methodology for the decomposition of energy in cutting during turning. The energy for chip formation, as well as the energy consumed in the interface between the tool flank and produced surfaces, can be singled out. The paper investigates the turning process as a function of the cutting conditions as well as the variable cutting edge geometry. It was found that the integration of a chip former valuably contributes to the lower chip ratios, as well as the more favourable shape of chips. The lower energy consumed in the tool flank region for the tool with the integrated chip former results in lower normal and shear forces despite the higher cutting edge radius. However, the differences in the surface strain accumulation expressed in terms of the dislocation density and residual stress depth profiles are only subtle. Full article

Urban recreational spaces (URSs) are pivotal for enhancing resident well-being, making the accurate assessment of public perceptions crucial for quality optimization. Compared to traditional surveys, social media data provide a scalable means for multi-dimensional perception assessment. However, existing studies predominantly rely on single-modal data, which limits the comprehensive capturing of complex perceptions and lacks interpretability. To address these gaps, this study employs cutting-edge large vision–language models (LVLMs) and develops an interpretable model, Qwen2.5-VL-7B-SFT, through supervised fine-tuning on a manually annotated dataset. The model integrates visual-linguistic features to assess four perceptual dimensions of URSs: esthetics, attractiveness, cultural significance, and restorativeness. Crucially, we generate textual evidence for our judgments by identifying the key spatial elements and emotional characteristics associated with specific perceptions. By integrating multi-source built environment data with Optuna-optimized machine learning and SHAP analysis, we further decipher the nonlinear relationships between built environment variables and perceptual outcomes. The results are as follows: (1) Interpretable LVLMs are highly effective for urban spatial perception research. (2) URSs within Beijing’s Third Ring Road fall into four typologies, historical heritage, commercial entertainment, ecological-natural, and cultural spaces, with significant correlations observed between physical elements and emotional responses. (3) Historical heritage accessibility and POI density are identified as key predictors of public perception. Positive perception significantly improves when a block’s POI functional density exceeds 4000 units/km² or when its 500 m radius encompasses more than four historical heritage sites. Our methodology enables precise quantification of multidimensional URS perceptions, links built environment elements to perceptual mechanisms, and provides actionable insights for urban planning. Full article

Indexable face milling tools are often used to machine workpieces with large axial and radial depth of cuts, and thus, the inserts quickly wear out in machining. A kernel technique of smart machining is tool wear compensation, which is to regularly and automatically measure the insert radius/length with a laser tool setter on the machine table during machining, and compensate them in the subsequent machining. Another technique is tool condition monitoring, which is to calculate the insert flank wear width for tool condition and compare with its threshold. When it is less than but close to its threshold of invalid inserts, the cutting tool is automatically changed right before it becomes invalid. On-machine laser tool setters have been equipped in CNC machine tools for several years; however, they cannot conduct cutting tool condition monitoring. The main reason is that the insert flank wear width cannot be measured on the on-machine laser tool setter, and the status quo is that the cutting tool is replaced either too early or too late. To address this problem, a novel tool condition monitoring technique of determining the insert flank wear width of indexable face milling tool using on-machine laser tool setters is proposed. According to the insert geometry, the worn cutting edge and a new workpiece milling mechanism proposed in this work, the insert flank wear width can be calculated. In machining, the insert radius wear is measured on the on-machine laser tool setter, and the insert flank wear width is calculated to evaluate whether it is invalid soon. The results indicate that the optimal height for radius measurement is located near the intersection of the corner and side edges point MR₃, and close to the cutting depth point MR₅. A wear land width threshold of 0.10 mm is established to define tool failure. The proposed calculation method achieves high accuracy, maintaining calculation errors within 14.00%. The inserts can be used in good condition with the maximum lifespan. This method has been verified in machining applications and can be directly applied in industry. Full article

Tool edge preparation is the process aimed at eliminating edge defects and optimizing the micro-geometric parameters of cutting tools. Drag finishing, the primary engineering method, subjects tools to planetary motion (simultaneous revolution and rotation) within abrasive media to remove burrs and micro-chips, thereby improving cutting performance and extending tool life. A discrete element method (DEM) model of drag finishing edge preparation was developed to investigate the effects of processing time, tool rotational speed, and rotation direction on abrasive-mediated tool wear behavior. The model was validated through milling cutter edge preparation experiments. Simulation results show that increasing the processing time causes fluctuating changes in average abrasive velocity and contact forces, while cumulative energy and tool wear increase progressively. Elevating tool rotational speed increases average abrasive velocity, contact forces, cumulative energy, and tool wear. Rotation direction significantly impacts tool wear: after 2 s of clockwise (CW) rotation, wear reached 1.45 × 10⁻⁸ mm; after 1 s of CW followed by 1 s of counterclockwise (CCW) rotation, wear was 1.25 × 10⁻⁸ mm; and after 2 s of CCW rotation, wear decreased to 1.02 × 10⁻⁸ mm. Experiments, designed based on simulation trends, confirm that edge radius increases with time and tool rotational speed. After 30 min of processing at 60, 90, and 120 rpm, average edge radius increased to 22.5 μm, 28 μm, and 30 μm, respectively. CW rotation increased the edge shape factor K, while CCW rotation decreased it. The close agreement between experimental and simulation results confirms the model’s effectiveness in predicting the impact of edge preparation parameters on tool geometry. Rotational speed control optimizes edge preparation efficiency, the predominant tangential cumulative energy reveals abrasive wear as the primary material removal mechanism, and rotation direction modulates the shape factor K, enabling symmetric edge preparation. Full article

To overcome the issues of excessive cutting force, poor chip segmentation, and premature tool wear during the drilling of Ti-6Al-4V titanium alloy. This study established the cutting edge motion trajectory function and instantaneous dynamic cutting thickness equation for ultrasonic vibration-assisted drilling through kinematic analysis. Based on this, an analytical model of drilling force was formulated, integrating tool geometry, cutting radius scale effects, dynamic chip thickness, and drilling depth. In parallel, a finite element model was constructed to achieve visual simulation analysis of chip deformation and cutting force. Finally, the accuracy of the model was verified through experiments, with a comprehensive analysis performed on how cutting parameters affect thrust force. The findings indicate that the average absolute prediction errors of thrust force and torque between the analytical model and finite element simulations were 7.87% and 6.26%, respectively, confirming the model’s capability to accurately capture instantaneous force and torque variations. Compared to traditional drilling methods, the application of ultrasonic vibration assistance resulted in reductions of 40.8% in thrust force and 41.7% in torque. The drilling force exhibited nonlinear growth as the spindle speed and feed rate were elevated, while it declined with greater vibration frequency and amplitude as drilling depth increased. Furthermore, the combined effect of optimized vibration parameters enhanced chip fragmentation, producing short discontinuous chips and effectively preventing entanglement. Overall, this research provides a theoretical and practical foundation for optimizing ultrasonic vibration-assisted drilling and improving precision hole making in titanium alloys. Full article

The unique cutting–burnishing coupling effect in BTA deep hole drilling generates a high-hardness and -brittleness white layer (ultrafine martensitic layer), which will degrade component performance and accelerate tool wear. This work investigated the formation mechanism and the mechanical properties of the white layer generated in three distinct regions (the cutting edge radius zone, cutting–burnishing corner zone, and guide pad edge zone) through nanoindentation, SEM and BSE. The microstructure and thickness of the white layer under different feedrates are investigated. The correlations between the white layer, the structure of guide pads, and wear behaviors of the TiN- and TiCN/Al₂O₃-coated guide pads are revealed. Variations in hardness are observed across different zones. The white layer undergoes a soft-to-hard transition due to rapid quenching and the cutting–burnishing effect at the sharp corner. The highest hardness (9.758 GPa) was observed in the guide pad zone, accompanied by grain refinement. The chamfered TiN-coated guide pad exhibits superior wear resistance but suffers fatigue cracking and adhesive wear in the initial guiding zone. The TiCN/Al₂O₃-coated pad with rounded corners experiences brittle spalling in the mid-to-rear guiding zone. These findings enhance the understanding of the white layer formation in deep hole drilling and provide a foundation for tool optimization. Full article