Nickel-based superalloys are widely used in aerospace and energy systems, and their surfaces often feature high-density micro-hole arrays for cooling or fluidic functions. Electrical discharge machining (EDM) is a widely adopted process for micro-hole fabrication. However, as nickel-based superalloys evolve from polycrystalline to single-crystal structures, the similarities and differences in their EDM behavior remain unclear. Arrayed cylindrical electrode EDM of micro-hole arrays can significantly improve machining efficiency and ensure hole positional accuracy. This study proposes a simple, low-cost, and scalable method to fabricate highly uniform cylindrical micro-electrode arrays by controlling the wear of micro-prism electrodes. Using this electrode array, comparative EDM experiments were conducted on single-crystal and polycrystalline nickel-based superalloys, and the resulting micro-holes were comprehensively characterized in terms of dimensional accuracy, surface morphology, and subsurface altered layer structure. The results show that micro-holes in single-crystal nickel-based superalloys have smaller diameters, higher roundness, lower surface roughness, and thinner recast layers. Particularly notable is the significant deformation of γ phase and γ′ phase in the heat-affected zone of the single-crystalline alloy. This study not only provides a practical approach for the low-cost fabrication of uniform micro-electrode arrays but also establishes a critical link between crystal structure and EDM-induced surface integrity, offering reference for the precision machining of single-crystal components.

This study characterised the hot-press forming process of long carbon fibre PA6 materials using laminates prepared from UD-CA708A prepregs manufactured by Nanjing Special Plastic Composites Materials Co., Ltd. In order to investigate the resin flow behaviour during the hot compression moulding process, a unified model integrating the material forming and resin flow sequences was established by Lagrangian and Eulerian discretization methods. Simultaneous measurements by rotational and torsional rheometers revealed that in-plane fibre flow dominated, and the long carbon fibre PA6 material showed anisotropic behaviour. The anisotropic viscosity tensor principal model was used to characterise this anisotropy, the parameters of which were determined experimentally by the rheometer. Based on these findings, a unified modelling approach for material forming and resin flow was developed and applied to simulation analysis. The validity of the anisotropic viscosity intrinsic model and the unified simulation framework is verified by integrating the rheological analysis, in-mold analysis, and evaluation of the microstructure and mechanical properties of the moulded specimens, which provides a technical framework and a strategy for the application of the model in complex geometries.

Addressing the challenge of accurately measuring and predicting spindle rotational errors during CNC machine tool cutting operations, this paper proposes an effective error separation method and establishes a high-precision prediction model. This provides a basis for implementing error compensation and enhancing machining accuracy. A spindle rotational error measurement model is established using the three-point method. The Whale Optimisation Algorithm (WOA) is employed to optimise sensor mounting angles, thereby eliminating harmonic suppression. An experimental platform is constructed to collect displacement and vibration signals under varying machining parameters, with spindle rotational errors extracted via error separation techniques. Furthermore, the Hybrid Strategy Flower Pollination Algorithm (HSFPA) is integrated to optimise the Radial Basis Function (RBF) network, constructing the HSFPA-RBF prediction model. Experimental results indicate that optimising sensor installation angles to α = 15.47° and β = 31.64° effectively prevents harmonic suppression. The established HSFPA-RBF model demonstrates optimal predictive performance, achieving a root mean square error (RMSE) of 5 μm, a mean absolute error (MAE) of 3.4 μm, and a coefficient of determination (R2) of 0.9442. This methodology effectively captures spindle rotational errors during cutting operations. The developed model exhibits high predictive accuracy, providing technical support for online error compensation and process optimisation.

To investigate the influence law of grinding parameters on workpiece surface quality during laser-assisted belt grinding of nickel-based superalloys and clarify the action characteristics of each parameter on grinding force and surface roughness, this study firstly adopts finite element simulation to conduct numerical simulation on the single-abrasive-grain grinding process of nickel-based superalloys under laser-assisted conditions. On this basis, the influence of grinding parameters on surface roughness is analyzed through orthogonal tests, and a mathematical model for predicting surface roughness of laser-assisted belt grinding of nickel-based alloys is established via regression analysis. The simulation and experimental results show that the grinding force increases with the rise of grinding depth and decreases with the increase of laser power; the linear velocity of the abrasive belt has no significant effect on the grinding force. Increasing the laser power can greatly strengthen the material softening effect, improve the material plasticity, significantly enhance the flow characteristics during material removal, and finally form obvious surface plowing textures. The established surface roughness prediction model has high accuracy and applicability, which can effectively explain the influence law of grinding parameters on surface roughness and provide theoretical guidance for subsequent related research.

To address the machining challenges of multi-component high-entropy alloys and to investigate their material removal characteristics, this study focuses on the milling performance of CoCrFeNiMn HEA. Minimum quantity lubrication (MQL) technology was employed in milling experiments and compared with dry milling, with emphasis on cutting force and surface roughness. The effects of milling parameters on bottom-surface roughness and burr formation were systematically analyzed through a combination of single-factor and orthogonal experiments. The results indicate that under the given experimental conditions, the material removal mechanism of CoCrFeNiMn HEA is purely plastic deformation. Compared with dry milling, MQL significantly reduces cutting force and improves surface quality, with its advantages becoming more pronounced as the milling depth increases. Both surface roughness and burr height increase with higher feed speed and milling depth, but decrease with increasing spindle speed. This study provides a theoretical foundation for the application of MQL technology in machining difficult-to-cut materials and offers technical guidance for improving the milling quality of HEAs.

This study proposes the use of Physics-Informed Neural Networks (PINNs) to further advance the curvature interference analysis method. The nonlinear equation system encountered in determining the curvature interference limit line is embedded into the PINN loss function, thereby enabling the solution of high-dimensional, nonlinear equations. Computational results demonstrate that the PINN model achieves a solution accuracy on the order of 10−13 when solving multidimensional nonlinear systems, which is comparable to the classical Fsolve algorithm. The curvature interference analysis reveals the presence of two curvature interference boundary lines, although they rarely extend to the worm gear tooth surface. A study on the influence of design parameters on the interference boundaries indicates that the axial installation distance has the greatest impact. Inadequate axial spacing causes the interference limit line to shift toward the inner end of the worm gear, significantly increasing the risk of interference in that region. The proposed curvature interference analysis method based on PINNs can be extended to other types of gear drives. It also lays the foundation for future work on establishing both forward and inverse mappings between design parameters and curvature interference using PINNs.

Bulk metallic glasses (BMGs) have wide applications in aerospace, automotive power, and healthcare, and have become a new material with broad application potential. High material removal rate and high-efficiency drilling are among the main processes for creating holes with high dimensional accuracy and high casting surface quality. Poor hole quality can lead to cracks and reduced reliability. To propose a machining process suitable for amorphous alloys and achieve better drilling quality, this paper focuses on the Zr-based bulk metallic glass Zr52Cu17.5Ti16Ni12Nb2.5 as the research object. The drilling characteristics of the bulk metallic glass are studied through a combination of experiments and simulations, finding that the trends of simulation and experimental results are consistent, though the difference is around 30

Zr-based bulk metallic glass is a kind of hard brittle material which is extremely sensitive to temperature. The processing method has brought challenges to researchers. Milling-grinding composite machining combines the high efficiency of milling with the precision of grinding. By coating abrasive grain on the back surface of the milling cutter, the milling cutter has the ability of grinding. However, due to the grinding effect of abrasive particles, the cutting temperature is higher than that of milling. Using a frozen chuck effectively improved heat dissipation and reduced cutting temperature, and realized the low- temperature milling-grinding composite machining of Zr-based bulk metallic glass. The variations in machined surface morphology were compared when the spindle speed, feed rate and radial cutting depth were changed at room temperature and low temperature. The effects of different abrasive grain sizes and different tool edge numbers on the machined surface morphology and roughness were analyzed under room temperature processing conditions. The results show that the low-temperature environment can effectively improve the machined surface morphology, inhibit the occurrence of ridge mounted morphology and crazing on the machined surface, and low-temperature machining yields smoother surfaces with reduced roughness; Use the milling-grinding cutter with smaller abrasive grain size for processing, and effectively eliminate the scaly burrs generated on the processed surface; Dimples appear on the machined surface of four edge milling-grinding cutter, and the machined surface morphology is obviously different; The main failure modes of milling-grinding composite tools are coating bond peeling, tool tip chipping and coating wear; The two edge milling-grinding cutter is more suitable for low temperature milling-grinding of Zr-based BMG than the four edge cutter.

CoCrFeNiMn high-entropy alloy (HEA) produces a large number of burrs and leads to rapid tool wear by conventional milling due to its high plasticity and strength. An icing clamp was used to fix the workpiece to achieve low-temperature milling of HEA, thus improving the cutting performance of HEA. The influence of low-temperature milling parameters on the burr length, burr morphology and chip morphology were analyzed, and the wear mechanism of the tool under the two conditions of low-temperature milling and room-temperature milling was compared and analyzed. The findings reveal that a low-temperature environment significantly reduces burr size by suppressing plastic flow and promoting brittle fracture during chip formation. The primary tool wear mechanisms during high-entropy alloy milling include adhesive and abrasive wear. Low-temperature conditions effectively inhibit adhesive wear, thereby protecting the tool coating and extending tool life.

K9 optical glass plays an important role in the field of optics and optoelectronic information due to its high thermal stability and excellent optical imaging properties. Considering the low polishing efficiency and surface quality from its extremely high hard and brittle properties, a novel SiO2 polishing slurry containing K2CO3 and 3aminopropyltriethoxysilane (C9H23NO3Si, KH550) is prepared for ultrasonic vibration chemical-mechanical polishing (UV-CMP) of K9 optical glass, and its polishing characteristics and mechanism are investigated. The results demonstrate that K2CO3 promotes the material removal rate (MRR) significantly, while the adsorption effect of KH550 reduces the wear ratio and coefficient of friction (COF), and improves the dispersion of SiO2 abrasive particles and polishing performance of UV-CMP remarkably. Ultrasonic wave further induces softening of surface hydration reaction, homogeneous distribution of abrasive particles and enhances impact and grinding ability of abrasive particles. The optimal MRR is14.5298 mu m/min and Sa is 54.07 nm at 1.5 wt% K2CO3, 1.6 wt% KH550 and the ultrasonic amplitude of 6 mu m, indicating that the UV-CMP supplied guidance for multi-fieldassisted polishing of hard and brittle materials.

This paper introduces a method for thermal error modeling that integrates digital twin (DT) technology with transfer learning (TL) techniques. This research seeks to construct a generalizable and resilient thermal error modeling framework for CNC feed systems, ensuring consistent predictive performance across complex operating environments. A DT model is consequently established to emulate the temperature field evolution and corresponding thermal deformation behaviors of the feed system under various operational conditions. This simulated data acts as the source domain ( D_S ). The target domain ( D_T ) consists of the temperature and thermal error data collected during system operation. Time series samples are generated using sliding window technology, and normalization is applied to both the temperature features and thermal error labels. A bidirectional long short-term memory (BiLSTM) network, enhanced with a domain adversarial mechanism, is developed to tackle the discrepancies in data distribution across domains. This mechanism aligns the feature distributions, while the BiLSTM utilizes temporal modeling to capture the relationships between temperature features and thermal errors over time. Experimental results demonstrate that the proposed approach, a bidirectional long short-term memory network based on domain adversarial mechanism (DANN-BiLSTM), performs well across six representative transfer tasks. When evaluated in the D_T , the proposed method achieves a mean absolute error (MAE) of 1.458 μm, a root mean square error (RMSE) of 2.082 μm, and a coefficient of determination (R²) of 0.968, averaged across all six tasks. In the D_S , the MAE is 2.752 μm, the RMSE is 3.115 μm, and the R² is 0.927. The findings demonstrate that the proposed method achieves high predictive precision and exhibits robust cross-domain adaptability in modeling thermal errors under multifaceted operational conditions. Furthermore, the results demonstrate that the DT model can be regarded as a reliable source of training data, offering a novel approach for accurate thermal error prediction in feed drive systems.

This paper proposes further developing mismatched modification technology in meshing theory via physics-informed neural networks (PINNs). Thus, a design approach that considers meshing performance and meshing theory is presented for the mismatched parameters. On this basis, an innovative point-contact face worm gear drive with symmetric benchmark points is developed and its meshing theory is systematically developed. This study addresses high-dimensional nonlinear equation systems in tooth contact analysis (TCA) via PINN technology to convert initial value problems in conventional iterative methods into physical boundary problems. A PINN technique driven by meshing theory and meshing performance is proposed, achieving a coordinated optimization design for multiple mismatched parameters. The accuracy and feasibility of the PINN technique are proven by comparing it with the traditional iterative method. Applying the established meshing theory, TCA and error sensitivity analysis are conducted for the drive. The numerical results demonstrate that the PINN model has excellent accuracy in solving high-dimensional nonlinear equation systems. The analysis of the meshing characteristics indicates outstanding performance and a reduced susceptibility to installation errors.

CoCrFeNiMn high-entropy alloy (HEA), as a difficult-to-cut material, produces a large amount of heat of plastic deformation in the cutting area during cutting, and this local overheating phenomenon will lead to thermal damage to the surface of the workpiece, forming burn defects. This study proposes the application of an icing clamp in the milling process of CoCrFeNiMn to achieve low-temperature machining in order to address issues such as poor machined surface quality. Finite element simulations of low-temperature milling of HEA were carried out. Orthogonal and single-factor experiments for low-temperature milling of HEA were designed. The action mechanisms of milling process parameters (spindle speed, feed speed, and cutting depth) on the cutting force and cutting temperature were analyzed, and simulation results related to chip shape and workpiece surface topography were obtained. The range of process parameters for the low-temperature milling experiments of HEA were determined. Finally, based on the error analysis between experimental and simulation data of cutting force, the reliability of the finite element simulation model was verified. The influence mechanisms of process parameters on surface roughness, 3D surface topography, surface micro-topography, and surface microhardness were analyzed under low-temperature and room-temperature. The formation characteristics of the machined surface and the material removal behavior were revealed.

K9 optical glass is a basic optical material frequently utilized in aerospace and optical instruments. It is difficult to process due to its typical hard and brittle characteristics. To maximize its surface damage and processing efficiency, a SiO2 slurry incorporating K2CO3 (alkali metal salt) and KH550 (surfactant) was developed for ultrasonic vibration chemical-mechanical polishing (UV-CMP) of K9 optical glass. The promotional effects of K2CO3 and KH550 on enhancing the polishing performances were investigated by scratching experiments. The effect of polishing slurry components on surface roughness (Sa and Ra) and MRR was investigated by orthogonal experiments and the influence laws were derived. The optimal combination of polishing slurries was determined by combining principal component analysis (PCA) and grey relation analysis (GRA): 12 wt% SiO2 abrasive particle, pH = 12, 1.5 wt% K2CO3, and 1.6 wt% KH550. Sa, Ra, and MRR were 47.41 nm, 24.69 nm, and 0.0611 mm3/min, respectively. The proposed novel polishing slurry will facilitate the extremely efficient polishing of K9 optical glass, which is of great significance in guiding its practical production and application.

ObjectivesHigh-entropy alloys (HEA) with multi-principal elements have many excellent characteristics such as high strength, high hardness and high wear resistance, which have attracted widespread attention from scholars. However, the mechanical processing of HEA is difficult. This study utilizes minimal quantity lubrication (MQL) technology for milling HEA to improve their machining performance and explore the influences of different milling parameters on their milling force. MethodsThe thermodynamic coupling milling model of HEA (CoCrFeNiMn) and a four-edge end milling cutter is established using finite element simulation software. The difference in milling force between MQL milling and dry milling is studied by analyzing the material removal mechanism, and the influences of different milling parameters on milling forces are studied by single-factor experiments. Firstly, the three-dimensional model of the four-edge end milling cutter, the J-C constitutive model of HEA (CoCrFeNiMn), the heat conduction model and the contact friction model are established, and the material failure separation criteria are determined and the milling model is established. Then, the material removal mechanism under the thermodynamic coupling condition is analyzed, and the changes in milling forces between MQL milling and dry milling are analyzed from the perspectives of equivalent stress, contact friction and the thermal softening effect, and the advantages of MQL technology for milling HEA (CoCrFeNiMn) are analyzed. Finally, the effects of feed speed, spindle speed and milling depth on milling force are obtained by single-factor tests.ResultsThrough comparative experiments between dry milling and MQL milling, it is found that：(1) The equivalent stress produced by the two milling methods are concentrated in the first deformation zone, and the equivalent stress of dry milling is also concentrated in the position near the cutting edge. (2) The equivalent stress value of MQL milling in the first deformation zone is slightly greater than that of dry milling. (3) The heat generated by the two milling methods is concentrated in the first deformation zone and the chips, and the chips take away most of the heat. The chip temperature generated by dry milling is significantly higher than that generated by MQL milling. (4) MQL milling significantly reduces the temperature at the cutting site and improves chip integrity. (5) When the milling depth is 0.15 to 0.20 mm, the milling force of MQL milling is basically the same as that of dry milling. When the milling depth is greater than 0.20 mm, the ability of MQL milling to reduce milling force increases with the increase of milling depth. This is due to the use of MQL technology in the milling process, which compensates for the reduced milling force caused by low friction coefficient and the increased milling force caused by weak thermal softening effect. The MQL milling single-factor tests show that: (1) The milling force increases with the increase of feed speed, and decreases with the increase of spindle speed, that is, it increases with the increase of feed rate per tooth. (2) The milling force increases with the increase of milling depths, and the effect of feed rate per tooth on the average milling force is gradually intensified with the increase of milling depth. ConclusionsThe MQL milling has obvious advantages, which can significantly reduce milling force at milling depth greater than 0.20 mm, and the ability to reduce milling force increases with the increase of milling depth. In addition, the use of MQL technology in the milling process can significantly reduce the temperature at the cutting position, improve HEA machining accuracy, and avoid a series of defects of traditional pouring lubrication. The cutting force in MQL milling conforms to the change law of cutting force in most metal milling with the process parameters. In MQL milling, the milling force can be further reduced by increasing the spindle speed and reducing the feed speed. When the milling depth is large, the spindle speed should be further increased and the feed speed should be reduced to reduce the feed per tooth, in order to deal with the high sensitivity of the milling force to the milling depth.

Titanium alloys are widely used in the aerospace industry due to their high strength, high hardness, and high heat resistance. However, their high specific strength and low thermal conductivity pose challenges in traditional grinding processes, including high grinding force, difficulty in ensuring surface quality, and rapid abrasive wear of grinding belts. To address the aforementioned issues, this paper employs laser-assisted belt grinding to process titanium alloys. Through single-factor experiments, the influence of processing parameters on surface roughness and grinding force is investigated. Orthogonal experiments are further conducted to analyze the extent of these parameter effects on surface roughness and grinding force. A comparative analysis is conducted between conventional belt grinding and laser-assisted belt grinding of titanium alloys regarding surface roughness and grinding force. Preliminary investigations explore the improvement effects of laser-assisted grinding with different parameter combinations on the machinability and surface quality of titanium alloys. Analysis indicates that laser-assisted belt grinding can enhance the uniformity of titanium alloy surface texture, effectively improving the surface quality of titanium alloys after machining. To obtain optimal processing parameters for laser-assisted belt grinding of titanium alloys to guide subsequent machining, a regression model for surface roughness was established using experimental data. The processing parameters were optimized via a swarm algorithm, yielding the optimal combination: belt linear speed of 11.3 m/s, workpiece feed rate of 240 mm/min, contact wheel positive pressure of 0.21 MPa, abrasive belt grit size of 45 µm, and laser power of 200 W. Additionally, surface texture became more uniform, with significant improvements in defects such as pits, microcracks, and scratches.

Objectives:Research on ceramic processing primarily focuses on areas such as single abrasive grinding methods,processing mechanisms,processing efficiency,material removal mechanisms,and surface quality.However,research on ZrO2 ceramic cutting processing is relatively insufficient.Therefore,the 3D cutting process of ZrO2 ceramic workpieces was numerically simulated using the finite element simulation method.The study discusses the mechanism of chip removal,the dynamic change and distribution of stress,and the evolution law of cutting force under various cut-ting conditions.Methods:The 3D cutting process of ZrO2 ceramic workpieces,under different machining parameters and tool parameters,was numerically simulated using the finite element simulation method.The cutting forces under various feed speeds and cutting depths were compared to explore the failure modes and material removal mechanisms of ZrO2 ceramic during the cutting process.Results:The hard contact behavior between the cutting tool and the workpiece significantly affects the material removal process,leading to failure modes such as chip collapse,material cracking,and crack propagation.When the cutting depth is 200 μm or 250 μm,numerous cracks appear at the end edge of the work-piece and expand in the vertical cutting direction,resulting in significant fragmentation at the edge.An increase in cut-ting speed will causes fluctuations in stress and cutting force,but overall,there is no significant change in cutting per-formance.The radius of the cutting edge affects the formation of cracks in the initial cutting stage.As the edge radius in-creases,the length of the crack at the front end of the tool shortens,though the impact on cutting force is not significant.A negative tool rake angle during cutting does not induce cracks in the workpiece,and it leads to better machining qual-ity.In addition,when the tool rake angle is 0 °,the maximum cutting force increases rapidly,but the cutting force vari-ation is not obvious with increasing rake angle.Conclusions:As the cutting depth increases,the stress layer on the tool surface gradually expands from the tip to the front and rear cutting surfaces,and gradually increases.As the cutting depth increases,local cracks form at the cutting end of the workpiece and propagate downward.The position of maxim-um stress on the front cutting surface of the tool gradually increases with the increase in edge radius.However,the influ-ence of the edge radius on the cutting force is relatively small.When cutting ZrO2 ceramics with a tool featuring a negat-ive rake angle,no internal cracks are caused,and good machining quality can be achieved.

Ultrasonic vibration polishing (UVP) is an important method for the precision processing of optical glass, which is good for improving surface quality and processing efficiency. So far, the material removal mechanism in UVP is not well understood and the various process parameters involved are not considered. To achieve ultra-precision polishing under optical glass, this paper carries out the axial UVP method. The material removal profile (MRP) is critical to affect the surface accuracy. A new MRP is developed for UVP based on the Urick attenuation model and the proposed material removal coefficient distribution function, considering the dynamic pressure changes under ultrasonic vibration, the attenuation effect of the acoustic pressure propagation process and the inhomogeneous distribution of the abrasive particles in the contact area during the ultrasonic electro-spindle rotation. Through a series of polishing experiments and simulations, the results show that the maximum errors of the actual material removal depth (MRD) and the actual material removal rate (MRR) from the model simulation results are 8.54% and 9.92%, respectively. The accuracy of the model is further demonstrated by the Pearson correlation coefficient. When the amplitude of UVP is 9μm, Sa and Ra are 60nm and 68nm, which are reduced by 37.50% and 22.73%, respectively, compared with conventional polishing. This research can contribute to the deterministic processing of UVP, and provide a theoretical basis for the application of optical glass.

To study the removal mechanism of ITO conductive glass materials,this paper uses a single abrasive particle to simulate the cutting process of the materials and establishes a material model for ITO glass.Based on the analysis of processed surface morphology,stress,and cutting force,the material removal mechanism of ITO glass is examined.Ad-ditionally,the influence of cutting parameters on cutting force and residual stress is studied and compared with soda-lime glass.The results show that during the cutting process of abrasive particle,material removal is influenced by the ITO film layer,the glass substrate,and cohesive contact behavior,leading to failure forms such as delamination,chan-nel cracking,and interlayer fracture.With the feed of the abrasive particle,the cutting force fluctuates within a certain range,exhibiting a pattern of growth,stability,and decrease.The cutting force of the abrasive particle is positively cor-related with both cutting speed and cutting depth.Compared to the glass substrate,the residual stress on the ITO film is larger and fluctuates more dramatically.The presence of the ITO film significantly influences cutting behavior,espe-cially when the cutting depth approaches the thickness of the ITO film.