Needle-punched C/C composites exhibit pronounced strain rate sensitivity during service. However, due to their highly complex internal structure, significant anisotropy is observed. The dynamic mechanical behavior of this material currently lacks adequate explanation and analysis. This study investigates the dynamic mechanical response under various conditions by conducting compression impact tests on needle-punched C/C composites at different strain rates and along different orientations. The results indicate that under high kinetic energy, crack nucleation and propagation occur within the material. Compression along different orientations alters crack propagation paths, leading to distinct failure modes: along the needling direction, failure primarily manifests as fiber shear fracture and interfacial debonding; perpendicular to it, failure is dominated by interfacial delamination and matrix cracking. Simultaneously, a certain level of kinetic energy exhibits an inhibitory effect on interfacial debonding, enhancing the load-bearing capacity to some extent. Finally, a dynamic constitutive model incorporating the strain rate effects on elastic modulus and peak strength is established. Validation through numerical simulations confirms that the model effectively describes the dynamic mechanical behavior of needle-punched C/C composites.

C/C composites tend to suffer from machining-related damage, typically manifested as debonding and fiber pull-out. To address this issue, the present study investigates the material removal mechanisms and surface formation patterns in ultrasonic vibration-assisted milling (UVAM) of needle-punched C/C composites. A kinematic model of the cutting trajectory was established to reveal how the matching among cutting speed, ultrasonic frequency, and amplitude influences the variation in cutting direction. Furthermore, a fiber deformation model was developed based on the elastic foundation beam theory for two typical cutting angles. The effects of cutting speed and ultrasonic vibration on fiber deformation and the fracture threshold were analyzed. On this basis, milling experiments were conducted under various combinations of amplitude and cutting speed. Theoretical and experimental results demonstrate that UVAM exhibits a pronounced directional dependence. At low spindle speeds, concentrated ultrasonic impacts reduce the cutting force by up to 28.35%, while frequent downward strokes aggravate secondary fiber fracture and increase fiber pull-out. Above a critical spindle speed of approximately 3500 r/min, the impact effect becomes more dispersed, leading to an increase in cutting force of up to 27.61% and only marginal improvement in surface quality. For fibers perpendicular to the machined surface, moderate rotational speeds and amplitudes can reduce pull-out pits. However, for fibers parallel to the surface, a step-like morphology predominates and ultrasonic vibration may exacerbate interfacial debonding. This study reveals the coupling mechanism between ultrasonic vibration and cutting parameters, providing new insights into the UVAM mechanism of carbon fiber reinforced composites.

Line laser technology provides a flexible, efficient, and cost-effective measurement strategy for blade manufacturing. A critical step in this process is to stitch the local point clouds acquired from different views through coarse-to-fine registration. For new-generation aero-engines, compressor blades are evolving towards blisk structures, resulting in extremely low overlap between adjacent-view local point clouds. Moreover, the blades feature thin-walled free-form shapes, high-reflective surfaces, and variable curvature profiles, leading to captured local point clouds with insignificant features, noise, and inconsistent density. These factors, combined with the influence of blade machining errors, pose major challenges to fine registration. To address these problems, a similarity-guided overlap registration method, i.e., scale comparison and bidirectional interaction (SCBI), is proposed. This approach guides registration by leveraging the fact that overlap regions of adjacentview point clouds are essentially identical. By enhancing scale and shape similarities in overlap regions, the robust registration of local point clouds is achieved. Additionally, a blade simulation dataset is developed to systematically evaluate six types of mainstream registration methods and SCBI, among which the latter achieves optimal results. Finally, a line laser-based on-machine measurement (LLOMM) system is established to measure compressor blisk blades, with a mean deviation less than 0.030 mm. Real measurement experiments are designed to elaborate its measurement deviation, machining error evaluation, and measurement efficiency. With detailed comparisons against four types of advanced measurement technologies, the LLOMM system demonstrates potential advantages in the above aspects. This study provides a new solution for blisk geometric error evaluation and its adaptive machining development.

Hyper-redundant robots (HRs), with their slender, flexible, and highly redundant structures, are uniquely suited for operation in hazardous, harsh, and confined environments where traditional rigid robots face limitations. This review systematically examines developments in the design, modeling, and control of HRs over the past two decades (2005∼2025), based on comprehensive literature retrieval from Web of Science and Scopus. We categorize key advances in actuation technologies-including electric motors, cable, pneumatic, and bionic muscle actuators-and structural innovations enabling compliance and dexterity in constrained spaces. The review contrasts traditional geometric modeling approaches, such as piecewise constant curvature and Cosserat rod theories, with modern data-driven and hybrid learning-based control methods. Applications span diverse domains, including nuclear facilities, aerospace engine inspection, pipeline and underwater maintenance, aerial robotics, and minimally invasive surgery. We further identify major research challenges, such as stiffness regulation, real-time dynamic modeling, integration of smart materials, miniaturization, proprioceptive sensing, and safe human-robot collaboration. By synthesizing design principles, modeling frameworks, and control methods, this review not only evaluates the current maturity of HR research but also identifies potential opportunities for future advancement. The purpose of this review is to provide a reference point for researchers interested in the design, modeling, and control of HRs operating in constrained environments.

Superalloy sealing rings are complex thin-walled components used in high-performance aero-engine sealing systems,generally produced through multi-pass roll forming.However,their quality evaluation highly relies on final destructive inspection,making it difficult to identify defects in real time during manufacturing.A wire laser-based on-machine measurement method using local-global contour non-rigid registration was proposed,enabling contour measurement in post-forming pass and in-forming pass of the multi-pass rolling forming of superalloy sealing rings.To address issues such as outliers,missing data,and noise in the measured point cloud,a local-global contour registration approach was adopted to align the design model point cloud with the measured point cloud.Additionally,the convex hull algorithm and ray-crossing method were introduced to eliminate redundant points from the local contour registration results.Experimental results show that the mean deviation of the contour measurements is within 0.020 mm.

Thin-walled casing components in aeroengines undergo significant elastic deflection under cutting forces,which can easily cause dimensional deviations and reduce machining efficiency.Effectively suppressing elastic deflec-tion during machining is crucial for enhancing the machining quality and efficiency of casing components.Taking aero-engine casings as the research subject,this study investigates elastic deflection induced by cutting forces and pro-poses an adaptive deflection control method based on a support-force-adjustable fixture.First,an adaptive auxiliary support fixture considering the geometric features of the casing part was designed.Its mechanical analysis was con-ducted,a clamping positioning constraint model was established,and the deflection control effectiveness was verified through simulation.Second,an in-process adaptive deflection control method was established,dynamically regulating support force along the milling path.An inter-process support force compensation strategy was proposed,adjusting compensation coefficients between different processes to enhance casing milling accuracy.Finally,an adaptive auxil-iary support fixture with modular adjustable support force was developed by integrating the aforementioned methods and validated during the milling of a mock-up engine casing.Compared to the condition without auxiliary support,the combined in-process and inter-process support force compensation strategy reduced elastic deflection by up to 63.04%.

In the milling of thin-walled ring parts (TWRPs), supporting fixtures play a critical role in suppressing machining-induced deflection and improving machining quality. The supporting force exerted by the support head directly influences the effectiveness of deflection control. However, in current practice, the supporting force is typically determined based on engineering experience, which often leads to inconsistent and suboptimal suppression of deflection. To address this issue, this paper proposes an adaptive supporting-force control method for the multi-process milling of TWRPs. First, a predictive equation for the optimal supporting force is established through an analysis of the support characteristics of a curved support head. Based on this model, a supporting-force control strategy that integrates real-time force regulation with inter-process iterative learning is developed, along with a continuous multi-process deflection simulation method. In addition, a force-adjustable supporting fixture and its pneumatic control system are designed to implement the proposed approach. Experimental results show that the proposed control method, when applied without iterative learning, can reduce the average deflection in the supported region by more than 80%. By further incorporating the iterative learning mechanism to update the supporting-force gain between successive machining processes, the average deflection reduction can be improved to 93%. These results demonstrate the effectiveness of the proposed method in suppressing machining deflection in thin-walled ring parts.

Water-jet guided laser machining is characterized by cold cutting, low kerfs of taper, smooth machined surfaces, large depth-to-width ratio and environmental friendliness. Although water-jet guided laser machining with vertical incidence has been extensively studied, there has been no systematic investigation into the effects of oblique incidence on groove geometry, and microstructure evolution in Ti-6Al-4V material. Existing studies have not investigated the direct relationship between angle-dependent thermal effects and local material properties. To address this problem, this study explores the mechanism of inclination angle (0-50 °) on the geometric morphology, microstructure and mechanical properties of the machined channel. The findings demonstrate that the inclination angle significantly affects material removal and microstructural evolution by regulating thermo-mechanical coupling behavior. Finite element simulation further confirms that the inclined heat source produces an asymmetric temperature-gradient distribution across the groove, which is consistent with the observed EBSD microstructure and microhardness variation. Increasing inclination angle redistributes effective heat input and produces asymmetric thermal histories across the groove. This suppresses the formation of acicular α' martensite, promotes the generation of (α+β) dual-phase structure, and induces the formation of an ultra-fine grained remelted layer. An optimal balance of geometric and mechanical properties was obtained at 40°, with an aspect ratio of 0.96, an average microhardness of 429.62±6.90 HV within the measured near-surface region, and a residual compressive stress of approximately −167 MPa. The findings provide both theoretical and practical support for low-stress manufacturing of high-precision water-jet guided laser machining of titanium alloy components.

During high-speed machining, the microstructure evolution of the machined superficial layer, driven by intense thermo-mechanical coupling, exerts substantial effects on mechanical properties and fatigue strength. The absence of reliable predictive models for superalloys, particularly in engineering contexts, underscores the necessity for developing novel modeling approaches. In this work, a framework of cross-scale modeling is proposed for orthogonal cutting process of GH4169 to study the grain-scale plastic accommodation in the machined superficial layer, which consists of a macro-scale orthogonal cutting model based on Johnson-Cook constitutive equation, and a meso-scale representative volume element (RVE) model based on the crystal plasticity finite element method (CPFEM). The RVE model is developed based on the actual microstructure characteristics of the machined superficial layer, and outputs of the macro-scale cutting model are assigned to the boundary condition of RVE model. Then, the RVE model is used and microstructure evolution of machined superficial layer is simulated by developing a user subroutine based on CFFEM. Finally, validation of the RVE model results is conducted through orthogonal cutting experiments and scanning electron microscopy (SEM) analysis. Besides, it is found that the strain distribution of the machined superficial layer is uneven, which is different from the macro-scale simulation.

Plasma electron density derived from Hα Stark broadening provides an indirect indicator of the surface hardness response during laser shock peening.

Thin-walled components made of difficult-to-machine materials are widely used in aerospace and energy industries but are highly susceptible to machining-induced deformation. Existing deformation prediction approaches are commonly oriented towards single-stage milling and assume stationary process conditions and therefore fail to capture the influence of tool wear, which introduces continuously evolving loading and stress states during multi-stage milling. To address this limitation, this study proposes a state-dependent deformation prediction framework, established under simplified modeling assumptions, in which tool wear is explicitly modeled as a continuously evolving internal variable governing deformation evolution. The framework integrates wear-dependent cutting-force-induced elastic deflection and machining-induced residual stress (MIRS)driven distortion within a unified finite element-based prediction scheme. Multi-stage milling experiments on GH4169 thin-walled parts are conducted under stress-relieved conditions for validation. The results show that average deformation prediction errors remain below 10% for machined surfaces and below 15% for unmachined regions across all machining stages. Neglecting tool wear leads to prediction errors exceeding 45% during rough machining, and MIRS-induced distortion prediction deviations can exceed 100% at a few nodes, demonstrating the critical role of wear-induced loading evolution in improving deformation prediction accuracy. The findings reveal that deformation in multi-stage milling is fundamentally governed by evolving process states, highlighting the necessity of explicitly incorporating tool wear into deformation prediction models.

Ceramic matrix composites (CMCs), by virtue of their exceptional combination of high-temperature resistance, low density, and high strength, have become critical materials in fields such as aerospace and semiconductors. However, their inherent multiphase heterogeneous structure and anisotropy cause conventional mechanical machining to fall into a physical dilemma of uncontrollable stress-induced damage and degraded surface integrity. Therefore, centered on the regulation of surface integrity, this review systematically traces and deeply deconstructs the evolutionary pathway of energy field machining technologies for CMCs, revealing a profound paradigm revolution from passive stress-induced removal to active energy regulation. Specifically, the single mechanical energy field exposes the intrinsic limitations of macroscopic disordered brittle fracture; the vibro-mechanical energy field achieves dimensional reduction and containment of microcracks through high-frequency dynamic intervention; the thermo-mechanical energy field triggers quasi-plastic micro-separation via localized thermal softening; and ultimately, the thermo-vibro-mechanical composite energy field reaches the physical pinnacle of surface integrity regulation through the highest-dimensional spatiotemporal synergy. By systematically examining surface morphology, roughness, and subsurface damage, this review demonstrates the intrinsic mechanisms by which energy field regulation drives material removal from random fracture to controlled separation. Furthermore, the study distills the paradigm shift into a three-fold systematic leap: The evolution of energy action modes from single continuous inputs to multi-field spatiotemporal programming, the evolution of material removal mechanisms from brittle fracture to micro-scale controlled failure, and the evolution of core processing objectives from geometric shaping to active performance empowerment. Finally, this review anticipates future research directions, including the deepening of multi-field coupling mechanisms, the exploration of novel energy carriers, intelligent process decision-making, and the integrated leap of manufacturing capabilities, aiming to provide cutting-edge theoretical support and technical references for the precision machining of critical components in extreme environments.

Mg-Li dual-phase alloys offer low density and good ductility but suffer from limited strength. This study investigates orientation-dependent deformation and slip transfer across the α-Mg/β-Li phase boundary in Mg-7Li alloy using micropillar compression tests. Single-phase α-Mg micropillars with angles of 0°, 45°, and 90° between the compression axis and the <0001> axis, and dual-phase micropillars with the same three orientations, are fabricated. Lithium addition dramatically lowers the critical resolved shear stress (CRSS) for prismatic ⟨a⟩ slip and pyramidal slip in α-Mg phase, resulting in a CRSSprismatic/CRSSbasal ratio of 1.11 and a CRSSpyramidal/CRSSbasal ratio of 4.1. Phase boundary strengthening strongly depends on the α-Mg orientation. In the 0° and 45° dual-phase micropillars, basal dislocations transfer directly across the phase boundary due to high values paired with the {110}⟨111⟩ slip systems in the β-Li phase. This causes negligible strengthening and agree well with the isostrain model. In the 90° dual-phase micropillar, prismatic ⟨a⟩ dislocations cannot transmit across the boundary. Instead, they cross-slip onto the basal plane, become immobile due to the low Schmid factor pf basal slip, and accumulate at the phase boundary. This generates HDI stress and contributes to phase boundary strengthening, thereby producing a “1+1>2” strengthening effect. Tailoring the α-Mg orientation to activate prismatic slip turns the phase boundary into an effective barrier, offering a promising route to achieve high strength in Mg-Li dual-phase alloys.

The aerodynamic performance and operational stability of aero-engine axial compressors are governed primarily by the machining accuracy of rotor blade leading edges (LE). Modern highly loaded, thin-walled compressor blades exhibit an exponential aerodynamic sensitivity to micron-scale LE manufacturing deviations, posing a critical challenge for high-precision small-batch production of aerospace blades. Traditional probabilistic uncertainty quantification (PUQ) methods rely heavily on large-sample Gaussian assumptions, which leads to statistical divergence and underestimation of extreme risks under small-sample constraints. Conventional non-probabilistic convex models suffer from inherent over-conservatism, and most existing approaches fail to establish a physically interpretable mapping between manufacturing defects and aerodynamic performance degradation. Focusing on steady-state near-design operating conditions, to address these limitations, this study proposes a novel Non-Probabilistic Bounded Field (NPBF) model for LE deviation dispersion quantification and aerodynamic penalty evaluation. The method integrates physics-informed modal decomposition, a hybrid MVEE-KDE uncertainty domain to balance boundary reliability and conservatism, and a Gaussian process regression-based Bayesian optimization framework for CNC segmented milling parameters. Within the framework of the proposed NPBF method, integrated with the Bayesian optimization algorithm, the co-evolution metric is improved by 21.3% and the computational efficiency is improved by 43.3% compared with the standard genetic algorithm, achieving simultaneous enhancement of solution accuracy and computational efficiency. Test results of titanium alloy blisk sectors made of TC11 and TC17 with different material specifications and dimensions demonstrate that the intra-blade geometric dispersion of the leading edge is reduced by up to 9.5%, while the inter-blade profile deviation is decreased by up to 4.5%. Meanwhile, this geometric homogenization effect suppresses premature boundary layer separation and effectively reduces the aerodynamic loss coefficient, establishing an initial baseline framework for aerodynamically constrained machining accuracy optimization for aerospace manufacturing under small-sample constraints.

Fibre pull-out and interfacial debonding during the macro-brittle removal of C/SiC composites produce severe subsurface damage, compromising surface integrity. Ultrasound-assisted grinding enhances the support stiffness of equivalent homogeneous materials and reduces fibre bending deformation, improving machined surface quality. However, the influence of ultrasonic vibration on machining damage mechanisms from micro-scale mechanical models and material removal mechanisms has not been published. To suppress machining damage, this paper first conducts a comprehensive analysis of the high-frequency oscillatory cutting behaviour and separation effects of active abrasive grit within the grinding zone. Furthermore, the machining damages, including fibre pull-out and interfacial debonding, are mechanically modeled in terms of the interface crack deflection effect, fibre deformation, and fracture behaviour. Finally, the internal stresses, removal behaviour, and fracture modes of fibres with various ultrasonic amplitudes are predicted, and the optimal amplitude range to effectively suppress machining damage is acquired. Surface microstructure, grinding chips, roughness, and fractal dimension demonstrate that the machining damage suppression strategy can effectively inhibit fibre pull-out and interface debonding defects.

Aerospace alloys often operate under extreme conditions. Accurate defect segmentation in images of aerospace components is the key to quantifying the defects and evaluating their impact for part lifespan. The components usually have complex free-form surfaces, leading to uneven light distribution in images. The variable image presentations pose a great challenge for accurate segmentation, especially with limited data. Generative adversarial networks and other training-based methods are commonly used for image generation, but they still rely on sufficient high-quality training data. In this paper, a physical-based image generation method is proposed to create any possible scratches according to physical laws to improve the scratch segmentation capability with limited data. First, an efficient scratched blade surface image generation pipeline is developed. Then, a systematic strategy to maximize the effect of physical synthetic scratch images is presented. The experiments show that the segmentation intersection-over-union could be improved from 0.66 to 0.83 with only 20 real images for training, and reveal the influences of network structure, image and label quality, data fusion strategy on segmentation performance.

The heterogeneous microstructure of TC17/TC4 joint manufactured by linear friction welding will reduce the mechanical properties compared with the base metals, of which the strength and ductility are hard to be improved simultaneously by traditional aging heat treatment (AHT), seriously limiting the application of LFW in the manufacturing of TC17/TC4 blisks. To this end, the present work proposes to use electric pulse treatment (EPT) to enhance the strength and ductility of the joint simultaneously by improving its microstructure. The results show that EPT effectively improves the plasticity of the joint compared with AHT. The tensile properties of aging treated joint are similar to that of the as welded joint, which present a strength around similar to 805 MPa and an elongation around similar to 13%. When the joint was electric pulse treated at 550 degrees C and 630 degrees C for 1 h, the elongation increases to 15.8% and 16.3%, which is an increase of 21.5% and 34.7% compared to the corresponding heat-treated joint. The microstructural response under AHT is the aging precipitation behavior of lamellar alpha affected by welding process. Whereas, the microstructural response under electric pulse treatment is driven by local Joule heating effect and the electron wind effect. After EPT, the basket-weave distribution of alpha-lamellae on TC17 side enhances ductility while maintaining strength and the spheroidized alpha phase on TC4 side reduces the microstructural gradient and prevents stress concentration at locations of microstructural discontinuities, thereby improving ductility. This study offers valuable insights for improving the strength and ductility of LFW TC17/TC4 blisks and advancing the application of LFW in aeroengine components.

Carbon-fibre-reinforced-polyetherketonketone (CF/PEKK) has attracted increasing interest in the aviation industry due to its self-healing/recycling properties. However, its machining performance is not well understood and there is a lack of optimization study for minimizing its hole damage and improving the production efficiency. Here, we report the first multi-objective optimization study for CF/PEKK drilling. A hybrid optimization algorithm integrating NSGA-II and TOPSIS is deployed to obtain the Pareto solutions and rank the multiple solutions based on closeness to ideal solutions. To highlight the impact of different matrix properties on the optimization outcome, comparative study with conventional thermoset CF/epoxy was carried out for the first time. Experimental validation shows the proposed method can achieve 91.5-95.7% prediction accuracy and the Pareto solutions effectively controlled the delamination and thermal damage within permissible tolerance. The vastly different optimal drilling parameters identified for CF/PEKK and CF/epoxy is attributed to the thermoplastic nature of CF/PEKK with unique thermal/mechanical interaction characteristics.

Superior strength and high-temperature performance make γ-TiAl vital for lightweight aero-engines. However, its inherent brittleness poses machining problems. This study employed Elliptical Ultrasonic Vibration Milling (EUVM) to address these problems. Considering the influence of machining parameters on vibration patterns of EUVM, a separation time model was established to analyze the vibration evolutionary process, thereby instructing the cutting mechanism. On this basis, deep discussions regarding chip formation, cutting force, edge breakage, and subsurface layer deformation were conducted for EUVM and Conventional Milling (CM). Chip morphology showed the chip formation was rooted in the periodic brittle fracture. Local dimples proved that the thermal effect of high-speed cutting improved the plasticity of γ-TiAl. EUVM achieved a maximum 18.17% reduction in cutting force compared with CM. The force variation mechanism differed with changes in the cutting speed or the vibration amplitude, and its correlation with thermal softening, strain hardening, and vibratory cutting effects was analyzed. EUVM attained desirable edge breakage by achieving smaller fracture lengths. The fracture mechanisms of different phases were distinct, causing a surge in edge fracture size of γ-TiAl under microstructural differences. In terms of subsurface deformation, EUVM also showed strengthening effects. Noteworthy, the lamellar deformation patterns under the cutting removal state differed from the quasi-static, which was categorized by the orientation angles. Additionally, the electron backscattering diffraction provided details of the influence of microstructural difference on the orientation and the deformation of grains in the subsurface layer. The results demonstrate that EUVM is a promising machining method for γ-TiAl and guide further research and development of EUVM γ-TiAl.