Search Results (443)

Bone drilling is a widely encountered process in orthopedic surgeries and keyhole neuro surgeries. We are developing a sensor-integrated smart end-effector for drilling for robotic surgical applications. In manual surgeries, surgeons assess tool wear based on experience and force perception. In this work, we propose a machine-learning (ML)-based tool condition monitoring system based on multi-sensor data to preempt excessive tool wear during drilling in robotic surgery. Real-time data is acquired from the six-component force sensor of a collaborative arm along with the data from the temperature and multi-axis vibration sensor mounted on the bone specimen being drilled upon. Raw data from the sensors may have noises and outliers. Signal processing in the time- and frequency-domain are used for denoising as well as to obtain additional features to be derived from the raw sensory data. This paper addresses the challenging problem of identification of the most suitable ML algorithm and the most suitable features to be used as inputs to the algorithm. While dozens of features and innumerable machine learning and deep learning models are available, this paper addresses the problem of selecting the most relevant features, the most relevant AI models, and the optimal hyperparameters to be used in the AI model to provide accurate prediction on the tool condition. A unique framework is proposed for classifying tool wear that combines machine learning-based modeling with multi-sensor data. From the raw sensory data that contains only a handful of features, a number of additional features are derived using frequency-domain techniques and statistical measures. Using feature engineering, we arrived at a total of 60 features from time-domain, frequency-domain, and interaction-based metrics. Such additional features help in improving its predictive capabilities but make the training and prediction complicated and time-consuming. Using a sequence of techniques such as variance thresholding, correlation filtering, ANOVA F-test, and SHAP analysis, the number of features was reduced from 60 to the 4 features that will be most effective in real-time tool condition prediction. In contrast to previous studies that only examine a small number of machine learning models, our approach systematically evaluates a wide range of machine learning and deep learning architectures. The performances of 47 classical ML models and 6 deep learning (DL) architectures were analyzed using the set of the four features identified as most suitable. The Extra Trees Classifier (an ML model) and the one-dimensional Convolutional Neural Network (1D CNN) exhibited the best prediction accuracy among the models studied. Using real-time data, these models monitored the drilling tool condition in real-time to classify the tool wear into three categories of slight, moderate, and severe. Full article

Reinforced composite prestressed concrete hollow square (RCPHS) piles, installed through pre-drilling, grouting, and static jacking, integrate the large lateral contact area of cement–soil casings with the high strength and stiffness of prestressed concrete cores. This study combines full-scale vertical static load tests and finite-element (FE) simulations to explore the interaction among the core pile, plain-concrete casing, and surrounding soil. Results show that, at 3600 kN, RCPHS piles exhibit 76% less pile-head settlement compared to PHS piles, and a 36.5% reduction in pile-material expenditure is achieved using the RCPHS scheme. At the same settlement of 23 mm, RCPHS piles carry 87% more load than PHS piles. A 3D FE model developed in ABAQUS reveals that the core pile carries approximately 94% of the applied load. When the load exceeds 4180 kN, the axial force in the casing sharply increases at depths of 7–10 m. The simulated P–s curves align well with field measurements, confirming model accuracy. The superior performance of RCPHS piles is attributed to the graded elastic modulus and coordinated stress distribution of the core–casing–soil system, which enhances interface friction and overall load capacity. These findings provide a foundation for the design optimization of RCPHS piles in dense sandy foundations. Full article

The interlaminar drilling of CFRPs is a new machining method different from traditional drilling, in which the feed direction of the drill bit is parallel to the interlayer interface. To reasonably select tools for CFRP interlaminar drilling, four different types of tool structures, including twist drills, dagger drills, candlestick drills, and step drills, are employed to conduct interlaminar drilling. The axial force and the morphologies of material damage are extracted, the comprehensive damage factors are calculated, and the relation among tool structures, machining parameters, and outlet damage is analyzed. Results show that the peak axial force induced by the four types of tool structures reduces sequentially. The dagger drill and the candlestick drill tend to cause burrs and large-area surface tears, respectively, while the twist drill and the step drill will lead to more significant 3D tears. Among the four tools, the average comprehensive damage factor produced by twist drills is the smallest, making it more suitable for CFRP interlaminar drilling. In addition, this study establishes a mathematical prediction model for the peak axial force and the comprehensive damage factor and optimizes the process parameter combination of twist drills, with the spindle speed set to 4732.87 r/min and the feed speed to 0.137 mm/r. Full article

The aim of the study was to determine correlations between performance of vertical jumps and dolphin kick sprints, and between the results of a dry-land butterfly arm pull test and butterfly arms-only swimming. The study recruited competitive junior male swimmers (15.9 (0.7) years, 179.3 (5.3) cm body height, 64.6 (4.3) kg body mass). On dry land, we measured jump height, lower-limb work and power, as well as peak velocity, power, and force in the butterfly arm pull test. In swimming tests, time, velocity, power, force, and work were assessed during the dolphin kick and butterfly arms-only trials. Pearson’s correlation coefficients and the coefficients of determination were calculated between measurements. The findings showed correlations between swimming velocity and power recorded during the dolphin kick test with jump height, work and power measured in the jump tests (maximum r = 0.90, r² = 0,81, p < 0.05). The best correlations between the results of the jump tests and swim variables were determined for the CJ30s test. The butterfly arm pull test was not associated with all parameters measured by the butterfly arms-only test. Our study demonstrates that targeted dry-land training programmes using exercises like vertical jumps can enhance competitive swimmers’ performance and offer coaches an accessible means of tracking athlete progress. Moreover, such simple drills may serve as a cost-effective approach for early evaluation of strength and power potential and for preventing musculoskeletal injuries, all without requiring pool access or specialized underwater equipment. However, the small and homogeneous sample (n = 12, junior males only) and the absence of reliability analyses limit the generalizability of the results. 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

In this study, aluminium matrix hybrid composites reinforced with boron carbide (B₄C) and silicon carbide (SiC) were fabricated using the direct hot-pressing technique under 35 MPa pressure at 600 °C for 5 min. Particle size distribution and scanning electron microscope analysis were conducted for the input powders. The microstructure, mechanical properties, and drillability of the fabricated composites were examined. As the SiC content increased, the density decreased, hardness improved, and transverse rupture strength declined. Drilling experiments were performed based on the Taguchi L₁₈ orthogonal array. The control factors included cutting speed (25 and 50 m/min), feed rate (0.08, 0.16, and 0.24 mm/rev), point angle (100°, 118°, and 136°), and SiC content (0%, 5%, and 10%). Quality characteristics such as thrust force, torque, surface quality indicators, diameter deviation, and circularity deviation were evaluated. The Taguchi method was applied for single-response optimization, while the Entropy-weighted, Taguchi-based CoCoSo method was used for multi-response optimization. Analysis of Variance was conducted to assess factor significance, and regression analysis was used to model relationships between inputs and responses, yielding high R² values. The optimal drilling performance was achieved at 50 m/min, 0.08 mm/rev, 136°, and 10% SiC, and the confirmation tests verified these results within the 95% confidence interval. Full article

In extended-reach wells, cuttings bed formation in high-deviation sections presents a major challenge for hole cleaning and borehole stability. This study analyzes the morphological and mechanical behavior of cuttings beds, focusing on particle size distribution and repose angle as key indicators of accumulation behavior. The modeling approach considers dominant interparticle forces, including buoyancy and cohesion, while neglecting secondary microscale forces for clarity. A theoretical model is developed to predict repose angles under both rolling and sliding regimes and is calibrated through laboratory-scale experiments using simulated drilling fluid with field-representative rheological properties. Results show that cohesive effects are negligible when cuttings are of similar size but exhibit higher densities. Laboratory measurements reveal that the repose angle of cuttings beds varies between 23.9° and 31.7°, with increasing polyacrylamide (PAM) concentration and particle size contributing to steeper repose angles. Additionally, the rolling repose angle is found to be relatively stable, ranging from 25° to 30°, regardless of fluid or particle property variations. These findings provide a predictive framework and practical guidelines for optimizing hole cleaning strategies and designing more effective models in extended-reach drilling. Full article

Fracture-induced loss poses severe challenges to drilling operations, particularly under high-temperature and high-salinity conditions encountered in deep wells. Conventional plugging materials, characterized by relatively large particle sizes and poor structural integrity, often exhibit insufficient thermal stability and salt tolerance under extreme drilling conditions, making them prone to structural degradation and loss of adhesion, which ultimately leads to drilling fluid deterioration and downhole complications. To address this issue, a core–shell-structured microgel, ANDT-70 (named after the acronyms of 2-acrylamido-2-methylpropane sulfonic acid, N-vinyl-2-pyrrolidinone, N, N-dimethylacrylamide, dimethyl diallyl ammonium chloride, and titanium dioxide nanoparticles), was synthesized and systematically evaluated for its thermal stability, salt resistance, and interfacial adhesion capabilities. The structural evolution, dispersion behavior, and colloidal stability of the microgel were thoroughly characterized using scanning electron microscopy (SEM), transmission electron microscopy (TEM), atomic force microscopy (AFM), Raman spectroscopy, and Zeta potential analysis. Experimental results indicate that ANDT-70 exhibits excellent thermal stability and resistance to salt-induced degradation at 260 °C, maintaining its fundamental structure and performance under harsh high-temperature and high-salinity conditions, with a viscosity retention of 81.10% compared with ambient conditions. Compared to representative materials reported in the literature, ANDT-70 exhibited superior tolerance to ionic erosion in saline conditions. AFM analysis confirmed that ANDT-70 significantly improves bentonite slurry dispersion and reduces salt sensitivity risks. ANDT-70 stably adsorbs onto bentonite lamellae via the synergistic action of electrostatic interactions and hydrogen bonding, thereby forming a dense cementation network that markedly enhances the structural stability and adhesion of the system. This network significantly enhances the cohesion and structural integrity of drilling fluid systems under extreme conditions. In conclusion, ANDT-70 demonstrates strong potential as a high-performance functional microgel for enhancing the stability and effectiveness of advanced drilling fluids under complex geological environments. Full article

The affordability, ease of manufacturing, and assembly efficiency of cold-formed steel profiles have contributed to their widespread use in structural applications. However, the presence of holes in these profile webs is likely to reduce their mechanical resistance. This study explores the bending behavior of a built-up box section constructed using lipped and unlipped C-profiles, which are commonly utilized in the construction industry. The investigation focuses on the influence of self-drilling screw layout density and hole distribution within the section. A total of 30 different models were analyzed, considering three primary variables: the spacing of self-drilling screws, hole diameter, and the number of holes. The steel profiles were connected using self-drilling screws with spacing intervals of 100, 200, and 400 mm. Key parameters, such as moment capacity, effects on elastic zones, shear forces on screws, and ductility, were examined in relation to these variables. The findings indicate that reducing screw spacing and increasing the number of holes are crucial design factors for improving joint strength. However, while greater screw spacing enhances ductility, it leads to lower plastic deformation rates. Additionally, optimizing the number of holes in the section proved to be an effective strategy for improving ductility in the analyzed models. Mathematical evaluation confirmed that hole number and screw spacing significantly affect moment capacity and estimation stability, highlighting the need for their joint optimization in structural design. Full article

Microwave irradiation of rocks can reduce the strength of rocks and ease their subsequent excavation. Exploring the combination of microwave and cutting tools for rock breaking under different conditions is important to the practical engineering application of microwaves. Based on a true triaxial microwave-assisted dual-mode mechanical rock-breaking test system, high-power microwave irradiation of rocks was investigated under different true triaxial stresses, durations of microwave irradiation, and cutting tool conditions such as mechanical drilling tools and tunnel boring machine (TBM) hobs. This research provides important data support for improving the rock-breaking efficiency of mine mining and tunneling as well as mechanical cutting tools and TBM hobs. In this experiment, Chifeng basalt with a relatively high strength was adopted as the research object. A 15 kW (2.45-GHz) open high-power microwave device was used to irradiate 200 mm × 200 mm × 200 mm cubic Chifeng basalt samples under conditions of different burial depths, and a cone drill bit was used for staged excavation. After microwave irradiation of Chifeng basalt measuring 400 mm × 400 mm × 400 mm, a 4-inch (102 mm) rotary cutter was employed to conduct round-by-circle cutting and rock-breaking tests in the microwave irradiation area. The results show that under true triaxial stress, the law of rock breaking by microwave irradiation combined with cone drill bits is as follows: the cutting force shows a trend of increasing–decreasing–increasing again–decreasing again. After microwave irradiation combined with hob cutting, the effective range of the influence of the hob is within the third cutting circle, with a range of diameters of approximately 200 mm. The results also indicate that the open microwave device can pre-crack rocks under deep stress, and there is obvious crack propagation. This research has good applicability to microwave-combined cantilever road-headers and TBM as well as in the mining field, and has a promising development prospect. Full article

The transport behavior of particles in tortuous fractures is prevalent in the oil and gas extraction process and has a profound impact on engineering. However, due to a variety of factors, drilling fluid leakage is prone to occur during drilling and completion, and an evaluation system for the influence of meander characteristics on the kinetic properties of particles has not yet been established. To this end, this paper constructs a numerical model based on CFD-DEM numerical simulation to simulate the particle–fluid two-phase flow in the meandering fracture, investigates the mechanism of surface meandering on particle force, particle transport velocity, and particle residence time, and proposes a mathematical method based on meandering for predicting particle transport velocity and particle residence time in the stable transport phase. The results show that the increase in tortuosity makes the force state of particles in the fracture show significant instability and intensifies the interaction between fluid and particles in the fracture; the effect of the tortuous wall intensifies the inhomogeneity of transport velocity, and the perturbation effect of the complex path structure on the x-direction velocity of particles is stronger; and the increase in tortuosity is not conducive to particle retention in the fracture. The results of the study can provide theoretical guidance for reducing the risk of drilling fluid leakage during drilling and completion. Full article

Complex engineering systems—such as ultra-long horizontal wells in energy exploitation and distributed rail transit infrastructure—operate under harsh physical and environmental conditions, where accurate physical modeling and real-time parameter estimation are essential for ensuring safety, efficiency, and reliability. Traditional empirical and black-box data-driven approaches often fail to account for the underlying physical mechanisms, thereby limiting interpretability and generalizability. To address this, we propose a unified framework that integrates physics-informed scenario-based modeling with data-driven parameter inversion. In the first stage, critical system parameters—such as friction coefficients in drill string movement or contact forces in rail–wheel interactions—are explicitly formulated based on mechanical theory, leveraging symmetries and boundary conditions to improve model structure and reduce computational complexity. In the second stage, model parameters are identified or updated through inverse modeling using historical or real-time field data, enhancing predictive performance and engineering insight. The proposed methodology is demonstrated through two representative cases. The first involves friction estimation during tripping operations in the SU77-XX-32H5 ultra-long horizontal well of the Sulige Gas Field, where a mechanical load model is constructed and field-calibrated. The second applies the framework to rail transit systems, where wheel–rail friction is estimated from dynamic response signals to support condition monitoring and wear prediction. The results from both scenarios confirm that incorporating physical symmetry and data-driven inversion significantly enhances the accuracy, robustness, and interpretability of engineering analyses across domains. Full article

The increasing use of carbon fiber reinforced polymer (CFRP) composites in industries such as aerospace, due to its high strength-to-weight ratio, durability, and resistance to corrosion has led to a growing demand for more efficient machining processes. However, the multilayered structure of CFRP composites, composed of densely packed fibers, presents significant challenges during machining. Additionally, when cutting fluids are used to improve effective cooling and lubrication, the material tends to absorb the fluid, causing damage and leading to problem of weaking of composite structure. To address these issues, this study compares ultrasonic-assisted drilling (UAD) and minimum quantity lubrication (MQL) techniques with conventional drilling (CD) and dry cutting to improve the performance of CFRP composite drilling. The results show that using UAD and MQL together reduced thrust force by up to 27%, improved surface roughness inside the holes by up to 31%, reduced improved hole diameter, cylindricity, roundness, and delamination. Full article

To investigate the settling behavior and drag characteristics of particles in fiber-containing non-Newtonian fluids, a series of systematic single-particle settling experiments were conducted. Power-law and Herschel–Bulkley fluids were prepared as base media, into which polyester fibers of various concentrations and lengths were introduced. The effects of fiber structural parameters on fluid rheology and terminal settling velocity were thoroughly evaluated. First, the rheological changes induced by fiber addition were quantitatively analyzed, revealing a nonlinear increase in both viscosity and yield stress with increasing fiber concentration and length. Subsequently, the total drag force was decomposed into viscous and fiber-induced components, and a predictive model for the fiber-induced drag coefficient was developed based on fiber structural parameters. A power-law fitting approach was employed to characterize the nonlinear relationship between the fiber drag coefficient and the particle Reynolds number. Furthermore, a parametric coupling strategy was employed, in which fiber concentration and length were embedded into the model coefficients to construct a unified and continuous predictive model for the total drag coefficient. Experimental validation demonstrated that the mean relative errors (MREs) of the proposed model were within 5.17% for power-law fluids and 9.95% for Herschel–Bulkley fluids, indicating strong predictive accuracy and applicability. The findings of this study provide a robust theoretical and experimental basis for optimizing fiber-enhanced cutting transport systems and modeling particle transportation under complex drilling conditions. Full article

Drilling-induced damage in fiber-reinforced polymer composite materials was measured excavating four laminates, basalt (B₁₄), glass (G₁₄) and their two sandwich type hybrids (B₄G₆B₄, G₄B₆G₄), with 6 mm twist drills at 1520 revolutions per minute and 0.10 mm rev⁻¹ under dry running with an uncoated high-speed steel (HSS-R), grind-coated high-speed steel (HSS-G) or physical vapor deposition-coated (high-speed steel coated with Titanium Nitride (TiN) and Titanium Aluminum Nitride (TiAlN)) drill bits. The hybrid sheets were deliberately incorporated to clarify how alternating basalt–glass architectures redistribute interlaminar stresses during drilling, while the hard, low-friction TiN and TiAlN ceramic coatings enhance cutting performance by forming a heat-resistant tribological barrier that lowers tool–workpiece adhesion, reduces interface temperature, and thereby suppresses thrust-induced delamination. Replacement of an uncoated, grind-coated, high-speed-steel drill (HSS-G) with the latter coats lowered the mechanical and thermal loads substantially: mean thrust fell from 79–94 N to 24–30 N, and peak workpiece temperatures from 112 °C to 74 °C. Accordingly, entry/exit oversize fell from 2.5–4.7% to under 0.6% and, from the surface, the SEM image displayed clean fiber severance rather than pull-out and matrix smear. By analysis of variance (ANOVA), 92.7% of the variance of thrust and 86.6% of that of temperature could be accounted for by the drill-bit factor, thus confirming that the coatings overwhelm the laminate structure and hybrid stacking simply redistribute, but cannot overcome, the former influence. Regression models and an artificial neural network optimized via meta-heuristic optimization foretold thrust, temperature and delamination with an R² value of 0.94 or higher, providing an instant-screening device with which to explore industrial application. The work reveals TiAlN- and TiN-coated drills as financially competitive alternatives with which to achieve ±1% dimensional accuracy and minimum subsurface damage during multi-material composite machining. Full article