Search Results (2,364)

One of the most important challenges the tire industry faces is becoming carbon-neutral and using 100% sustainable materials by 2050. Utilizing materials from renewable sources and recycled substances is a key aspect of achieving this goal. Petroleum-based oils, such as Treated Distillate Aromatic Extract (TDAE), are frequently used in rubber compounds, and a promising strategy to enhance sustainability is to use bio-based plasticizer alternatives. However, research has shown that the replacement of TDAE oil with bio-based oils or resins can significantly alter the glass transition temperature (T_g) of the final compound, influencing the tire properties. In this study, the theory was proposed that using a plasticizer blend, comprising oil and resin, in a rubber compound would result in similar T_g values as the reference compound containing TDAE. To test this, the cycloaliphatic di-ester oil Hexamoll DINCH, which can be made out of bio-based feedstock by the BioMass Balance approach, was selected and blended with the cycloaliphatic hydrocarbon resin Escorez 5300. Various oil-to-resin ratios were investigated, and a linear increase in the T_g of the vulcanizate was obtained when increasing the resin content and decreasing the oil content. Additionally, a 50/50 blend, consisting of 18.75 phr Hexamoll DINCH and 18.75 phr Escorez 5300, resulted in the same T_g of −19 °C as a compound containing 37.5 phr TDAE. Furthermore, this blend resulted in similar curing characteristics and cured Payne effect as the reference with TDAE. Moreover, a similar rolling resistance indicator (tan δ at 60 °C = 0.115), a slight deterioration in wear resistance (ARI = 83%), but an improvement in the stress–strain behavior (M300 = 9.18 ± 0.20 MPa and Ts = 16.3 ± 0.6 MPa) and wet grip indicator (tan δ at 0 °C = 0.427) were observed. The results in this work show the potential of finding a balance between optimal performance and sustainability by using plasticizer blends. Full article

Optimising the friction coefficient helps reduce friction losses and improve the efficiency of mechanical systems. The purpose of this study is to experimentally investigate the impact of roughness orientation on the friction coefficient in elastohydrodynamic (EHD) contact. Tests were carried out on a twin-disc machine. Three pairs of discs of identical material (nitrided steel) and geometry were tested: a smooth pair (the root mean square surface roughness Sq = 0.07 µm), a pair with transverse roughness and another with longitudinal roughness. The two rough pairs have similar roughness amplitudes (Sq = 0.5 µm). A comparison of the friction generated by these different pairs was carried out to highlight the effect of the roughness orientation under different operating conditions (oil injection temperature from 60 to 80 °C, Hertzian pressure from 1.2 to 1.5 GPa and mean rolling speed from 5 to 30 m/s). Throughout all the tests conducted in this study, longitudinal roughness resulted in higher friction than transverse, with an increase of up to 30%. Moreover, longitudinal roughness is more sensitive to variations in operating conditions. Finally, in all tests, the asperities of longitudinal roughness were found to influence the friction behaviour, unlike transverse roughness. Full article

This paper addresses the problem of loss of control during flight caused by failures of flight control surfaces. It presents a study of an emergency thrust control system based on linear-quadratic control with integral action. The research encompasses an analysis of thrust modulation control characteristics, a review of existing control systems, and a detailed description of the development process, including the research platform configuration, identification of the aircraft state-space model, control law design, integration of system components within the MATLAB and Simulink environment, and software-in-the-loop testing conducted in the X-Plane 11 flight simulator using a Boeing 757-200 model. The study also investigates the issue of control channel cross-coupling and its impact on simultaneous control of the aircraft’s longitudinal and lateral dynamics. The simulation results demonstrate that the proposed emergency system provides adequate controllability, with settling times of approximately 12 s for achieving a flight path angle setpoint of +5°, and 13 s for attaining a maximum (limited) roll angle of 20°, achieved in separate manoeuvres. Furthermore, simulated landing attempts suggest that the system could potentially enable successful landings at approach speeds significantly higher than standard recommendations. However, further investigation is required to address decoupling of control channels, ensure system stability, and evaluate control performance across a broader range of aircraft configurations. Full article

Reducing gear noise in electric vehicle (EV) drivetrains is crucial due to the absence of internal combustion engine noise, making even minor acoustic disturbances noticeable. Manufacturing parameters significantly influence gear-generated noise, yet traditional analytical methods often fail to predict these complex relationships accurately. This research addresses this gap by introducing a data-driven approach using machine learning (ML) to predict gear noise levels from manufacturing and sensor-derived data. The presented methodology encompasses systematic data collection from various production stages—including soft and hard machining, heat treatment, honing, rolling tests, and end-of-line (EOL) acoustic measurements. Predictive models employing Random Forest, Gradient Boosting (XGBoost), and Neural Network algorithms were developed and compared to traditional statistical approaches. The analysis identified critical manufacturing parameters, such as surface waviness, profile errors, and tooth geometry deviations, significantly influencing noise generation. Advanced ML models, specifically Random Forest, XGBoost, and deep neural networks, demonstrated superior prediction accuracy, providing early-stage identification of gear units likely to exceed acceptable noise thresholds. Integrating these data-driven models into manufacturing processes enables early detection of potential noise issues, reduces quality assurance costs, and supports sustainable manufacturing by minimizing prototype production and resource consumption. This research enhances the understanding of gear noise formation and offers practical solutions for real-time quality assurance. Full article

Addressing lateral-directional control challenges during unmanned aerial vehicle (UAV) landing in complex wind fields, this study proposes a drift angle control strategy that integrates coordinated heading and trajectory regulation. An adaptive radius optimization method for the Dubins approach path is designed using wind speed estimation. By developing a wind-coupled flight dynamics model, we establish a roll angle control loop combining the $L_1$ nonlinear guidance law with Linear Active Disturbance Rejection Control (LADRC). Simulation tests against conventional sideslip approach and crab approach, along with flight tests, confirm that the proposed autonomous landing system achieves smoother attitude transitions during landing while meeting all touchdown performance requirements. This solution provides a theoretically rigorous and practically viable approach for safe UAV landings in challenging wind conditions. Full article

Background/Objectives: The extensive use of computed tomography (CT) has led to a significant increase in the detection of small and non-palpable pulmonary nodules, necessitating the use of invasive methods for definitive diagnosis. Video-assisted thoracoscopic surgery (VATS) has become the preferred procedure for nodule resections; however, intraoperative localization remains challenging, especially for deep or subsolid lesions. This study explores whether SPECT/CT improves the technical and clinical outcomes of radio-guided occult lesion localization (ROLL) before uniportal video-assisted thoracoscopic surgery (u-VATS). Methods: This is a retrospective study involving consecutive patients referred for the resection of pulmonary nodules who underwent CT-guided ROLL followed by u-VATS between September 2017 and December 2024. From January 2023, SPECT/CT was systematically added after planar imaging. The cohort was divided into a planar group and a planar + SPECT/CT group. The inclusion criteria involved nodules sized ≤ 2 cm, with ground glass or solid characteristics, located at a depth of <6 cm from the pleural surface. ^99mTc-MAA injected activity, timing, the classification of planar and SPECT/CT image findings (focal uptake, multisite with focal uptake, multisite without focal uptake), spillage, and post-procedure complications were evaluated. Statistical analysis was performed, with continuous data expressed as the median and categorical data as the number. Comparisons were made using chi-square tests for categorical variables and the Mann–Whitney U test for procedural duration. Cohen’s kappa coefficient was calculated to assess agreement between imaging modalities. Results: In total, 125 patients were selected for CT-guided radiotracer injection followed by uniportal-VATS. The planar group and planar + SPECT/CT group comprised 60 and 65 patients, respectively. Focal uptake was detected in 68 (54%), multisite with focal uptake in 46 (36.8%), and multisite without focal uptake in 11 patients (8.8%). In comparative analyses between planar and SPECT/CT imaging in 65 patients, 91% exhibited focal uptake, revealing significant differences in classification for 40% of the patients. SPECT/CT corrected the classification of 23 patients initially categorized as multisite with focal uptake to focal uptake, improving localization accuracy. The mean procedure duration was 39 min with SPECT/CT. Pneumothorax was more frequently detected with SPECT/CT (43% vs. 1.6%). The intraoperative localization success rate was 96%. Conclusions: SPECT/CT imaging in the ROLL procedure for detecting pulmonary nodules before u-VATs demonstrates a significant advantage in reclassifying radiotracer positioning compared to planar imaging. Considering its limited impact on surgical success rates and additional procedural time, SPECT/CT should be reserved for technically challenging cases. Larger sample sizes, multicentric and prospective randomized studies, and formal cost–utility analyses are warranted. Full article

Objectives: Pelvic tumor resections demand high surgical precision to ensure clear margins while preserving function. Although patient-specific instruments (PSIs) improve osteotomy accuracy, positioning errors remain a limitation. This study evaluates the feasibility, accuracy, and usability of a novel dual-function augmented reality (AR) system for intraoperative guidance in PSI positioning and osteotomy execution using a head-mounted display (HMD). The system provides dual-function support by assisting both PSI placement and osteotomy execution. Methods: Ten fresh-frozen cadaveric hemipelves underwent AR-assisted internal hemipelvectomy, using customized 3D-printed PSIs and a new in-house AR software integrated into an HMD. Angular and translational deviations between planned and executed osteotomies were measured using postoperative CT analysis. Absolute angular errors were computed from plane normals; translational deviation was assessed as maximum error at the osteotomy corner point in both sagittal (pitch) and coronal (roll) planes. A Wilcoxon signed-rank test and Bland–Altman plots were used to assess intra-workflow cumulative error. Results: The mean absolute angular deviation was 5.11 ± 1.43°, with 86.66% of osteotomies within acceptable thresholds. Maximum pitch and roll deviations were 4.53 ± 1.32 mm and 2.79 ± 0.72 mm, respectively, with 93.33% and 100% of osteotomies meeting translational accuracy criteria. Wilcoxon analysis showed significantly lower angular error when comparing final executed planes to intermediate AR-displayed planes (p < 0.05), supporting improved PSI positioning accuracy with AR guidance. Surgeons rated the system highly (mean satisfaction ≥ 4.0) for usability and clinical utility. Conclusions: This cadaveric study confirms the feasibility and precision of an HMD-based AR system for PSI-guided pelvic osteotomies. The system demonstrated strong accuracy and high surgeon acceptance, highlighting its potential for clinical adoption in complex oncologic procedures. Full article

Efficient maintenance is paramount for rail transport systems to avoid catastrophic accidents. Therefore, a method that enables the early detection of defects in critical components is crucial for increasing the availability of rolling stock and reducing maintenance costs. This work’s main contribution is the proposal of a methodology for analyzing vibration signals. The vibration signals, obtained from a bogie axle on a test bench, are decomposed into intrinsic functions, to which classical signal processing techniques are then applied. Finally, decision trees are employed to characterize the axle’s state, yielding excellent results. Full article

Rolling bearings serve as the most widely utilized general components in drive systems for rotating machinery, and they are susceptible to regular malfunctions. To address the performance degradation encountered by current convolutional neural network-based rolling-bearing-fault diagnosis methods due to significant noise interference and variable working conditions in industrial settings, we propose a rolling-bearing-fault diagnosis method based on dual multi-scale mechanism applicable to noisy-variable operating conditions. The suggested approach begins with the implementation of Variational Mode Decomposition (VMD) on the initial vibration signal. This is succeeded by a denoising process that utilizes the goodness-of-fit test based on the Anderson–Darling (AD) distance for enhanced accuracy. This approach targets the intrinsic mode functions (IMFs), which capture information across multiple scales, to obtain the most precise denoised signal possible. Subsequently, we introduce the Dynamic Weighted Multi-Scale Feature Convolutional Neural Network (DWMFCNN) model, which integrates two structures: multi-scale feature extraction and dynamic weighting of these features. Ultimately, the signal that has been denoised is utilized as input for the DWMFCNN model to recognize different kinds of rolling-bearing faults. Results from the experiments show that the suggested approach shows an improved denoising performance and a greater adaptability to changing working conditions. Full article

To address the challenges of unstable vibration signals, indistinct fault features, and difficulties in feature extraction during rolling bearing operation, this paper presents a novel fault diagnosis method based on the fusion of PSR-CRP and DenseNet. The Phase Space Reconstruction (PSR) method transforms one-dimensional bearing vibration data into a three-dimensional space. Euclidean distances between phase points are calculated and mapped into a Color Recurrence Plot (CRP) to represent the bearings’ operational state. This approach effectively reduces feature extraction ambiguity compared to RP, GAF, and MTF methods. Fault features are extracted and classified using DenseNet’s densely connected topology. Compared with CNN and ViT models, DenseNet improves diagnostic accuracy by reusing limited features across multiple dimensions. The training set accuracy was 99.82% and 99.90%, while the test set accuracy is 97.03% and 95.08% for the CWRU and JNU datasets under five-fold cross-validation; F1 scores were 0.9739 and 0.9537, respectively. This method achieves highly accurate diagnosis under conditions of non-smooth signals and inconspicuous fault characteristics and is applicable to fault diagnosis scenarios for precision components in aerospace, military systems, robotics, and related fields. Full article

The experimental tests needed for the estimation of the fatigue limit generally require extensive time and many specimens. A valid but not standardized alternative is the thermographic analysis of the self-heating phenomenon. The present work is aimed at using Infrared thermography to determine the fatigue limit in two kinds of Ti-6Al-4V samples obtained by hot rolling: (1) with the standard dog-bone shape (unnotched specimen) and (2) with two opposed semicircular notches at the sides (notched specimen). Uniaxial tensile experiments are performed on unnotched samples, and the surface temperature variation during loading is monitored. The stress corresponding to the end of the thermoelastic stage gives a rough indication of the fatigue limit. Then, fatigue tests at different sinusoidal loads are performed, and the thermographic signal is monitored and processed. The results obtained using lock-in thermography in dissipative mode, e.g., analyzing the second harmonic, showed a sudden change in slope when the applied stress exceeded a certain limit. This slope change is related to the fatigue limit. In addition, the ratio between the fatigue limits obtained for notched and unnotched specimens, e.g., the fatigue strength reduction factor, is consistent with literature values based on the selected geometry. Full article

Curved plate forming is essential in shipbuilding but traditionally relies on manual methods with low efficiency. Achieving automation in curved plate forming requires robust methods to generate processing solutions. This paper introduces a novel method for deriving the processing routes and strain distributions necessary to form complex curve plate using integrated heating and mechanical rolling forming equipment. The key aspects of this method include analyzing the target surface and solving for the required processing strains based on finite element analysis, discretizing the strain paths and refining them into engineering-feasible processing routes, deriving processing schemes from the calculated strains, and predicting and validating the processing schemes using the inherent strain method. The method is validated by applying it to typical surface of ship hull plates. Key outcomes demonstrate the method’s effectiveness and applicability: (1) The proposed method effectively establishes a quantitative relationship between the target surface geometry, processing routes, and the required processing strains. (2) By analyzing various target surface cases, the method demonstrates wide applicability. Standardized procedures can be applied to different surface shapes to derive the necessary processing routes and strains, thereby laying a solid foundation for the automation of curved hull plate forming. (3) Experimental forming tests on typical curved surfaces confirm that the processing schemes based on the proposed strain generation method can reliably achieve the desired geometries, showcasing the method’s capability to guide practical forming processes. The comparison between the formed and target shapes shows that the processing deviation of the schemes generated by this method remains within 5 mm, demonstrating high accuracy. Full article

Sustainable deepwater drilling for oil and gas offers significant potential. In this work, we synthesized a nanoscale collapse-prevention agent by grafting didecyldimethylammonium chloride onto spherical nano-silica and characterized it using Fourier-transform infrared spectroscopy, thermogravimetric analysis, zeta-potential, and particle-size measurements, as well as SEM and TEM. Adding 1 wt% of this agent to a bentonite slurry only marginally alters its rheology and maintains acceptable low-temperature flow properties. Microporous-membrane tests show filtrate passing through 200 nm pores drops to 55 mL, demonstrating excellent plugging. Core-immersion studies reveal that shale cores retain integrity with minimal spalling after prolonged exposure. Rolling recovery assays increase shale-cutting recovery to 68%. Wettability tests indicate the water contact angle rises from 17.1° to 90.1°, and capillary rise height falls by roughly 50%, reversing suction to repulsion. Together, these findings support a synergistic plugging–adsorption–hydrophobization mechanism that significantly enhances wellbore stability without compromising low-temperature rheology. This work may guide the design of high-performance collapse-prevention additives for safe, efficient deepwater drilling. Full article

As investment portfolios become increasingly diversified and financial asset risks grow more complex, accurately forecasting the risk of multiple asset classes through mathematical modeling and identifying their heterogeneity has emerged as a critical topic in financial research. This study examines the volatility and tail risk of gold, crude oil, Bitcoin, and selected stock markets. Methodologically, we propose two improved Value at Risk (VaR) forecasting models that combine the autoregressive (AR) model, Exponential Generalized Autoregressive Conditional Heteroskedasticity (EGARCH) model, Extreme Value Theory (EVT), skewed heavy-tailed distributions, and a rolling window estimation approach. The model’s performance is evaluated using the Kupiec test and the Christoffersen test, both of which indicate that traditional VaR models have become inadequate under current complex risk conditions. The proposed models demonstrate superior accuracy in predicting VaR and are applicable to a wide range of financial assets. Empirical results reveal that Bitcoin and the Chinese stock market exhibit no leverage effect, indicating distinct risk profiles. Among the assets analyzed, Bitcoin and crude oil are associated with the highest levels of risk, gold with the lowest, and stock markets occupy an intermediate position. The findings offer practical implications for asset allocation and policy design. Full article

In the industrial practice of metal forming, the consistent and reasonable characterization of the material behavior under the coupling effect of strain, strain rate, and temperature on the material flow stress is very important for the design and optimization of process parameters. The purpose of this work was to establish an appropriate constitutive model to characterize the rheological behavior of a hot-formed steel plate (22MnB5 steel) produced through the TSCR (Thin Slab Casting and Rolling) process under practical deformation temperatures (150–250 °C) and strain rates (0.001–3000 s⁻¹). Subsequently, the material flow behavior was modeled and predicted using the Johnson–Cook flow stress constitutive model. In this study, uniaxial tensile tests were conducted on 22MnB5 steel at room temperature under varying strain rates, along with elevated-temperature tensile tests at different strain rates, to obtain the engineering stress–strain curves and analyze the mechanical properties under various conditions. The results show that during room-temperature tensile testing within the strain rate range of 10⁻³ to 300 s⁻¹, the 22MnB5 steel exhibited overall yield strength and tensile strength of approximately 1500 MPa, and uniform elongation and fracture elongation of about 7% and 12%, respectively. When the strain rate reached 1000–3000 s⁻¹, the yield strength and tensile strength were approximately 2000 MPa, while the uniform elongation and fracture elongation were about 6% and 10%, respectively. Based on the experimental results, a modified Johnson–Cook constitutive model was developed and calibrated. Compared with the original model, the modified Johnson–Cook model exhibited a higher coefficient of determination (R²), indicating improved fitting accuracy. In addition, to predict the material’s damage behavior, three distinct specimen geometries were designed for quasi-static strain rate uniaxial tensile testing at ambient temperature. The Johnson–Cook failure criterion was implemented, with its constitutive parameters calibrated through integrated finite element analysis to establish the damage model. The determined damage parameters from this investigation can be effectively implemented in metal forming simulations, providing valuable predictive capabilities regarding workpiece material performance. Full article