Search Results (252)

Divinylisoprene rubber, a copolymer of butadiene and isoprene, is used as raw material for rubber technical products, combining isoprene rubber’s elasticity and butadiene rubber’s wear resistance. These properties depend quantitatively on the copolymer composition, which depends on the kinetics of its synthesis. This work aims to theoretically describe how the monomer mixture composition in the butadiene–isoprene copolymerization affects the activity of the TiCl₄–Al(i-C₄H₉)₃ catalytic system (expressed by active sites concentration) via kinetic modeling. This enables development of a reliable kinetic model for divinylisoprene rubber synthesis, predicting reaction rate, molecular weight, and composition, applicable to reactor design and process intensification. Active sites concentrations were calculated from experimental copolymerization rates and known chain propagation constants for various monomer compositions. Kinetic equations for active sites formation were based on mass-action law and Langmuir monomolecular adsorption theory. An analytical equation relating active sites concentration to monomer composition was derived, analyzed, and optimized with experimental data. The results show that monomer composition’s influence on active sites concentration is well described by a two-step kinetic model (physical adsorption followed by Ti–C bond formation), accounting for competitive adsorption: isoprene adsorbs more readily, while butadiene forms more stable active sites. Full article

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

To address the wear life prediction challenge of Guide Cones in passive compliant connectors under dynamic loads within specialized equipment, this study proposes a dynamic wear modeling and life assessment method based on the improved Archard model. Through integrated theoretical modeling, finite element simulation, and experimental validation, we establish a bidirectional coupling framework analyzing dynamic contact mechanics and wear evolution. By developing phased contact state identification criteria and geometric constraints, a transient load calculation model is established, revealing dynamic load characteristics with peak contact forces reaching 206.34 N. A dynamic contact stress integration algorithm is proposed by combining Archard’s theory with ABAQUS finite element simulation and ALE adaptive meshing technology, enabling real-time iterative updates of wear morphology and contact stress. This approach constructs an exponential model correlating cumulative wear depth with docking cycles (R² = 0.997). Prototype experiments demonstrate a mean absolute percentage error (MAPE) of 14.6% between simulated and measured wear depths, confirming model validity. With a critical wear threshold of 0.8 mm, the predicted service life reaches 45,270 cycles, meeting 50-year operational requirements (safety margin: 50.9%). This research provides theoretical frameworks and engineering guidelines for wear-resistant design, material selection, and life evaluation in high-reliability automatic docking systems. Full article

The ${\gamma }^{\prime }$-Fe₄N system has a high technological relevance due to its multiple applications in the field of surface treatment against wear and corrosion of iron in steel parts, as well as in the manufacturing of high-density magnetic recording devices, and so on. In the present work, we present a wide research of the structural, elastic, magnetic, vibrational, and thermophysical properties by means of the phonon analysis. For these purposes, we have compared theoretical and experimental results. The theoretical data were obtained by employing ab initio electronic structure calculations in the framework of density functional theory (DFT), and different experimental measurements, such as X-ray diffraction, magnetization measurements, and calorimetric techniques, were used to characterize the ${\gamma }^{\prime }$-Fe₄N system. The resulting comparison showed an excellent agreement between the theoretical and experimental data reported. Full article

Tungsten and tungsten alloys are widely used in important industrial fields due to their high density, hardness, melting point, and corrosion resistance. However, machining often leaves processing marks on their surface, significantly affecting the surface quality of precision components in industrial applications. Electrolytic polishing offers high efficiency, low workpiece wear, and simple processing. In this study, an electrolytic polishing method is adopted and a novel trisodium phosphate–sodium hydroxide electrolytic polishing electrolyte is developed to study the effects of temperature, voltage, polishing time, and solution composition on the surface roughness of a tungsten–nickel–iron alloy. The optimal voltage, temperature, and polishing time are determined to be 15 V, 55 °C, and 35 s, respectively, when the concentrations of trisodium phosphate and sodium hydroxide are 100 g·L⁻¹ and 6 g·L⁻¹. In addition, glycerol is introduced into the electrolyte as an additive. The calculated LUMO value of glycerol is −5.90 eV and the HOMO value is 0.40 eV. Moreover, electron enrichment in the hydroxyl region of glycerol can form an adsorption layer on the surface of the tungsten alloy, inhibit the formation of micro-pits, balance ion diffusion, and thus promote the formation of a smooth surface. At 100 mL·L⁻¹ of glycerol, the roughness of the tungsten–nickel–iron alloy decreases significantly from 1.134 μm to 0.582 μm. The electrochemical polishing mechanism of the tungsten alloy in a trisodium phosphate electrolyte is further investigated and explained according to viscous film theory. This study demonstrates that the trisodium phosphate–sodium hydroxide–glycerol electrolyte is suitable for electropolishing tungsten–nickel–iron alloys. Overall, the results support the application of tungsten–nickel–iron alloy in the electronics, medical, and atomic energy industries. Full article

This study investigates the development of a tire wear model using finite element techniques. Experimental testing was conducted using the Hoosier R25B slick tire mounted onto a Mustang Dynamometer (MD-AWD-500) in the Automotive Center of Excellence, Oshawa, Ontario, Canada. A general acceleration/deceleration procedure was performed until the battery was completely exhausted. A high-fidelity finite element tire model using Virtual Performance Solution by ESI Group, a part of Keysight Technologies, was developed, incorporating highly detailed material testing and constitutive modeling to simulate the tire’s complex mechanical behavior. In conjunction with a finite element model, Archard’s wear theory is implemented algorithmically to determine the wear and volume loss rate of the tire during its acceleration and deceleration procedures. A novel application using a modified wear theory incorporates the temperature dependence of tread hardness to measure tire wear. Experimental tests show that the tire loses 3.10 g of mass within 45 min of testing. The results from the developed finite element model for tire wear suggest a high correlation to experimental values. This study demonstrates the simulated model’s capability to predict wear patterns, ability to quantify tire degradation under dynamic loading conditions and provides valuable insights for optimizing performance and wear estimation. Full article

This work studies the issue of distributed fault-tolerant control for a vehicle platoon with actuator faults, saturation, and external disturbances. As the degrees of wear, age, and overcurrent of a vehicle actuator might change during the working process, it is more practical to consider the actuator faults to be time-varying rather than constant. Considering a situation in which actuator faults may cause partial actuator effectiveness loss, a novel adaptive updating mechanism is developed to estimate this loss. A new nonlinear observer is proposed to estimate external disturbances without requiring us to know their upper bounds. Since non-zero initial spacing errors (ISEs) may cause instability of the vehicle platoon, a novel exponential spacing policy (ESP) is devised to mitigate the adverse effects of non-zero ISEs. Based on the developed nonlinear observer, adaptive updating mechanism, radial basis function neural network (RBFNN), and the ESP, a novel nonlinear observer-based distributed adaptive fault-tolerant control strategy is proposed to achieve the objectives of platoon control. Lyapunov theory is utilized to prove the vehicle platoon’s stability. The rightness and effectiveness of the developed control strategy are validated using a numerical example. Full article

Accurately revealing the sliding wear mechanisms of mechanical surfaces is crucial for enhancing the performance of mechanical surfaces. This study reveals the mechanism of stage transitions in three-dimensional surface wear processes from a microscopic contact perspective. Firstly, according to the fractal theory, a mathematical model for the critical area scale controlling debris particle formation is established. Secondly, incorporating the contact area scale, a mathematical expression for the wear coefficient of surfaces, is proposed based on the multi-stage contact theory. Finally, the influences of fractal parameters on critical contact load, wear rate, and wear coefficient are systematically examined. The experimental findings substantiate that the proposed wear model exhibits an explicit deterministic formulation and demonstrates high predictive accuracy for the wear rate. Full article

Aiming at the engineering problems of the severe wear and limited service life of mandrels during the hole extrusion strengthening of critical aerospace components, this study proposes a surface modification strategy for mandrels based on the anti-friction mechanism of micro-textures. Based on the Lame stress equation and the Mises yield criterion, a plastic strengthening stress distribution model of the hole wall was developed. Integrating Bowden’s adhesive friction theory, a parameterized numerical model was constructed to investigate the influence of micro-texture morphology on interfacial friction and wear behavior. An elastic–plastic contact model for micro-textured mandrels during hole extrusion strengthening was established using ANSYS. The effects of key parameters such as the micro-texture depth and area ratio on the contact pressure field, friction stress distribution, and strengthening performance were quantitatively analyzed. The results show that a circular micro-texture with a depth of 50 μm and an area ratio of 20% can reduce the fluctuation and peak value of the contact pressure by 41.0% and 29.7%, respectively, and decrease the average friction stress by 8.1%. The interfacial wear resistance and the uniformity of the residual compressive stress distribution on the hole wall are significantly enhanced, providing tribological insight and surface optimization guidance for improving the anti-wear performance and extending the service life of mandrels. Full article

The muzzle velocity of electromagnetic rail launchers approaches 1550 m/s, exhibiting typical hypervelocity electrical contact characteristics. During the electromagnetic launching process, extreme conditions, such as high current density, high temperature rise, and strong strain can cause wear on the surfaces of the armature and rail. Electromagnetic launch tests are conducted to study the wear conditions of the rail surface and the relationship between the wear state and contact resistance. After the rail is abraded by hundreds of launching armatures, its surface 2D profile and morphological characteristics are measured and analyzed. Based on fractal theory, the static contact resistance model is developed. Concurrently, the contact resistance at various positions is measured to reveal the evolution of the static contact resistance between the armature and the rail under wear. The research results show that along the direction of the armature launch, the rail surface wear transitions from mechanical wear to electrical wear, the fluctuation range of the 2D profile becomes smoother, and the roughness of the rail surface shows a decreasing trend. When the roughness is greater, the contact resistance is more sensitive to changes in external load. Full article

This article examines the modernization of railway systems with a focus on sustainable infrastructure development, aligning with the European Commission’s strategy for integrating 1520 mm gauge railways into the European 1435 mm gauge network. A key challenge lies in addressing the technical aspects of the railway infrastructure that are not explicitly detailed in the European strategy but have evolved through the parallel historical development of two distinct railway engineering systems. An analysis of calculation methodologies highlights that the primary difference in determining technical parameters for 1435 mm and 1520 mm tracks stems from the selection of the primary classifier based on functional purpose and strength requirements. Furthermore, the existing concept of mechanical system motion presents limitations in harmonizing the technical aspects of railway systems with different track gauges. To bridge this gap, two potential solutions are proposed. The first suggests expanding the conventional mechanical system motion framework by incorporating principles from the theory of relativity, while the second explores the application of elastic wave propagation theory as a novel conceptual model for railway system dynamics. The choice of modernization strategy will play a crucial role in ensuring long-term sustainability of the railway infrastructure, requiring a balanced approach that accounts for the operational intensity, infrastructure wear, and specific technical requirements of track elements in different railway gauge systems. Full article

During the operation of mechanical equipment, due to the intense friction among raw material or filler particles, there is conspicuous wear on the contact surfaces of components. Using green lubricants assumes a crucial role in mitigating the friction and wear, enhancing the equipment’s service life and the production’s reliability. This review centers on investigating the wear mechanism of green lubricants and undertakes a comprehensive summary and in-depth analysis of the research approach, integrating numerical simulation and friction and wear experiments. Moreover, the construction of the friction and wear testing machine and the intelligence of the testing system were probed, offering valuable design theories and research schemes for the development of effective anti-wear green lubricants. Full article

The surface roughness of blisks during vibratory finishing is a critical evaluation index for their processing effect. Establishing a surface roughness prediction model helps reveal the processing mechanism and guide the optimization of process parameters. Therefore, based on wear theory and the least squares centerline system, a relationship between the surface roughness and material removal depth was established, and a scratch influence factor was introduced to correct the impact of surface scratches on the theoretical model. Interaction parameters between the blisk and granular media were obtained through discrete element simulations and used as input parameters for the model. Machining experiments were conducted to solve the model coefficients and verify the model’s effectiveness. The results show that the average error between the surface roughness model predictions and experimental results is 11.8%. As the machining time increases, the surface roughness exhibits three successive stages: accelerated decrease, decelerated decrease, and stability. The surface roughness decreases most rapidly at 48 min of machining and reaches the machining limit at 198 min. The surface roughness prediction model established in this study effectively reveals the coupling mechanism between the scratch accumulation and material removal during vibratory finishing, providing a basis and methodology for determining the process parameters in blisk vibratory finishing. Full article

The feed industry is characterized by high energy consumption during the grinding stage, where hammer mills can account for up to 50% of total electricity usage; furthermore, efficiency analyses are based only on the classical equations reported in the literature. In this context, the present theoretical-applied research aimed to improve the efficiency of a plant operating below its nominal capacity. To achieve this, a comprehensive mathematical model was developed, integrating power and grain disintegration equations while overcoming the limitations of classical comminution theories. The model incorporates key factors such as feed rate, moisture content, absorbed power and hammer wear. Additionally, specific correction factors for temperature ($K_t$) and mechanical degradation ($K_d$) were introduced to accurately represent real operating conditions. The study was based on extensive measurements of electrical current, power factor, energy consumption, particle size distribution and thermal variations under different load conditions. The statistical analysis, which included ANOVA, ANCOVA and multiple regressions, demonstrated a predictive accuracy of 98% (R²) and a pseudo-R² of 89%. This high correlation allowed for an 18% reduction in energy consumption equivalent to 4 kWh/t and up to a 30% improvement in particle size uniformity, surpassing typical factory performance. The findings highlight that integrating operational, thermodynamic and wear-related factors enhances the robustness of the model, promoting more reliable energy-management practices in hammer mills. Consequently, the results confirm that the developed model serves as a scientifically robust, efficient and applicable tool for improving energy efficiency and reducing environmental impacts in the agri-food industry. Full article

Accurate quantification of metallic contaminants in rocket exhaust plumes serves as a critical diagnostic indicator for engine wear monitoring. This paper develops a hybrid method combining atomic emission spectroscopy (AES) theory with a genetic algorithm (GA) optimized backpropagation (BP) network to quantify the metallic element concentrations in liquid-propellant rocket exhaust plumes. The proposed method establishes linearized intensity–concentration mapping through the introduction of a photon transmission factor, which is derived from radiative transfer theory and experimentally calibrated via AES measurement. This critical innovation decouples the inherent nonlinearities arising from self-absorption artifacts. Through the use of the transmission factor, the training dataset for the BP network is systematically constructed by performing spectral simulations of atomic emissions. Finally, the trained network is employed to predict the concentration of metallic elements from the measured atomic emission spectra. These spectra are generated by introducing a solution containing metallic elements into a CH₄-air premixed jet flame. The predictive accuracy of the method is rigorously evaluated through 32 independent experimental trials. Results show that the quantification error of metallic elements remains within 6%, and the method exhibits robust performance under conditions of spectral self-absorption, demonstrating its reliability for rocket engine health monitoring applications. Full article