Performance Of Wheel Research Articles

Grain wear properties and grinding performance of porous diamond grinding wheels

Conventional diamond grinding wheels present challenges such as poor self-sharpening and difficulties in achieving ductile domain machining when processing hard and brittle materials, reducing machining quality and efficiency. This paper introduces a novel grinding wheel composed of porous diamond abrasive grains for better ultra-precision machining. Thermochemical etching is used to produce porous diamond grains of varying corrosion levels, and the cutting and wear mechanisms of these grains are investigated through molecular dynamics simulations and single-grain scratch tests. Compared to conventional diamond grains, the increased "micro-edge" and "multi-edge" features of porous diamond grains effectively reduce cutting force and heat. Notably, corrosion pore sizes ranging from 2 μm to 5 μm reduce cutting damage. Conventional diamond abrasive grains primarily incur damage through crystal surface dissociation and block crushing, whereas porous diamond abrasive grains experience damage mainly due to micro-crushing and micro-fracture. Ultra-precision grinding tests on 4H–SiC revealed that conventional abrasives produced cracks and pits on the grinding surface. In contrast, abrasives with a 2 μm eroded aperture exhibited predominantly ductile removal with minimal cracks and pits present. Abrasives with a 5 μm eroded aperture displayed desirable characteristics. This research offers valuable technical insights for enhancing the grinding performance of diamond wheels.

Progress in grinding performance by additive manufacturing of grinding wheels integrated with internal venturi cooling channels and surface slots

Among the most promising features of additive manufacturing are tool or form-free manufacturing and the ability to create intricate geometries that are difficult or even impossible to fabricate with traditional methods. These advantages can be employed to produce enhanced grinding tools. Efficient coolant fluid delivery into the cutting zone of the grinding operation has been a challenging problem since high frictional contact in the arc zone deteriorates the resin bond and lessens the grinding performance. This research study was dedicated to assessing the influence of internal cooling along with surface structures on the grinding performance of resin-bonded grinding wheels fabricated via additive manufacturing. This research introduced a novel structure that benefits from internal venturi shape cooling channels to provide exceptional fluid velocity in the tool and workpiece interaction zone. The grinding wheels have been produced employing vat photopolymerization. Grinding experiments with and without internal cooling were conducted on an aluminium plate to study the impact of introduced structures on the main aspects of grinding performance, such as cutting forces, surface roughness, tool wear, and dimensional accuracy. Two different grinding scenarios comprising shallow (10 μm depth of cut) and deep grinding (100 μm depth of cut) were carried out to reveal the influence of the material removal rate on the grinding experiments. The measured grinding forces revealed that integrating internal cooling channels and surface slots in a grinding tool could significantly reduce the grinding forces, which was more pronounced in the case of using venturi channels. Measured tool wear and dimensional accuracy together with calculated grinding ratio revealed that using cooling channels could participate in a notable increase in tool life and material removal ability, especially for venturi channels, due to improved cutting conditions, by which higher dimensional accuracy was obtained as well for the ground parts. Besides, it was discovered that the cooling channels could improve the surface quality of the ground part, which was less noticeable with the venturi channel grinding wheel. Furthermore, the optical and confocal microscopy detection confirmed that internal cooling channels could reduce chip loading on the grinding wheel surface, decrease the required number of dressing intervals, and cause effective promotion of tool life.

Permeability design and assessment of the additively manufactured metal-bonded diamond grinding wheel based on TPMS structures

The development of porous metal-bonded diamond grinding wheel with excellent permeability and satisfying mechanical properties is a huge challenge for traditional manufacturing process. In this paper, a novel design and fabrication method of metal-bonded diamond grinding wheel with human-designed open porous structure is proposed based on triply periodic minimal surfaces (TPMS) and additive manufacturing (AM) process. Darcy’ law and Kozeny-Carman equation are used to calculate the permeability coefficient for the porous grinding wheel. The optimal design method of grinding wheel porous structure is proposed comprehensively considering the geometric characteristic, permeability and mechanical properties. The grinding performance of AM porous grinding wheel is evaluated by BK7 glass grinding experiment. The permeability test result proves the effectiveness of permeability design method for the novel diamond grinding wheel. The grinding test result proves the advantages of the novel diamond grinding wheel.

Study on the Preparation and Performance of Silicone-Modified Phenolic Resin Binder for Rail Grinding Wheels.

A scheme for manufacturing heavy-duty rail grinding wheels with silicone-modified phenolic resin (SMPR) as a binder in the field of rail grinding is presented to improve the performance of grinding wheels. To optimize the heat resistance and mechanical performance of rail grinding wheels, an SMPR for industrial production of rail grinding wheels was prepared in a two-step reaction using methyl-trimethoxy-silane (MTMS) as the organosilicon modifier by guiding the occurrence of the transesterification and addition polymerization reactions. The effect of MTMS concentration on the performance of silicone-modified phenolic resin for application in rail grinding wheels was investigated. The molecular structure, thermal stability, bending strength, and impact strength values of the SMPR were characterized by Fourier transform infrared spectroscopy (FTIR), thermogravimetric analysis (TGA), and mechanical property testing, and the effect of MTMS content on the resin properties was investigated. The results indicated that MTMS successfully improved the performance of the phenolic resin. The thermogravimetric weight loss temperature of the SMPR modified by MTMS with 40% phenol mass at 30% weight loss is 66% higher than that of common phenolic resin (UMPR), exhibiting the best thermal stability; in addition, its bending strength and impact strength were enhanced by approximately 14% and 6%, respectively, compared with those of common UMPR. This study utilized an innovative Bronsted acid as a catalyst and simplified several intermediate reactions in the conventional silicone-modified phenolic resin technology. This new investigation of the synthesis process decreases the manufacturing cost of the SMPR, liberates it from the restrictions of grinding applications, and enables the SMPR to maximize its performance in the rail grinding industry. This study serves as a reference for future work on resin binders for grinding wheels and the development of rail grinding wheel manufacturing technology.

Time-Domain Electromagnetic Characterization of Reaction Wheel for Space Applications

The electromagnetic characterization of reaction wheels is crucial to comply with the demanding ac magnetic field cleanliness requirements of space science missions, thus, preventing interference on sensitive onboard instrumentation. Therefore, a complete assessment, including the measurement of the magnetic flux vector at different operational modes and under dynamic conditions, is proposed as a contribution beyond conventional testing methodologies. This article investigates the worst-case magnetic field emissions experimentally, using a test setup based on a multichannel acquisition and multidomain postprocessing system. The focus of the measurement campaign was on the low-frequency range (10 Hz–2 kHz). Moreover, capturing the B-field in the time-domain enabled further analysis, that is, complementary outputs for understanding the electromagnetic performance of the reaction wheel. As a result, we can relate the wheel rotation with the current and the magnetic fields, compute the field orientation, and evaluate in-band interference for the magnetic field.

Multi-objective optimization of desiccant wheel via analytical model and genetic algorithm

The dehumidification performance and energy consumption of desiccant wheel are affected by many design parameters and operating variables. However, there are few researches concerning multi-objective optimization. Therefore, an optimal design framework combining analytical model, multi-objective optimization and decision-making is proposed. The model was based on the overall heat and mass balances, so the objective functions of the desiccant wheel were derived, and the constraints for the equilibrium of the adsorption and desorption were obtained. Then, the non-dominated sorting genetic algorithm II (NSGA-II) was employed to calculate the Pareto optimal front of the two-objective optimization, and the results were analyzed with psychrometric chart. This solution set includes not only the optimum one with the design method of psychrometric charts, but also includes other better solutions. From the Pareto solutions, the final optimal solution was obtained with the technique for order preference by similarity to ideal solution (TOPSIS) based on four criteria. With the final optimal parameters applied to existing example, the further improvements on the outlet process air humidity ratio and the dehumidification coefficient of performance were found.

Thermofluidic characteristics for a novel complementary adsorption-absorption post-combustion partial CO2 capture system

A novel complementary adsorption-absorption post-combustion partial CO2 capture strategy was proposed to decrease the energy penalty by integrating the rotary adsorption wheel with traditional chemical absorption process. The finite volume method is used for modeling the adsorption process, and the absorption process is simulated based on the rate-based model and the double-film theory. The techno-economic analyses of the novel complementary system were performed. In the adsorption part, the CO2 concentration of the flue gas can be effectively improved from 5.0%, 10.0% and 15.0% as much as to 17.3%, 27.0% and 33.7%, respectively. By adjusting the flue gas ducts of the adsorption wheel, the flue gas can be concentrated to a CO2 concentration making the absorption process work economically. The performance of the rotary adsorption wheel influenced by different geometrical and operational parameters were investigated. The energy penalty of the chemical absorption part can be significantly decreased. The major equipment cost was dramatically decreased by 48.6%, and the levelized cost of CO2 capture was decreased by 32.3%, when the CO2 concentration in the flue gas was increased from 5% to 20%. In addition, the acceptable investment of the rotary adsorption wheel has been estimated. The smallest acceptable capital cost of rotary adsorption wheel for coal-fired boiler corresponding to one payback year is 3.72 M$.

Electroplating a miniature diamond wheel for grinding of the calcified plaque inside arteries

A miniature grinding wheel (0.85mm diameter) was fabricated by nickel (Ni)-diamond electroplating on a thin (0.65mm outer diameter) flexible hollow stainless steel drive shaft to remove the calcified plaque in coronary and peripheral arteries by atherectomy procedure. To coat electrically nonconductive diamond grits, the drive shaft was submerged in a pile of diamond grit during Ni electroplating. The electroplating current density and temperature were investigated for better surface finishing and Faraday efficiency. The electroplating time to obtain the designed coating thickness was modeled based on Faraday's law of electrolysis and the geometry of drive shaft, wheel, and diamond grit. To validate the miniature wheel performance in atherectomy, grinding experiments were conducted on an atherectomy cardiovascular simulator with a calcified plaque surrogate. The wheel motion, material removal rate, and wheel surface wear were studied via high-speed camera imaging and laser confocal microscopy. The grinding wheel with 80,000rpm rotational speed had an orbital speed of 14,300rpm around the 1.5mm diameter plaque surrogate lumen. After grinding for 120s, the plaque surrogate inner diameter was enlarged to 3.03mm, and no wear or loss of diamond abrasive was observed on the grinding wheel. This study demonstrated that the proposed electroplating process for fabricating miniature grinding wheels could effectively remove the calcified plaque surrogate. This research could lead to a more effective and safer atherectomy device with sub-mm miniature diamond wheels to treat lesions deep in coronary and peripheral arteries.

13-degree impact test of long-fiber-reinforced thermoplastic composite wheel manufactured by injection molding–Improved co-simulation approach and experimental investigation

The excellent mechanical properties, ease of processability and intrinsic recyclability drive the long-fiber-reinforced thermoplastic composite to be recognized as a potential alternative material. And combined with injection molding process, a new path to promote the lightweight design of automobile wheels may be opened up. At present, some numerical methods of 13-degree impact test have been proposed to evaluate the mechanical performance of such composite wheels, but the simulation accuracy is insufficient arising from the following drawbacks to provide a reliable basis for the optimal design. Specifically, the one is to use the simplified tire model to evaluate its effect on the impact resistance of wheel, and the other is that during establishing the anisotropic material model of composite wheel by using the mapped fiber orientation information, the finite element mesh model for injection molding analysis is not matched with the one for structural analysis. Aiming at these problems, an improved co-simulation method is proposed to more accurately predict the impact performance of such wheels. Then, the long-glass-fiber reinforced polyamide 66 composite wheels are fabricated through injection molding process and the corresponding impact test is performed to verify the validity of this approach. And compared with the existing co-simulation method, the calculation accuracy of this improved version is obviously increased. Besides, the effects of these improvements on the simulation results are comparatively analyzed, and the influence of different actual tires on the impact performance of wheel is also investigated by test. The results show that, whether or not to achieve the match state between the two types of mesh models significantly affects the final impact simulation results, and the impact performance of composite wheel varies obviously with different tires used but no consistent rule can be followed.

Performance enhancement of desiccant wheels by adsorption/desorption in stages with type-S isotherm desiccants

Desiccant wheels coated with desiccants possessing a single kind of adsorption isotherm face the drawback that the moisture transfer driving force decreases along the direction of air flow in the channel, which hinders the efficiency of regeneration and dehumidification processes. In this study, a new concept of adsorption/desorption in stages with type-S isotherm desiccants was proposed to improve the performance of a counter flow type desiccant wheel by increasing the moisture transfer driving force during both dehumidification and regeneration processes. The numerical results show that compared with conventional wheel made up of silica gel, the two desiccant wheels with various hypothetical type-S isotherm desiccants designed in this study output air with more stable humidity during dehumidification, and have superior performance when both cycling time (tcyc) is high and regeneration temperature (Tr,i) exceeds the critical value.

Evaluation of vitrified bonding strength using aluminum oxide with boron nitride grinding wheel

The bonding material used to make the grinding wheel determines the strength of the grinding wheel during the grinding process. Poor bonding is a significant problem in the grinding process, affecting work piece interaction, grinding force, surface finish, and wheel performance. To improve the bonding strength of the grinding wheel, Al2O3 with Boron Nitride vitrified bonded grinding wheel samples were investigated in this study. The bonding strength properties of Al2O3 grinding wheels with 10%, 15%, and 20% Boron nitride were compared to those of Al2O3 + 0% Boron nitride grinding wheels. The compression and shear strength of the grinding wheel were tested under various conditions by keeping the grinding wheel in lateral and axial positions against the applied load. The maximum compression strength values were 125.7 MPa and 19.8 MPa for axial and lateral position, and the maximum shear strength values were 42 MPa compared to the wheel made out of Al2O3 alone.

Investigation on workpiece microstructure and wheel performance on grinding titanium metal matrix composites

Investigation on workpiece microstructure and wheel performance on grinding titanium metal matrix composites

Investigation on Workpiece Microstructure and Wheel Performance on Grinding Titanium Metal Matrix Composites

Investigation on Workpiece Microstructure and Wheel Performance on Grinding Titanium Metal Matrix Composites

Effect of normal load on the wear and rolling contact fatigue behaviour of AAR class B wheel against R350HT rail in a twin disc simulator

The normal load at the wheel-rail contact interface plays a significant role in wear and rolling contact fatigue (RCF) performance of both wheel and rail steels. In recent years, there has been an increase in axle loads due to increased demand for railway services. This study investigated the effect of normal load on the wear and RCF behaviour of the AAR class B wheel versus R350HT rail using a twin disc wear simulator. The mass loss, surface damage and depth of deformation were used to assess wear and RCF, respectively. From the mass loss results, wear maps were obtained to identify different wear regimes being mild, severe and catastrophic at different contact loads and slip ratios. Scanning electron microscopy was also used to assess the surface damage of wheel and rail steels in order to identify the wear regimes with surface cracking and delamination being observed at higher contact loads indicating severe and catastrophic wear. Furthermore, the RCF crack density was found to be higher on specimens evaluated at higher normal loads with more cracks evident and crack branching forming.

Research on Online Monitoring Model of Grinding Performance of Different Grinding Wheels in Internal Plunge Grinding

Research on Online Monitoring Model of Grinding Performance of Different Grinding Wheels in Internal Plunge Grinding

Research on impact resistance of steel wheel considering vehicle effect

Although there is no public standard for 90° impact test of steel wheel, some wheel manufactures have introduced the impact test to ensure the safety performance of steel wheel. It is often referred to the standard methods used for light alloy wheels. However, whether light alloy wheel 90° impact test methods are applicable to steel wheels have not been studied. In this paper, the vehicle model and road model were established in ADAMS/Car to simulate the vehicle passing through bumps and potholes. The maximum impact force on the wheel was obtained by changing vehicle speed and obstacle size. The simulation result of the wheel under the maximum impact force was compared with those of the 90° bench impact tests. The results show that test method I of 90° impact standard for light alloy wheels is applicable to steel wheels and test method II is too stringent for steel wheels.

Increasing the performance of the raw material wheel and fiber quality when processed by the sawing machine

The saw gin, the primary technical device used in the cotton ginning process, is responsible for separating the cotton fiber from the cotton seed. After being cleansed of khaschops and dried to the desired humidity in the drying, cleaning, and cleaning shops, seeded cotton is transferred to the main building of the business for ginning (separation of fiber). Up to now, 4DP-130, 5DP-130, and DPZ saw gins have been employed in cotton ginning operations to spin medium fiber seeded cotton. The ginning machine's operation, which separates the fiber from the seed in cotton gins, is largely responsible for the creation of high-quality fiber. Maintaining natural quality indicators during the technical process of first processing of cotton, i.e. the appearance, length, and presence of minute impurities in the fiber, is key to ensuring the competitiveness of cotton fiber produced in our nation on the global market. One of the most crucial processes is the ginning of seeded cotton with the appropriate amount of moisture and dirt, which involves removing the fiber from the seed. The length of the fiber, the impurities in the content, the absence of damage, and the hairiness of the seed all play a significant role in this process.

Evaluation of the performance of wheelchair wheels climbing stair when tensile force is kept constant.

Evaluation of the performance of wheelchair wheels climbing stair when tensile force is kept constant.

Wheel impact test by deep learning: prediction of location and magnitude of maximum stress

For ensuring vehicle safety, the impact performance of wheels during wheel development must be ensured through a wheel impact test. However, manufacturing and testing a real wheel requires a significant time and money because developing an optimal wheel design requires numerous iterative processes to modify the wheel design and verify the safety performance. Accordingly, wheel impact tests have been replaced by computer simulations such as finite element analysis (FEA); however, it still incurs high computational costs for modeling and analysis, and requires FEA experts. In this study, we present an aluminum road wheel impact performance prediction model based on deep learning that replaces computationally expensive and time-consuming 3D FEA. For this purpose, 2D disk-view wheel image data, 3D wheel voxel data, and barrier mass values used for the wheel impact test were utilized as the inputs to predict the magnitude of the maximum von Mises stress, corresponding location, and the stress distribution of the 2D disk-view. The input data were first compressed into a latent space with a 3D convolutional variational autoencoder (cVAE) and 2D convolutional autoencoder (cAE). Subsequently, the fully connected layers were used to predict the impact performance, and a decoder was used to predict the stress distribution heatmap of the 2D disk-view. The proposed model can replace the impact test in the early wheel-development stage by predicting the impact performance in real-time and can be used without domain knowledge. The time required for the wheel development process can be reduced using this mechanism.

A New Deep Tensor Autoencoder Network for Unsupervised Health Indicator Construction and Degradation State Evaluation of Metro Wheel

For metro vehicles, wheel performance degradation is inevitable due to the continuous wear of tread and rim. It is of significant value to apply machine learning techniques to evaluate the wheel’s degradation state with vibration signals, as it can lessen expert dependence and optimize repair strategy. In the real metro operation process, however, the wheels’ vibration signal is easily disturbed by irregular noise from many factors, such as load, road condition, and temperature, etc., and lacks essential tendency characteristics for the intelligent state evaluation. To solve this problem, this paper proposes a new unsupervised degradation state evaluation method for metro wheels against irregular noise disturbance. First, a new deep tensor autoencoder (TAE) network is proposed based on the merit of tensor representation in exploring the intrinsic information from raw signals. By extracting the core tensor from hidden features via Tucker decomposition, a new decoding process is rebuilt and a tensorized tendency regularizer is designed with the core tensor. Moreover, a new training algorithm with alternating minimization scheme is constructed to seek the optimal tensor representation and unsupervised feature extraction. Second, a health indicator (HI) of the degradation process is built with the extracted features. A HI-based state assessment algorithm is further proposed to adaptively determine the interval of state change in order to substitute the first/second warning in the current maintenance strategy. A set of comparative experiments are conducted using the wheel data from Beijing Subway. The results demonstrate that TAE can extract features with good monotonicity and tendency from the raw signals under irregular noise disturbance. More importantly, the obtained warning positions can precisely match the wheel diameter’s change in the actual repair record, which offers an easy-to-deploy and intelligent solution for the health management of metro wheels.