Browse Topic: Tribology
For brake and clutch components of aircraft vehicles which require higher mechanical strength and wear resilient, light-weight aluminium composites were developed infusing solid lubricant. In this study, hybrid composites were developed using powder metallurgy route with aluminum alloy AA356 and various amounts of zirconium oxide (ZrO2) (0, 5, 10, 15, and 20 wt.%) as reinforcements. A solid lubricant hexagonal boron nitride (hBN) at a fixed 5 wt.% is considered. Following the appropriate ASTM guidelines, the specimens were mechanically characterized by measuring their density, porosity, micro-hardness, compression strength, impact strength, and flexural strength, among other properties. The findings showed that the composites' mechanical and physical behaviour were greatly affected by the inclusion of ZrO2. Porosity increased as a result of particle clustering and interfacial voids, while density increased gradually as ceramic content increased. Consistently increasing ZrO2 addition led to micro-hardness improvements; at 20 wt.% reinforcement, values reached their maximum, indicating that the hard ceramic phase contributed to better surface resistance. The best balance between particle reinforcement and matrix continuity was suggested by the compression and flexural strengths peaking at 15 wt.% ZrO2. However, when the addition was raised to 20 wt.%, brittleness and porosity began to marginally deteriorate. Unreinforced and lower ZrO2 composites had superior toughness in impact, whereas materials with a higher content had a poorer energy absorption capacity. The 5 wt.% hBN improved fracture arresting capabilities and helped load transmission over the interface. Inclusion of hBN provides solid-lubricating tribofilm formation that enhances the tribological performance. This study reveals that AA356/ZrO2-hBN hybrid composites have good hardness and compressive strength improvements, with 15 wt.% ZrO2 being the best composition with good strength, toughness, and wear resistance.
Live-line operation is a critical technique for maintaining the reliability and continuity of power supply in modern distribution networks. Insulating mats serve as essential protective equipment during such operations by providing both electrical insulation and mechanical shielding. In practical service conditions, insulating mats are subjected to repeated mechanical contact and friction against conductors, metallic fittings, and ground surfaces, which progressively deteriorates their surface integrity and compromises operational safety. Current performance standards for insulating mats emphasize dielectric and tensile properties, while tribological durability remains unaddressed. In this study, an EVA – PA6 composite film fabricated via the tape casting method was selected as the representative outer insulating layer of insulating mats. Reciprocating friction tests were conducted using an SDR339 abrasion tester to evaluate the effects of normal load and sliding speed on wear behavior. The results indicate that wear mass increased monotonically with friction cycles at a given speed, whereas the incremental wear rate gradually decreased due to contact area evolution. A pronounced transition from mild surface abrasion to severe material removal was observed when the applied load reached 5 N, accompanied by surface scratching and exposure of the internal fibrous layer. These findings demonstrate that the wear resistance of the EVA – PA6 composite film is insufficient for long-term service under realistic frictional conditions. The results provide experimental evidence supporting the necessity of incorporating standardized wear resistance evaluation into performance criteria for insulating mats used in live-line operations.
After four decades of research and 3.5 year prototype testing campaign, Penn State's pericyclic transmission technology demonstrator, dubbed the 'Pericycler', has achieved its operating speed of 5,000 RPM at 17 HP. The characterization of this system by experimental efficiency and vibration represents a major milestone in pericyclic gear technology. A post-test inspection procedure was performed to analyze component wear and validate hypotheses on mesh behavior. This work concludes with structural, tribological, and instrumentation modifications to the Pericycler for future testing.
Bench-level tribological experiments were utilized to evaluate material, coating, and lubricant formulation effects on the loss-of-lubricant survivability of tapered roller end and cone rib contacts. Cone rib and roller end contacts were simulated using a single rotating roller and rotating flat disk. The applied load and rotational speeds of the roller and disk were controlled to simulate representative rotorcraft gearbox bearing operating conditions. The contacts were lubricated for an initial period before the lubricant supply was shut off, and the supply tube was then removed. Tests continued to run, without additional oil, until the measured friction force reached a predetermined cutoff value. Weibull-based statistical analysis was used to compare the loss-of-lubrication runtimes.
Fused deposition modeling (FDM) is a rapidly growing additive manufacturing method employed for printing fiber-reinforced polymer composites. Nonetheless, the performance of printed parts is often constrained by inherent defects. This study investigates how the varying annealing parameter affects the tribological properties of FDM-produced polypropylene carbon fiber composites. The composite pin specimens were created in a standard size of 35 mm height and 12 mm diameter, based on the specifications of the tribometer pin holder. The impact of high-temperature annealing process parameters are explored, specifically annealing temperature and duration, while maintaining a fixed cooling rate. Two set of printed samples were taken for post-annealing at temperature of 85°C for 60 and 90 min, respectively. The tribological properties were evaluated using a dry pin-on-disc setup and examined both pre- (as-built) and post-annealing at temperature of 85°C for 60 and 90 min printed samples. Tribological tests were conducted under varying normal loads (5, 10, 15, and 20 N) and sliding velocities (1 and 3 m/s), following the ASTM G99 standard test procedure. Significantly notable enhancements in wear and friction properties were consistently observed across all tribometer test conditions when the composites underwent annealing at 85°C for 60 min, surpassing the performance of other samples. These particular samples, subjected to the 85°C/60-min annealing process, exhibited elevated hardness, diminished wear rates, and reduced coefficients of friction (COF). A detailed examination using a scanning electron microscope revealed that the wear mechanism on the surface of the tribometer-tested samples exhibited milder wear when carbon fiber was added, followed by annealing at 85°C for 60 min, compared to the 90-min annealing. These promising results suggest that the proposed composites have potential applications in industries such as prosthetics, aerospace, and automobiles.
The overarching objective of the present study is to apply a quasi-two-dimensional approach to analyze the laminar flow of lubricating oil. Lubricating oils are non-Newtonian by nature. For these types of oils, the Sisko fluid model is the most suitable model of the nonlinear stress–strain relationship for these types of oils. It is hoped that by omitting the dependence of flow quantities in one direction, more qualitative information can be obtained on the characteristics of the purely three-dimensional boundary layer flow of lubricating oils. Some of the most familiar flow geometries discussed are steady flow over a flat plate, a corner of a wedge, and a stagnation region; steady flow in a convergent and divergent channel; and impulsively started flow over an infinite flat plate and semi-infinite flat plate. The governing equations of all flow geometries are transformed into nonlinear ordinary differential equations (ODE) using the free parameter transformation. The results are discussed briefly in the graphical presentation.
The once rarified field of Artificial Intelligence, and its subset field of Machine Learning have very much permeated most major areas of engineering as well as everyday life. It is already likely that few if any days go by for the average person without some form of interaction with Artificial Intelligence. Inexpensive, fast computers, vast collections of data, and powerful, versatile software tools have transitioned AI and ML models from the exotic to the mainstream for solving a wide variety of engineering problems. In the field of braking, one particularly challenging problem is how to represent tribological behavior of the brake, such as friction and wear, and a closely related behavior, fluid consumption (or piston travel in the case of mechatronic brakes), in a model. This problem has been put in the forefront by the sharply crescendo-ing push for fast vehicle development times, doing high quality system integration work early on, and the starring role of analysis-based tools in enabling this strategy. Focusing even further, brake corner systems under duress – such as high temperatures, and high braking power, can exhibit highly non-linear and in-stop varying behavior that can be exceedingly difficult to model accurately. The present work chronicles efforts by the author and colleagues to develop machine learning models that capture this complex behavior and generalize sufficiently well to continue representing the performance of the brake under high energy driving conditions, even as the models are presented with new braking conditions that were not part of the training of the models. The utility of the models in the prediction of system-level performance is demonstrated through a case study application to calibrating a fade warning feature. The present work is shown from the perspective of a practicing engineer, not a data scientist, with some details that may prove mundane to the latter – but a strong motivation behind this work is to share the experience of getting started and some practical lessons learned towards the use of these powerful machine learning tools to solving practical problems in the field of brake engineering.
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