Lifetime Of Mechanical Components Research Articles

Combining Tailored Ionic Liquids with Ti3C2Tx MXenes for an Enhanced Load‐Carrying Capacity Under Boundary Lubrication

To improve the efficiency and lifetime of mechanical components, new lubrication systems are needed. Two complementary material classes, which have demonstrated a promising tribological performance, are ionic liquids and MXenes (2D transition metal carbides and nitrides). Herein, Ti3C2Tx MXenes are used as additives in ionic liquids (ILs) to improve their load‐carrying capacity under boundary lubrication. The specifically synthesized ILs share the same cation (trioctyl(methyl)phosphonium) but different anions (dimethyl phosphate and dibutyl phosphate for IL1 and IL2, respectively) to assess the effect of the anion's alkyl chain length. The wear reduction performance is tested with a cylinder‐on‐ring contact in a standardized Brugger tester, which is suitable to study boundary lubrication and to assess the antiwear ability of the IL/MXene lubricant blends. MXenes indicate an excellent dispersibility in both ILs over 24 h. It is found that, irrespective of the used IL, the addition of MXenes always increases the load‐carrying capacity. Particularly, significantly reduced wear and thus a high load‐carrying capacity are observed for the combination IL2/MXenes, which also outperform fully formulated commercially available lubricants such as turbine oils.

OPTIMIZATION OF CNC PARAMETERS ACCORDING TO PRODUCTIVITY CRITERIA USING A MACHINE MODEL BASED ON NEURAL NETWORKS

Every machine-tool user wants to maximize the productivity of their machines looking for balance between speed, precision and lifetime of mechanical components. Nevertheless, because CNCs have wide-ranging use, their correct parametrization for each case is key to achieving the desired objectives; on the other hand, minimizing the numbers of experimental tests to be performed on the machine is essential to reduce time and costs of the set-up process. In order to solve both difficulties, this paper presents a tool to give final user necessary information to properly adjust CNC parameters according to productivity criteria. The method makes use of experimental data to obtain a model of the machine based on neural networks. With this model machining time, geometric error and smoothness of any piece to be manufactured can be predicted, and therefore minimizing test on the real machine and recommending the appropriate values for the CNC. Keywords: optimization, CNC, neural network, model, machine tool, productivity criteria.

FEA of Fretting Fatigue: A Comparison between ANSYS and ABAQUS

Fretting fatigue occurs when two contact bodies undergo small oscillatory relative motion due to cyclic loading. It leads to fretting damage, which reduces the service life of the bodies in contact. This can be explained by the high stresses generated at the contact surface between the two bodies. Therefore, numerical analysis, such as Finite Element Analysis (FEA), would be useful to understand the fretting fatigue phenomenon and to investigate techniques to reduce its effect on fatigue lifetime of mechanical components. In this paper, FEA of fretting fatigue Aluminum specimen is carried out in order to study the stress distribution and crack initiation location. Two commercial FEA packages, namely ANSYS and ABAQUS are used to analyze the specimen. The stress distribution along the contact surface between the two bodies obtained using both codes is compared and analyzed.

Traction Drive Control with PI State Controller and Kalman Filter - First Experimental Results

Torque oscillations occur in poorly damped drive trains of electrical high-speed locomotives due to the stochastic wheel-rail-contact. These reduce the life time of mechanical components. High-dynamic torque control and single-fed traction motors enable a new control concept based on a state controller while taking the mechanical system into account It shifts the poles of both natural oscillations in the negative real direction and increases the damping. As the control concept should not need more sensors than the conventional speed controlled AC drive, the missing states have to be reconstructed by an observer or a filter. Simulation results with deterministic and stochastic load torques show that the state controller with Kalman filter reduces both oscillations of natural torsion and thereby increases the lifetime of mechanical components in the drive train. Also first experimental results from a special test stand are presented.