Modelling of mixed lubrication in plain bearings based on the theory of flow factors and incorporating a dry contact analysis

Three topics are considered in this thesis. The first is evaluation of the effective elastic moduli of porous materials and considers materials such as porous glass, sandstone, sintered bronze and iron materials, porous ceramics. Models with spherical pores were first considered showing good agreement for some materials but not for materials prepared by powder sintering. A number of modifications of increasing complexity were introduced accounting for non-spherical pores and their interaction. The models then compare well with experimental data for sintered materials. The other topics of the thesis can be used to model mixed lubrication in plain bearings where part of the load is carried by contacting asperities and part by the lubricant film. The roughness features affect the ability of the lubricant to flow in the gap between the surfaces and surface deflection is caused by asperity contact pressures only. A method is presented to solve dry contact problems for nominally plane surfaces using a simple elastic-plastic model at asperity contacts and a differential formulation for the elastic deflection. Periodic roughness defined over a representative area is incorporated using Fourier transforms to calculate the convolutions. The method is validated by comparison with the results of an elastic-plastic rough surface contact analysis obtained using a finite element method. A method is then developed to model the mixed lubrication problem based on the homogenised Reynolds equation where the effect of the roughness features is isolated from that of the global geometry of the bearing. Local rough problems are solved and the average effect of the roughness on lubricant flow expressed in terms of flow factors, which are functions of global film thickness. When direct asperity contact occurs the deflected shape is obtained from dry contact analysis of the representative roughness area. The global problem is then solved using the Reynolds equation modified with appropriate flow factors taking the mean contact pressure obtained from the local problem into account in load determination. The homogenised method is validated against the series of deterministic solutions and cases of surfaces with measured roughness are presented

Modelling the formation and breakup of particle clusters in metal melt subjected to external fields

Aluminium and magnesium based metal matrix nano-composites (MMNC) with ceramic nano-reinforcements promise low weight with high durability and superior strength, desirable properties in aerospace, automobile and other applications. However, due to the small size of the particles, adhesion force between becomes significant which leads to particle agglomeration. Large clusters of nano-particles are detrimental for the final properties of the MMNC. To prevent agglomeration and to break up clusters, ultrasonic processing is used via an immersed sonotrode, or alternatively via electromagnetic vibration. The collapse of the cavitation bubbles as a result of ultra-sonication is believed to be the main mechanism of breaking up the clusters of nano-particles. The complex interaction of flow and co-joint particles subjected to the shockwave induced by cavitation is addressed in detail using a discrete-element method (DEM) code. Adhesive, elastic and frictional forces between the particles are incorporated and various models of adhesion are compared

Multiple timescale modelling of particle suspensions in metal melts subjected to external forces

Electro-magnetic (EM) fields are widely used in metallurgy in order to stir conducting metals without the risk of contamination or causing an instability or chemical reaction. During the manufacturing of metal matrix composites (MMC), ceramic micro- and nano-particles are added into the metal melt, and ultrasonic (US) processing and EM stirring are used to break the agglomerates and to enhance the dispersion of the particles. EM stirring can also be used to remove the unwanted particles from liquid metal by pushing them towards the walls of the cru-cible where they adhere and can be easily removed. A model has been developed to account for the complex interaction of the particles with each other, with the walls, as well as with the flow of the metal melt. Particles are modelled as elastic spheres with adhesion. Adhesion is incorporated in the model using the Johnson, Kendal, Robert (JKR) and Derjaguin, Muller, Toporov (DMT) theories. The case of the oblique impact of the particles is modelled according to the Thornton and Yin method based on the partial-slip theory developed by Mindlin & Deresievics. The developed particle model is then coupled with the magneto-hydrodynamics (MHD) code PHYSICA in order to demonstrate the effect of the EM stirring and vibration. Multiple time-scales are used which permits modelling the realistic time range of metal-processing and at the same time capture the individual collisions between particles with suffi-cient precision. Several methods of predicting the particle collisions are employed and their ef-ficiency is compared for the case of removing contaminating particles from liquid meta

Modelling the deagglomeration of nanoparticle inclusions by ultrasonic melt processing

The aerospace and automotive industries are seeking advanced materials with low weight-to-strength ratio, such as light alloy-based metal matrix composites (MMC) with nanoparticle rein-forcements. However, van der Waals and adhesive forces between nanoparticles result in large agglomerates that compromise the final properties of MMCs. Ultrasonic melt processing is a potential technology for de-agglomerating these clusters and producing samples with improved properties via grain refinement. This paper considers two hypotheses of cluster de-agglomeration: the breakup of a cluster due to the growth of gas contained in the cluster and the stripping of nanoparticles by pulsating neighbouring bubbles

Coupling of acoustic cavitation with DEM-based particle solvers for modeling de-agglomeration of particle clusters in liquid metals

The aerospace and automotive industries are seeking advanced materials with low weight yet high strength and durability. Aluminum and magnesium-based metal matrix composites with ceramic micro- and nano-reinforcements promise the desirable properties. However, larger surface-area-to-volume ratio in micro- and especially nanoparticles gives rise to van der Waals and adhesion forces that cause the particles to agglomerate in clusters. Such clusters lead to adverse effects on final properties, no longer acting as dislocation anchors but instead becoming defects. Also, agglomeration causes the particle distribution to become uneven, leading to inconsistent properties. To break up clusters, ultrasonic processing may be used via an immersed sonotrode, or alternatively via electromagnetic vibration. This paper combines a fundamental study of acoustic cavitation in liquid aluminum with a study of the interaction forces causing particles to agglomerate, as well as mechanisms of cluster breakup. A non-linear acoustic cavitation model utilizing pressure waves produced by an immersed horn is presented, and then applied to cavitation in liquid aluminum. Physical quantities related to fluid flow and quantities specific to the cavitation solver are passed to a discrete element method particles model. The coupled system is then used for a detailed study of clusters’ breakup by cavitation

Modeling the break-up of nano-particle clusters in aluminum- and magnesium-based metal matrix nano-composites

Aluminum- and magnesium-based metal matrix nano-composites with ceramic nano-reinforcements promise low weight with high durability and superior strength, desirable properties in aerospace, automobile, and other applications. However, nano-particle agglomerations lead to adverse effects on final properties: large-size clusters no longer act as dislocation anchors, but instead become defects; the resulting particle distribution will be uneven, leading to inconsistent properties. To prevent agglomeration and to break-up clusters, ultrasonic processing is used via an immersed sonotrode, or alternatively via electromagnetic vibration. A study of the interaction forces holding the nano-particles together shows that the choice of adhesion model significantly affects estimates of break-up force and that simple Stokes drag due to stirring is insufficient to break-up the clusters. The complex interaction of flow and co-joint particles under a high frequency external field (ultrasonic, electromagnetic) is addressed in detail using a discrete-element method code to demonstrate the effect of these fields on de-agglomeration

Modelling of elastic properties of sintered porous materials

Models for prediction of the elastic characteristics of natural and synthetic porous materials are re-examined and new models are introduced. First, the Vavakin–Salganik (VS) model for materials with isolated spherical pores is extended in order to take into account various statistical distributions of pore sizes. It is shown that the predictions of the extended VS model are in good agreement with experimental data for porous materials with isolated pores such as foamed titanium, porous glass and sandstone. However, the model is in a considerable disagreement with the experimental data for materials sintered from metal powders. The disagreement is explained by the presence of merged and open pores whose shapes cannot be well approximated as spheres. Using the theory of geometrical probabilities, the amount of pores that are close enough to overlap is estimated, and a model is introduced where merging pores are modelled as corresponding ellipsoids. Another modification is proposed to take into account open pores. This modification is based on the classical Rabotnov–Kachanov approach to damage accumulation in the loaded material. Finally, predictions given by the above models, and their combination is compared with experiments. A good agreement is observed between the combined model and the available experimental data for a variety of sintered materials