Surface texture processing for tribological performance improvement of UHMWPE-based water-lubricated bearings

Purpose Water-lubricated bearings can significantly reduce the pollution to environment because the traditional oil lubricant is replaced by water in the bearings. The ultrahigh molecular weight polyethylene (UHMWPE) has proven to be effective and reliable for the manufacturing of water-lubricated bearings. However, limited work has been done to address the improvement of the tribological performance of the UHMWPE-based water-lubricated bearings using surface texture processing. This paper aims to investigate the effects of bar-grooved surface on the tribological performance improvement of UHMWPE-based water-lubricated bearings. Design/methodology/approach For the first time, the bar grooves were processed on the surfaces of UHMWPE-based water-lubricated bearings. The CBZ-1 friction and wear tester have been used to test the wear and friction performance of the bearing samples. The LI laser interference surface contour graph and the digital microscope have been used to measure the surface morphology of the specimens. The tribological characteristics of the tested bearings were analyzed. Findings With bar grooves added on the surfaces of the specimens, the friction coefficient of the specimens were lower than that of the specimens without surface texture processing; the wear quantity of the two kinds of specimens were almost the same; by using the LI laser interference surface contour graph and the digital microscope to measure the surface morphology of the specimens, the furrows of the specimens with bar grooves were narrower and shallower than that of the specimens without bar grooves. Practical implications The paper implicates that the surface texture processing using bar grooves can reduce the friction coefficient and prolong the service life of the water-lubricated bearings in practical applications. Originality/value This paper fulfills an identified need to provide important theoretical and experimental support to the design of water-lubricated bearings in practical applications.

‘A Thread to the Afterlife’ - Textiles and the Otherworld in Irish Poetry: Yeats, Boland, Heaney and Meehan

This essay explores fabric, clothing and textile motifs in Irish poetry concerned with the relationship between this life and the afterlife. It intersplices readings of poems by W.B.Yeats, Eavan Boland, Seamus Heaney and Paula Meehan which acknowledge the fact that doubleness of presence and absence is integral to all human lives, and which are alert to the fact that this same duality is already embedded in man’s engagement with cloth. The essay argues that Irish poetry attends to the dense physicality, immediacy and depth texture of textile materials, as a key image complex allowing negotiation of significant loss, including the task of reconstructing life’s meaning following bereavement. Therefore, the essay explores how a concern with texture, processing, feeling and mood is facilitated in a special way through the haptic power of fabric symbolism in Irish elegiac poetry. It proposes that by mediating the theme of afterlife as a space which allows us to imagine multiple alternative lives in the here-and-now, fabric imagery as deployed by Irish poets challenges us to accept both our losses in this world and our on-going potential for life-renewal.

A texture-processing model of the ‘visual sense of number’

It has been suggested that numerosity is an elementary quality of perception, similar to colour. If so (and despite considerable investigation), its mechanism remains unknown. Here, we show that observers require on average a massive difference of approximately 40% to detect a change in the number of objects that vary irrelevantly in blur, contrast and spatial separation, and that some naive observers require even more than this. We suggest that relative numerosity is a type of texture discrimination and that a simple model computing the contrast energy at fine spatial scales in the image can perform at least as well as human observers. Like some human observers, this mechanism finds it harder to discriminate relative numerosity in two patterns with different degrees of blur, but it still outpaces the human. We propose energy discrimination as a benchmark model against which more complex models and new data can be tested.