Investigation of load carriage capacity of journal bearings by surface texturing

Industrial Lubrication and Tribology

Volumn 61, Issue 5, 2009, Pages 261-270

  Sinanoglu, Cem ^a  

^a ERCIYES UNIVERSITY   (Turkey)

Author keywords

Bearings; Load capacity; Neural nets; Surface texture

Indexed keywords

ARTIFICIAL NEURAL NETWORK; BEARINGS; DELTA-BAR-DELTA; DESIGN/METHODOLOGY/APPROACH; EXPERIMENTAL DATA; EXPERIMENTAL SYSTEM; FEED FORWARD; HYDRODYNAMIC BEARINGS; HYDRODYNAMIC LUBRICATION; LOAD CAPACITY; LOAD CARRYING CAPACITIES; LOAD-CARRIAGE CAPACITY; MECHANICAL SEALS; MIXED LUBRICATION; NEURAL MODELS; NEURAL NETS; NEURAL NETWORK PREDICTOR; REGULAR SURFACE STRUCTURES; SHAFT SURFACES; STARVED LUBRICATION; SURFACE TEXTURE; SURFACE-TEXTURING; TEXTURED SURFACE; THEORETICAL MODELS;

CONCRETE BEAMS AND GIRDERS; ELASTOHYDRODYNAMIC LUBRICATION; FLUID DYNAMICS; HYDRODYNAMICS; JOURNAL BEARINGS; MINING; NEURAL NETWORKS; NEURONS; PISTON RINGS; SCREW THREADS; SURFACE STRUCTURE; TEXTURES;

BEARING CAPACITY;

EID: 70149099337     PISSN: 00368792     EISSN: None     Source Type: Journal    
DOI: 10.1108/00368790910976096     Document Type: Article

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