Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.702148
Title: Stochastic modelling of the cold forming nosing process
Author: Woodhead, Johnpaul
ISNI:       0000 0004 5994 9640
Awarding Body: University of Bristol
Current Institution: University of Bristol
Date of Award: 2016
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Abstract:
Nosing is a cold metal-forming process, used during the manufacture of self-lubricating plain spherical aerospace bearings. This process ensures the outer bearing race conforms to the shape of the inner race, with a central composite liner in-between (Figure 1). The outer race, or bearing sleeve, is subject to large plastic deformation during the nosing process which imparts stresses into the sleeve. This can produce any number of failure modes identified. These aerospace bearings must be precision engineered due to the large forces and demanding environments they operate within, yet many companies are still heavily reliant on empirical data and experimental methods; however, FEA simulation can be used to predict and characterise complex material behaviour in forming operations. In this work, the mechanical properties of several materials used in the nosing process are characterised, and tribological testing is conducted in order to establish a pressure versus friction relationship. This data is used to model the nosing process analytically and virtually, in order to provide a better understanding of process parameters, tooling design and the resultant forces which are needed for processing. Virtual models and analytical calculations are validated against experimental data, stochastically, to ensure developed methods are robust. Novel findings from this work include: • Characterisation of the strain-rate sensitivity of 3 bearing high-alloy steels and the effect on flow stress; • A pressure versus friction relationship of the same high-alloy Steels, enabling the development of a dynamic friction model; • Neutron diffraction experimentation to establish residual strains within the outer race of (a) a normally-formed bearing, and (b) an over-formed bearing; in-process tracking of bearings through the manufacturing process to calculate process capability indices and the coefficient of variation for the geometric features on the outer race, acting as 'real-life' inputs for stochastic modelling; • The stochastic finite-element modelling (SFEM) of the nosing process for various bearing models. Ultimately, a costly and time-consuming experimental process can be replaced with a virtual rapid one, in order to mitigate defects, secondary processing and low yield rates experienced in new product introductions.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.702148  DOI: Not available
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