Development of a vibration fatigue failure prediction model for automotive lamps made of polymers
type: CreativeWork
description: This thesis presents a technique for numerically modelling and predicting the fatigue life of automotive lamps made of thermoplastic polymers. The primary aim is to use the fatigue failure prediction technique developed in this research to address fatigue challenges in the design of automotive lamps. The research combined numerical simulation and experimental studies. As part of design verification, automotive lamps are subjected to accelerated random vibration tests during design to assess their integrity over a life-time exposure to mechanical vibration loading. Often, the lamp assemblies experience fatigue failure during testing. Currently, in the design phase, it is difficult to identify the weaknesses within the assembly. The product development is hence based on trials. This results in a costly and time-consuming design cycle. Having a robust mathematical failure prediction model (a virtual prototype) will eliminate many of the shortcomings listed, enabling reduction in the design cycle, eventually successfully meeting vibration specification economically and efficiently. However, there are challenges in numerically predicting the fatigue of polymers. Modern automotive lamp assemblies have complex geometry and are composed of different parts made of polymer materials. Polymers exhibit hyperelastic behaviour and they also exhibit inter-sample variation due to manufacturing processes. Some of the material properties required for dynamic and fatigue life analysis are not readily available. The key to robust fatigue analysis of lamp assemblies is the availability of reliable input parameters, such as identifying the reliable hyperelastic material model from the existing models, fatigue data (S-N curves) and variability in the behaviour of manufactured constructions. Also, dynamic and fatigue models need to be established. A study was conducted to identify from the existing models, hyperelastic material model that can reliably describe the hyperelastic behaviour of…
abstract: This thesis presents a technique for numerically modelling and predicting the fatigue life of automotive lamps made of thermoplastic polymers. The primary aim is to use the fatigue failure prediction technique developed in this research to address fatigue challenges in the design of automotive lamps. The research combined numerical simulation and experimental studies. As part of design verification, automotive lamps are subjected to accelerated random vibration tests during design to assess their integrity over a life-time exposure to mechanical vibration loading. Often, the lamp assemblies experience fatigue failure during testing. Currently, in the design phase, it is difficult to identify the weaknesses within the assembly. The product development is hence based on trials. This results in a costly and time-consuming design cycle. Having a robust mathematical failure prediction model (a virtual prototype) will eliminate many of the shortcomings listed, enabling reduction in the design cycle, eventually successfully meeting vibration specification economically and efficiently. However, there are challenges in numerically predicting the fatigue of polymers. Modern automotive lamp assemblies have complex geometry and are composed of different parts made of polymer materials. Polymers exhibit hyperelastic behaviour and they also exhibit inter-sample variation due to manufacturing processes. Some of the material properties required for dynamic and fatigue life analysis are not readily available. The key to robust fatigue analysis of lamp assemblies is the availability of reliable input parameters, such as identifying the reliable hyperelastic material model from the existing models, fatigue data (S-N curves) and variability in the behaviour of manufactured constructions. Also, dynamic and fatigue models need to be established. A study was conducted to identify from the existing models, hyperelastic material model that can reliably describe the hyperelastic behaviour of…
author: Okeke, Chukwudi
language: en
date published: 2020
date modified: 2026-07-24T03:41:51Z
provider: Oxford Brookes University
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: Oxford Brookes University

PropertyValue
property ID: DOI
value: 10.24384/zcbe-bd15