Skip to content Skip to navigation
University of Warwick
  • Study
  • |
  • Research
  • |
  • Business
  • |
  • Alumni
  • |
  • News
  • |
  • About

University of Warwick
Publications service & WRAP

Highlight your research

  • WRAP
    • Home
    • Search WRAP
    • Browse by Warwick Author
    • Browse WRAP by Year
    • Browse WRAP by Subject
    • Browse WRAP by Department
    • Browse WRAP by Funder
    • Browse Theses by Department
  • Publications Service
    • Home
    • Search Publications Service
    • Browse by Warwick Author
    • Browse Publications service by Year
    • Browse Publications service by Subject
    • Browse Publications service by Department
    • Browse Publications service by Funder
  • Help & Advice
University of Warwick

The Library

  • Login
  • Admin

Privatised policing duties in a constitutional state: the case of postcolonial Tanzania in socio-legal context

Tools
- Tools
+ Tools

Zhang, Ye (2020) Privatised policing duties in a constitutional state: the case of postcolonial Tanzania in socio-legal context. PhD thesis, University of Warwick.

[img]
Preview
PDF
WRAP_Theses_ZhangYe_2020.pdf - Submitted Version - Requires a PDF viewer.

Download (4Mb) | Preview
Official URL: http://webcat.warwick.ac.uk/record=b3710767

Request Changes to record.

Abstract

Nylon spur gears were 3D printed using Nylon 618, Nylon 645, alloy 910 filaments, together with Onyx and Markforged nylon proprietary materials, with wear rate tests performed on a custom-built gear wear test rig. The results showed that Nylon 618 provided the best wear performance among the 5 different 3D printing materials tested. It is hypothesised that the different mechanical performance between nylon filaments was caused by differences in crystallinity and uniqueness of the Fused Deposition Modelling (FDM) process. The performance results showed that gears 3D printed using Nylon 618 actually performed better than injection moulded nylon 66 gears when low to medium torque was applied. The selection of printing parameters for 3D printing can dramatically affect the dynamic performance of components such as polymer spur gears. Performance of 3D printed gears has been optimised using a machine learning process. A genetic algorithm (GA)–based artificial neural network (ANN) multi-parameter regression model was created. There were four print parameters considered in 3D printing process, i.e. printing temperature, printing speed, printing bed temperature and infill percentage. The parameter setting was generated by the Sobol sequence. Moreover, sensitivity analysis was carried out, and leave-one cross validation was applied to the genetic algorithm-based ANN which showed a relatively accurate performance in predictions and performance optimisation of 3D printed gears.

Small-angle X-ray scattering (SAXS), wide-angle X-ray scattering (WAXS), differential scanning calorimetry (DSC), X-ray fluorescence (XRF) and Fourier-transform infrared (FTIR) test were carried out to analyse the influence from different Nylon materials to the dynamic performance and mechanical properties of 3D printed gears, and demonstrate the intrinsic links between processing parameter, mechanical performance, and materials. Various of computer simulation has been carried out to test the different loading scenario affecting gear and materials performance. The Objective of this project is to improve the performance of the 3D printed polymer gears.

Item Type: Thesis or Dissertation (PhD)
Subjects: T Technology > TA Engineering (General). Civil engineering (General)
T Technology > TS Manufactures
Library of Congress Subject Headings (LCSH): Mechanical wear -- Testing, Gearing, Polymers -- Industrial applications, Additive manufacturing, Three-dimensional printing -- Industrial applications
Official Date: February 2020
Dates:
DateEvent
February 2020UNSPECIFIED
Institution: University of Warwick
Theses Department: School of Engineering
Thesis Type: PhD
Publication Status: Unpublished
Supervisor(s)/Advisor: Mao, Ken ; Leigh, Simon J.
Format of File: pdf
Extent: ix, 131 leaves : illustrations
Language: eng

Request changes or add full text files to a record

Repository staff actions (login required)

View Item View Item

Downloads

Downloads per month over past year

View more statistics

twitter

Email us: wrap@warwick.ac.uk
Contact Details
About Us