Development and characterization of Metal matrix Composit using Red Mud on Industrial Wage for Wear Registant Applications

By: Prasad, NareshContributor(s): Acharya, S K [Supervisor] | Department of Mechanical EngineeringMaterial type: TextTextLanguage: English Publisher: 2006Description: 204 pSubject(s): Engineering and Technology | Metallurgical and Materials Science | Composites | Metal-MatrixOnline resources: Click here to access online Dissertation note: Thesis (Ph.D)- National Institute of Technology, Rourkela Summary: Red mud emerges as the major waste material during production of alumina from bauxite by the Bayer’s process. It comprises of oxides of iron, titanium, aluminum and silica along with some other minor constituents. Based on economics as well as environmental related issues, enormous effort s have been directed worldwide towards red mud management issues i.e. of utilization, storage and dispos al. Different avenues of red mud utilization are more or less known but none of them have so far proved to be economically viable or commercially feasible. It is generally agreed that resistance to wear of MMCs is created by reinforcement and also the wear properties are improved remarkably by introducing hard intermetallic compound into the aluminium matrix. The reinforcing materials are generally SiC, Al 2 O 3 , TiB 2 etc and are costly. The present research work has been undertaken with an objective to explore the use of red mud as a reinforcing material as a low cost option. This is due to the fact that red mud alone c ontains all these reinforcement elements and is plentifully available. Experiments have been conducted under laboratory condition to assess the wear characteristics of the aluminium red mud composite unde r different working conditions in pure sliding mode on a pin-on- disc machine. This has been possible by fabricating the samples through usual stir casting technique. To enhance the wear properties, the samples were also subjected to heat treatment. The worn surfaces of the wear out samples were studied und er optical microscope to get an idea about the effect of particulate reinforcement on the wear behavior of the composite. Dispersion of red mud particles in aluminiu m matrix improves the hardness of the matrix material and also the wear behavior of the com posite. Wear resistance of the composite can be improved by heat treatmen t and proper choice of cooling media. A prediction model using artificial neural networks (ANN) is al so employed to simulate the property parameters correlation and a fairly good agreement in the experimental and predicted value is obtained. There are other fabrication techniques ava ilable where the volume fraction of reinforcements could be increased and are likely to vary the wear performances of the composite. This work can be further extended to those techniques. However these results can act as a starting point for both industria l designers and researchers to design and develop MMC components using this industrial waste for applications in wear environment. The whole disserta tion has been divided into six chapters to put the analysis independent of each other as far as possible. The major work on wear characteristics and validation of results through Artificial Neural Network ( ANN) techniques are given in chapter 3, 4, and 5 respectively.
Tags from this library: No tags from this library for this title. Log in to add tags.
    Average rating: 0.0 (0 votes)
Item type Current location Collection Call number Status Date due Barcode
Thesis (Ph.D/M.Tech R) Thesis (Ph.D/M.Tech R) BP Central Library
Thesis Section
Reference Not for loan T12

Thesis (Ph.D)- National Institute of Technology, Rourkela

Red mud emerges as the major waste material during production of alumina
from bauxite by the Bayer’s process. It comprises of oxides of iron, titanium, aluminum
and silica along with some other minor constituents. Based on economics as well as
environmental related issues, enormous effort
s have been directed worldwide towards red
mud management issues i.e. of
utilization, storage and dispos
al. Different avenues of red
mud utilization are more or less known but
none of them have so far proved to be
economically viable or commercially feasible.
It is generally agreed that resistance to wear of MMCs is created by
reinforcement and also the wear properties are improved remarkably by introducing hard
intermetallic compound into the
aluminium matrix. The reinforcing materials are generally
SiC, Al
2
O
3
, TiB
2
etc and are costly. The present research work has been undertaken with
an objective to explore the use of red mud as
a reinforcing material as a low cost option.
This is due to the fact that red mud alone c
ontains all these reinforcement elements and is
plentifully available.
Experiments have been conducted under laboratory condition to assess the
wear characteristics of the aluminium
red mud composite unde
r different working
conditions in pure sliding mode on a pin-on-
disc machine. This has been possible by
fabricating the samples through usual stir
casting technique. To
enhance the wear
properties, the samples were also subjected to
heat treatment. The worn surfaces of the
wear out samples were studied und
er optical microscope to get
an idea about the effect of
particulate reinforcement on the wear behavior of the composite.
Dispersion of
red mud particles in aluminiu
m matrix improves the hardness
of the matrix material and also
the wear behavior of the com
posite. Wear resistance of the
composite can be improved by heat treatmen
t and proper choice of cooling media. A
prediction model using artificial
neural networks (ANN) is al
so employed to simulate the
property parameters correlation and a fairly
good agreement in the experimental and
predicted value is obtained.
There are other fabrication techniques ava
ilable where the volume fraction
of reinforcements could be increased and are likely to vary the wear performances of the
composite. This work can be further extended
to those techniques. However these results
can act as a starting point for both industria
l designers and researchers to design and
develop MMC components using this industrial waste for applications in wear
environment.
The whole disserta
tion has been divided into six
chapters to put the analysis
independent of each other as far as possible.
The major work on wear characteristics and
validation of results through
Artificial Neural Network (
ANN) techniques are given in
chapter 3, 4, and 5 respectively.

There are no comments on this title.

to post a comment.

Implemented and Maintained by Biju Patnaik Central Library.
For any Suggestions/Query Contact to library or Email: library@nitrkl.ac.in OR bpcl-cir@nitrkl.ac.in. Ph:91+6612462103
Website/OPAC best viewed in Mozilla Browser in 1366X768 Resolution.

Powered by Koha