Abstract: Composite pins of rubber dust collected from tyre
retreading centres of trucks, cars and buses etc.and epoxy with
weight percentages of 10. 15, and 20 % of rubber (weight fractions of
9, 13 and 17 % respectively) have been prepared in house with the
help of a split wooden mould. The pins were tested in a pin-on-disc
wear monitor to determine the co-efficient of friction and weight
losses with varying speeds, loads and time. The wear volume and
wear rates have also been found out for all these three specimens.. It
is observed that all the specimens have exhibited very low coefficient
of friction and low wear rates under dry sliding condition. Out of the
above three samples tested, the specimen with 10 % rubber dust by
weight has shown lowest wear rates. However a peculiar result i.e
decreasing trend has been obtained with 20% reinforcement of rubber
in epoxy while rubbed against steel at varying speeds. This might
have occurred due to high surface finish of the disc and formation of
a thin transfer layer from the composite
Abstract: Ultrasonic machining (USM) is a non-traditional
machining process being widely used for commercial machining of
brittle and fragile materials such as glass, ceramics and
semiconductor materials. However, USM could be a viable
alternative for machining a tough material such as titanium; and this
aspect needs to be explored through experimental research. This
investigation is focused on exploring the use of ultrasonic machining
for commercial machining of pure titanium (ASTM Grade-I) and
evaluation of tool wear rate (TWR) under controlled experimental
conditions. The optimal settings of parameters are determined
through experiments planned, conducted and analyzed using Taguchi
method. In all, the paper focuses on parametric optimization of
ultrasonic machining of pure titanium metal with TWR as response,
and validation of the optimized value of TWR by conducting
confirmatory experiments.
Abstract: Particulate reinforced metal matrix composites
(MMCs) are potential materials for various applications due to their
advantageous of physical and mechanical properties. This paper
presents a study on the performance of stir cast Al2O3 SiC reinforced
metal matrix composite materials. The results indicate that the
composite materials exhibit improved physical and mechanical
properties, such as, low coefficient of thermal expansion, high
ultimate tensile strength, high impact strength, and hardness. It has
been found that with the increase of weight percentage of
reinforcement particles in the aluminium metal matrix, the new
material exhibits lower wear rate against abrasive wearing. Being
extremely lighter than the conventional gray cast iron material, the
Al-Al2O3 and Al-SiC composites could be potential green materials
for applications in the automobile industry, for instance, in making
car disc brake rotors.
Abstract: This paper addresses modeling and optimization of process parameters in powder mixed electrical discharge machining (PMEDM). The process output characteristics include metal removal rate (MRR) and electrode wear rate (EWR). Grain size of Aluminum powder (S), concentration of the powder (C), discharge current (I) pulse on time (T) are chosen as control variables to study the process performance. The experimental results are used to develop the regression models based on second order polynomial equations for the different process characteristics. Then, a genetic algorithm (GA) has been employed to determine optimal process parameters for any desired output values of machining characteristics.
Abstract: The present work compares the performance of three
turbulence modeling approach (based on the two-equation k -ε
model) in predicting erosive wear in multi-size dense slurry flow
through rotating channel. All three turbulence models include
rotation modification to the production term in the turbulent kineticenergy
equation. The two-phase flow field obtained numerically
using Galerkin finite element methodology relates the local flow
velocity and concentration to the wear rate via a suitable wear model.
The wear models for both sliding wear and impact wear mechanisms
account for the particle size dependence. Results of predicted wear
rates using the three turbulence models are compared for a large
number of cases spanning such operating parameters as rotation rate,
solids concentration, flow rate, particle size distribution and so forth.
The root-mean-square error between FE-generated data and the
correlation between maximum wear rate and the operating
parameters is found less than 2.5% for all the three models.
Abstract: Tribological behavior and wear regimes of ascast
and heattreted Al-Cu-Mg matrix composites containing SiC
particles were studied using a pin-on-disc wear testing apparatus
against an EN32 steel counterface giving emphasis on wear rate as
a function of applied pressures (0.2, 0.6, 1.0 and 1.4 MPa) at
different sliding distances (1000, 2000, 3000, 4000 and 5000
meters) and at a fixed sliding speed of 3.35m/s. The results showed
that the composite exhibited lower wear rate than that of the matrix
alloy and the wear rate of the composites is noted to be invariant to
the sliding distance and is reducing by heat treatment. Wear
regimes such as low, mild and severe wear were observed as per the
Archard-s wear calculations. It is very interesting to note that the
mild wear is almost constant in all the wear regimes.