Abstract: Particle size distribution, the most important
characteristics of aerosols, is obtained through electrical
characterization techniques. The dynamics of charged nanoparticles
under the influence of electric field in Electrical Mobility
Spectrometer (EMS) reveals the size distribution of these particles.
The accuracy of this measurement is influenced by flow conditions,
geometry, electric field and particle charging process, therefore by
the transfer function (transfer matrix) of the instrument. In this work,
a wire-cylinder corona charger was designed and the combined fielddiffusion
charging process of injected poly-disperse aerosol particles
was numerically simulated as a prerequisite for the study of a
multichannel EMS. The result, a cloud of particles with no uniform
charge distribution, was introduced to the EMS. The flow pattern and
electric field in the EMS were simulated using Computational Fluid
Dynamics (CFD) to obtain particle trajectories in the device and
therefore to calculate the reported signal by each electrometer.
According to the output signals (resulted from bombardment of
particles and transferring their charges as currents), we proposed a
modification to the size of detecting rings (which are connected to
electrometers) in order to evaluate particle size distributions more
accurately. Based on the capability of the system to transfer
information contents about size distribution of the injected particles,
we proposed a benchmark for the assessment of optimality of the
design. This method applies the concept of Von Neumann entropy
and borrows the definition of entropy from information theory
(Shannon entropy) to measure optimality. Entropy, according to the
Shannon entropy, is the ''average amount of information contained in
an event, sample or character extracted from a data stream''.
Evaluating the responses (signals) which were obtained via various
configurations of detecting rings, the best configuration which gave
the best predictions about the size distributions of injected particles,
was the modified configuration. It was also the one that had the
maximum amount of entropy. A reasonable consistency was also
observed between the accuracy of the predictions and the entropy
content of each configuration. In this method, entropy is extracted
from the transfer matrix of the instrument for each configuration.
Ultimately, various clouds of particles were introduced to the
simulations and predicted size distributions were compared to the
exact size distributions.
Abstract: Metal matrix composites (MMCs) attract considerable
attention as a result from its ability in providing a high strength, high
modulus, high toughness, high impact properties, improving wear
resistance and providing good corrosion resistance compared to
unreinforced alloy. Aluminium Silicon (Al/Si) alloy MMC has been
widely used in various industrial sectors such as in transportation,
domestic equipment, aerospace, military, construction, etc.
Aluminium silicon alloy is an MMC that had been reinforced with
aluminium nitrate (AlN) particle and become a new generation
material use in automotive and aerospace sector. The AlN is one of
the advance material that have a bright prospect in future since it has
features such as lightweight, high strength, high hardness and
stiffness quality. However, the high degree of ceramic particle
reinforcement and the irregular nature of the particles along the
matrix material that contribute to its low density is the main problem
which leads to difficulties in machining process. This paper examined
the tool wear when milling AlSi/AlN Metal Matrix Composite using
a TiB2 (Titanium diboride) coated carbide cutting tool. The volume
of the AlN reinforced particle was 10% and milling process was
carried out under dry cutting condition. The TiB2 coated carbide
insert parameters used were at the cutting speed of (230, 300 and
370m/min, feed rate of 0.8, Depth of Cut (DoC) at 0.4m). The
Sometech SV-35 video microscope system used to quantify of the
tool wear. The result shown that tool life span increasing with the
cutting speeds at (370m/min, feed rate of 0.8mm/tooth and DoC at
0.4mm) which constituted an optimum condition for longer tool life
lasted until 123.2 mins. Meanwhile, at medium cutting speed which
at 300m/m, feed rate of 0.8mm/tooth and depth of cut at 0.4mm we
found that tool life span lasted until 119.86 mins while at low cutting
speed it lasted in 119.66 mins. High cutting speed will give the best
parameter in cutting AlSi/AlN MMCs material. The result will help
manufacturers in machining process of AlSi/AlN MMCs materials.