The aim of this research is to study the factors affecting drag coefficient (C d ) in
non-Newtonian fluids which are the rheological properties ,concentrations of non-
Newtonian fluids, particle shape, size and the density difference between particle and
fluid .Also this study shows drag coefficient (C d ) and particle Reynolds' number (Re
P ) relationship and the effect of rheological properties on this relationship.
An experimental apparatus was designed and built, which consists of Perspex pipe
of length of 160 cm. and inside diameter of 7.8 cm. to calculate the settling velocity,
also electronic circuit was designed to calculate the falling time of particles through
fluid.
Two types of solid particles were used; glass spheres and crushed rocks as
irregularly shaped particles with different diameters and compared with each other.
The concept of equivalent spherical diameter (D S ) was used to calculate the
diameters of irregularly shaped particles.
The flow behavior for Non-Newtonian fluids was represented by Power-Law model.
Two types of polymers were used, Carboxy Methyl Cellulose CMC with
concentrations of (3.71, 5, 15 and 17.5) g/l and polyacrylamide with concentrations of
(2, 4 and 6) g/l.
The results showed that the drag coefficient decreased with increasing settling
velocity and particle diameters and sizes; and increased as fluid become far from
Newtonian behavior and concentrations and the density difference between particle
and fluid.
The results also showed that the rheological properties of Non-Newtonian fluids
have a great effect on the drag coefficient and particle Reynolds number relationship,
especially in laminar-slip regime and decreases or vanishes at transition and turbulentslip
regimes.
New correlations were obtained which relates drag coefficient with concentrations
of polymers and with flow behavior indices for spherical and irregular shaped
particles in Carboxy Methyl Cellulose CMC and polyacrylamide solutions.
This paper studies a novel technique based on the use of two effective methods like modified Laplace- variational method (MLVIM) and a new Variational method (MVIM)to solve PDEs with variable coefficients. The current modification for the (MLVIM) is based on coupling of the Variational method (VIM) and Laplace- method (LT). In our proposal there is no need to calculate Lagrange multiplier. We applied Laplace method to the problem .Furthermore, the nonlinear terms for this problem is solved using homotopy method (HPM). Some examples are taken to compare results between two methods and to verify the reliability of our present methods.
Non-thermal argon plasma needle at atmospheric pressure was
constructed. The experimental setup was based on a simple and low
cost electric component that generates a sufficiently high electric
field at the electrodes to ionize the argon gas which flow at
atmospheric pressure. A high AC power supply was used with 1.1
kV and 19.57 kHz. Non-thermal Argon plasma used on blood
samples to show the ability of non-thermal plasma to promote blood
coagulation. Three tests have been done to show the ability of plasma
to coagulate both normal and anti-coagulant blood. Each blood
sample has been treated for varying time from 20sec. to 180sec. at
different distances. The results of the current study showed that the
co
Two hundred fifty mid-stream urine specimens were collected from Baqubah Teaching Hospital and Al-Batool Teaching Hospital from patients with urinary tract infections (UTI). Of these investigated urine specimens, 66 (26.4%) specimens showed positive growth culture of Gram-negative bacteria. From these, Escherichia coli was the most prevalent bacteria of the examined culture (41, 62.12%). Additionally, the cup assay was used to determine colicin producers while the most efficient colicin producers were estimated by the formation of larger inhibition zone. Approximately half of the investigated E. coli isolates (20, 49 %) was colicin producers. Colicins was extracted after induction by mitomycin-C showed a concentration o
... Show MoreIn this paper, a self-tuning adaptive neural controller strategy for unknown nonlinear system is presented. The system considered is described by an unknown NARMA-L2 model and a feedforward neural network is used to learn the model with two stages. The first stage is learned off-line with two configuration serial-parallel model & parallel model to ensure that model output is equal to actual output of the system & to find the jacobain of the system. Which appears to be of critical importance parameter as it is used for the feedback controller and the second stage is learned on-line to modify the weights of the model in order to control the variable parameters that will occur to the system. A back propagation neural network is appl
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