The research work covers a study of the possibility of producing porous ceramic bodies
as a thermal insulators by adding fired Dechla kaolinite (grog)to the same non burned
kaolinite.
Different weight percentage ranged between (0,15,25,35and40)from grog and sawdust
passed through mesh 50 to Deuchla-clay kaolinit.Cylindrical shape samples (30mm diameter
and 30mm height) were prepared by the semi-dry methed,moulding pressure was 50 N/mm
2
.
After drying at 110
o
c,the samples were burnet in the furnace at temperatures
900,950,1000,1050,and 1100
o
c. The sawdust burnt out and leaves air spaces which contribute
to the high thermal insulation value.
The fired samples were investigated to determine bulk density , porosity, compressive
strength and the thermal conductivity .It was found that the increase of grog ratio produces a
decrease in bulk density ,compressive strength and thermal conductivity, but addition of
sawdust to the samples produces decrease greater than when addition the grog
Possibility of Reducing the Thermal Conductivity of Ceramic Refractory Materials
thermal insulator
bulk density
compressive strength
Porosity
thermal conductivity.
Publication Date
Wed Apr 25 2018
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Different Estimation Methods for System Reliability Multi-Components model: Exponentiated Weibull Distribution
Exponentiated Weibull Distribution (EWD)
Reliability of multi-component Stress – Strength models R(s
k)
Maximum likelihood estimator (MLE)
Moment estimator (MOM)
shrinkage method (Sh)
Least Squares Estimator (LS)
Rank Set Sampling (RSS). and mean squared error (MSE).
In this paper, estimation of system reliability of the multi-components in stress-strength model R(s,k) is considered, when the stress and strength are independent random variables and follows the Exponentiated Weibull Distribution (EWD) with known first shape parameter θ and, the second shape parameter α is unknown using different estimation methods. Comparisons among the proposed estimators through Monte Carlo simulation technique were made depend on mean squared error (MSE) criteria
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