TMA Technique was used to study the behavior of the thermal expansion (α) of the unsaturated polyester resin(UP) containing ratios wt % of different phenolic Bakelite. We can through this technique evaluate the coefficient of linear thermal expansion (α) on the one hand and the glass transition temperature(Tg) of his other hand of polymer composite prepared .Evidenced from this study that extravagant increases the ratio of phenolic Bakelite in polyester prepared led to a decrease in the Tg and it was observed that there is increase in the values of (α) in low temperture and decrease in high temperture due to transformation of polymeric material from elastic to plastic , and therefore, increase the ratio to 15% phenolic which gave a low value of (α)compared to the other the samples prepared.
The charge density distributions (CDD) and the elastic electron scattering form
factors F(q) of the ground state for some odd mass nuclei in the 2s 1d shell, such
as K Mg Al Si 19 25 27 29 , , , and P 31
have been calculated based on the use of
occupation numbers of the states and the single particle wave functions of the
harmonic oscillator potential with size parameters chosen to reproduce the observed
root mean square charge radii for all considered nuclei. It is found that introducing
additional parameters, namely; 1 , and , 2 which reflect the difference of the
occupation numbers of the states from the prediction of the simple shell model leads
to very good agreement between the calculated an
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
(1)
The comparison of double informative priors which are assumed for the reliability function of Pareto type I distribution. To estimate the reliability function of Pareto type I distribution by using Bayes estimation, will be used two different kind of information in the Bayes estimation; two different priors have been selected for the parameter of Pareto type I distribution . Assuming distribution of three double prior’s chi- gamma squared distribution, gamma - erlang distribution, and erlang- exponential distribution as double priors. The results of the derivaties of these estimators under the squared error loss function with two different double priors. Using the simulation technique, to compare the performance for
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