An experimental and theoretical investigation of three phase direct contact heat transfer by evaporation of refrigerant drops in an immiscible liquid has been carried out. Refrigerant Rl2 and R134a were used for the dispersed phase, while water and brine were the immiscible continuous phase. A numerical analysis is presented to predict the temperature distribution throughout the circular test column radially and axially is achieved. Experimental measurements of the temperature distribution have been compared with the numerical results and are discussed .A comparison between the experimental and theoretical results showed acceptable agreement and applicability of the derived equations. Comparison with other related work showed similar behavior.
It is an established fact that substantial amounts of oil usually remain in a reservoir after primary and secondary processes. Therefore; there is an ongoing effort to sweep that remaining oil. Field optimization includes many techniques. Horizontal wells are one of the most motivating factors for field optimization. The selection of new horizontal wells must be accompanied with the right selection of the well locations. However, modeling horizontal well locations by a trial and error method is a time consuming method. Therefore; a method of Artificial Neural Network (ANN) has been employed which helps to predict the optimum performance via proposed new wells locations by incorporatin
In this paper, a Monte Carlo Simulation technique is used to compare the performance of the standard Bayes estimators of the reliability function of the one parameter exponential distribution .Three types of loss functions are adopted, namely, squared error loss function (SELF) ,Precautionary error loss function (PELF) andlinear exponential error loss function(LINEX) with informative and non- informative prior .The criterion integrated mean square error (IMSE) is employed to assess the performance of such estimators
Methods of estimating statistical distribution have attracted many researchers when it comes to fitting a specific distribution to data. However, when the data belong to more than one component, a popular distribution cannot be fitted to such data. To tackle this issue, mixture models are fitted by choosing the correct number of components that represent the data. This can be obvious in lifetime processes that are involved in a wide range of engineering applications as well as biological systems. In this paper, we introduce an application of estimating a finite mixture of Inverse Rayleigh distribution by the use of the Bayesian framework when considering the model as Markov chain Monte Carlo (MCMC). We employed the Gibbs sampler and
... Show MoreThis research involves studying the influence of increasing the
number of Gaussian points and the style of their distribution, on a circular exit pupil, on the numerical calculations accuracy of the point spread function for an ideal optical system and another system having focus error of (0.25 A. and 0.5 A. )
It was shown that the accuracy of the results depends on the type of
distributing points on the exit pupil. Also, the accuracy increases with the increase of the number of points (N) and the increase of aberrations which requires on increas (N).
This study includes Estimating scale parameter, location parameter and reliability function for Extreme Value (EXV) distribution by two methods, namely: -
- Maximum Likelihood Method (MLE).
- Probability Weighted Moments Method (PWM).
Used simulations to generate the required samples to estimate the parameters and reliability function of different sizes(n=10,25,50,100) , and give real values for the parameters are and , replicate the simulation experiments (RP=1000)
... Show MoreIn this paper, Bayes estimators of Poisson distribution have been derived by using two loss functions: the squared error loss function and the proposed exponential loss function in this study, based on different priors classified as the two different informative prior distributions represented by erlang and inverse levy prior distributions and non-informative prior for the shape parameter of Poisson distribution. The maximum likelihood estimator (MLE) of the Poisson distribution has also been derived. A simulation study has been fulfilled to compare the accuracy of the Bayes estimates with the corresponding maximum likelihood estimate (MLE) of the Poisson distribution based on the root mean squared error (RMSE) for different cases of the
... Show MoreThis paper deals with constructing mixed probability distribution from mixing exponential
The main aim of this paper is to study how the different estimators of the two unknown parameters (shape and scale parameter) of a generalized exponential distribution behave for different sample sizes and for different parameter values. In particular,
. Maximum Likelihood, Percentile and Ordinary Least Square estimators had been implemented for different sample sizes (small, medium, and large) and assumed several contrasts initial values for the two parameters. Two indicators of performance Mean Square Error and Mean Percentile Error were used and the comparisons were carried out between different methods of estimation by using monte carlo simulation technique .. It was obse
... Show MoreSeasonal variations of the species composition and abundance of Cladocera were studied in two stations at the end of the Tigris River and one station at the confluence of the Tigris with Euphrates area, at the beginning of the Shatt Al-Arab River in Al-Qurnah North of Basrah Province, from October 2015 to August 2016. Samples of zooplankton were collected by plankton net 100-µm. mesh size. The population density of Cladocera ranged between 1 Ind /m³ during summer and 211 Ind./m³ during winter at station 1 (Al-Jewaber Bridge). A total of 16 species of Cladocera belonging to 12 genera were recorded in the study. The average density of Cladocera ranged from 23.2 ind./m3 at Station 2 (Hamayon Bridge) to 53.7 Ind./m3
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