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In this paper, the results obtained from experimental measurements of average and turbulence quantities of a turbulent rectangular impinging jet hitting a fixed wall is reported using the laser doppler anemometry (LDA) method. The nozzle to plate distance is 10 times the nozzle width, and the tests are repeated for three different Reynolds numbers, namely Re=3000, 6000 and 9000. The aim of the current research was to investigate and comparise of flow in different Re and also to determine the two effective experimental errors on average velocities, namely data sampling and residence time in measurement volume. The results reveal that the previous stated correlation for prediction of the number of data required for ensuring independence of the average flow variables on the number of the sampled data is not sufficient by itself, and depending on the turbulence intensity of the flow, this correlation could become ineffective. Further, in the present study, the residence time is used for calculation of average velocities, and the results are compared with those obtained by particle image velocimetry (PIV) method. The comparison shows good agreement between the results from LDA and PIV when considering effect of residence time within the avaraging equations in the former method. The results show that the behavior and quantity of the dimensionless average velocities for various Reynolds numbers are identical at most cross sections of the flow domain while the dimensionless turbulent stresses have different quantities at different values of the Reynolds number.

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Population age structure is a main factor affecting government consumption expenditure. This paper examines the effects of changes in population age structure on government consumption expenditure by using a Mixed Frequency Data Sampling (MIDAS) approach. The estimation results indicate that population age structure are of positive and significant effects on government consumption expenditure. In addition, government consumption expenditure is forecasted for 2014. To assess the predictive power of the model, the actual data in 2014 was not used. The expenditure forecasted by the model is 1437079 billion Rials, and corresponding real value is 1438316 billion Rials. This indicates the goodness of fit of model.