This paper presents a method for controlling and operating a multi-chillers system: (1) Model-based control approach was used by MATLAB/SIMULINK to model a building containing two non-identical chillers depending on thermal loads. (2) ON/OFF all chillers alternately using the model reinforcement learning controller (RL-control) to select the appropriate chiller for the building conditioning process. The results were in terms of energy efficiency and performance of the enhanced learning control for the chiller, and a control unit signal (PID) was applied to make a comparison with the signals of energy, power, and temperatures. After comparison, it was found that the energy saving through the proposed controller is 45% of the traditional (PID) strategy, where can the proposed strategy control for the chiller appropriate for the building's conditioning process.

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The improvement of Basrah asphalt cement that used in hot mix pavement can be achieved by using four influencing variables, which are the value of temperature needed for mixing, time of mixing, the amount of wasted car tire rubber (WCR) and the amount of wasted truck tire rubber (WTR). The main virtue of this study is to know the affecting of classifying the CRM sources, and how that will enhance the properties of tire rubber modified asphalt binder. The improvement is estimated through using the ranges (150-180 o C) of temperature, (20-60) minute of mixing time, (10-20) gm of WCR and (0-4) gm of WTR.The using of two different types of waste tires had shown clearly the affecting on the results of responses studied. The effect of independent variables was studied by using Box-Wilson technique of experimental design. Moreover, the regression coefficients for responses models equation and the optimum conditions were estimated by using STATISTICA software.The results had shown that the optimum values of the independent variables to submit the Journal of Environment and Ecology 28 best responses of penetration test and softening point test was at temperature (180 o C), mixing time (60 minute), WCR (20 gm), and WTR (4gm) and then found new mathematical models to estimate these responses at any values of independent variables. The Marshall stability result of the modified asphalt mixes was higher than of the unmodified asphalt mixes.

This research was carried out to optimize the blending process for Iraqi oil. Physical and chemical properties of three different Iraqi crude oils were obtained through analytical analysis of oil samples. A unique petroleum assay for each crude oil was used to identify the various boiling point, density, viscosity and sulphur content of fractions that we can obtain through the atmospheric distillation of crude. Petroleum assays were manually imported to Aspen HYSYS to simulate the behaviour for each crude oil. A trial of more than 60 different blending scenarios was simulated and blends’ results were tested for API gravity and sulphur content variation. Aspen HYSYS was also used to simulate shortcut distillation for each blend and the possible API gravity and sulphur content of distillation fractions.

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