The cement industry is considered one of the strategic industries, because it is directly related to construction work and cement is used as a hydraulic binder. However, it is a simple industry compared to major industries and depends on the availability of the necessary raw materials. This study focuses on optimizing and coordinating the location of raw materials needed for the cement manufacturing in Wasit Governorate in Iraq. Field works include detailed reconnaissance, topographic work, and description and sampling of 24 lithological sections that represent the carbonate deposits, which crop out in the area. The investigated area has the following specifications: The weighted averages of chemical components in the industrial bed are as follows: CaO = 47.83%, MgO = 1.12%, SiO2 = 7.28%, SO3 = 0.34%, Fe2O3 = 1.85%, Al2O3 = 1.85%, L.O.I = 39.26%, Na2O = 0.29%, and K2O = 0.38%. The average thickness of the investigated raw materials is 15.68 m. The average bulk density of the investigated raw materials is 2.32 g/cm3. The compressive strength of the investigated raw materials ranges from 6.182 to 55.21 MN/m2. The positive area is 922,552 m2. The volume of the industrial bed is 14,466,242 m3. The economic reserve of the industrial bed is 33,561,682 tons.
Tin Selenide (SnSe) Nano crystalline thin films of thickness 400±20 nm were deposited on glass substrate by thermal evaporation technique at R.T under a vacuum of ∼ 2 × 10− 5 mbar to study the effect of annealing temperatures (as-deposited, 100, 150 and 200) °C on its structural, surface morphology and optical properties. The films structure was characterized using X-ray diffraction (XRD) which showed that all the films have polycrystalline in nature and orthorhombic structure, with the preferred orientation along the (111) plane. These films was synthesized of very fine crystallites size of (14.8-24.5) nm, the effect of annealing temperatures on the cell parameters, crystallite size and dislocation density were observed.
... Show MoreThe university course timetable problem (UCTP) is typically a combinatorial optimization problem. Manually achieving a useful timetable requires many days of effort, and the results are still unsatisfactory. unsatisfactory. Various states of art methods (heuristic, meta-heuristic) are used to satisfactorily solve UCTP. However, these approaches typically represent the instance-specific solutions. The hyper-heuristic framework adequately addresses this complex problem. This research proposed Particle Swarm Optimizer-based Hyper Heuristic (HH PSO) to solve UCTP efficiently. PSO is used as a higher-level method that selects low-level heuristics (LLH) sequence which further generates an optimal solution. The proposed a
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