Almost all thermal systems utilize some type of heat exchanger. In a lot of cases, evaporators are important for systems like organic Rankine cycle systems. Evaporators give a share in a large portion of the capital cost, and their cost is significantly attached to their size or transfer area. Open-cell metal foams with high porosity are taken into consideration to enhance thermal performance without increase the size of heat exchangers. Numerous researchers have tried to find a representation of the temperature distribution closer to reality due to the different properties between the liquid and solid phases. Evaporation heat transfer in an annular pipe of double pipe heat exchanger (DPHEX) filled with cooper foam is investigated numerically with utilizing the local thermal non-equilibrium (LTNE) model. Warm water with constant inlet conditions flows in the inner pipe while R143a is used as cooling fluid in the annular pipe. The effects of pores per inch (PPI), mass flux of R134a and copper foam porosity on solid and fluid temperatures, liquid saturation and heat transfer coefficient are analysed and illustrated. Forchheimer-extended Darcy flow model is utilized with the adopting of the two-phase mixture model (TPMM). The governing equations in two-dimensional steady state regime were written in LTNE model. These equations were discretized using the finite volume method and a MATLAB program was built to solve these equations with its initial and boundary conditions. The obtained data illustrates that LTNE effect in metal foam is important for lower porosity, lower pore density and higher mass flux. The ratio of liquid will arrive its lowest value at the outlet, and it decreases with PPI increase and it increases with porosity and mass flux increase. The mean heat transfer coefficient approximately doubled when PPI increased from 10 to 50 and it increased by 70% when porosity decreased from 0.95 to 0.85.
The research problem is that most of the construction projects exceed the planned value, due to the failure to implement the plans on time. The current study aims to monitor the implementation of the project and for each of the executed tasks of the table of quantities in order to detect deviations at the time they occur, evaluate the time and cost performance, and then identify the areas of waste and analyze the implementation of each task in order to diagnose the underlying problems and find possible and applicable solutions in the environment Iraqi. The research was applied in one of the companies specialized in the field of construction projects, and one of the most important conclusions reached is the possibility of applying
... Show MoreIn this study multi objective optimization is utilized to optimize a turning operation to reveal the appropriate level of process features. The goal of this work is to evaluate the optimal combination of cutting parameters like feed, spindle speed, inclination angle and workpiece material to have a best surface quality Taguchi technique L9 mixed orthogonal array, has been adopted to optimize the roughness of surface. Three rods of length around (200 mm) for the three metals are used for this work. Each rod is divided into three parts with 50 mm length. For brass the optimum parametric mix for minimum Ra is A1, B1 and C3, i.e., at tool inclination angle (5), feedrate of 0.01, spindle speed of 120
... Show MoreThe monitoring weld quality is increasingly important because great financial savings are possible because of it, and this especially happens in manufacturing where defective welds lead to losses in production and necessitate time consuming and expensive repair. This research deals with the monitoring and controllability of the fusion arc welding process using Artificial Neural Network (ANN) model. The effect of weld parameters on the weld quality was studied by implementing the experimental results obtained from welding a non-Galvanized steel plate ASTM BN 1323 of 6 mm thickness in different weld parameters (current, voltage, and travel speed) monitored by electronic systems that are followed by destructive (Tensile and Bending) and non
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