Performance assessment of a solar dryer system using small parabolic dish and alumina/oil nanofluid : simulation and experimental study
- Authors: Arkian, Amir , Najafi, Gholamhassan , Gorjian, Shiva , Loni, Reyhaneh , Bellos, Evangelos , Yusaf, Talal
- Date: 2019
- Type: Text , Journal article
- Relation: Energies Vol. 12, no. 24 (Dec 2019), p. 22
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- Description: In this study, a small dish concentrator with a cylindrical cavity receiver was experimentally investigated as the heat source of a dryer. The system was examined for operation with pure thermal oil and Al2O3/oil nanofluid as the working fluids in the solar system. Moreover, the design, the development, and the evaluation of the dried mint plant are presented in this work. Also, the solar dryer system was simulated by the SolidWorks and ANSYS CFX software. On the other side, the color histogram of the wet and dried mint samples based on the RGB method was considered. The results revealed that the different temperatures of the solar working fluids at the inlet and outlet of the cavity receiver showed similar trend data compared to the variation of the solar radiation during the experimental test. Moreover, it is found that the cavity heat gain and thermal efficiency of the solar system was improved by using the nanofluid as the solar working fluid. Furthermore, the required time for mint drying had decreased by increasing the drying temperature and increasing air speed. The highest drying time was measured equal to 320 min for the condition of the air speed equal to 0.5 m/s and the drying temperature of 30 degrees C. A good agreement was observed between the calculated numerical results and measured experimental data. Finally, based on the color histogram of the wet and dried mint samples, it was concluded that intensity amount of the red color of the mint increased with the drying process compared to intensity amount of the red color of the wet mint sample.
Artificial neural network modeling and sensitivity analysis of performance and emissions in a compression ignition engine using biodiesel fuel
- Authors: Jaliliantabar, Farzad , Ghobadian, Barat , Najafi, Gholamhassan , Yusaf, Talal
- Date: 2018
- Type: Text , Journal article
- Relation: Energies Vol. 11, no. 9 (2018), p. 1-24
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- Description: In the present research work, a neural network model has been developed to predict the exhaust emissions and performance of a compression ignition engine. The significance and novelty of the work, with respect to existing literature, is the application of sensitivity analysis and an artificial neural network (ANN) simultaneously in order to predict the engine parameters. The inputs of the model were engine load (0, 25, 50, 75 and 100%), engine speed (1700, 2100, 2500 and 2900 rpm) and the percent of biodiesel fuel derived from waste cooking oil in diesel fuel (B0, B5, B10, B15 and B20). The relationship between the input parameters and engine cylinder performance and emissions can be determined by the network. The global sensitivity analysis results show that all the investigated factors are effective on the created model and cannot be ignored. In addition, it is found that the most emissions decreased while using biodiesel fuel in the compression ignition engine.