In this paper the production and characterization of compacted graphite iron alloys in ten chemical compositions is presented. The specimens were obtained through a foundry process performed by a gating system model developed in order to allow the incorporation of silicon, copper and tin. Hardness and tensile tests were performed, as well as microstructural evaluation. Additionally, the results related to the experimental investigation were compared to those obtained from a finite element method analysis. The results showed a correlation between the addition of silicon and the increase of ferrite and graphite count per mm 2 . Regarding copper and tin additions, the percentage increase of pearlite was associated with the reduction of graphite average size. Changes in chemical composition led to different values of ultimate tensile strength, yield strength and hardness, whose magnitude was mainly related to the amount of ferrite. Computer simulation was considered efficient in predicting these results.
Drying food involves complex physical atmospheric mechanisms with non-linear relations from the air-food interactions, and those relations are strongly dependent on the moisture contents and the type of food. Such dependence makes it complex to design suitable dryers dedicated to a single drying process. To streamline the design of a novel compact food-drying machine, a heat pump dryer component design optimization algorithm was developed as a subprogram of a Computer Aided Engineering tool. The algorithm requires inputting food and air properties, the volume of the drying container, and the technical specifications of the heat pump off-the-shelf components. The heat required to dehumidify the food supplied by the heat exchange process from condenser to evaporator, and the compressor's requirements (refrigerant mass flow rate and operating pressures) are then calculated. Compressors can then be selected based on the volume and type of food to be dried. The algorithm is shown via a flow chart to guide the user through three different stages: Changes in drying air properties, heat flow within dryer and product moisture content. Example results of how different compressors are selected for different types of produces and quantities (Agaricus blazei mushroom with three different moisture contents or fish from Thunnini tribe) conclude this article.
Drying food involves complex physical atmospheric mechanisms with non-linear relations from the air-food interactions and those relations are strongly dependent on the moisture contents and the type of food. Such dependence makes it complex to design suitable dryers dedicated to a single drying process. To streamline the design of a novel compact food-drying machine, a heat pump dryer component design optimization algorithm was developed as a subprogram of a Computer Aided Engineering tool. The algorithm requires inputting food and air properties, the volume of the drying container and the technical specifications of the heat-pump off-the shelf components. The heat required to dehumidify the food supplied by the heat exchange process from condenser to evaporator, and the compressor’s requirements (refrigerant mass flow rate and operating pressures) are then calculated. Compressors can then be selected based in the volume and type of food to be dried. The algorithm is shown via a flow chart to guide the user through 3 different stages: Changes in drying air properties, Heat flow within dryer and Product moisture content. Example results of how different compressors are selected for different type of produces and quantities (Agaricus Blazei mushroom with 3 different moisture contents or fish from Thunnini tribe) conclude this article.
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