those with which the mismatch between experimental and numerical temperature changes is minimised. Finally, the optimisation procedure using a multi-objective genetic algorithm was performed, with the goal of finding optimal values for the input parameters, i.e. Further simulations, in which the value of the chosen factors was changed, made it possible to create response surfaces using as a response variable the value of the mismatch between the experimental and numerical temperature changes in the same points. Firstly, the most influential input parameters were chosen in order to determine the factors to be investigated using a reduced factorial scheme. 5.2) in order to calculate the temperature at the same points at any step of the process.
Magmasoft heat transfer software#
Experimental instrumented castings were used to acquire (both in the casting and in the sand) temperature changes for a number of points of interest by means of thermocouples in addition, the entire process was simulated using the finite difference method commercial software package MAGMASOFT® (v. This work focuses on the most appropriate methodology to determine the heat transfer coefficients for the numerical modelling of the casting process of a super duplex stainless steel (ASTM A890 Gr.
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