20.500.12556/RUL-126685 Evaluating magnetocaloric effect in magnetocaloric materials a novel approach based on indirect measurements using artificial neural networks The thermodynamic characterisation of magnetocaloric materials is an essential task when evaluating the performance of a cooling process based on the magnetocaloric effect and its application in a magnetic refrigeration cycle. Several methods for the characterisation of magnetocaloric materials and their thermodynamic properties are available in the literature. These can be generally divided into theoretical and experimental methods. The experimental methods can be further divided into direct and indirect methods. In this paper, a new procedure based on an artificial neural network to predict the thermodynamic properties of magnetocaloric materials is reported. The results show that the procedure provides highly accurate predictions of both the isothermal entropy and the adiabatic temperature change for two different groups of magnetocaloric materials that were used to validate the procedure. In comparison with the commonly used techniques, such as the mean field theory or the interpolation of experimental data, this procedure provides highly accurate, time-effective predictions with the input of a small amount of experimental data. Furthermore, this procedure opens up the possibility to speed up the characterisation of new magnetocaloric materials by reducing the time required for experiments. magnetic refrigeration magnetocaloric effect gadolinium artificial neural network modelling LaFe$_{13−x−y}$Co$_x$Si$_y$ magnetno hlajenje magnetokalorični učinek gadolinij nevronske mreže true false true Angleški jezik Slovenski jezik Članek v reviji 2021-05-04 13:12:32 2021-05-04 13:12:34 2022-09-06 03:48:35 0000-00-00 00:00:00 2019 0 0 22 str. iss. 10, art. 1871 Vol. 12 May 2019 0000-00-00 Zaloznikova Objavljeno NiDoloceno 0000-00-00 0000-00-00 0000-00-00 536:697(045) 1996-1073 10.3390/en12101871 16618011 RAZ_Maiorino_Angelo_2019.pdf RAZ_Maiorino_Angelo_2019.pdf 1 748DB15658FC7E70196C3C8CA500787C cc400d2d5d2f2abe612830727e287a7f15f132ec3c4f7ea7a01298c99bc13a7f bf9edbdb-31a8-11ec-abdb-00155dcfd717 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=149875 https://www.mdpi.com/1996-1073/12/10/1871 1 9b38b44a-acc9-11eb-a523-00155dcfd717 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=142740 Fakulteta za strojništvo 0 0 0