Computational Phase Diagrams and their Database Based on CALPHAD T. Abe Computational Phase Diagrams and their Database Based on CALPHAD 1 Research Center for Structural Materials National Institute for Materials Science (NIMS) T. Abe Through the assessment of the Gibbs energy functions of the phases in various alloy systems using the 1 Research Center for Structural Materials National Institute for Materials Science (NIMS) CALPHAD method, we are constructing a computational phase diagram database where users can download TDB (Thermodynamic database) files for calculations of thermodynamic quantities such as Through the assessment of the Gibbs energy functions of the phases in various alloy systems using the phase equilibria and Gibbs energies in unary to multicomponent systems. The CPDDB: Computational CALPHAD method, we are constructing a computational phase diagram database where users can phase diagram database and its digitalized version, Digital-CPDDB, are available on MatNavi in the download TDB (Thermodynamic database) files for calculations of thermodynamic quantities such as NIMS DICE system [1]. These databases cover more than 700 unary, binary, and ternary systems. We phase equilibria and Gibbs energies in unary to multicomponent systems. The CPDDB: Computational are also constructing databases for Ni-Base superalloys: Ni-Al-Co-Cr-Ti+α, Nd-based permanent phase diagram database and its digitalized version, Digital-CPDDB, are available on MatNavi in the magnets: Nd-Fe-B-Co-Cu-Dy-Al-Ga and Nd-Fe-B-Cu-O-C-Dy [2], Ag-based solder materials, high NIMS DICE system [1]. These databases cover more than 700 unary, binary, and ternary systems. We entropy alloys and MoSiBTiC alloys. These phase diagram databases enable the thermodynamic are also constructing databases for Ni-Base superalloys: Ni-Al-Co-Cr-Ti+α, Nd-based permanent calculations for the actual processes of practical materials and provide effective knowledge for the magnets: Nd-Fe-B-Co-Cu-Dy-Al-Ga and Nd-Fe-B-Cu-O-C-Dy [2], Ag-based solder materials, high optimization of process parameters. Since the Gibbs energy functions described in the TDB files are entropy alloys and MoSiBTiC alloys. These phase diagram databases enable the thermodynamic critically assessed by experts, they can be used as a high-quality data source for machine learning to calculations for the actual processes of practical materials and provide effective knowledge for the estimate various properties. optimization of process parameters. Since the Gibbs energy functions described in the TDB files are M.Morishita, Y.Chen, References: critically assessed by experts, they can be used as a high-quality data source for machine learning to A.Saengdeejing, K.Hashimoto, Y.Kobayashi, I.Ohnuma, T.Koyama, S.Hirosawa, STAM, 22 [1] (2021) estimate various properties. 557-570. M.Morishita, Y.Chen, References: A.Saengdeejing, K.Hashimoto, Y.Kobayashi, I.Ohnuma, T.Koyama, S.Hirosawa, STAM, 22 [1] (2021) 557-570. Numerical Prediction of Strength Scatter in Ceramics Based on Information Numerical Prediction of Strength Scatter in Ceramics Based on T. Maeda 1,2, T. Osada 2,3 and S. Ozaki 2,3 Information 1 Graduate School of Engineering Science, Yokohama National University 2 High Temperature Materials Group, Research Center for Structural Materials, National Institute for T. Maeda 1,2, T. Osada 2,3 and S. Ozaki 2,3 Materials Science (NIMS) 1 Graduate School of Engineering Science, Yokohama National University 3 Division of System Research, Faculty of Engineering, Yokohama National University 2 High Temperature Materials Group, Research Center for Structural Materials, National Institute for Materials Science (NIMS) Ceramics are used in a wide range of applications such as electric equipment components and medical 3 Division of System Research, Faculty of Engineering, Yokohama National University products due to their light weight, high heat resistance, insulation, and biocompatibility. However, those use as a structural member is prevented because of scatter and size dependency of strength caused by Ceramics are used in a wide range of applications such as electric equipment components and medical their brittleness and microstructural heterogeneity. For overcoming the challenges and designing highly products due to their light weight, high heat resistance, insulation, and biocompatibility. However, those reliable ceramic members, it is necessary to predict the member strength by understanding the strength use as a structural member is prevented because of scatter and size dependency of strength caused by scatter, which is caused by the stochastic distribution of defects. their brittleness and microstructural heterogeneity. For overcoming the challenges and designing highly In this study, we proposed a numerical simulation method to predict the strength scatter of ceramics and reliable ceramic members, it is necessary to predict the member strength by understanding the strength its size dependency based on internal microstructural data obtained by using X-ray computed scatter, which is caused by the stochastic distribution of defects. tomography and scanning electron microscopy with a fracture mechanics model. The microstructure In this study, we proposed a numerical simulation method to predict the strength scatter of ceramics and information, such as pore size and grain size, was organized based on extreme value statistics, focusing its size dependency based on internal microstructural data obtained by using X-ray computed only on fracture origin candidates. Prediction of the bending strengths was examined for the four types tomography and scanning electron microscopy with a fracture mechanics model. The microstructure of bending tests with different effective volumes, of which the results were in good agreement with the information, such as pore size and grain size, was organized based on extreme value statistics, focusing experimental ones. It was also confirmed that the proposed method is applicable to analysis model only on fracture origin candidates. Prediction of the bending strengths was examined for the four types discretized with arbitrary element size. of bending tests with different effective volumes, of which the results were in good agreement with the experimental ones. It was also confirmed that the proposed method is applicable to analysis model discretized with arbitrary element size. [1][1] CPDDB, https://cpddb.nims.go.jp/cpddb/, CPDDB, https://cpddb.nims.go.jp/cpddb/, Poster Presentation ｜NIMS Award Symposium 2023 P4 ｜ ModelingT.Abe, [2] [2] T.Abe, Microstructural Microstructural PP44--0011 PP44--0011 PP44--0022 PP44--0022 69
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