Multiphysics of polycrystalline materials

The research of this laboratory focuses on multiphysics in a broad spectrum of materials including metals, polymers and ceramics. We conduct mathematical modeling and numerical simulation of materials for functional devices such as fuel cells by coupling the mechanical behavior with other phenomena and/or bridging different scales of a phenomenon.

Topics:

Large Scale Simulation of SOFC Stack

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Components of solid oxide fuel cells (SOFCs) are exposed to high temperatures and gas pressures under operation. Subjected to the starting and stopping operations, the performance of SOFCs is gradually degraded. One of the degradation factors can be thermal expansive deformation due to temperature change, while the expansive deformation under a reducing environment is a characteristic of SOFCs. These deformations inevitably invoke an unexpectedly large stress owing to the mutual constraints of the components, which causes mechanical deterioration. In addition, creep plays a primary role in long-term operation at high temperatures.
Our research group is investigating deformation of SOFC by combining mechanical and electrochemical phenomena. The target covers cells from laboratory-level to practical large scale.

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Keywords:
  • Electrochemistry
  • Solid Oxide Fuel Cell
  • Inelasticity
  • Large Scale Computation
References:
  • Muramatsu, M., Sato, M., Terada, K., Watanabe, S., Yashiro, K., Kawada, T., Iguchi, F. and Yokokawa, H., "Shape Deformation Analysis of Anode-supported Solid Oxide Fuel Cell by Electro-chemo-mechanical Simulation", Solid State Ionics, Vol. 319, pp. 194-202, (2018).
  • Yokokawa, H., Kishimoto, H., Yamaji, K., Muramatsu, M., Terada, K., Yashiro, K. and Kawada, T., "Simulation Technology on SOFC Durability with an Emphasis on Conductivity Degradation of ZrO2-base Electrolyte", Journal of Electrochemical Energy Conversion and Storage, Vol. 14, No. 1, 011004, (2017).
  • Muramatsu, M., Yashiro, K., Kawada, T. and Terada, K., "Numerical simulations of non-stationary distributions of electrochemical potentials in SOFC", Engineering Computations, Vol. 34, No. 6, pp. 1956-1988, (2017).
  • Muramatsu, M., Terada, K., Kawada, T., Yashiro, K., Takahashi, K. and Takase, S., "Characterization of Time-varying Macroscopic Electro-chemo-mechanical Behavior of SOFC Subjected to Ni-sintering in Cermet Microstructures", Computational Mechanics, Vol. 56, No. 4, pp. 653-676, (2015).

Ferroelastic phase transformation of LSCF based on phase-field model

In order to predict the formation of ferroelastic phases in crystal grains of La0.6Sr0.4Co0.2Fe0.8O3-δ (LSCF), which is a common material used for solid oxide fuel cells (SOFCs), we propose an analysis method based on a phase-field model. The phase-field model equipped with the elastic energy is introduced to realize the ferroelastic phase formation in a crystal grain. The finite element method (FEM) is employed to solve the phase transformation, and strain distributions are also calculated by FEM. On the basis of the developed analysis method, some numerical examples of analysis are performed to reproduce the deformation-induced nucleation and growth of ferroelastic phases of LSCF. The microstructures obtained from the simulations are varied in accordance with the initial microstructure and their tendencies are discussed. These microstructures are reproduced by the proposed analysis method based on finite element method, which enables us to evaluate the deformation field in terms of changes of shape and stress.

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example graphic example graphic Keywords:
  • Ferroelasticity
  • Microstructure Formation
  • Phase-field Model
  • Multiscale Analysis
References:
  • Muramatsu, M., Yashiro, K., Kawada, T. and Terada, K., "Simulation of Ferroelastic Phase Formation Using Phase-field Model", International Journal of Mechanical Sciences, [Accepted].
  • Muramatsu, M., Kawada, T. and Terada, T., "A Simulation of Ferroelastic Phase Formation by Using Phase Field Model", Key Engineering Materials, Vol. 725, pp 208-213, (2017).

Development of CAE Method Using Physical Simulation by Artificial Intelligence

We aim to develop a high-speed CAE system of microstructure of materials by employing artificial intelligence (AI) to investigate the suitable microstructures for specific macroscopic properties, and establish reinforcement guidelines for various devices.

Keywords:
  • Machine Learning
  • Microstructure

Multiphysics Formulation of Ferroelectric Materials Based on Thermodynamics and Continuum Mechanics

We are working on constitutive modeling of multiphysics of materials. Especially, the focus is placed on the ferroelectric materials.

Keywords:
  • Thermodynamics
  • Ferroelectricity