Metallic open cell foams have multiple applications in industry, e.g. as catalyst supports in chemical processes. Their regular or heterogeneous microscopic structure determines the macroscopic thermodynamic and chemical properties. We present an object-oriented python library that generates state space models for simulation and control from the microscopic foam data, which can be imported from the image processing tool iMorph. The foam topology and the 3D geometric data are the basis for discrete modeling of the balance laws using the cell method. While the material structure imposes a primal chain complex to define discrete thermodynamic driving forces, the internal energy balance is evaluated on a second chain complex, which is constructed by topological duality. The heat exchange between the solid and the fluid phase is described based on the available surface data. We illustrate in detail the construction of the dual chain complexes, and we show how the structured discrete model directly maps to the software objects of the python code. As a test case, we present simulation results for a foam with a Kelvin cell structure, and compare them to a surrogate finite element model with homogeneous parameters.     «

Metallic open cell foams have multiple applications in industry, e.g. as catalyst supports in chemical processes. Their regular or heterogeneous microscopic structure determines the macroscopic thermodynamic and chemical properties. We present an object-oriented python library that generates state space models for simulation and control from the microscopic foam data, which can be imported from the image processing tool iMorph. The foam topology and the 3D geometric data are the basis for discre...     »