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Inverse identification of constitutive model parameters in FE-based SPS simulation
A numerical model of the SPS process requires the solution of the involved multi-physics partial differential equations with mixed boundary conditions. For a good predictive numerical model, the material model plays a pivotal role and some constitutive laws, e.g., Olevsky’s and Abouf’s models, are already available in the literature; however, these existing models are lacking a systematic approach for their parameter identification with experimental validation. In this project, we would
like to resolve this issue by utilizing an efficient and fully coupled electro-thermo-mechanical FEM model in the commercial package COMSOL Multiphysics.
Keywords: Mechanical engineering, constitutive modelling, finite element (FE) analysis, spark plasma sintering (SPS), material parameter identification.
In this project, we will implement an inverse identification framework to identify the material parameters for the sintering model by using a fully coupled electro-thermo-mechanical FEM model of SPS. The student also needs to develop a framework that can be run in parallel on the ETH Euler cluster to reduce the computational cost. By the completion of this student project, it is expected to determine a set of optimized parameters for SPS constitutive modeling that can increase the overall modeling accuracy and predict the thermo-mechanical aspects of the process with minimum errors.
In this project, we will implement an inverse identification framework to identify the material parameters for the sintering model by using a fully coupled electro-thermo-mechanical FEM model of SPS. The student also needs to develop a framework that can be run in parallel on the ETH Euler cluster to reduce the computational cost. By the completion of this student project, it is expected to determine a set of optimized parameters for SPS constitutive modeling that can increase the overall modeling accuracy and predict the thermo-mechanical aspects of the process with minimum errors.
In this project, our aim is to implement the inverse identification approach for the sintering model to identify the material parameters in COMSOL for SPS. In summary, the following points are to be achieved:
• Development of a fully coupled FEM model on COMSOL
• Validation of FEM data with experiments at AMLZ
• Determination of constitutive material parameters
• Development of an automated identification framework to run in parallel
In this project, our aim is to implement the inverse identification approach for the sintering model to identify the material parameters in COMSOL for SPS. In summary, the following points are to be achieved: • Development of a fully coupled FEM model on COMSOL • Validation of FEM data with experiments at AMLZ • Determination of constitutive material parameters • Development of an automated identification framework to run in parallel