Sequential particle filter estimation of a time-dependent heat transfer coefficient in a multidimensional nonlinear inverse heat conduction problem

In the applied mathematical modelling of heat transfer systems, coefficient (HTC) is one most important parameters. This paper proposes a combination Method Fundamental Solutions (MFS) with particle filter Sequential Importance Resampling (PF-SIR) to estimate time-dependent HTC in two-dimensional transient inverse conduction problems from non-standard boundary integral measurements. These measurements ensure unique solvability identification problem. Numerical results show high performance on several test cases both linear and nonlinear Robin conditions, supporting synergy between MFS simulation-based sequential analysis methods.