Parameter estimation of temperature dependent material parameters in the cooling process of TMCP steel plates

TL;DR

This paper develops a numerical method to estimate temperature-dependent material parameters in the cooling process of TMCP steel plates, crucial for controlling microstructure and mechanical properties.

Contribution

It introduces an inverse heat conduction problem approach to identify unknown material parameters without prior information.

Findings

Successfully estimates material parameters from temperature data.

Provides a numerical framework for thermophysical characterization.

Enhances control over steel microstructure during cooling.

Abstract

Accelerated cooling is a key technology in producing thermomechanically controlled processed (TMCP) steel plates. In a TMCP process hot plates are subjected to a strong cooling what results in a complex microstructure leading to increased strength and fracture toughness. The microstructure is strongly affected by the temperature evolution during the cooling process as well as residual stresses and flatness deformations. Therefore, the full control (quantification) of the temperature evolution is very important regarding plate design and processing. It can only be achieved by a thermophysical characterization of the material and the cooling system. In this paper, we focus on the thermophysical characterization of the material parameters. Mathematically, we consider a specific inverse heat conduction problem. The temperature evolution of a heated steel plate passing through the cooling device is modeled by a 1D nonlinear partial differential equation (PDE) with unknown temperature dependent material parameters, which describe the characteristics of the underlying material. We present a numerical approach to identify these material parameters up to some canonical ambiguity without any a priori information.