Reconstruction by data assimilation of the inner temperature field from outer measurements in a thick pipe

TL;DR

This paper presents a data assimilation method combining simulations and numerical techniques to accurately reconstruct the inner temperature field of a thick pipe from outer measurements, crucial for pipe aging management.

Contribution

It introduces a novel approach integrating impulse response and data assimilation for precise temperature reconstruction in thick pipes.

Findings

Reconstruction accuracy is less than 0.5% of temperature values.

Method effectively handles extreme thermal transients.

Demonstrated on scenarios with thermal shocks.

Abstract

The detailed knowledge of the inner skin temperature behavior is very important to evaluate and manage the aging of large pipes in cooling systems. We describe here a method to obtain this information as a function of outer skin temperature measurements, in space and time. This goal is achieved by mixing fine simulations and numerical methods such as impulse response and data assimilation. Demonstration is done on loads representing extreme transient stratification or thermal shocks. From a numerical point of view, the results of the reconstruction are outstanding, with a mean accuracy of the order of less than a half percent of the temperature values of the thermal transient.