Sensitivity analysis of an unsteady char particle combustion

Ahmed Hassan, Taraneh Sayadi*, Vincent Le Chenadec, Antonio Attili

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Simulations of unsteady char particle combustion rely on various models that are necessary in order to correctly predict the governing flow and combustion processes. These models, in turn, rely on model parameters, which are determined by experiments or small scale simulations and contain a certain level of uncertainty. It is therefore, essential to correctly determine the sensitivities of quantities of interest measured using such simulations, with respect to the existing parameters. In this study, a discrete adjoint algorithm is employed to extract sensitivities of various quantities of interest with respect to physical and model parameters. This adjoint framework bears a great advantage in cases where a large input space is analyzed, since a single forward and backward sweep provides sensitivity information with respect to all parameters of interest. Sensitivities are extracted for relevant quantities of interest, such as burning rate and particle temperature, and are then compared as free stream composition changes from air to oxy atmosphere. The evolution of sensitivities in time is shown to be dependent on the selected quantity of interest. Model sensitivities with respect to heterogeneous reaction parameters (oxidation of carbon, in particular) are shown to be the highest, whereas the sensitivities with respect to free stream composition are shown to be significantly lower.

Original languageEnglish
Article number119738
JournalFuel
Volume287
Early online date2 Dec 2020
DOIs
Publication statusPublished - 1 Mar 2021

Keywords / Materials (for Non-textual outputs)

  • Computational fluid dynamics
  • Sensitivity analysis
  • Unsteady char burnout

Fingerprint

Dive into the research topics of 'Sensitivity analysis of an unsteady char particle combustion'. Together they form a unique fingerprint.

Cite this