Development of an aqueous lignin mixture thermophysical model for hydrothermal liquefaction applications using uncertainty quantification tools

TL;DR

This study develops a thermophysical model for lignin mixtures under hydrothermal conditions, incorporating uncertainty quantification to predict reactor behavior and mixing dynamics with improved confidence.

Contribution

It introduces an uncertainty-aware thermophysical model for lignin mixtures, validated through flow simulation, highlighting key property uncertainties affecting reactor performance.

Findings

Density and heat capacity uncertainties impact residence time.

Viscosity uncertainty influences mixing efficiency.

Increasing flow rates reduces uncertainty in simulated outcomes.

Abstract

A thermophysical model is developed that can predict the properties of two lignin mixtures, black liquor and lignosulfonates, up to 50% mass fractions, at hydrothermal conditions. An uncertainty quantification framework linked with classic thermodynamical modelling was included to account for the extreme variability of the raw material. An idealized flow simulation verified the model, where hot compressed water mixes with a cold, aqueous lignin stream in a T-piece reactor configuration. The uncertainty quantification procedure determined that density and heat capacity uncertainty significantly influence residence time, and viscosity uncertainty mainly affects mixing. Micromixing time is five-fold and ten-fold higher for black liquor and lignosulfonates mixtures, respectively, compared to pure water mixing. The uncertainty in all simulated quantities of interest caused by the thermophysical model is reduced by increasing flow rates. This study predicted chemical reactor behaviour under varying thermophysical conditions and their final effect in terms of confidence intervals.