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 idealised 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 fivefold 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.

开发了一种热物理模型，该模型可以预测两种木质素混合物（黑液和木质素磺酸盐）在水热条件下质量分数高达 50% 的性质。包括与经典热力学模型相关的不确定性量化框架，以解释原材料的极端可变性。理想化的流动模拟验证了该模型，其中热压缩水与冷的木质素水流在 T 型反应器配置中混合。不确定性量化程序确定密度和热容量不确定性显着影响停留时间，粘度不确定性主要影响混合。与纯水混合相比，黑液和木质素磺酸盐混合物的微混合时间分别高出五倍和十倍。由热物理模型引起的所有模拟量的不确定性通过增加流速而降低。该研究预测了不同热物理条件下的化学反应器行为及其在置信区间方面的最终影响。