Rigorous and Data-Driven Simulation of the Plant-Wide Bio-Jet Fuel Production Processes from Biomass Liquefaction

In order to mitigate the CO2 emission caused by the aviation industry, the development of bio-jet fuels has received great attentions recently. In this 3-year project, two biomass liquefaction processes to produce bio-jet fuel will be investigated, which are the process through fast pyrolysis and hydrothermal liquefaction. Rigorous simulation and data-driven simulation will be performed to study these two processes. In the first year, the bio-jet fuel production process through fast pyrolysis of lignocellulosic biomass will be studied. And in the second year, the process through hydrothermal liquefaction of algae will be studied. There are several sub-processes included in both plant-wide processes, which are the main reaction section, upgrading section and hydrogen production and so on. In order to understand these processes at the plant-wide scale, the investigation will be started from rigorous steady-state simulation, and followed by optimization, dynamic simulation, heat integration and economical evaluation. Furthermore, the mechanisms for both reactions are complicated, and the product compositions are also very difficult to identify. This leads to the fact that the simplifications on the description of reaction kinetics are required. Hence, in the third year, the statistical and multivariate analysis will be firstly used to construct the relation between the reactant, reacting conditions and the product properties. And the artificial intelligence techniques will be adopted to build up the data-driven model, which may improve the prediction of kinetic model. Lastly, the data-driven model and the rigorous model will be integrated into a hybrid data-rigorous simulation model. The proposed model is target to be able to predict those accurate and generalizable results for these two process routes. In summary, the contents covered in this three-year project are of great novelty. Through combination of rigorous simulation, statistical and multivariate analysis, and data-driven modeling, it is that this study can be served as a critical basis for the future, possible development of the related biomass techniques here in Taiwan.

Project ID:PB10901-0398
External Project ID:MOST108-2218-E182-009-MY3