Multiscale modelling of biorefineries

Current fuel ethanol research deals with process engineering trends for improving the efficiency of bioethanol production. This thesis is devoted to modelling and optimisation of the lignocellulosic to bioethanol conversion process with a special emphasis on pretreatment and enzymatic hydrolysis units. The first part of the thesis is devoted to the lignocellulosic biomass pretreatment process. A multiscale model for a pretreatment process is developed. This considers both the chemical and physical natures of the process. A new mechanism for hydrolysis of hemicellulose is proposed in which the reactivity is function of position in the hemicellulose chain and all the bonds with same position undergo breakage at the same time. A method to find the optimum chip size for pretreatment has been developed. We show that with the proposed optimization method, an average saving equivalent to a 5% improvement in the yield of biomass to ethanol conversion process can be achieved. In the second part of this thesis a new approach to consider the evolution of cellulose chain length during the enzymatic hydrolysis by endo- and exoglucanase is developed. This employs a population balance approach. Having established the models for the action of endo- and exoglucanase, a universal model for cellulose hydrolysis at the biomass surface and inside the particle is developed. An experimental procedure to locate unknown parameters in the holistic model is proposed. The third part of this thesis integrates the models developed into a rigorous mass and energy balances of typical biorefinery. It was found that, most of the energy input is for pretreatment and distillation. Two process modifications are considered capable of reducing the energy requirement for pretreatment and distillation by almost 50%. It is shown that with process optimization and some alternative design it is possible to save 21% of plant energy requirement. Finally, the novel features and advantages of the work are discussed, as are potential areas for future research.EThOS - Electronic Theses Online ServiceGBUnited Kingdo