10.00
-
15.30
Porsgrunn, Room A-271 and Zoom
Nastaran Samani is defending her dissertation for the degree philosophiae doctor (PhD) at the University of South-Eastern Norway. 
The doctoral work has been carried out at the Faculty of Technology, Natural Sciences and Maritime Sciences.
You are invited to follow the trial lecture and the public defence.
Summary
Achieving efficient and sustainable energy production from biomass requires optimized reactor design, suitable operating conditions, and accurate process control. Biomass gasification is a promising technology for producing hydrogen-rich syngas and converting waste into renewable fuels, but its performance is highly sensitive to feedstock properties, gasifying agents, and multiphase flow dynamics.
This PhD thesis presents an integrated computational and experimental approach to simulate, validate, and optimize biomass gasification processes in entrained flow and bubbling fluidized bed reactors, addressing the inherent complexities and uncertainties in reactor performance.
The thesis initially develops advanced Eulerian–Lagrangian Computational Particle Fluid Dynamics (CPFD) models to capture hydrodynamics, reaction kinetics, and heat transfer with high fidelity. These models accurately predict syngas composition and reactor efficiency under varying conditions, including changes in temperature, steam-to-biomass ratio, and gasifying agents. Validation against laboratory-scale gasification experiments confirmed the reliability of the models. However, their high computational demand presents challenges for extensive optimization and large-scale industrial deployment.
To address this limitation, systematic optimization studies were conducted to identify the role of oxygen, steam, and CO₂ in enhancing hydrogen production and cold gas efficiency. Results demonstrated that CO₂–steam gasification increases hydrogen yield by 15–20% compared to conventional air gasification. Furthermore, co-gasification of sewage sludge digestate with wood powder was shown to significantly improve carbon conversion efficiency, stabilize reactor operation, and enhance phosphorus retention in ash, thereby linking energy production with sustainable waste management.
The research also establishes a comprehensive framework for process optimization and feedstock blending strategies, providing new insights into scaling up gasification technologies for industrial applications. In addition, the validated models extend the capabilities of simulation tools for predicting reactor performance and guiding the design of next-generation biomass-to-energy systems.
The findings of this work emphasize the importance of integrating high-fidelity computational modeling, experimental validation, and process optimization to maximize efficiency, enable hydrogen-rich syngas production, and support the transition to a low-emission energy system.