Exploration of process parameters for continuous hydrolysis of canola oil, camelina oil and algal oil
KAUST DepartmentClean Combustion Research Center
Mechanical Engineering Program
Physical Science and Engineering (PSE) Division
high-pressure combustion (HPC) Research Group
Permanent link to this recordhttp://hdl.handle.net/10754/562231
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AbstractThermal hydrolysis of triglycerides to form free fatty acid (FFA) is a well-established industry practice. Recently, this process has been employed as a first step in the production of biofuels from lipids. To that end, batch and continuous hydrolysis of various feedstocks has been examined at the laboratory scale. Canola, the primary feedstock in this paper, camelina and algal oils were converted to high quality FFA. For the different reaction temperatures, the continuous hydrolysis system was found to provide better yields than the laboratory batch system. In addition, CFD simulation with ANSYS-CFX was used to model the performance and reactant/product separation in the continuous, counter-flow reactor. The effects of reaction temperature, water-to-oil ratio (ratio of water and oil volumetric inflow rate), and preheating of the reactants were examined experimentally. Optimization of these parameters has resulted in an improved, continuous process with high mass yields (89-93%, for reactor temperature of 260°C and water-to-oil ratio of 4:1) and energy efficiency (76%, for reactor temperature of 250°C and water-to-oil ratio of 2:1). Based on the product quality and energy efficiency considerations, the reactor temperature of 260°C and water-to-oil ratio of 4:1 have provided the optimal condition for the lab scale continuous hydrolysis reaction. © 2012 Elsevier B.V.
CitationWang, W.-C., Turner, T. L., Stikeleather, L. F., & Roberts, W. L. (2012). Exploration of process parameters for continuous hydrolysis of canola oil, camelina oil and algal oil. Chemical Engineering and Processing: Process Intensification, 57-58, 51–58. doi:10.1016/j.cep.2012.04.001
SponsorsThis material is based upon work supported by the National Science Foundation under Grant No. 0937721. The authors also express their gratitude to Mr. Phil Harris for his technical assistance, to Dr. Lisa Dean for her lipid analysis and to Dr. Fei Zheng for his helpful suggestions regarding ANSYS-CFX.