CFD Modelling and Experimental Validation of Emulsification Processes

曼彻斯特大学和联合利华的这个令人兴奋的联合项目将通过预测计算流体动力学（CFD）模拟和实验方法的模拟验证相结合来研究搅拌槽内的混合。水包油乳液在消费品中随处可见。乳剂存在于除臭剂和冰淇淋等日常消费品中。乳剂是典型的剪切变薄的非牛顿液体。乳状液内部油滴的大小分布对乳状液的稳定性和粘度有重要影响。因此，预测这些液滴大小分布的能力是非常可取的。许多消费品都是在搅拌槽中生产油和水的乳液，在搅拌槽中，各种成分混合形成乳液。乳状液中的油滴大小是混合次数、湍流涡流耗散率、所用搅拌槽类型和其他关键变量的函数。该项目要求使用CFD模拟油在搅拌槽内形成的水乳液，并预测油滴的大小分布。该项目的一个关键部分将是根据实验数据验证CFD预测，实验数据将来自功率测量和电断层扫描方法。成功的候选人将承担CFD模拟和实验工作。CFD模拟将是多阶段的，包括种群平衡模型以及分裂和聚结核。CFD和实验方法已经成功地用于预测高压均质器和Silverson高剪切装置中的油粒度分布。因此，有信心这些模型可以推广到模拟搅拌槽内油滴的大小分布。该学生将受益于在联合利华（一家领先的消费品公司）的支持下攻读与工业相关的博士学位。学生将得到学术和行业顾问的密切支持。积极鼓励持续的专业发展，例如向特许工程师（CEng）身份或同等学历迈进。将有机会参加著名的会议（英国和海外），并在高影响因子期刊上发表新颖的作品。

This exciting joint project between the University of Manchester and Unilever will investigate mixing inside stirred tanks through a combination of predictive computational fluid dynamics (CFD) simulations, and simulation validation via experimental methods. Oil in water emulsions are ubiquitous in consumer products. Emulsions are found in everyday consumer goods such as deodorants and ice creams. The emulsions are typically shear thinning non-Newtonian liquids. Oil droplet size distributions inside emulsions has a significant effect on emulsion stability and as well as on viscosity. Therefore, the ability to predict these droplet size distributions is highly desirable. Many consumer goods involving oil in water emulsions are produced inside stirred tanks, where the ingredients are mixed to form an emulsion. The oil droplet sizes inside the emulsions are a function of mixing times, turbulent eddy dissipation rates, the type of stirred tank used, and other key variables. The project requirement is to use CFD to perform simulations of oil in water emulsions as they are formed inside stirred tanks, and provide predictions of the oil droplet size distributions. A key part of the project will be to validate the CFD predictions against experimental data, where the data will be from power measurements and electrical tomography methods. The successful candidate will undertake the CFD simulations and experimental work. The CFD simulations will be multiphase, involving population balance modelling coupled with breakup and coalescence kernels. CFD and experimental methods have been used previously with success to predict oil size distributions in high pressure homogenizers and Silverson high shear devices. Therefore, there is confidence that those models can be generalised to simulate oil droplet size distributions inside stirred tanks. The student will benefit by undertaking an industrially relevant PhD, supported by Unilever, a leading consumer goods company. The student will receive close support from the academic and the industrial advisers. Continuing professional development is actively encouraged, such as charting progress towards chartered engineer (CEng) status or equivalent. There will be opportunities to attend renowned conferences (UK and overseas), and publish novel work in high impact factor journals.