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CFD Modelling and Experimental Validation of Emulsification Processes

乳化过程的 CFD 建模和实验验证

基本信息

批准号：
1918781
负责人：
金额：
--
依托单位：
University of Manchester
依托单位国家：
英国
项目类别：
Studentship
财政年份：
2017
资助国家：
英国
起止时间：
2017 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=studentship-1918781
关键词：
CFD Modelling Experimental Validation Emulsification

项目摘要

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.

曼彻斯特大学和联合利华之间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）模拟和通过实验方法的模拟验证相结合来研究搅拌罐内的混合。水包油乳液在消费品中普遍存在。乳化液存在于日常消费品中，如甜味剂和冰淇淋。乳液通常是剪切稀化的非牛顿液体。乳状液内部的油滴尺寸分布对乳状液的稳定性和粘度有显著影响。因此，预测这些液滴尺寸分布的能力是高度期望的。许多涉及水包油乳液的消费品是在搅拌罐内生产的，在搅拌罐中将成分混合以形成乳液。乳状液内部的油滴大小是混合时间、湍流涡流耗散率、所用搅拌槽类型和其他关键变量的函数。项目要求是使用计算流体动力学对搅拌槽内形成的水包油乳状液进行模拟，并提供油滴尺寸分布的预测。该项目的一个关键部分将是根据实验数据验证CFD预测，其中数据将来自功率测量和电气层析成像方法。成功的候选人将承担CFD模拟和实验工作。计算流体动力学模拟将是多阶段的，涉及人口平衡模型加上分裂和合并内核。计算流体动力学和实验方法已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的油滴尺寸分布。学生将受益于承担工业相关的博士学位，由联合利华，一家领先的消费品公司的支持。学生将得到学术和工业顾问的密切支持。积极鼓励持续的专业发展，例如绘制迈向特许工程师（CEng）地位或同等地位的进度。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。