Linking fluid flow to cleaning performance via tailored food-grade soils

通过定制的食品级污垢将流体流动与清洁性能联系起来

• 批准号: 2409810
• 金额: --
• 依托单位: University of Cambridge
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2020
• 资助国家: 英国
• 起止时间: 2020 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2409810
• 关键词: Linking; fluid; flow; cleaning; performance

Cleaning is a critically important operation in the food, pharmaceutical and other sectors. Many cleaning in place (CIP) systems employed in manufacturing industry rely on the flow of cleaning solutions or solvents to achieve removal of the soiling layer. It would be highly desirable to be able to predict the cleanability of an item of process equipment or a production line at the design stage, so that plant and CIP processes can be designed for efficient cleaning. The potential impact is significant: cleaning consumes large quantities of fresh, potable water as well as thermal energy and chemicals, all of which influence the financial and ecological sustainability of food manufacturing operations. Advances in computational fluid dynamics (CFD) methods mean that the flow behaviour can be estimated with good levels of accuracy for many of the geometries and flow configurations which arise in practice. The link to cleanability lies in the rheology of the deposit and how it responds to the forces imposed by the fluid both instantaneously and over time. This project brings together expertise in CFD (Prof. Cant) with rheology (Prof. Wilson) to develop methods for predicting the cleaning performance of a range of food types.

在食品、制药和其他部门，清洁是一项至关重要的操作。制造业中使用的许多就地清洗(CIP)系统依靠清洗液或溶剂的流动来实现污垢的去除。非常希望能够在设计阶段预测工艺设备或生产线的可清洁性，以便能够设计工厂和CIP工艺以进行有效的清洗。潜在的影响是巨大的：清洁会消耗大量的淡水、饮用水以及热能和化学品，所有这些都会影响食品制造业务的财务和生态可持续性。计算流体动力学(CFD)方法的进步意味着可以对实际中出现的许多几何形状和流动形态进行高精度的流动行为估计。与可清洁性的联系在于沉积物的流变性，以及它如何在瞬间和随着时间的推移对流体施加的力做出反应。这个项目将CFD(坎特教授)和流变学(威尔逊教授)的专业知识结合在一起，开发出预测一系列食品类型的清洁性能的方法。