The Centre in Advanced Fluid Engineering for Digital Manufacturing (CAFE4DM)

数字化制造先进流体工程中心 (CAFE4DM)

• 批准号: EP/R00482X/1
• 负责人: Christopher Hardacre
• 金额: $ 407.47万
• 依托单位: University of Manchester
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2017
• 资助国家: 英国
• 起止时间: 2017 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FR00482X%2F1
• 关键词: Centre; Advanced; Fluid; Engineering; Digital

This 5 year project aims to address the challenges in understanding, creating and scaling up manufacturing processes for formulated products with particular reference to those in fast moving consumer goods (home/personal care and food products). The main objective is to develop a new modelling approach which will be combined with experimental measurements of the liquid properties to describe these complex fluids and enable a significant reduction in the conventional physical experimentation required to develop new formulations. The methodologies developed will provide a detailed understanding of the behaviour of these liquids under process conditions which will facilitate the decision making process and accelerate the introduction of new, innovative products to the market optimised to deliver benefits to consumers, e.g. shiny hair or mouthfeel for ice cream. The project brings together a multi-disciplinary team from the University of Manchester, the University of Cambridge and Unilever who are a global leader in the research, process design and manufacture of formulated products. The project is also supported by Process Systems Enterprise Ltd.. A major outcome of the project will be a demonstrator of the Industry 4.0 concept which will enable smart factories to be realised in the process sector and thus allow the UK to remain at the forefront of manufacturing in this field.

这个为期 5 年的项目旨在解决理解、创建和扩大配方产品制造工艺方面的挑战，特别是快速消费品（家庭/个人护理和食品）中的制造工艺。主要目标是开发一种新的建模方法，该方法将与液体特性的实验测量相结合，以描述这些复杂的流体，并显着减少开发新配方所需的传统物理实验。开发的方法将提供对这些液体在工艺条件下的行为的详细了解，这将促进决策过程并加速将新的创新产品引入市场，并优化为消费者带来利益，例如闪亮的头发或冰淇淋的口感。该项目汇集了来自曼彻斯特大学、剑桥大学和联合利华的多学科团队，他们在配方产品的研究、工艺设计和制造方面处于全球领先地位。该项目还得到了 Process Systems Enterprise Ltd. 的支持。该项目的一个主要成果将是工业 4.0 概念的示范，这将使智能工厂在流程领域得以实现，从而使英国保持在工业领域的前沿。该领域的制造。

项目成果

A general methodology for extracting and categorising flow patterns in turbulent stirred tank mixers based on 2-D network-of-zones (NoZ) model

基于二维区域网络 (NoZ) 模型的湍流搅拌罐混合器中流型的提取和分类的通用方法

• DOI: http://dx.10.1016/j.cherd.2023.05.022
• 发表时间: 2023
• 期刊: Chemical Engineering Research and Design
• 影响因子: 3.9
• 作者: Bai Y

Large-eddy simulation in a Sonolator high-pressure homogeniser

Sonolator 高压均质器中的大涡模拟

• DOI: http://dx.10.1016/j.ces.2019.115441
• 发表时间: 2020
• 期刊: Chemical Engineering Science
• 影响因子: 4.7
• 作者: Bagkeris I

A rapid method for flow pattern, mixing time estimation and turbulent dissipation rates in turbulent stirred mixers based on 2-D network-of-zones (NoZ) model

基于二维区域网络 (NoZ) 模型的湍流搅拌混合器中流型、混合时间估计和湍流耗散率的快速方法

• DOI: http://dx.10.1016/j.ces.2023.119577
• 发表时间: 2024
• 期刊: Chemical Engineering Science
• 影响因子: 4.7
• 作者: Bai Y

The Relationship Between Wormlike Micelle Scission Free Energy and Micellar Composition: The Case of Sodium Laurylethersulphate and Cocamidopropyl Betaine

蠕虫状胶束断裂自由能与胶束组成的关系——以十二烷基醚硫酸钠和椰油酰胺丙基甜菜碱为例

• DOI: http://dx.10.26434/chemrxiv.11734635
• 发表时间: 2020
• 作者: Carbone P

Model stacking to improve prediction and variable importance robustness for soft sensor development

模型堆叠可提高软传感器开发的预测和变量重要性鲁棒性

• DOI: 10.1016/j.dche.2022.100034
• 发表时间: 2022-05-01
• 期刊: Digital Chemical Engineering
• 作者: M. Barton;B. Lennox
• 通讯作者: B. Lennox