Investigation of Continuous-Flow Mixing of Non-Newtonian Fluids through Advanced Flow Visualization Techniques (e.g. Tomography and Ultrasonic Velocimetry) and Computational Fluid Dynamics

通过先进的流动可视化技术（例如断层扫描和超声波测速）和计算流体动力学研究非牛顿流体的连续流动混合

• 批准号: RGPIN-2014-03957
• 负责人: EinMozaffari, Farhad
• 金额: $ 1.46万
• 依托单位: Ryerson University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2017
• 资助国家: 加拿大
• 起止时间: 2017-01-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=638028
• 关键词: Investigation; Continuous; Flow; Mixing; Non

The mixing of non-Newtonian fluids plays a significant role in chemical, biochemical, food, polymer, pulp and paper, cosmetic, wastewater treatment, and pharmaceutical industries. Previous studies have focused on the mixing of non-Newtonian fluids in the batch mode and little information is available regarding the continuous-flow mixing of these complex fluids. Continuous-flow mixing is prevalent in most of chemical and allied process industries because it provides high production rates, improves process control, and saves operation time and labor costs. The studies conducted in our research lab show that the complex rheology of non-Newtonian fluids creates non-ideal flows (e.g. channeling, recirculation, and dead zone) that significantly affect the efficiency of continuous-flow mixers. A comprehensive literature review reveals that our current understanding and implementation of continuous mixing of non-Newtonian fluids is insufficient to ensure good mixing. The current design of continuous mixing of non-Newtonian fluids is based on limited published information, and trial and error method. In fact, this issue has not been fully delineated yet and there is a clear need to explore this topic in more detail. Thus, our long term research program goal is to develop methodology and tools to design continuous mixing systems for fluids with complex rheology through advanced flow visualization techniques (e.g. tomography and ultrasonic velocimetry) and advanced computational fluid dynamics (CFD) methods. The work is of great importance to the chemical industry of Canada. Mixing is a critical unit operation and is not operating to its fullest potential. Failure to provide the necessary mixing may result in severe manufacturing problems ranging from costly corrections in the plant to complete failure of a process. The annual loss due to poor mixing is estimated at $10 billion in the North America chemical industry alone. The proposed experimental and modeling research program will improve our understanding of continuous mixing of non-Newtonian fluids and enable us to develop the reliable design criteria. Applying the findings of this study will improve variability reduction in the continuous mixing processes. This will lead to capital cost savings, chemical cost reduction, improved equipment design and selection, more reliable process monitoring and control, increased throughput for existing plant, improved quality of products, and more efficient use of power. Thus, the proposed research will contribute to the increased economic activity of the Canadian chemical industry, and will impact our society, quality of life, health and environment. It will also contribute to the education and training of highly qualified personnel (HQP) in the field of mixing technology, advanced flow visualization techniques, computational fluid dynamics, rheology, and dynamic modeling and identification.

非牛顿流体的混合在化工、生化、食品、聚合物、纸浆和造纸、化妆品、废水处理和制药工业中发挥着重要作用。以前的研究主要集中在间歇模式下非牛顿流体的混合，关于这些复杂流体的连续流动混合的信息很少。连续流混合在大多数化工及相关过程工业中普遍存在，因为它提供了高生产率，改善了过程控制，并节省了操作时间和人力成本。我们研究实验室进行的研究表明，非牛顿流体的复杂流变性会产生非理想流动(如沟槽、回流和死区)，从而显著影响连续流混合器的效率。全面的文献回顾表明，我们目前对非牛顿流体连续混合的理解和实施不足以确保良好的混合。目前非牛顿流体连续混合的设计是基于有限的已发表的信息和试错法。事实上，这一问题尚未得到充分说明，显然需要更详细地探讨这一问题。因此，我们的长期研究计划目标是开发方法和工具，通过先进的流动可视化技术(如层析成像和超声波测速仪)和先进的计算流体动力学(CFD)方法，为具有复杂流变性的流体设计连续混合系统。这项工作对加拿大的化学工业非常重要。混合是一项关键的单元操作，并未充分发挥其潜力。未能提供必要的混合可能会导致严重的制造问题，从工厂昂贵的修正到工艺的完全失败。仅在北美化学工业，由于混合不良而造成的年度损失估计就达100亿美元。建议的实验和模型研究计划将提高我们对非牛顿流体连续混合的理解，并使我们能够制定可靠的设计标准。应用这项研究的结果将改善连续混合过程中的变异性降低。这将节省资本成本，降低化工成本，改进设备设计和选择，更可靠的过程监测和控制，提高现有工厂的生产能力，提高产品质量，并更有效地利用电力。因此，拟议的研究将有助于加拿大化学工业经济活动的增加，并将影响我们的社会、生活质量、健康和环境。它还将有助于在混合技术、高级流动可视化技术、计算流体力学、流变学以及动态建模和识别领域的高素质人员(HQP)的教育和培训。