Predicticting performance of carbon capture in intensified rotating packed beds using CFD

使用 CFD 预测强化旋转填充床中的碳捕获性能

• 批准号: 2883569
• 金额: --
• 依托单位: University of Sheffield
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2883569
• 关键词: Predicticting; performance; carbon; capture; intensified

Carbon capture is considered the only technology able to decarbonise thehard-to-abate industries. Many of these industries utilise legacy sites with littlespace for large new unit operations required in conventional carbon capture.Rotating packed beds (RPB) look to solve this problem by intensifying carboncapture and reducing the footprint required by up to ten times, while alsosignificantly decreasing the capital cost of these units. When combined withproprietary solvents, it is believed the cost of capture can be reduced to$30/tonne CO2 in some cases, helping to enable the rapid uptake of carboncapture and progression towards net zero.RPB is a novel technology that utilises the principles of process intensificationto enhance the performance of mass transfer processes between fluids. Giventhe application of RPB to the field of CO2 capture is relatively new, there isuncertainty regarding the impact of different process variables on theperformance of the RPB that would otherwise require a significant amount ofpractical experimentation to investigate. Computational fluid dynamics canenable the process to be accurately modelled, allowing for quick andinexpensive prediction of performance under various conditions.In this project a rotating packed bed absorber will be modelled in AnsysFLUENT, with validation of the model's outputs through use of the 1 tonnes ofCO2 per day (TPD) pilot-scale rotating packed bed absorber at the University ofSheffield's Translational Energy Research Centre. Initial research will involveinvestigating the impact of operational conditions and physical properties ofthe solvent on capture performance. As the project continues, the scope willwiden to include sensitivity analysis of design parameters and the impact ofscaling the RPB absorber on the existing project outputs and learnings.Additionally, further rotating unit operations could also be investigated.This project will utilise and develop your knowledge surrounding CFDmodelling, mass and heat transfer, reaction kinetics and chemical equilibria.You will work closely with Carbon Clean, a global leader in the development ofcarbon capture technology and pioneers in the use of RPB for industrialdecarbonisation. Your findings could directly impact the design and operationof commercial working carbon capture facilities, supporting the pathway to netzero

碳捕获被认为是唯一能够使难以减少的工业脱碳的技术。这些行业中的许多都利用传统的碳捕获所需的大型新单元操作的旧场地，空间很小。旋转填料床（RPB）希望通过加强碳捕获并将所需的足迹减少多达十倍来解决这个问题，同时还显着降低这些单元的资本成本。当与专有溶剂结合使用时，据信在某些情况下捕获成本可以降低到30美元/吨CO2，有助于实现碳捕获的快速吸收和向净零的进展。RPB是一种利用过程强化原理来提高流体之间传质过程性能的新型技术。考虑到RPB在CO2捕集领域的应用相对较新，因此不确定不同工艺变量对RPB性能的影响，否则需要大量的实际实验来研究。计算流体动力学可以使该过程被准确地建模，允许快速和廉价的预测性能在各种条件下，在这个项目中，一个旋转填充床吸收器将在AnsysFLUENT建模，与验证模型的输出，通过使用1吨二氧化碳每天（TPD）的试点规模旋转填充床吸收器在谢菲尔德大学的转化能源研究中心。初步研究将涉及调查的影响，操作条件和物理性质的溶剂上的捕获性能。随着项目的继续，范围将扩大到包括设计参数的敏感性分析以及RPB吸收器缩放对现有项目输出和学习的影响。此外，还可以研究进一步的旋转单元操作。该项目将利用和发展您在CFD建模，传质和传热，反应动力学和化学平衡方面的知识。您将与Carbon Clean密切合作，碳捕获技术开发的全球领导者，以及将RPB用于工业脱碳的先驱者。您的发现可能会直接影响商业工作的碳捕获设施的设计和运营，支持通往净零的途径