碳捕集和封存技术（CCS）是降低CO2排放的主要手段，其中管道输送CO2质量流量的精确测量是CCS应用中亟待解决的关键问题。在CCS条件下输送管道内CO2可以呈现单相气、单相液、气液两相、超临界等状态，并随工况不断变化，给精确测量CO2流量带来挑战。本项目针对动态CCS条件下管道输送CO2质量流量的在线测量方法开展研究，其研究成果将为碳贸易结算提供测量依据，并为CCS管道网络监控及泄漏检测提供手段。基于科氏力流量计，结合常规传感器所得数据，提出CO2质量流量在线测量的数据驱动模型；利用多物理场耦合模型对科氏力流量计传感机理进行研究，获得动态CCS条件下测量误差的产生原因和变化规律；建立实验监测系统研究动态CCS条件下CO2的热力学和流动特性；进一步，搭建CO2质量流量测量系统，通过在两相CO2、含杂质CO2、超临界CO2和动态工况下的实验研究，优化质量流量测量系统及数据驱动模型。

Carbon capture and storage (CCS) is a key technology to reduce CO2 emissions from industry. Accurate mass flow metering of CO2 is essential in the practical deployment of CCS. This project will study methods for on-line mass flow metering of CO2 in transportation pipelines under dynamic CCS conditions, the research outcome of which will provide reliable measurement data to enable effective carbon trading and facilitate the monitoring and control of CO2 in transportation networks including leakage detection. Data-driven modeling techniques will be applied to on-line mass flow measurement of CO2 using the data from a Coriolis flowmeter and other sensors. By optimizing the structure and parameters of the model, its accuracy and generalization performance will be improved. A multi-physical model will be built to investigate the sensing mechanism of the Coriolis flowmeter and the underlying reasons for the varying characteristics of the measurement error of CO2 mass flow rate under dynamic CCS conditions will be identified. In addition, thermophysical and flow characteristics of CO2 under dynamic CCS conditions will be analyzed using a propose-built monitoring system. Based on the above results, a CO2 mass flow metering system will be designed and implemented and its experimental investigations will be conducted under the conditions of two-phase CO2, CO2 with impurities and supercritical CO2 under dynamic process conditions, during which the CO2 mass flow metering system and the data-driven model will be optimized.