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CBET-EPSRC: Enhancing the CSMHyK fluid dynamics calculations via the inclusion of a stochastic model of hydrate nucleation, agglomeration and growth

CBET-EPSRC：通过包含水合物成核、团聚和生长的随机模型来增强 CSMHyK 流体动力学计算

基本信息

批准号：
2015201
负责人：
Carolyn Koh
金额：
$ 37.98万
依托单位：
Colorado School of Mines
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2020
资助国家：
美国
起止时间：
2020-02-15 至 2024-01-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2015201&HistoricalAwards=false
关键词：
CBET EPSRC Enhancing CSMHyK fluid

项目摘要

The abundance of natural gas hydrate deposits across the world could provide abundant energy resources for the future. Natural gas hydrates are solid structures formed by water and gas that can block oil & gas pipelines, which can lead to pipeline ruptures, causing spills and environmental disasters, production interruptions, and even loss of life. The ability to predict gas hydrate formation and fluid dynamics based on molecular-level models has the potential to revolutionize the strategies used for gas hydrate control in oil and gas pipelines, as well as other gas hydrate energy applications. The predictive capability of gas hydrate fluid dynamics models is currently lacking due to the inability to fundamentally model the timescales for hydrate formation. The principle aim of the project is to develop a kinetic molecular model to predict gas hydrate formation times based on a synergistic experimental and molecular modeling campaign, leading to the ability to predict quantitatively gas hydrate formation in pipelines. The project is also focused on inclusion of under-represented minority students in STEM disciplines, via outreach activities that target students at all stages of development, industry engagement, and state-of-the-art web-based materials.The goal of the project is to quantify the rate-limiting mechanisms in gas hydrate formation to provide a predictive fluid dynamics model for gas hydrate formation. Identification of which mechanisms of hydrate formation (i.e. nucleation, growth, agglomeration, adhesion) is rate-limiting under different scenarios remains unknown, and yet must be overcome in order to have a predictive fluid dynamics model. This knowledge gap will be filled by the four main aims of the project: (1) obtain free energy barriers representative of gas hydrate growth, agglomeration and adhesion; (2) assess the reliability of (1) with in-situ micromechanical force and film growth measurements; (3) develop a computationally efficient stochastic kinetic Monte Carlo model that incorporates information from (1) and (2); (4) incorporate the outcomes from (3) into the transient fluid dynamics model and validate this predictive stochastic model against flow-loop experiments. This approach will provide a potential game-changing improvement to the fluid dynamics simulation model and molecular-based predictions of hydrate formation in pipelines. This research was funded under the NSF Engineering – UKRI Engineering and Physical Sciences Research Council opportunity NSF 20-510.” Co-PIs included Alberto Striolo and Michail Stamatakis at the University College of London.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

世界各地丰富的天然气水合物矿藏可以为未来提供丰富的能源资源。天然气水合物是由水和气体形成的固体结构，可以堵塞油气管道，从而导致管道破裂，造成泄漏和环境灾难，生产中断，甚至生命损失。基于分子水平模型预测气体水合物形成和流体动力学的能力有可能彻底改变用于石油和天然气管道中的气体水合物控制以及其他气体水合物能源应用的策略。由于无法从根本上模拟水合物形成的时间尺度，目前缺乏天然气水合物流体动力学模型的预测能力。该项目的主要目标是开发一种动力学分子模型，以预测基于协同实验和分子模拟活动的天然气水合物形成时间，从而能够定量预测管道中天然气水合物的形成。该项目还通过针对处于各个发展阶段的学生的外展活动、行业参与和最先进的网络材料，重点关注在STEM学科中代表性不足的少数民族学生。该项目的目标是量化天然气水合物形成的限速机制，为天然气水合物形成提供预测性流体动力学模型。在不同的情况下，水合物形成的机制（即成核，生长，凝聚，粘附）是限速的识别仍然是未知的，但必须克服，以便有一个预测的流体动力学模型。该项目的四个主要目标将填补这一知识空白：（1）获得代表天然气水合物生长、凝聚和粘附的自由能势垒;（2）通过原位微机械力和膜生长测量评估（1）的可靠性;（3）开发一个计算效率高的随机动力学蒙特卡罗模型，其中包括（1）和（2）的信息;（4）将（3）的结果结合到瞬态流体动力学模型中，并针对流动回路实验验证该预测随机模型。这种方法将为流体动力学模拟模型和基于分子的管道中水合物形成预测提供潜在的改变游戏规则的改进。这项研究是由NSF工程- UKRI工程和物理科学研究理事会机会NSF 20-510资助的。” 合作PI包括阿尔贝托Striolo和迈克尔Stamatakis在伦敦大学学院。这个奖项反映了NSF的法定使命，并已被认为是值得通过评估使用基金会的知识价值和更广泛的影响审查标准的支持。