A Caltech Library Service

High-resolution simulation of pattern formation and coarsening dynamics in 3D convective mixing

Fu, Xiaojing (2015) High-resolution simulation of pattern formation and coarsening dynamics in 3D convective mixing. Masters thesis, Massachusetts Institute of Technology.

[img] PDF - Published Version
See Usage Policy.


Use this Persistent URL to link to this item:


Geologic CO₂ sequestration is considered a promising tool to reduce anthropogenic CO₂ emissions while allowing continued use of fossil fuels for the current time. The process entails capturing CO₂ at point sources such as coal-fired power plants, and injecting it in its supercritical state into deep saline aquifers for long-term storage. Upon injection, CO₂ partially dissolves in groundwater to form an aqueous solution that is denser than groundwater. The local increase in density triggers a gravitational instability at the boundary layer that further develops into columnar CO₂-rich plumes that sink away. This mechanism, also known as convective mixing, greatly accelerates the dissolution rate of CO₂ into water and provides secure storage of CO₂ underground. Understanding convective mixing in the context of CO₂ sequestration is essential for the design of injection and monitoring strategies that prevent leakage of CO₂ back into the atmosphere. While current studies have elucidated various aspects of this phenomenon in 2D, little is known about this process in 3D. In this thesis we investigate the pattern-formation aspects of convective mixing during geological CO₂ sequestration by means of high-resolution three-dimensional simulation. We find that the CO₂ concentration field self-organizes as a cellular network structure in the diffusive boundary layer right beneath the top boundary. By studying the statistics of the cellular network, we identify various regimes of finger coarsening over time, the existence of a nonequilibrium stationary state, and an universal scaling of 3D convective mixing. We explore the correlation between the observed network pattern and the 3D flow structure predicted by hydrodynamics stability theory.

Item Type:Thesis (Masters)
Related URLs:
URLURL TypeDescription
Fu, Xiaojing0000-0001-7120-704X
Additional Information:© 2015 Massachusetts Institute of Technology. Submitted to the School of Engineering on June, 2015, in partial fulfillment of the requirements for the degree of Master of Science in Computation Design and Optimization. Thesis Supervisor: Ruben Juanes. Title: Associate Professor of Civil and Environmental Engineering. I would like to express my deepest gratitude to my research advisor, Ruben Juanes, for your insightful teaching, encouragement, wisdom and patience; To my dearest collaborator and mentor Luis Cueto-Felgueroso, I am deeply grateful for your unreserved sharing of knowledge, your wisdom, patience and friendship; I owe my achievement to the full-hearted support from the members of the Juanes Research Group and the Parsons laboratory, with you I share great memories; To the administrative staff at the CDO program, Barbara Lechner, thank you for being so strong for yourself and so supportive to the CDO students during your years with us; we miss you deeply; and, last but not least, to my parents Ming Fu and Li Wan, and my partner Ryan Lewis for your love, encouragement and companion. I am so blessed to have you in my life.
Record Number:CaltechAUTHORS:20200902-145201396
Persistent URL:
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:105227
Deposited By: Tony Diaz
Deposited On:09 Sep 2020 00:15
Last Modified:09 Sep 2020 00:15

Repository Staff Only: item control page