3700 O'Hara Street, Pittsburgh, PA 15261

Title: 

"Membrane Modeling for Post-Combustion Carbon Capture and Direct Ocean Capture 

 

 

ABSTRACT: 

  

The aim of this thesis is to use readily available carbon capture technology to further advance the carbon capture research field in order to mitigate global warming effects. Specifically, membranes have been deployed at a pilot scale for carbon capture from pre- and post-combustion carbon capture. This thesis organizes current computational models for post-combustion carbon capture and builds upon and applies these modeling approaches for novel carbon capture applications such as direct ocean carbon capture. First, a thorough literature review organizing membrane contactor models for post-combustion carbon capture 

was created to provide a rigorous comparison of state-of-the-art 1D, 2D and 3D models for post-combustion carbon capture membrane contactors. Using the information from the review, a study using hollow fiber membrane contactors for direct ocean carbon capture research was conducted consisting of experimental testing, 1D modeling of a hollow fiber membrane contactor, and finally a techno-economic analysis of a pilot scale system. The study discovered that while hollow fiber membrane contactors can be used to separate COfrom seawater, the technology needs to be further developed to become economically competitive. 

Finally, a flat sheet membrane model was developed that represents Membrane Technology Research’s (MTR’s) latest membrane currently undergoing pilot testing. This model accounts for channel size distributions that result from realistic manufacturing conditions. It was found that non-uniform channel heights affect the overall performance of a flat sheet membrane for gas separation. However, when comparing these non-uniform geometric conditions against a hollow fiber membrane for gas separation, both membrane configurations were equally affected and one should therefore chose a membrane configuration based on their individual advantages discussed throughout this thesis. 

 

 

 

Event Details

Please let us know if you require an accommodation in order to participate in this event. Accommodations may include live captioning, ASL interpreters, and/or captioned media and accessible documents from recorded events. At least 5 days in advance is recommended.

Riveroo2023 

Join Zoom Meeting: 

Link: https://pitt.zoom.us/j/91794642720 

Passcode: Riveroo2023 

Meeting ID: 917 9464 2720 

University of Pittsburgh Powered by the Localist Community Event Platform © All rights reserved