Performance Analysis of Solvent-Based Post-Combustion CO2 Capture Process Employing Smart Techniques

Global warming is a very concerning mater, which needs serious attention and the development of the technologies to decrease the rate of CO2 concentration increase. In this project, a solvent-based post-combustion CO2 capture process is evaluated through the development of smart models (e.g., ML) and optimization techniques (e.g., PSO). The data for the smart model development are collected from the literature and the relevant industry. Also, the capability of several solvents to efficiently capture CO2 is examined. The process model considers the most vital operating conditions and the dynamic nature of the process. The model outputs are utilized to develop a sophisticated optimization strategy to determine the most optimal operating conditions of the process. The project offers the operating conditions that result in the efficient process performance in terms of cost, energy, and CO2 emission. Moreover, the research finding can be applied to the relevant process industry.

Faculty Supervisor:

Sohrab Zendehboudi

Student:

Partner:

Energy, Matter & Environmental (EM&E) Consultants Inc

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

Memorial University of Newfoundland

Program: