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Multiscale Equation-Oriented Optimization Decreases the Carbon Intensity of Shale Gas to Liquid Fuel Processes
Kanishka Ghosh1, Santiago D Salas2, Alejandro Garciadiego1
1Department of Chemical and Biomolecular Engineering, University of Notre Dame, Notre Dame, Indiana 46556, United States.
This study introduces an equation-oriented modeling framework for shale gas processing. It optimizes liquid hydrocarbon production and reduces emissions by over 35%, aiding a sustainable energy transition.
Area of Science:
- Chemical Engineering
- Energy Systems Analysis
- Sustainable Technology
Background:
- Shale gas is a key U.S. energy resource with potential for sustainable applications.
- Current process design lacks efficient integration of microkinetic details and life-cycle analysis.
- Transitioning to a decarbonized economy requires innovative energy solutions.
Purpose of the Study:
- To develop an equation-oriented (EO) multiscale modeling framework for shale gas process design.
- To integrate microkinetic detail using reduced-order kinetic (ROK) models within the IDAES-PSE platform.
- To optimize shale gas conversion for minimizing selling price and process emissions simultaneously.
Main Methods:
- Developed an equation-oriented (EO) multiscale modeling framework using IDAES-PSE.
- Incorporated microkinetic detail via reduced-order kinetic (ROK) models.
- Employed multiobjective optimization with heat integration and life-cycle analysis, including a CO2 tax.
Main Results:
- Achieved over 35% reduction in greenhouse gas emissions per MJ of fuel compared to literature.
- Attained 87% carbon efficiency in shale gas conversion.
- Demonstrated optimal process design insensitivity to CO2 tax rate variations and enabled fast sensitivity analysis for shale gas composition.
Conclusions:
- The open-source EO framework facilitates fast, scalable, and reproducible analysis for sustainable energy technologies.
- This approach effectively minimizes both production costs and environmental impact.
- The methodology is adaptable for optimizing various shale gas utilization pathways and beyond.
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