(698b) Integrated Process and Solvent Design of Physical CO2 Absorption Using the SAFT-? Mie Equation of State and Hierarchical Optimisation | AIChE

(698b) Integrated Process and Solvent Design of Physical CO2 Absorption Using the SAFT-? Mie Equation of State and Hierarchical Optimisation


Burger, J. - Presenter, University of Kaiserslautern
Papaioannou, V., Imperial College London
Galindo, A., Imperial College London
Jackson, G., Imperial College London
Adjiman, C. S., Imperial College London

During the design of new processes, molecular-level decisions need to be made, such as choosing a solvent or other working fluid. Often, these decisions are made prior to the design of the process on the basis of experience, heuristic rules, or a few guiding experiments. The choices of solvents or other additives are, however, closely linked to decisions of process operation and therefore influence the overall performance. Thus, an integration of process and solvent design is necessary to identify an optimal process design.

In our work, discrete decisions on the molecular structure of the solvent to be used for high-pressure separation are integrated into process optimisation. This integration enables simultaneous optimisation of the process and the solvent structure. The physical properties required by the process model are calculated by a molecular based equation of state that explicitly considers intermolecular interactions. For the first time, a group contribution version of SAFT (SAFT-γ Mie [1]) is used in process and solvent design. Due to its firm physical foundation, the property model needs only few parameters to describe the thermodynamic properties accurately over a wide range of pressures and temperatures for a large number of solvents.

To overcome the complexity of the resulting MINLP problem of integrated process and solvent design, a novel hierarchical optimisation approach is proposed: in a first step, a multi-objective optimisation is carried out with a simplified process model developed here to reduce the space of solvent candidates. It is shown that the simplified model provides a reliable assessment of the best performance that can be achieved in each unit operation and is computationally cheap and robust. In a second step, an optimisation in the reduced solvent space is carried out using the full process model. The Pareto optimal set obtained in the first step serves as initial guesses to improve convergence of the design problem.

The approach is applied to a novel high pressure physical absorption process to remove CO2 from natural gas. A group of poly ethers are identified as optimal solvents, with a performance predicted to be superior to commonly used alternatives such as dimethyl ethers of polyethylene glycol. This provides a useful focus for future experimental studies.


[1] C. Avendano, T. Lafitte, C.S. Adjiman, A. Galindo, E.A. Muller, G. Jackson. SAFT-γ Force Field for the Simulation of Molecular Fluids: 2. Coarse-Grained Models of Greenhouse Gases, Refrigerants, and Long Alkanes. J. Phys. Chem. B (117) p. 2717-2733, 2013


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