Imperial College London


Faculty of EngineeringDepartment of Chemical Engineering








ACE ExtensionSouth Kensington Campus





Publication Type

3 results found

Gopinath S, Jackson G, Galindo A, Adjiman CSet al., 2016, Outer approximation algorithm with physical domain reduction for computer-aided molecular and separation process design, AICHE Journal, Vol: 62, Pages: 3484-3504, ISSN: 0001-1541

Integrated approaches to the design of separation systems based on computer-aided molecular and process design (CAMPD) can yield an optimal solvent structure and process conditions. The underlying design problem, however, is a challenging mixed integer nonlinear problem, prone to convergence failure as a result of the strong and nonlinear interactions between solvent and process. To facilitate the solution of this problem, a modified outer-approximation (OA) algorithm is proposed. Tests that remove infeasible regions from both the process and molecular domains are embedded within the OA framework. Four tests are developed to remove subdomains where constraints on phase behavior that are implicit in process models or explicit process (design) constraints are violated. The algorithm is applied to three case studies relating to the separation of methane and carbon dioxide at high pressure. The process model is highly nonlinear, and includes mass and energy balances as well as phase equilibrium relations and physical property models based on a group-contribution version of the statistical associating fluid theory (SAFT-γ Mie) and on the GC+ group contribution method for some pure component properties. A fully automated implementation of the proposed approach is found to converge successfully to a local solution in 30 problem instances. The results highlight the extent to which optimal solvent and process conditions are interrelated and dependent on process specifications and constraints. The robustness of the CAMPD algorithm makes it possible to adopt higher-fidelity nonlinear models in molecular and process design.

Journal article

Gopinath S, Galindo A, Jackson G, Adjiman CSet al., 2016, A feasibility-based algorithm for Computer Aided Molecular and Process Design of solvent-based separation systems, 26th European Symposium on Computer Aided Process Engineering (ESCAPE 26), Publisher: Elsevier, Pages: 73-78, ISSN: 1570-7946

Computer-aided molecular and product design (CAMPD) can in principle be used to find simultaneouslythe optimal conditions in separation processes and the structure of the optimal solvents.In many cases, however, the solution of CAMPD problems is challenging. In this paper, we proposea solution approach for the CAMPD of solvent-based separation systems in which implicitconstraints on phase behaviour in process models are used to test the feasibility of the processand solvent domains. The tests not only eliminate infeasible molecules from the search space butalso infeasible combinations of solvent molecules and process conditions. The tests also providebounds for the optimization of the process model (primal problem) for each solvent, facilitatingnumerical solution. This is demonstrated on a prototypical natural gas purification process.

Conference paper

Gopinath S, Galindo A, Jackson G, Adjiman CSet al., 2015, Computer aided molecular and process design using complex process and thermodynamic models: A screening based approach, Pages: 107-109

The design of optimal processing materials (molecules) and optimal process variables for a given process is referred to as Computer Aided Molecular and Process Design (CAMPD). Processing materials used to achieve process goals include mass separating agents (such as solvents for absorption, extraction, leaching and adsorbents), catalysts, heat transfer fluids and reaction medium solvents. Choosing processing molecules influences the optimal process variables and vice versa. Molecular and process decision variables are linked, interacting with each other in a complex manner. Hence, neither of these decisions can be made in isolation.

Conference paper

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