Optimal design of solvent blends for environmental impact minimization

A Convex Hull Formulation for the Design of Optimal Mixtures

“…Two aspects of general mixture design problems make them particularly challenging: the complexity that arises from dealing with a mixture with an unknown number of components and the numerical difficulties that accompany large nonlinear and combinatorial problems. Indeed, the majority of existing methodologies focus on the design of mixtures with a fixed number of components and have been applied mostly to binary mixtures (Buxton et al, 1999;Karunanithi et al, 2005;Papadopoulos et al, 2013;Siougkrou et al, 2014;Duvedi and Achenie, 1997), with some exceptions such as the work of Klein et al (1992), Solvason et al (2009) and Yunus et al (2014) who have presented methodologies for the design of multicomponent mixtures. Furthermore, within the CAM b D framework, the design problems have often been posed as Mixed-Integer Nonlinear Programming (MINLP) problems, where the optimal molecular structure is determined with respect to a set of property constraints.…”

“…Several methodologies for designing solvent mixtures, blends of refrigerants and polymers have been reported in the literature. Buxton et al (1999) proposed a systematic decomposition-based procedure to select optimal solvent blends for nonreactive, multicomponent gas absorption processes. Karunanithi et al (2005) proposed a decomposition-based computer-aided molecular/mixture design methodology which was applied successfully to two solvent design case studies.…”

A feasibility-based algorithm for Computer Aided Molecular and Process Design of solvent-based separation systems

“…The determination of targets by using property "clusters" has been investigated (Eljack et al, 2008). Buxton et al (1999) proposed a screening approach embedded in an MINLP optimizer and applied it to the design of a solvent for a separation unit with fixed operating conditions. In their approach, tests based on property targets, the ability to initialize model subproblems and the feasibility of mass transfer were used prior to solving the primal problem.…”

Outer approximation algorithm with physical domain reduction for computer‐aided molecular and separation process design

“…The integrated design of an organic Rankine cycle process conditions and working fluid was also solved as a full MINLP in recent work, facilitated by the fact that only pure component phase behavior is of relevance in such a case. 44 To handle more general design problems, one can adopt the approach of Buxton et al 8 who modified the generalized Benders decomposition (GBD) algorithm 45 : they introduced several steps prior to the solution of the primal problem, including a series of property tests that form a subset of the CAMD problem constraints, the initialization of various sets of equations in the process model, and mass-transfer feasibility tests, in which the process operating conditions were assumed to be fixed a priori. This approach was extended to tackle mixed-integer dynamic optimization problems, 46 to enable the simultaneous design of a batch process and the associated solvent.…”

“…Discrete variables are used to represent molecularlevel decisions such as the number of groups of a given kind (for example, how many hydroxyl groups the optimal molecule contains, if any), with constraints used to specify how the groups can be combined. [6][7][8][9] Discrete variables can also be used to represent the connectivity between the groups, 10,11 and the identity of components if the material of interest is a mixture. [12][13][14] The CAMPD problem is inherently more complex than the corresponding process design problem with fixed material choices.…”