Korbinian Kraemer

A Framework for the Systematic Design of Hybrid Separation Processes

The design of optimal separation flow sheets for multi-component mixtures is still not a solved problem. This is especially the case when non-ideal or azeotropic mixtures or hybrid separation processes are considered. We review recent developments in this field and present a systematic framework for the design of separation flow sheets. This framework proposes a three-step approach. In the first step different flow sheets are generated. In the second step these alternative flow sheet structures are evaluated with shortcut methods. In the third step a rigorous mixed-integer nonlinear programming (MINLP) optimization of the entire flow sheet is executed to determine the best alternative. Since a number of alternative flow sheets have already been eliminated, only a few optimization runs are necessary in this final step. The whole framework thus allows the systematic generation and evaluation of separation processes and is illustrated with the case study of the separation of ethanol and water.

Conceptual Design of a Butyl-levulinate Reactive Distillation Process by Incremental Refinement

Abstract Butyl-levulinate has been identified as a promising fuel candidate with high oxygen content. Its combustion in diesel engines yields very low soot and NO x emissions. It can be produced by the esterification of butanol and levulinic acid, which themselves are platform chemicals in a biorenewables-based chemical supply chain. Since the equilibrium of esterification limits the conversion in a conventional reactor, reactive distillation can be applied to overcome this limitation. The presence of the high-boiling catalyst sulfuric acid requires a further separation step downstream of the reactive distillation column to recover the catalyst for recycle. Optimal design specifications and an optimal operating point are determined using rigorous flowsheet optimization. The challenging optimization problem is solved by a favorable initialization strategy and continuous reformulation. The design identified has the potential to produce a renewable transportation fuel at reasonable cost.

An efficient solution method for the MINLP optimization of chemical processes

Abstract Process synthesis often involves the solution of large nonlinear discretecontinuous optimization problems, which are usually formulated as mixedinteger nonlinear programming (MINLP) or generalized disjunctive programming (GDP) problems and solved with MINLP solvers. This paper presents an efficient solution method for these problems named successive relaxed MINLP (SR-MINLP), where the model formulations are reformulated to contain only continuous variables. The discrete decisions are relaxed and successively tightened in a sequential solution procedure to facilitate convergence and to obtain local optima of good quality. The solution method is illustrated by a simple numerical example as well as a large and complex example from process synthesis.

Continuous Reformulation of MINLP Problems

The solution of mixed-integer nonlinear programming (MINLP) problems often suffers from a lack of robustness, reliability, and efficiency due to the combined computational challenges of the discrete nature of the decision variables and the nonlinearity or even nonconvexity of the equations. By means of a continuous reformulation, the discrete decision variables can be replaced by continuous decision variables and the MINLP can then be solved by reliable NLP solvers. In this work, we reformulate 98 representative test problems of the MINLP library MINLPLib with the help of Fischer-Burmeister (FB) NCP-functions and solve the reformulated problems in a series of NLP steps while a relaxation parameter is reduced. The solution properties are compared to the MINLP solution with branch & bound and outer approximation solvers. Since a large portion of the reformulated problems yield local optima of poor quality or cannot even be solved to a discrete solution, we propose a reinitialization and a post-processing procedure. Extended with these procedures, the reformulation achieved a comparable performance to the MINLP solvers SBB and DICOPT for the 98 test problems. Finally, we present a large-scale example from synthesis of distillation systems which we were able to solve more efficiently by continuous reformulation compared to MINLP solvers.

Separation of butanol from acetone-butanol-ethanol fermentation by a hybrid extraction-distillation process

The alternative fuel butanol can be produced via acetone-butanol-ethanol (ABE) fermentation from renewable resources, i.e. biomass. Expensive feedstocks and the high costs for the separation of ABE from the dilute fermentation broth in the downstream processing have so far prohibited the industrial-scale production of bio-butanol. The low productivities and butanol yields of ABE batch fermentation can be increased by continuous fermentation with cell recycle and integrated product removal. In order to facilitate an effective and energy-efficient product removal, we suggest to apply a hybrid extraction-distillation process with ABE extraction in an external column. The removal of ABE outside the fermenter in an extraction column is favored from an operational point of view. By means of computer-aided molecular design (CAMD), mesitylene has been identified as a new solvent for ABE extraction from the fermentation broth. The solvent properties of mesitylene are compared to those of oleyl alcohol, which is the most common solvent for ABE extraction. Subsequently, we propose a hybrid extraction-distillation downstream process for product removal and purification. It is shown that the specific energy demand of this process is significantly lower when mesitylene is used as extraction solvent instead of oleyl alcohol.

Design of Heat-Integrated Distillation Processes Using Shortcut Methods and Rigorous Optimization

Abstract The stepwise optimization based procedure for the design of heat-integrated distillation processes as presented by Harwardt et al. (2009) is extended to include complex column designs such as the divided wall column. In the first design step, the optimal flowsheet structure of simple columns is identified using a superstructure formulation and shortcut models based on rigorous thermodynamics. The column pressure is variable in this early design stage to allow for heat integration between the column and the network of heat exchangers. In the second design step, a rigorous MINLP optimization of the most promising flowsheet structure is performed for a thorough assessment of the cost savings potential of heat integration and to determine the optimal column tray numbers and feed stage location. The rigorous optimization can be solved with good robustness, efficiency and reliability due to a continuous reformulation of the MINLP. In a third design step, it is investigated via rigorous optimization whether the energy and capital costs can be further reduced by a fully heat-integrated complex column system such as a divided wall column setup. The design procedure is illustrated by a case study considering the complete separation of a quaternary azeotropic mixture.