Andreas Harwardt

Is biomass fractionation by Organosolv-like processes economically viable? A conceptual design study

In this work, the conceptual designs of the established Organosolv process and a novel biphasic, so-called Organocat process are developed and analyzed. Solvent recycling and energy integration are emphasized to properly assess economic viability. Both processes show a similar energy consumption (approximately 5 MJ/kg(dry biomass)). However, they still show a lack of economic attractiveness even at larger scale. The Organocat process is more favorable due to more efficient lignin separation. The analysis uncovers the remaining challenges toward an economically viable design. They largely originate from by-products formation, product isolation, and solvent recycling. Necessary improvements in process chemistry, equipment design, energy efficiency and process design are discussed to establish economically attractive Organosolv-like processes of moderate capacity as a building block of a future biorefinery.

Conceptual Design of Distillation-Based Hybrid Separation Processes

Hybrid separation processes combine different separation principles and constitute a promising design option for the separation of complex mixtures. Particularly, the integration of distillation with other unit operations can significantly improve the separation of close-boiling or azeotropic mixtures. Although the design of single-unit operations is well understood and supported by computational methods, the optimal design of flowsheets of hybrid separation processes is still a challenging task. The large number of operational and design degrees of freedom requires a systematic and optimization-based design approach. To this end, a structured approach, the so-called process synthesis framework, is proposed. This article reviews available computational methods for the conceptual design of distillation-based hybrid processes for the separation of liquid mixtures. Open problems are identified that must be addressed to finally establish a structured process synthesis framework for such processes.

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.

Optimal column sequencing for multicomponent mixtures

Abstract The separation of a multicomponent mixture using distillation is usually possible in a large number of different sequences, which will provide the same products but have different energy demand. In this contribution, we provide a systematic method to find the optimal column sequence based on exergy demand. The screening of design alternatives is done within a superstructure framework, which allows for the decomposition of the separation sequences into unique separation tasks. The use of the task concept significantly reduces the computational work. The individual separation tasks are evaluated using shortcut methods. For the application to azeotropic mixtures, the mixture topology is determined and feasibility checks are performed for every split. In this context, azeotropes are treated as pseudo-components.

Conceptual Design of Azeotropic Distillation Processes

Abstract This chapter introduces the major types of azeotropic distillation processes and describes a systematic framework for their conceptual design. The framework is based on a three-step approach consisting of (1) variant generation, (2) screening of all variants based on shortcut methods, and (3) the final detailed design by means of rigorous optimization. Different approaches for the generation of distillation flowsheets and the analysis of inherent limitations are presented and compared in the context of a qualitative and quantitative assessment of split feasibility. An elaborate overview on different shortcut methods for the evaluation of distillation process performance is given, and their applicability to the design of azeotropic distillation processes is discussed. Since rigorous optimization should always follow shortcut-based design and evaluation steps, recent advances in this field with a focus on azeotropic distillation are highlighted. The chapter closes with the presentation of a few example case studies for the conceptual design of different types of azeotropic distillation processes.

Reaction networks – A rapid screening method

Abstract Innovative and sustainable processes for the conversion of whole plants into fuels are developed in the cluster of excellence “Tailor-Made Fuels from Biomass” (TMFB) at RWTH Aachen University. In order to guarantee an efficient production a large number of process alternatives needs to be evaluated systematically at an early design stage, including both preliminary research results and literature knowledge. In order to review potential chemical synthesis routes, a rapid screening method is developed to detect andto classify all combinations of reaction steps using mixed integer programming. Based on these results promising reaction pathways as well as bottlenecks can be identified and a first insight in possible process chains can be gained. This paper introduces the scope and the methodology of the approach and illustrates both on an appropriate example.

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.

On the integration of model identification and process optimization

Abstract Reliable models for rate-based phenomena are the backbone of model-based process design. These models are often unknown in the early design phase and need to be determined from laboratory experiments. Although model-based experimental analysis and process design are often executed sequentially, the kinetic models might not be suitable to reliably design a process. In this paper, we address this problem and present a first step on the integration of model identification and process optimization. Rather than decoupling model identification and process optimization, we use information from process optimization to design optimal experiments for improving the quality of the kinetic model given the intended use of the model. Sensitivities, which describe the influence of parametric uncertainties on the economic objective used in process optimization, are used as weights for optimal experimental design. This way, the confidence in the parameter values is maximized to reduce their influence on the process optimization objective. This first step on the integration of model identification and process optimization improves the predictive quality of a reaction kinetic model for process design without any further experimental effort.

Bio-based Value Chains of the Future - An Opportunity for Process Systems Engineering

Abstract This paper argues for a paradigm shift to properly address the requirements of modelbased design of future bio-based value chains. Rather than focusing on the process with emphasis on separations and heat integration, the decisions on the molecular level require much more attention. A rough sketch of a systematic sequential and iterative model-based design strategy is presented and illustrated by a few examples related to the manufacturing of future bio-based fuels.