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Item type:Publication, Access status: without files , Exergy-based optimization for the synthesis of heat pump assisted distillation columnsWhile distillation columns are the main unit operation in fluid separation processes, considered versatile, robust, and well-understood, they are also oftentimes framed as energy intensive and potentially inefficient. Heat pumps bear the potential to improve the energy efficiency of distillation processes and simultaneously allow for the electrification of the thermal-driven separation processes. However, the economic viability and potential for energy savings depend strongly on the temperature lift and the compression ratio of the heat pump. Both can be reduced by considering intermediate heat exchangers rather than a full temperature lift from below the top vapor to above the bottoms temperature. Such intermediate heat exchangers may furthermore improve the internal efficiency of the distillation column and thereby improve the overall energy efficiency. The current contribution presents an exergy-based optimization that allows for an improved heat load distribution that can provide significant improvements of the internal efficiency and further enables a conceptual design of heat pump assisted distillation, using vapor recompression to provide the heat loads at the intermediate heat exchangers. The benefits of the approach are illustrated for the separation of a nonideal acetone-water mixture, highlighting the capability to identify unintuitive designs with significant saving potential.Publicationtype: Conference Paper126 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Towards self-consistent graph neural networks for predicting the ideal gas heat capacity, enthalpy, and entropyIdeal gas heat capacity correlations are indispensable for modelling energy systems and evaluating process efficiency. While most correlations are empirical in nature, few are theoretically motivated, where the model parameters reflect physical quantities relating to the molecule. These however are rarely modelled through quantitative structure-property relationships, which hinders extending their applicability to new compounds. This work provides a realisation of a hybrid model that combines data-driven modelling in the form of a graph neural network that outputs a set of parameters used for the ideal gas heat capacity correlation. The study covered over 22,000 data points across 1,909 organic compounds resulting in a mean absolute error of 31.97 J/mol-K, a mean relative error of 11.63% and a correlation coefficient of 0.97.Publicationtype: Conference Paper84 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Optimal retrofit of simple distillation sequences to thermally coupled side-stream configurationsRetrofitting existing plant equipment to a more energy efficient setup is a promising and sustainable way to cut down on the energy demand and consequently the operating costs of a chemical processing plant. While this opportunity is attractive in terms of low capital expenditure and construction time, it is also highly challenging for the design engineers. Degrees of freedom in grassroot design transform into constraints in the retrofit project and finding an optimal design within the constraints of the existing equipment, requires a sophisticated model-based approach. In this work, such an approach is presented for the retrofit of distillation column sequences to thermally coupled side-stream configurations. Based on this approach, an easy evaluation of retrofit opportunities in terms of investment and operating costs is facilitated. The potential of this retrofit is illustrated in the current contribution by means of a case study, which compares the retrofit option to a fully thermally coupled dividing wall column grassroot design. While the dividing wall column generally allows for higher energy savings, the investment in the retrofit is significantly smaller, which yields a considerably quicker amortization.Publicationtype: Conference Paper54 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , From problem specification to converged flowsheet simulations: integrated workflow in an industrial context(Elsevier, 2023-06); ; 29 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Automatic synthesis of hybrid processes using distillation and liquid-liquid extraction for the separation of azeotropic mixturesSolvent-based separation processes, such as liquid-liquid extraction are important options for the separation of aqueous mixtures with low relative volatilities, tangent pinches or azeotropes, for which distillation is either infeasible or energy intensive. As the choice of solvent is of utmost importance, various methods for solvent screening have been proposed, focusing either on properties like solubility and capacity, or the minimum solvent requirement. While some do evaluate the energy for solvent recovery, they assume a fixed process structure, based on the integration of an extraction and a distillation column. Therefore, additional constraints restrict feasible solvents to those that do not form azeotropes and show specific boiling points. While such constraints are oftentimes reasonable, overcoming this limitation requires the identification of solvent-specific process configurations, which is a complex task usually performed by graphical analysis or trial and error. For this purpose, the current work introduces a novel algorithmic synthesis approach and illustrates its application for the separation of a ternary mixture of acetone, acetic acid and water using chloroform as solvent.Publicationtype: Conference Paper99 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Hierarchical approach for solvent selection in circular economyChemical recycling allows upcycling of polymers into their monomers and/or other valuable chemicals and contributes to a resource-efficient future. This demands selective depolymerization of a particular fraction from a mixed waste stream and thereby, necessitates the use of appropriate solvents. The solvent not only governs the effective depolymerization of the polymer but also influences the sustainability of the process. Conventionally, the tendency of the solvent to dissolve the polymer is considered as the only selection criterion. However, careful consideration should also be given to its interaction with other process reagents and its sustainability. This research proposes a systematic approach to identify potential solvents suitable for a particular recycling strategy. The hierarchical approach begins with identifying potential solvents using computer-aided molecular design based on the Hansen Solubility Parameters (HSPs) of the target polymer. Further, their interactions with other process reagents are also considered. Subsequently, they are screened for their sustainability through a comprehensive life-cycle assessment and some short-listed systems are further evaluated using process simulation. The application of this methodology for developing a recycling strategy for PLA is illustrated.Publicationtype: Conference Paper78 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , ANN-assisted optimization-based design of energy-integrated distillation columnsThe optimal design of chemical processes is of essential importance for an increased sustainability. However, the resulting non-convex mixed-integer nonlinear programming (MINLP) problems cannot directly be solved to global optimality. Therefore, different alternatives have been proposed, which either build on the application of a simulation-based optimization by means of a metaheuristic or the global optimization of a surrogate model, both requiring extensive simulations. The current work proposes a novel alternative approach for a surrogate-assisted hybrid optimization, which exploits a local deterministic optimization of a full MINLP problem to generate a compact artificial neural network (ANN) model that allows for the direct optimization on a reduced search space. In order to provide a sufficient accuracy of the ANN while targeting the global optimum of the design problem, a tailored mixed adaptive sampling is introduced. Application of the algorithm is illustrated for the optimal design of a distillation-based separation of benzene, toluene, and xylene with different means for energy integration.Publicationtype: Conference Paper93 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Conceptual design based on superstructure optimization in GAMS with accurate thermodynamic models(Elsevier, 2020-08); ; ; ; Conceptual design based on superstructure optimization is a complex task that neither commercial simulators nor dedicated modeling and optimization environments like GAMS, AMPL, and AIMMS are able to perform well by themselves: the first lack interfaces to state-of-the-art solvers, the latter do not provide accurate thermodynamic models. While previous research shows that GAMS can be interfaced with an external thermo engine, this interfacing requires additional C ++ code, whose manual generation and consistent implementation is tedious, making the approach both error prone and impractical for larger design problems. By using MOSAICmodeling as a modeling environment, this shortcoming of the existing approach is eliminated by automatically generating all code needed for interfacing GAMS with an external CAPE-OPEN thermodynamic property package.Publicationtype: Conference Paper104 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Optimization-based design of rotating packed beds with zickzack packingsDue to the fast development of the market in the chemical industry, more flexible and efficient equipment is obligatory. High-gravity contactors in form of Rotating Packed Beds (RPBs) have the potential to meet these needs since they offer an enhanced mixing by imposing centrifugal forces resulting in an intensified mass and energy transport. With the rotational speed as an additional degree of freedom, RPBs offer faster start-up times and an enlarged operating window. Despite the increasing scientific work in the areas of experimental investigations and modeling, industrial applications are still limited due to a lack of reliable methods for scale-up and design. In respect to the latter, this work presents a nested superstructure approach for the optimization-based design of RPBs with zickzack packings that is further demonstrated for the dehydration of methanol.Publicationtype: Conference Paper112 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Automatic synthesis of distillation processes for the separation of heterogeneous azeotropic multi-component mixturesThe separation of azeotropic mixtures is a complex task that is frequently addressed by means of graphical analysis of residue curve maps and trial-and-error flowsheet simulations. While miscibility gaps in heterogeneous mixtures result in considerably more complex phase behaviour, the possible exploitation of a combination of decantation and distillation bears the potential for efficient separation processes. In order to enable an automatic generation of alternative separation sequences with closed recycle loops the current article presents an extension of a previously developed algorithmic framework for process synthesis of homogeneous distillation processes. This extension includes the computation and characterization of heterogeneous azeotropes and the analysis of the topology of the system, as well as an extended split feasibility algorithm, which also accounts for decantation at different temperature levels. The approach is fully algorithmic and includes a shortcut-based computation of the energy demand of the generated flowsheet variants.Publicationtype: Conference Paper53