Mykhaylo Krasnyk

Operating Behavior and Scale-Up of an EXPrOx Unit for CO Removal from Reformate for PEM Fuel Cell Application

Recently, an approach involving electrochemical preferential oxidation (ECPrOx) of CO was suggested as having the potential to replace the PrOx concept for deep CO removal from reformate gas in proton exchange membrane (PEM) fuel cells. The first part of this paper deals with the characterization of such an ECPrOx unit from a reaction engineering point of view. Based on a spatially lumped, isothermal model, the qualitative selectivity-conversion behavior is discussed for varying feed flow rates and CO inlet mole fractions. A simple two-phase mechanism is suggested that explains the findings. The second part of the contribution considers qualitative questions on cascading of two ECPrOx reactors. The crucial importance of the configuration of their electrical connection is demonstrated and explained. While two cells connected electrically in parallel exhibit almost the same selectivity-conversion behavior in comparison with a single cell, an electrical series connection enables a considerable increase in the selectivity at the same CO conversion.

The ProMoT/Diana Simulation Environment

Abstract We introduce the object-oriented modeling tool ProMoT and the simulation environment Diana suitable for numerical analysis of problems in chemical engineering and systems biology. The key aspects of this environment are flexible structured models, and efficient modular numerical kernel, and the use of the scripting language Python as a powerful command line interface. The implementation is based on CAPE-OPEN interfaces to allow a modular software design and easy extensions of the system. The contribution discusses the design and implementation rationale of the simulation environment.

Numerical analysis of higher order singularities in chemical process models

In this contribution, a tool is presented that allows the continuation of singularities of higher codimension for complex chemical process models. The tool is an extension of the process-modelling tool ProMoT. It allows creating augmented systems for simple zero eigenvalue bifurcation points. Parameter continuation of such points allows to produce different varieties for hysteresis, isolas, pitchforks or winged cusps singularities. Required higher order directional derivatives are obtained analytically via an interface to the computer algebra system Maxima.

Model reduction techniques for the simulation of particle populations in fluid flow

Crystallization processes are characterized by a close interaction between particle formation and fluid flow. A detailed physical description of these processes leads to complicated high-order models whose numerical solution is challenging and expensive. For advanced process control and other model-based online applications, reduced-order models are required. In this work, a reduced model for a urea crystallizer is developed using the method of moments for the internal coordinate and proper orthogonal decomposition for the external coordinate. Simulations are carried out to compare the reduced model with the detailed reference model.

Application of Proper Orthogonal Decomposition to Particulate Processes

Abstract Particulate processes like industrial crystallisation or granulation are often described by population balances. This leads to mathematical models containing partial integro differential equations. In many cases, the flow conditions of the fluid phase have a strong impact on the particle formation. To describe this properly, Navier Stokes equations have to be solved in addition. The resulting model equation system is too complicated to apply them to typical process control tasks. Reduced models are desirable. In this contribution, the use of proper orthogonal decomposition is suggested as a powerful reduction method. The usefulness of the approach is illustrated by two application examples: a granulation process with particle aggregation and a crystallisation process with particle growth and complex fluid dynamics.

Modellreduktion von Populationssystemen mit Hilfe von Proper Orthogonal Decomposition

Zusammenfassung Der Beitrag beschreibt den Einsatz der Proper Orthogonal Decomposition (POD) für die Modellreduktion von Partikelprozessen in fluider Strömung. Diese Prozessklasse ist von großer Bedeutung für die chemische und pharmazeutische Industrie. Physikalische Modelle solcher Prozesse sind häufig sehr komplex und für Regelungsaufgaben wenig geeignet. POD bietet hier eine attraktive Möglichkeit, zu reduzierten Prozessmodellen zu gelangen, da das Verfahren sehr flexibel ist, keine spezielle Struktur des Referenzmodells erfordert und interne und externe Koordinaten in einheitlicher Weise behandelt. Der Beitrag stellt das Reduktionsverfahren vor und illustriert es an Beispielen. Abstract This paper discusses the application of Proper Orthogonal Decomposition (POD) to the model reduction of particle processes in fluid flow. This class of processes is highly relevant for chemical and pharmaceutical industry. As detailed first principle models of such processes tend to be very complicated, reduced models are required for process control and process design. POD is an attractive method to obtain the reduced models, as it is highly flexible, does not require a special structure of the reference model and treats internal and external coordinates in the same manner. The method is presented and illustrated by examples.