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Solvent degradation is one of the main operational drawbacks of post-combustion CO 2 capture with amine solvents. Although the different degradation mechanisms have been largely studied in recent years, it is still impossible to predict the solvent losses and the emissions of degradation products that may occur in a CO 2 capture plant depending on its size and on its operating conditions. In the present work, we experimentally study the degradation of MEA (monoethanolamine) under accelerated conditions implying high temperature, continuous gas feed and vigorous agitation. A special focus is set on the oxidative degradation of MEA, which is studied in the absence of CO 2 . Based on the experimental results, we propose a kinetic model to describe both MEA oxidative and thermal degradation pathways. The degradation kinetics is then included into a global model of the CO 2 capture process, enabling solvent losses and emissions of degradation products to be predicted as a function of the process operating conditions. The predicted MEA loss is in the same order of magnitude as reported in degradation measurements from pilot plants, although lower by a factor 3. This kind of model assessing solvent degradation could and should be used for the design of large-scale CO 2 capture plants in order to simultaneously consider the energy consumption of the process and its environmental impact related to the emissions of degradation products and amine solvent. Further developments shall consider the effect of SO x , NO x and dissolved metals on MEA degradation.

The present paper addresses the evolution and perspectives in the teaching of CAPE methods in the Department of Chemical Engineering at the University of Liege. The transition that happened in the 90ies with the arrival of commercial software is highlighted, as the learning outcomes evolved from the ability of building programs to solve chemical engineering problems towards the ability to use complex commercial software and to understand their limitations. Moreover, CAPE methods were extended to non-dedicated CAPE courses, which is illustrated here by the goals and challenges of their use in courses like “Reactor Engineering” and “Life Cycle Analysis”. It was observed that students sometimes assume that CAPE softwares provide straightforward and trustworthy solutions without the need of understanding their mathematical bases and assumptions. Thus, solutions to make students aware of these limitations are proposed, including the creation of an integrated project focussing on complex multi-disciplinary issues, evidencing the need for critical input from the operator.

The results of a collaborative study on the operation of a steam production network are presented in this paper. An overdesigned utility network is first modelled, based on plant measurements, where the network equipment is modelled through sets of conventional processing blocks. Data reconciliation methods are applied to determine design parameters, as turbine efficiencies, pump efficiencies etc. A multiperiod optimization framework is then employed to determine network operation and energy management schedules for variable demand levels and for uncertain process parameters.

Carbon Capture and Utilization (CCU) has the potential to reduce both greenhouse gas emissions and fossil fuel use. However, the conversion of CO 2 is intrinsically difficult due to its low energetic state. Thus, a positive environmental effect of a CO 2 -consuming reaction cannot be taken for granted. In this work, we therefore present a graphical method to identify promising reaction schemes using CO 2 as a feedstock. Reactant mixtures leading to minimal life-cycle greenhouse gas (GHG) emissions are determined. The optimal reaction schemes strongly depend on the reactants global warming potential (GWP); in the case of CCU, the future GWP values of CO2 and H 2 are particularly critical and subject to major uncertainty today. The graphical method therefore provides GWP targets for CO 2 capture and H 2 production technologies. The method is demonstrated for the production of methanol. Five optimal reaction schemes are identified depending on the GWP values of CO 2 and H 2 . Thus, four threshold relations for the GWP of CO 2 and H 2 are derived showing directly under which conditions the utilization of CO 2 as a feedstock is environmentally preferential.

The experience gained in the development of a CAPE-OPEN 1.0 thermo socket for the BELSIM-VALI software is presented. VALI is a data validation and reconciliation software that provides consistent mass and energy balances, reliable and accurate Key Performance Indicators and soft sensors. It is not a simulation software per definition, but rather a powerful equation based software that is used online, to monitor and manage the operations of different processes. VALI has its own thermodynamic database of chemical compounds (> 800 fluids, > 650 solids) and methods. After demands of our clients it was decided to make VALI compliant with other thermodynamic packages via a CAPE-OPEN 1.0 thermo socket. The source code of the VALI physical property modules had to be modified, to call the Material Object components instead of built-in thermodynamic functions (thermo socket). In the user interface, we had to develop a CAPE-OPEN thermo plugs viewer to allow the selection of a CAPE-OPEN thermo plug from our Graphical User Interface (GUI). Several case studies were analysed, with performance comparison between the native thermodynamic model, and properties obtained from several CAPE-OPEN thermoplugs. We will particularly analyse here the modelling of a gas liquefaction system and a distillation case study.

The once-through heat recovery steam generator design is ideally matched to very high temperature and pressure, well into the supercritical range. Moreover this type of boiler is structurally simpler than a conventional one, since no drum is required. A specific mathematical model has been developed. Thermodynamic model has been implemented to suit very high pressure (up to 240 bar), sub- and supercritical steam properties. We illustrate the model use with a 180 bar once-through boiler (OTB).

A systematic method to design sensor networks able to identify key process parameters with a required precision at a minimal cost is presented. The procedure is based on a linearised model, derived automatically from a rigorous non-linear data reconciliation model. A genetic algorithm is used to select the sensor types and locations.