Christoph Lehmann

The FEM Simulation Software OpenGeoSys 6

OpenGeoSys (OGS) together with its predecessors looks back at a long history as a simulation code of coupled thermal, hydraulic, mechanical and chemical (THMC) phenomena in fractured porous media: starting as the Fortran code Rockflow in the 1986, ranging over a C implementation and now using different flavours of the C++ programming language; in the meantime undergoing two renames, namely to GeoSys and now OpenGeoSys.

Laboratory-Scale Adsorption Chamber Simulation

In this chapter, the first real-world scenario is simulated using the model developed in Chap. 2.

Mathematical Model of the THC Processes in a Fixed Adsorbent Bed

In this chapter a mathematical model for a fixed bed of adsorbent pellets in an open-mode heat storage device is derived. At first a the general modelling workflow is presented. Afterwards the governing equations of the system are derived from the physical balance laws in combination with constitutive relations for material properties. Special focus is laid on the constitutive relations for the sorption equilibrium and kinetics.

THC Processes in Energy Systems

Water adsorption to zeolites is a promising means for heat storage , including the seasonal storage of solar energy. We have added a material model to OpenGeoSys that calculates the equilibrium water loading of the zeolite and the heat of adsorption using the Dubinin-Polanyi theory of adsorption to microporous solids .

Consensus Information and Consensus Rating

Quantifying credit risk with default probabilities is a standard technique for financial institutes, investors or rating agencies. To get a higher precision of default probabilities, one idea is the aggregation of different available ratings (i.e. default probabilities) to a so called ‘consensus rating’. But does the concept of ‘consensus rating’ really make sense? What is a ‘real’ consensus rating? This paper tries to clarify under which conditions a consensus rating exists. Therefore, the term of ‘consensus information’ is used. This leads to a concept that deals with the precision of aggregated rating characteristics. Within this framework the problem of misinformation resp. contradictory information is addressed. It is shown that consensus information is not necessarily more informative than individual information. Furthermore, the aggregation aspects are discussed from a statistical perspective.