Recovered paper needs to be sorted before it can be used as secondary raw material for the manufacture of new paper. For the planning or operation of sorting plants for recovered paper flowsheet simulations could be a valuable instrument. In flow sheet simulations an abstract network of material streams and unit operation models is generated to virtually investigate process plants. Due to missing tools the potential of flow sheet simulations can currently not be exploited for recovered paper sorting. Therefore the main objective of this thesis is to develop a material stream description and models for the unit operations of recovered paper sorting. Additional aim is the development of a method for collecting data of material streams in industrial sorting plants based on sampling. At the beginning of the thesis the state of the art of sorting plants for recovered paper in Germany is summarized and the state of knowledge about tools for flowsheet simulations of sorting plants for recovered paper is compiled. The material stream description is developed afterwards. In this description recovered paper is a mixture of material groups and those groups are characterised by properties. In this thesis 18 materials groups, which are relevant for recovered paper sorting, are specified in a material group catalogue. The particle size distribution is taken into account as a characterising property. The structure of the material stream description is modular so that it can be adapted to different flowsheet simulation tasks. The method for collecting data of recovered paper streams in industrial sorting plants is based on the material stream description. Procedures for sampling, for the analysis of samples and for measuring mass flows are defined. For the analysis of samples an instrument in form of an automatic measuring system is designed. The main sensor of the system is a colour camera. Image analysis algorithms are implemented to determine the particle size distribution of a sample. Additional algorithms for pattern recognition are developed so that the system can automatically distinguish between objects of the material groups newspapers, magazines, advertisement, white papers, grey papers and brown corrugated board. The time needed for analysing samples with the system amounts to 1 hour per 10 kg of recovered paper. This is substantially shorter than the time needed for manual sample analyses. The developed method is used to collect data in industial sorting plants for recovered paper. Five plants that process recovered paper from household collection and produce sorted graphic paper for deinking are investigated during standard operation. The unit operations for recovered paper sorting, coarse screening, fine screening, paperspike processes, hand picking and sensor-based sorting, are modelled afterwards. A basic steady state black box model is used to describe all unit operations in general. This basic model is specified for each individual unit operation. In the model for the screening processes the particle size is taken into account by screen classification functions. All unit operation models contain parameters which are fitted to the collected data. At the end of the thesis the application of the developed flowsheet simulation tools is demonstrated. A flowsheet of an entire sorting plant for recovered paper is set up with unit operation models and validated by measured data. This flowsheet is used in two simulations with scenarios of practical relevance. The simulations show that the developed tools are suitable for a virtual investigation of sorting plants for recovered paper. Application fields for the developed tools are the planning and operating of industrial sorting plants for recovered paper. In research the tools can, for example, be applied in investigations covering the circle of paper recycling.