Central project: Dynamic simulation of interconnected processes

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The main objective of the SPP is the dynamic modeling of interconnected solids processes. While in the individual projects, in which the process models are developed, the modeling of individual appliances or subprocesses is foregrounded, in the here proposed central project the individual models will be linked to process chains. Based on the simulation system, which is developed within this project, the dynamics of the entire process chain can be investigated.In the first and second funding periods the main focus of this project was on the development, verification and extension of the simulation framework. Therefore, during these periods main calculation algorithms, data structures and several interfaces have been developed and implemented as simulation framework Dyssol. The simulation system has been distributed among all members of the SPP, and several training seminars focused on the usage of the system and the developments of new dynamic models were conducted. To validate the framework and to approximate the efficiency of the developed calculation methods, the dynamic behavior of several solids processes has been investigated.In the third funding period the project is going to be focused on the integration of dynamic models, material parameters, algorithms and methods into the simulation framework. Therefore, to provide efficient integration of the results of all subprojects of the SPP, the work related to the coupling of new components to the Dyssol system will be performed in this project. It will include not only support during implementation of modules in C++ programming language, but also troubleshooting of the existing system, extension of it with new interfaces and internal functions needed by models developers as well as further optimization of calculation methods.Concerning further extension of the Dyssol functionality, the work is going to be carried out in two main directions. Firstly, algorithms and methods for the process optimization will be developed and implemented. They will allow calculation of the optimal process parameters with regard to specific target variables. Secondly, a module for the parameter estimation will be designed and integrated into the system.