Department of Modelling and Valuation
Whether ores, tailings or recycled materials – all these raw material sources can greatly vary in their chemical and physical characteristics. How such variations impact the efficiency of minerals processing is investigated by the Modelling and Valuation Department. It combines petrographic analysis results with mathematical models to optimize the metal extraction from particularly complex composite raw material sources. The approach is called Geometallurgy. The Department also develops new methods and powerful mathematical models to improve the entire process chain of metalliferous raw materials in terms of economic and resource-confined aspects.
Geostatistics of Geometallurgical Parameters
Potential analysis for deposits are based on chemical and physical data, often of limited amount or different origin. For optimal analysis, the Department of Modelling and Valuation uses geostatistical tools to predict spatial distributions while quantifying uncertainties. The focus is on geostatistical simulations and geostatistics of nonlinear scales for ore bodies.
3D Modeling of Microstructures with Stochastic Geometry
Unpredictable interactions between particle systems make a quantitative result prediction for mechanical and physicochemical processing difficult. The microstructures of the particles, which help analyzing the interactions, can so far only be displayed in 2D and therefore cannot be fully investigated. The Department, therefore, develops stochastic geometric 3D microstructure models as a basis for particle-based process modeling.
Particle-based Process Modelling
The department develops particle-based process models for quantitative prediction of energy-efficient processing routes. The models enable the simulation of particle flows under different process conditions and the deduction of optimal process parameters. For this purpose, physically based models are combined with statistical particle tracking models.
Model-based Adaptive Processing
Choosing optimal process routes and parameters is key to efficient benificiation. Based on the geostatistical ore-based process models generated in the department, scientists are developing decision-making theories and techniques to predict and adapt the choice of optimal process routes and parameters in real-time.
The department calculates and evaluates the efficiency and costs of metals production and values. In order to be able to appropriately assess the results the scientists study economic laws and dynamics of the commodity markets.