Rule-based controlling of a multiscale model of precipitation kinetics

Rule-based controlling of a multiscale model of precipitation kinetics

Piotr Macioł

Faculty of Metals Engineering and Industrial Computer Science, AGH University of Science and Technology, al. Mickiewicza 30, 30-059 Krakow, Poland.



One of the most important obstacles of widening of multiscale modelling is its high computational demand. It is caused by the fact, that each of numerous fine scale models has comparable computational requirements to a coarse scale one. There are several ways of decreasing of computational time of multiscale models. Optimization of a structure of a model is one of the most promising. In this paper the Adaptive Multiscale Modelling Methodology is described, including Knowledge-Based adaptation of the multiscale model of precipitation kinetics during heat treatment. Core features of the methodology are introduced. The numerical model of heat treatment of an aluminium alloy based on the methodology and the dedicated framework is presented. Besides modelling of macroscopic heat transfer, models of precipitation kinetics based on thermodynamic calculations are included. To decrease computational requirements arising from coupling of the macroscale model and the thermodynamic models, metamodeling and similarity approaches are applied. Computations with several configuration of rules are described, as well as their results. Reliability and time consumption of computations are discussed. Future perspectives of combining of modelling and metamodeling in one, integrated model are discussed.

Cite as:

Macioł, P. (2018). Rule-based controlling of a multiscale model of precipitation kinetics. Computer Methods in Materials Science, 18(2), 64 – 78.

Article (PDF):


Multiscale modelling, Precipitation kinetic, Knowledge-based systems, Knowledge-based optimization, Aluminium alloys, Metamodeling


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