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Predictive Modeling

Kintech Lab service in R&D fields in different industries is based on the mechanistic modeling of processes, i.e., on understanding the mechanism of corresponding process. This approach allows one to consider complex problems, for which intuition-driven solutions do not work or the number of possible solutions is intractable for direct experimental verification. Mechanistic modeling in these cases saves resources for R&D investigations and provides knowledge-driven solutions.

The elaboration of a detailed kinetic mechanism is a key step in predictive modeling. Kintech Lab applies  this technique as a powerful tool for simulating complex physicochemical phenomena and the development of accurate models. In that case, model building is based on underlying physics and chemistry governing the process behavior. The development of a mechanistic model implies the use of the fundamental knowledge of interactions between process variables in order to define model structure.

Mechanisms as Key Element of Mechanistic Modeling Technique:
Predictive Modeling, Mechanisms as Key Element of Mechanistic Modeling Technique

Using detailed kinetic mechanism allows the model to be predictive in a wide range of parameters.

One of the main R&D servises of Kintech Lab is constructing, analysis and reducing of new and known mechanisms. Combining of leading kinetic experts and multilevel-multiphysisc methodology permits us to construct reliable mechanisms in different application areas.

Mechanisms reliability is provided by using state-of-art computational techniques and codes (including in-house software) which give a possibility of evaluating properties of macrosystems starting from level of elementary processes up to the reactor model level. Physical and chemical phenomena on very different time and space scales can be taken into account by using of multiscale-multiphysiscs methodology at different levels of refining. This refining covers a very wide region of parameters starting from the structure of species up to the macro chemical mechanism of their transformation. Additional inhouse chemistry oriented rigorous mathematical methods like sensitivity and rate production analysis permits us to reduce detailed chemical mechanism for computational fluid dynamics (CFD) needs.

See applications for specific industries