The study is dedicated to modelling of the Quiet-Sun (QS) structure and dynamics by means of SDO/AIA and HMI data. To perform this we adopt a complex approach that combines several methods. We use DEM analysis to investigate temperature/density profiles during the events under consideration. We utilize a modified EBTEL model (Klimchuk et al, ApJ 2008) to reconstruct the dynamics of the QS heating. We employ MCT and MCC models to study structure and topology of local magnetic fields. Finally, we use Bayesian network approach to fit observational results into the model. All the methods are to be realized as a single (redistributible) module written in Python 2.7. To show the effectiveness of the developed framework we outline the recent results on analysis and simulation of strong nanoflare detected on 25 February 2011.