A lot of researchers are developing new DEM parameters calibration approaches based on an experiment plan or the use of learning algorithms. This research is aimed at improving iterative algorithms frequently used for calibration. The big time consumption as a main problem of iterative algorithms is questioned. It is proposed to use Random forest algorithm to determine DEM parameters impact on the measured bulk responses. Measured responses are the parameters obtained by image processing using a technical vision system. As a result of 200 experiments processing, DEM parameters impact values on each bulk response were generated and presented as histograms. Obtained results were interpreted on the basis of the bulk material behavior and its physical properties. There is a discussion on the possibility of developing a universal DEM parameters calibration method based on the iterative algorithm.

The problem of DEM models calibration is considered in the article. It is proposed to divide models input parameters into those that require iterative calibration and those that are recommended to measure directly. A new method for model calibration based on the design of the experiment for iteratively calibrated parameters is proposed. The experiment is conducted using a specially designed stand. The results are processed with technical vision algorithms. Approximating functions are obtained and the error of the implemented software and hardware complex is estimated. The prospects of the obtained results are discussed.

Dramatic changes in the global energy market due to COVID-19 pandemic, the OPEC+ agreement, and increasing rates of green energy share in the world community have brought negative effects on the oil sector. In the long term, oil will reduce its importance as an energy resource, but for many years, it will continue to play a significant role in the world of energy. The oil industry has huge potential in terms of technical expertise, management, and financial resources to reduce its greenhouse emissions and ensuring an affordable availability of predictable energy. However, nowadays this sector has lost investing attractiveness. It is an interdisciplinary problem with a solution at the intersection of different stakeholders’ interests. The article is a review one and devoted to the issue of the implementation a public-private partnership (PPP) as a key tool that allows the use of the state and the business’ available resources to achieve the sector’s sustainable development and investment attractiveness. Research and analysis of PPP were based on foreign and domestic literature, using classification and generalization methods, retrospective and critical analysis. This paper contains identified groups of drivers, constraints, and recommendations for further successful PPP implementation in the Russian case.