News

An unusual method for welding dissimilar materials is being investigated at Novosibirsk State Technical University.  The unique technology allows you to connect parts that previously could not be welded using other methods.

Novosibirsk State Technical University (NETI) has proposed optimizing the operation of hydroelectric power plants using predictive models based on machine learning methods. This will make it possible to use water more efficiently and minimize idle discharges during flood periods.

Scientists from Novosibirsk State Technical University (NETI) have proposed using mathematical models to monitor dangerous developing defects in power transformers.

Scientists at Novosibirsk State Technical University (NETI) have developed a corrosion-resistant coating based on high-entropy alloys reinforced with refractory particles. Owing to its increased corrosion resistance, wear resistance and ductility, the coating can be used in the chemical industry and the energy sector.

Novosibirsk State Technical University (NSTU) investigated the features of the structure formation and evaluated the properties of the composite coatings of the copper-chromium system obtained from detonation spraying. The work was carried out jointly with scientists from the SB RAS Institute of Hydrodynamics named after M. A. Lavrentieva.

A training program for unmanned aerial vehicle operators is being launched at Novosibirsk State Technical University (NSTU). Students of the program will master the skills of technical and flight operation of multirotor and aircraft-type UAVs.

Scientists from Novosibirsk State Technical University (NETI) have proposed an innovative method of soil purification from oil and petroleum products. The basis of the development was a protective shield that helps to quickly collect mixtures of hydrocarbons after their spill.

Novosibirsk State Technical University (NETI) has developed a method for multi-stage predictive monitoring of the success of asynchronous motor start-up. The unique method, which has no analogues in Russia and abroad, makes it possible to ensure the reliable operation of local power supply systems with commensurate total generation capacity and large single engines.

Students of Novosibirsk State Technical University (NETI) are developing a system for analyzing the operating modes of the heating network using machine learning methods that will predict emergencies and technical accidents on heating networks.