Russia is experiencing a steady shortage of raw materials for the production of alumina, and therefore, the search for unconventional cheap raw materials for its production is very relevant.In this paper, we consider two types of raw materials for the alumina production -ash and slag waste from CHPP-9 (Angarsk) and New Irkutsk CHPP (Irkutsk) PJSC “Irkutskenergo”, and wet magnetic separation tails obtained after the separation of iron-containing components.Laboratory studies were conducted on the sintering of the charge from ash and slag waste, tailings of wet magnetic separation with limestone and soda.Self-moldering sinter obtained; the recovery of alumina from them during leaching was 87% forNew Irkutsk CHPP and 83% for CHPP-9. The optimal conditions of experiments on sintering samples of ash-and-slag materials were determined.Two-stage desiliconization and carbonization of sinter leaching solutions, and calcination of aluminum hydroxide experiments were carried out.Alumina, corresponding in composition to metallurgical alumina (alumina content of 97,77%) was obtained.The technological scheme of alumina production from ash and slag waste of thermal power plants of the Irkutsk region is proposed.

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In a wide range of applications, heating or cooling systems provide not only temperature changes, but also small temperature gradients in a sample or industrial facility. Although a conventional proportional-integral-derivative (PID) controller usually solves the problem, it is not optimal because it does not use information about the main sources of change—the current power of the heater or cooler. The quality of control can be significantly improved by including a model of thermal processes in the control algorithm. Although the temperature distribution in the device can be calculated from a full-fledged 3D model based on partial differential equations, this approach has at least two drawbacks: the presence of many difficult-to-determine parameters and excessive complexity for control tasks. The development of a simplified mathematical model, free from these shortcomings, makes it possible to significantly improve the quality of control. The development of such a model using generative design techniques is considered as an example for a precision adiabatic calorimeter designed to measure the specific heat capacity of solids. The proposed approach, which preserves the physical meaning of the equations, allows for not only significantly improving the consistency between the calculation and experimental data, but also improving the understanding of real processes in the installation.