Search Results (5)

In this paper, a universal technology is proposed for processing low-titanium mineral raw material—apatite-nepheline ore waste, including its treatment with sulfuric or hydrochloric acid in a two-stage mode with a sequential increase in the concentration. This technique allowed us to remove nepheline and apatite in the first stage and achieve a titanium mineral content of TiO₂ of more than 30%; in the second stage, we were able to convert the titanium into its precursors—titanyl sulfate monohydrate TiOSO₄·H₂O and a hybrid rutile-silica composition. The key stage in the sorbent synthesis is the reaction of the precursor with a phosphoric acid solution. The preferred sequence of operations begins with the mechanical activation of the precursor, causing morphological changes in it, and subsequent treatment with phosphoric acid at different concentrations under atmospheric conditions and in an autoclave, accompanied by phase transformations. Conditions for the chemical reactions which regulated the composition and structure of the final product and, accordingly, its sorption activity were found. With the help of XFA, the phase compositions of the sorbents were identified, including the individual crystalline phase α-TiP obtained from TS or the crystalline phase αTi(HPO₄)₂∙H₂O, which is in an amorphous silica matrix obtained from a rutile–silica composition. Full article

This paper proposes multilevel architecture for an intelligent control system for the complex chemical energy technological process of yellow phosphorus production from apatite-nepheline ore processing waste. The research revealed that, when controlling this process, one has to deal with large amounts of multiformat and polymodal information, and control goals differ at different levels not only in effectiveness criteria, but also in the structuredness of the level problems. On this basis, it is proposed that intelligent methods be used for the implementation of information processes and control goals at individual levels and the whole system. The artificial intelligence methods underlying the informational model of a control system offer solutions to problems of analyzing control processes at different hierarchy levels, namely the initial level of sensing devices, the levels of programmable logic controllers, dispatching of control and production processes, enterprise management and strategic planning. Besides, the intelligent control system architecture includes analytical and simulation models of processes occurring in the multistage procedure of ore waste processing by a plant consisting of a granulating machine, a conveyor-type multichambercalcining machine, and an ore thermal furnace. The architecture of information support for the control system comprises a knowledge-based inference block intended for implementing the self-refinement of neural network and simulation models. Fuzzy logic methods are proposed for constructing this block. The paper considers the deployment of control algorithms for a phosphorus production system using the Matlab software environment on the basis of a modern complex system development paradigm known as the model-oriented design concept. Full article

The paper presents a structure of the digital environment as an integral part of the “digital twin” technology, and stipulates the research to be carried out towards an energy and recourse efficiency technology assessment of phosphorus production from apatite-nepheline ore waste. The problem with their processing is acute in the regions of the Russian Arctic shelf, where a large number of mining and processing plants are concentrated; therefore, the study and creation of energy-efficient systems for ore waste disposal is an urgent scientific problem. The subject of the study is the infoware for monitoring phosphorus production. The applied study methods are based on systems theory and system analysis, technical cybernetics, machine learning technologies as well as numerical experiments. The usage of “digital twin” elements to increase the energy and resource efficiency of phosphorus production is determined by the desire to minimize the costs of production modernization by introducing advanced algorithms and computer architectures. The algorithmic part of the proposed tools for energy and resource efficiency optimization is based on the deep neural network apparatus and a previously developed mathematical description of the thermophysical, thermodynamic, chemical, and hydrodynamic processes occurring in the phosphorus production system. The ensemble application of deep neural networks allows for multichannel control over the phosphorus technology process and the implementation of continuous additional training for the networks during the technological system operation, creating a high-precision digital copy, which is used to determine control actions and optimize energy and resource consumption. Algorithmic and software elements are developed for the digital environment, and the results of simulation experiments are presented. The main contribution of the conducted research consists of the proposed structure for technological information processing to optimize the phosphorus production system according to the criteria of energy and resource efficiency, as well as the developed software that implements the optimization parameters of this system. Full article

The waste of apatite-nepheline ore processing was chosen as the material of study for the present investigation. The chemical and phase compositions have been analyzed and the route of the new technology has been developed. Treatment of the waste with diluted hydrochloric acid enables to separate apatite, nepheline, titano-magnetite minerals from titanite (CaSiTiO₅). The obtained titanite concentrate contains 30–32% of titanium dioxide. Interaction of titanite with hydrochloric acid under heating and stirring conditions results in calcium leaching. The titanite decomposition is accompanied by titanium and silica oxides precipitation. The resulting solid has been used as a precursor for the synthesis of functional materials. Mechanochemical activation of the precursor provides the structural and morphological disorder of the initial particles. Thermodynamic stability of activated particles is achieved by chemisorption or roasting. Full article

The development of apatite and rare-metal deposits of the Khibiny and Lovozero—the world’s largest ultrabasic massifs located in the Kola Alkaline Province—is accompanied by accumulation of huge amounts of sandy tailings dumps, about half consisting of nepheline. These tailings, on the one hand, pose a real threat of environmental pollution. On the other hand, they are “technogenic deposits” that contain reserves of valuable components (Na₂O, K₂O, Al₂O₃, etc.). In this paper, methods of processing of the nepheline-containing mining waste using mechanical activation to produce binding materials—geopolymers and blended cements—are observed. The advantages of combining the nepheline containing tailings dumps with other mining wastes accumulated in the region, such as Cu–Ni slag, are presented. Full article