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Energy and Resource Efficiency in Apatite-Nepheline Ore Waste Processing Using the Digital Twin Approach

机译:利用数字双胞胎方法的磷灰石 - 尼触线矿石废物处理中的能量和资源效率

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摘要

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.
机译:本文介绍了数字环境的“数字双胞胎”技术的一个组成部分的结构,并规定了研究对能源和磷灰石,霞石废弃物磷生产的追索效率技术评估来进行。他们处理的问题是在俄罗斯北极大陆架,那里有大量的采矿和加工厂集中的地区严重;因此,对于矿废物处置研究和高能效系统的创建是一个紧迫的科学难题。这项研究的对象是用于监测磷生产infoware。该应用研究方法是基于系统理论和系统的分析,技术控制,机器学习技术以及数值实验。 “数字双”元素的使用,以增加磷生产能源和资源效率是通过引进先进的算法和计算机体系结构,以尽量减少生产现代化成本的愿望来确定。对能源和资源效率的优化建议工具的算法部分是基于深层神经网络设备和热物理,热力学,化学品的以前开发的数学描述,并在黄磷生产系统发生的流体动力学过程。深层神经网络的合奏应用允许对磷技术过程多信道控制和用于技术系统操作期间的网络连续额外训练的执行,创建高精度数字拷贝,其被用于确定控制动作和优化能量和资源消耗。算法和软件元素是为了在数字环境下开发和仿真实验的结果。传导研究的主要贡献在于提出的结构对技术信息处理来优化根据能源和资源效率的标准磷生产体系,以及开发的软件实现该系统的优化参数。

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