| 2. |
- Kazemi, Mania, et al.
(author)
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Investigation of Selective Reduction of Iron Oxide in Zinc Ferrite by Carbon and Hydrogen
- 2016
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In: Journal of Sustainable Metallurgy. - : Springer. - 2199-3831 .- 2199-3823. ; 2:1, s. 73-78
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Journal article (peer-reviewed)abstract
- The feasibility of selective reduction of iron oxide in zinc ferrite, which is one of the main components of electric arc furnace dust (EAFD), was examined. Experiments were carried out by using graphite powder or pure hydrogen gas as reducing agents. The carbothermal reduction experiments performed at temperatures between 973 and 1073 K in inert atmosphere indicated that the method was difficult to apply in practice due to slow rates of reaction and vaporization of zinc. Selective reduction of iron oxide in zinc ferrite was achieved by using pure hydrogen gas as the reductant. The iron oxide was reduced to metallic iron, while ZnO remained unreacted in the solid phase. As reaction times were increased at 873 K, ZnO was also reduced and zinc evaporated. The main advantages of H2 reduction are high reaction rates, low energy requirements, and no CO2 emissions. The addition of this process prior to the hydrometallurgical techniques for treatment of EAFD could overcome the difficulties for dissolution of zinc ferrite.
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| 3. |
- Lv, Z., et al.
(author)
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Blockchain-Based Communication for Digital Twins
- 2022
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In: Advances in Blockchain Technology for Cyber Physical Systems. - Cham : Springer International Publishing. - 2199-1073. ; , s. 193-210
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Book chapter (peer-reviewed)abstract
- Blockchain technology can safely and reliably track the creation process of digital twins. To ensure the data security in the case of untrusted multiple parties sharing data and to improve users’ satisfaction with the use of digital assets in daily transactions, in this article, the digital twin technology is combined with the blockchain technology, and for multiple scenarios in blockchain networks, a credible and efficient edge computing resource allocation method is proposed based on deep reinforcement learning (DRL) theory. The log storage system of the blockchain is mainly used as the interface for writing and reading data operation logs, and a hybrid storage strategy is put forward for the log storage system. As for the trusted resource allocation under the decentralized model of the blockchain network, to prevent the system from directly offloading the computing tasks submitted by the user each time to the edge server, first, the task is submitted to the system, and then a more reasonable resource allocation strategy is implemented with the user satisfaction as the standard. The simulation experiment results show that the improved environment after the introduction of the log storage system reduces the storage overhead by about 75% compared with the blockchain benchmark environment. When the number of servers is greater than 5, compared with other resource allocation algorithms, user satisfaction of the resource allocation algorithm based on DRL theory has been significantly improved, and compared with Q-learning algorithm, its user satisfaction has increased by 15%. In conclusion, the digital twins use credible source data as input. In this process, the blockchain ensures the security of data management, and finally, the data analysis is performed to predict events and evaluate related factors. The resource allocation method based on DRL realizes credible resource utilization based on recorded data on the blockchain.
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