In the early Proterozoic the Li'eryu Formation and Dashiqiao Formation of eastern Liaoning province, China, there are distributed Mg-rich carbonate rock formations, in which large to superlarge deposits of boron, ...In the early Proterozoic the Li'eryu Formation and Dashiqiao Formation of eastern Liaoning province, China, there are distributed Mg-rich carbonate rock formations, in which large to superlarge deposits of boron, magnesite, talc, Xiuyan jade etc. occur. The formation of these magnesian nonmetallic deposits was related to early Proterozoic evaporates; then these deposits underwent reworking of regional metamorphism and hydrothermal metasomatism during the Lüliang orogeny and tectono-magmatism during the Indosinian-Yanshanian. Among other things, the Mg-rich carbonates formations, minerogenetic structures and ore-forming fluids played a controlling role in the formation of the mineral deposits. Therefore, it can be concluded that the mineral deposits are products of combined processes of the coupling of ore source field, fluid field, thermal field (energy field) and stress field under certain time-space conditions in the early Proterozoic and the late-stage superimposed reworking of tectono-magmatism.展开更多
On the basis of a simulated bright continuous annealing experimental machine, a process control model for heating system was built. The heating model was simplified and self-learning parameters were normalized to enha...On the basis of a simulated bright continuous annealing experimental machine, a process control model for heating system was built. The heating model was simplified and self-learning parameters were normalized to enhance the precision of temperature control. By means of the division of temperature layers and the exponential smoothing disposal of the annealing experimental data, the self-learning of the heating model was carried out. Through exponentially smoothing the deviation of self-learning parameters of the heated phase in heating process, dynamic modifications of self-learning parameters and heating electric current were carried out, and the precision of temperature control was confirmed. The application indicated that the process control model for the heating system can control temperature with high precision, and the deviation can be controlled within 8 ℃.展开更多
基金supported by the Foundation for Development of Geological Science and Technology of the former Ministry of Geology and Mineral Resources of China grant HY979830
文摘In the early Proterozoic the Li'eryu Formation and Dashiqiao Formation of eastern Liaoning province, China, there are distributed Mg-rich carbonate rock formations, in which large to superlarge deposits of boron, magnesite, talc, Xiuyan jade etc. occur. The formation of these magnesian nonmetallic deposits was related to early Proterozoic evaporates; then these deposits underwent reworking of regional metamorphism and hydrothermal metasomatism during the Lüliang orogeny and tectono-magmatism during the Indosinian-Yanshanian. Among other things, the Mg-rich carbonates formations, minerogenetic structures and ore-forming fluids played a controlling role in the formation of the mineral deposits. Therefore, it can be concluded that the mineral deposits are products of combined processes of the coupling of ore source field, fluid field, thermal field (energy field) and stress field under certain time-space conditions in the early Proterozoic and the late-stage superimposed reworking of tectono-magmatism.
基金Item Sponsored by National Natural Science Foundation of China (50527402)
文摘On the basis of a simulated bright continuous annealing experimental machine, a process control model for heating system was built. The heating model was simplified and self-learning parameters were normalized to enhance the precision of temperature control. By means of the division of temperature layers and the exponential smoothing disposal of the annealing experimental data, the self-learning of the heating model was carried out. Through exponentially smoothing the deviation of self-learning parameters of the heated phase in heating process, dynamic modifications of self-learning parameters and heating electric current were carried out, and the precision of temperature control was confirmed. The application indicated that the process control model for the heating system can control temperature with high precision, and the deviation can be controlled within 8 ℃.
