This paper describes Yixiang Aluminum Red Mud Heap Dam overflow pipes filling grouting governance programs,the implementation process and evaluation of effects.
The heat losses of aluminium reduction cells depend strongly on the heat transfer coefficients between the bath and side ledge or anodes. Using of anodes with slots can greatly change heat transfer. In order to investigate the heat loss dynamics in reduction cells with slotted anodes, a modeling of heat transfer coefficients in cells was firstly undertook. This enables understanding of how slotted anode changes heat dissipation from the bath. Then, a thermal field was been calculated by using heat transfer coefficients obtained in the first step. All these studies were carried out with 500kA cells.
In modern industrial systems, high-dimensional process data provide rich information for process monitoring. To make full use of local information of industrial process, a distributed robust dictionary pair learning (DRDPL) is proposed for refined process monitoring. Firstly, the global system is divided into several sub-blocks based on the reliable prior knowledge of industrial processes, which achieves dimensionality reduction and reduces process complexity. Secondly, a robust dictionary pair learning (RDPL) method is developed to build a local monitoring model for each sub-block. The sparse constraint with l2,1 norm is added to the analytical dictionary, and a low rank constraint is applied to the synthetical dictionary, so as to obtain robust dictionary pairs. Then, Bayesian inference method is introduced to fuse local monitoring information to global anomaly detection, and the block contribution index and variable contribution index are used to realize anomaly isolation. Finally, the effectiveness of the proposed method is verified by a numerical simulation experiment and Tennessee Eastman benchmark tests, and the proposed method is then successfully applied to a real-world aluminum electrolysis process.
Abstract The microseismicity associated with hydraulic fracturing in unconventional reservoir (i.e. shale gas play) has been investigated in the past several decades. Few experimental studies with respect to the focal mechanism and stress inversion was conducted, especially for Glutenite reservoir. In this study, the glutenite core was taken from the underground of 2600 m. Next, we performed scaled hydraulic fracturing tests on the cubic core (50×50×50mm) under geological principle stress condition in true tri-axial stress cell. Meanwhile, we monitored wellbore and pore pressure, and micro-seismic events during the fracture propagation from six faces of the cubic rock. Micro-seismic survey and events were interpreted to identify the induced fractures distribution in three dimension. Source mechanism and stress inversion were analyzed by moment tensor decomposition. The correlation of failure plane from microseismicity and tested sample implied that the microseismic events were accurately localized. The distribution of microseismic events from secondary and reopening tests indicated that the hydraulic fracturing induced microseismicity are mainly caused by significant tip effect (i.e. reactivate preexisting natural fractures). Based on source mechanism analysis, we found that the most of the failure are dominated by double-couple (DC). The correlation between original principle stress state and the one from STESI inversion indicated that the direction of principle stresses, especially for σ2 and σ3 inversed from reopening test, can be highly influenced by the hydraulic induced fracture or weak planes during secondary fracturing test.
'/%3e%3cuse xlink:href='%23a' transform='rotate(23.036 .093 25.536)'/%3e%3cuse xlink:href='%23a' transform='rotate(45.87 1.273 16.18)'/%3e%3cuse xlink:href='%23a' transform='rotate(69.945 .996 12.078)'/%3e%3cuse xlink:href='%23a' transform='rotate(20.66 -19.689 31.932)'/%3e%3c/svg%3e)