(1. 北京科技大学 金属矿山高效开采与安全教育部重点实验室，北京 100083；
2. 北京科技大学 土木与资源工程学院，北京 100083；
3. 北京市建筑节能与建筑材料管理办公室，北京 101160)
摘 要: 针对全尾砂充填采用水泥作胶结剂导致的成本较高的问题，本文利用当地固废资源开发低成本胶凝材料，并基于矿山要求优化料浆配比。首先，基于试验材料进行物化分析，采用正交试验、极差分析和BP神经网络等方法确定镁渣胶凝材料配比为镁渣30%、脱硫石膏12%、矿渣微粉58%；然后，采用XRD和SEM等手段分析其水化机理；最后，基于熵权多属性决策法进行料浆配比优化试验，以7 d强度、28 d强度、坍落度、泌水率和充填成本为指标优化料浆配比。结果表明：采用镁渣胶凝材料时，料浆优化配比为胶砂比1:4，料浆质量浓度为72%，并进行试验验证，得到相应的7 d强度、28 d强度、坍落度和泌水率分别为2.72 MPa、8.49 MPa、20.0 cm和6.5%，均满足矿山要求，且充填成本为111 CNY/m3，较原来使用水泥时的充填成本192 CNY/m3，降低了42.2%。
关键字: 充填采矿法；镁渣；胶凝材料；神经网络；熵权多属性决策；配比优化
（1. Key Laboratory of High Efficient Mining and Safety of Metal Mine, Ministry of Education, University of Science and Technology Beijing, Beijing 100083, China;
2. School of Civil and Resource Engineering, University of Science and Technology Beijing, Beijing 100083, China;
3. Beijing Building Energy Conservation and Building Materials Management Office, Beijing 101160, China）
Abstract:In view of the high cost of cement for full tailings filling, the low-cost cementitious materials were developed by using local solid waste resources, and the slurry ratio was optimized based on mine requirements. Firstly, the proportion of magnesium slag cementitious material was determined by the orthogonal test, the range analysis and BP neural network based on the physicochemical analysis of the test materials. The mass fraction of magnesium slag (MS) was 30%, that of desulfurization gypsum (DSG) was 12% and that of ground granulated blast furnace slag (GGBFS) was 58%. Then, the hydration mechanism was analyzed by XRD and SEM. Finally, the slurry ratio optimization test was carried out based on entropy weight multi-attribute decision with 7 d strength, 28 d strength, slump, bleeding rate and filling cost as indexes. The results show that, when using magnesium slag cementitious material, the proportioning optimization of filling slurry is cement/tailings ratio (C/T) of 1:4, and mass concentration (MC) of 72%. The verification tests are carried out, and the corresponding 7 d strength, 28 d strength, slump and bleeding rate (BR) are obtained, which are 2.72 MPa, 8.49 MPa, 20.0 cm and 6.5%, respectively. These indexes meet the requirements of the mine, and the filling cost (FC) is 111 CNY/m3, which is 42.2% lower than the original FC of 192 CNY/m3 when using cement.
Key words: filling mining method; magnesium slag; cementitious material; neural network; entropy weight multi-attribute decision; proportioning optimization
