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作 者:张浩强 Zhang Haoqiang(China Nonferrous Metals Int l Mining Pakrut LLC.)
机构地区:[1]中色国矿帕鲁特有限责任公司
出 处:《黄金》2024年第10期59-67,共9页Gold
基 金:中国有色集团科技专项青年专项(2023KJZX003)。
摘 要:为探明某金矿废石全尾砂料浆的稳定性情况及硬化强度特性,对废石全尾砂料浆开展了泌水率、分层度及硬化强度测试。以泌水率及分层度为指标评价了充填料浆的稳定性;对充填体的单轴应力-应变曲线及破坏行为、强度的影响因素及演化规律进行了深入分析。基于试验数据建立了充填体强度回归模型,并通过补充试验对模型进行了验证。试验研究结果表明:料浆浓度68%以下时,废石占比对分层度的影响占主要地位;浓度高于68%时,废石的添加则对料浆离析的程度影响减弱,转而表现为灰砂比的增大或减小使得料浆抗离析性能降低。高灰砂比条件下,废石占比的增大将使得弹性应变值减小;反之,充填体的塑性特性随废石占比增大而减弱。充填体强度增长主要发生在养护龄期0~7 d,此后强度增长速率逐渐降低,影响充填体强度增长速率的因素:灰砂比>料浆浓度。建立的充填料浆配比参数预测模型误差控制在±15%以内,模型预测可信度尚可,可为后续配比优化提供一定参考依据。To determine the stability and hardening strength characteristics of waste rock-ungraded tailings slurry in a gold mine,tests were conducted on the slurry s bleeding rate,stratification degree,and hardening strength.The stability of the filling slurry was evaluated using the bleeding rate and stratification degree as indicators.An in-depth analysis was performed on the uniaxial stress-strain curve,failure behavior,factors influencing the strength,and the evolution of the filling body's strength.Based on the test data,a regression model for the strength of the filling body was established and verified through supplementary tests.The test results showed that when the concentration is below 68%,the proportion of waste rock has a dominant effect on the stratification degree.When the concentration exceeds 68%,the influence of waste rock addition on slurry segregation decreases,while changes in the cement-sand ratio lead to reduced anti-segregation performance.Under conditions of a high cement-sand ratio,increasing the proportion of waste rock reduces the elastic strain value,whereas the plasticity of the filling body decreases as the waste rock proportion increases.The main strength increase of the filling body occurs within the first 0-7 d of curing,after which the rate of strength growth gradually slows.Factors influencing the rate of strength growth are cement-sand ratio>slurry concentration.The established regression model for predicting the filling slurry mix parameters shows an error margin within±15%,making the model reliable for providing a reference for future mix optimization.
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