Study On Time-dependent Changes In Flow Properties Of Cemented Coal Gangue Backfill Materials

The exploitation of coal resources has caused a lot of environmental problems such as surface subsidence,coal gangue accumulation,surface water loss,groundwater pollution,and the difficulty ofmining under constructions,water and railways has lead to huge waste of coal,which is a urgent problem to be solved.According to studies both domestic and foreign,these problems can be resolved in an effective way by filling cemented coal gangue backfill materials into goaf to support the overlying rock.During backfillmining,the backfill material's flow properties are changed during the transpotation process from the ground to the goaf,which adversely affects the workability of the backfill material and the mechanic properties and durability of the backfill body after hardening.In this paper,the effects of fly ash content,coarse aggregate ratio,mass concentration and superplasticizer dosage on the time dependent change of flow properties of cemented coal gangue backfill materials(CCGBM)were investigated by laboratory test and theoretical analysis.The relationship between slump and yield stress was also established through theoretical derivation and it was in good coincidence with the test results,as well as the relationship between slump flow and plastic viscosity.Futhermore,the predicton model of rheologial parameters was build based on BP neural network.Follows are the main content and conclusions:(1)The slump and slump flow of twenty groups CCGBM were measured within 120min to research the influence of above-mentioned factors on the time dependent change of the fluidity.The results showed that the slump and slump flow decreased over time.As fly ash content increases,the slump loss and slump flow loss decrease.As the proportion of coarse aggregate increases,the slump and slump flow loss increase,but the increase is small.As mass concentration increases,the slump and slump flow loss increase first and then decrease,and the slump and slump flow loss of slurry with mass concentration of 81%is the largest.With the increase of superplasticizer dosage,the slump loss increased first and then decreased,and the slump flow loss gradually increased.The significance of influence on the fluidity loss of the backfill material is:fly ash content>superplasticizer dosage>mass concentration>coarse aggregate ratio.(2)The yield stress and plastic viscosity of twenty groups CCGBM were detected within 120min to study the influence of above-mentioned factors on the time dependent change of the yield stress and plastic viscosity.It was shown that yield stress increases over time while plastic viscosity first increases and then decreases.As fly ash content increases,the yield stress gradual decreases and the plastic viscosity increases with time.As the proportion of coarse aggregate increases,the yield stress and plastic viscosity increase over time.As mass concentration increases,the yield stress increases over time and the plastic viscosity increases first and then decreases.With the increase of superplasticizer dose,the yield stress and plastic viscosity increase over time.The significance of these four factors on the yield stress is:superplasticizer dosage>fly ash content>coarse aggregate proportion>mass concentration.The significance of these four factors on plastic viscosity is fly ash content>mass concentration>superplasticizer dosage>coarse aggregate proportion.(3)Using MATLAB software for 3D modeling and fitting,the prediction model of slump,slump flow,yield stress and plastic viscosity in material ratio and test time is obtained.Multiple correlation coefficients are greater than 0.9,the prediction model can be better used to predict slump,slump flow,yield stress and plastic viscosity of the backfill material with material ratio and test time.(4)The function between slump and yield stress is established,and verified through the experimental datas,as well as the relationship between slump flow and plastic viscosity.The results showed that these functions are highly accurate.According to the slump and the slump flow,the yield stress and plastic viscosity of CCGBM can be calculated using the functions,which provides theoretical guidance for the judgment of the rheological properties of CCGBM.(5)Based on the BP neural network tool in MATLAB software,the network structure of the slump-slump flow prediction model is[5 11 2]and the network structure of the yield stress-plastic viscosity prediction model is[5 9 2]by computational analysis and multiple training.The slump-slump flow prediction model shows that the Correlation coefficient R~2 of these models are 0.986 and0.997 respectively,and the Correlation coefficient R~2 of the yield stress-plastic viscosity prediction model are 0.867 and 0.77 correspondingly.Therefore,the BP neural network prediction model can be used to predict the slump-slump flow and yield stress-plastic viscosity of CCGBM with great accuration.