In order to precisely predict the hazard degree of goaf(HDG), the RS-TOPSIS model was built based on the results of expert investigation. To evaluate the HDG in the underground mine, five structure size factors, i.e. ...In order to precisely predict the hazard degree of goaf(HDG), the RS-TOPSIS model was built based on the results of expert investigation. To evaluate the HDG in the underground mine, five structure size factors, i.e. goaf span, exposed area, goaf height, goaf depth, and pillar width, were selected as the evaluation indexes. And based on rough dependability in rough set(RS)theory, the weights of evaluation indexes were identified by calculating rough dependability between evaluation indexes and evaluation results. Fourty goafs in some mines of western China, whose indexes parameters were measured by cavity monitoring system(CMS), were taken as evaluation objects. In addition, the characteristic parameters of five grades' typical goafs were built according to the interval limits value of single index evaluation. Then, using the technique for order preference by similarity to ideal solution(TOPSIS), five-category classification of HDG was realized based on closeness degree, and the HDG was also identified.Results show that the five-category identification of mine goafs could be realized by RS-TOPSIS method, based on the structure-scale-effect. The classification results are consistent with those of numerical simulation based on stress and displacement,while the coincidence rate is up to 92.5%. Furthermore, the results are more conservative to safety evaluation than numerical simulation, thus demonstrating that the proposed method is more easier, reasonable and more definite for HDG identification.展开更多
Some attributes are uncertain for evaluation work because of incomplete or limited information and knowledge.It leads to uncertainty in evaluation results.To that end,an evaluation method,uncertainty entropy-based exp...Some attributes are uncertain for evaluation work because of incomplete or limited information and knowledge.It leads to uncertainty in evaluation results.To that end,an evaluation method,uncertainty entropy-based exploratory evaluation(UEEE),is proposed to guide the evaluation activities,which can iteratively and gradually reduce uncertainty in evaluation results.Uncertainty entropy(UE)is proposed to measure the extent of uncertainty.First,the belief degree distributions are assumed to characterize the uncertainty in attributes.Then the belief degree distribution of the evaluation result can be calculated by using uncertainty theory.The obtained result is then checked based on UE to see if it could meet the requirements of decision-making.If its uncertainty level is high,more information needs to be introduced to reduce uncertainty.An algorithm based on the UE is proposed to find which attribute can mostly affect the uncertainty in results.Thus,efforts can be invested in key attribute(s),and the evaluation results can be updated accordingly.This update should be repeated until the evaluation result meets the requirements.Finally,as a case study,the effectiveness of ballistic missiles with uncertain attributes is evaluated by UEEE.The evaluation results show that the target is believed to be destroyed.展开更多
The principle of sonic wave measurement was introduced, and cumulative damage effects of underground engineering rock mass under blasting load were studied by in situ test, using RSM-SY5 intelligent sonic wave apparat...The principle of sonic wave measurement was introduced, and cumulative damage effects of underground engineering rock mass under blasting load were studied by in situ test, using RSM-SY5 intelligent sonic wave apparatus. The blasting test was carried out for ten times at some tunnels of Changba Lead-Zinc Mine. The damage depth of surrounding rock caused by old blasting excavation （0.8-1.2 m） was confirmed. The relation between the cumulative damage degree and blast times was obtained. The results show that the sonic velocity decreases gradually with increasing blast times, hut the damage degree （D） increases. The damage cumulative law is non-linear. The damage degree caused by blast decreases with increasing distance, and damage effects become indistinct. The blasting damage of rock mass is anisotropic. The damage degree of rock mass within charging range is maximal. And the more the charge is, the more severe the damage degree of rock mass is. The test results provide references for researches of mechanical parameters of rock mass and dynamic stability analysis of underground chambers.展开更多
基金Project(51074178)supported by the National Natural Science Foundation of ChinaProject(2011ssxt274)supported by the Graduated Students’ Research and Innovation Foundation of Central South University of China+1 种基金Project(2011QNZT087)supported by the Graduated Students’ Free Exploration Foundation of Central South University of ChinaProject(1343-76140000011)supported by Scholarship Award for Excellent Doctoral Student granted by Ministry of Education,China
文摘In order to precisely predict the hazard degree of goaf(HDG), the RS-TOPSIS model was built based on the results of expert investigation. To evaluate the HDG in the underground mine, five structure size factors, i.e. goaf span, exposed area, goaf height, goaf depth, and pillar width, were selected as the evaluation indexes. And based on rough dependability in rough set(RS)theory, the weights of evaluation indexes were identified by calculating rough dependability between evaluation indexes and evaluation results. Fourty goafs in some mines of western China, whose indexes parameters were measured by cavity monitoring system(CMS), were taken as evaluation objects. In addition, the characteristic parameters of five grades' typical goafs were built according to the interval limits value of single index evaluation. Then, using the technique for order preference by similarity to ideal solution(TOPSIS), five-category classification of HDG was realized based on closeness degree, and the HDG was also identified.Results show that the five-category identification of mine goafs could be realized by RS-TOPSIS method, based on the structure-scale-effect. The classification results are consistent with those of numerical simulation based on stress and displacement,while the coincidence rate is up to 92.5%. Furthermore, the results are more conservative to safety evaluation than numerical simulation, thus demonstrating that the proposed method is more easier, reasonable and more definite for HDG identification.
基金the National Natural Science Foundation of China(61872378).
文摘Some attributes are uncertain for evaluation work because of incomplete or limited information and knowledge.It leads to uncertainty in evaluation results.To that end,an evaluation method,uncertainty entropy-based exploratory evaluation(UEEE),is proposed to guide the evaluation activities,which can iteratively and gradually reduce uncertainty in evaluation results.Uncertainty entropy(UE)is proposed to measure the extent of uncertainty.First,the belief degree distributions are assumed to characterize the uncertainty in attributes.Then the belief degree distribution of the evaluation result can be calculated by using uncertainty theory.The obtained result is then checked based on UE to see if it could meet the requirements of decision-making.If its uncertainty level is high,more information needs to be introduced to reduce uncertainty.An algorithm based on the UE is proposed to find which attribute can mostly affect the uncertainty in results.Thus,efforts can be invested in key attribute(s),and the evaluation results can be updated accordingly.This update should be repeated until the evaluation result meets the requirements.Finally,as a case study,the effectiveness of ballistic missiles with uncertain attributes is evaluated by UEEE.The evaluation results show that the target is believed to be destroyed.
基金Project (50490272) supported by the National Natural Science Foundation of ChinaProject(040109) supported by the Doctor Degree Paper Innovation Engineering of Central South University
文摘The principle of sonic wave measurement was introduced, and cumulative damage effects of underground engineering rock mass under blasting load were studied by in situ test, using RSM-SY5 intelligent sonic wave apparatus. The blasting test was carried out for ten times at some tunnels of Changba Lead-Zinc Mine. The damage depth of surrounding rock caused by old blasting excavation （0.8-1.2 m） was confirmed. The relation between the cumulative damage degree and blast times was obtained. The results show that the sonic velocity decreases gradually with increasing blast times, hut the damage degree （D） increases. The damage cumulative law is non-linear. The damage degree caused by blast decreases with increasing distance, and damage effects become indistinct. The blasting damage of rock mass is anisotropic. The damage degree of rock mass within charging range is maximal. And the more the charge is, the more severe the damage degree of rock mass is. The test results provide references for researches of mechanical parameters of rock mass and dynamic stability analysis of underground chambers.
