Rock burst is a kind of geological disaster in rock excavation of high stress areas.To evaluate intensity of rock burst,the maximum shear stress,uniaxial compressive strength,uniaxial tensile strength and rock elastic...Rock burst is a kind of geological disaster in rock excavation of high stress areas.To evaluate intensity of rock burst,the maximum shear stress,uniaxial compressive strength,uniaxial tensile strength and rock elastic energy index were selected as input factors,and burst pit depth as output factor.The rock burst prediction model was proposed according to the genetic algorithms and extreme learning machine.The effect of structural surface was taken into consideration.Based on the engineering examples of tunnels,the observed and collected data were divided into the training set,validation set and prediction set.The training set and validation set were used to train and optimize the model.Parameter optimization results are presented.The hidden layer node was450,and the fitness of the predictions was 0.0197 under the optimal combination of the input weight and offset vector.Then,the optimized model is tested with the prediction set.Results show that the proposed model is effective.The maximum relative error is4.71%,and the average relative error is 3.20%,which proves that the model has practical value in the relative engineering.展开更多
The effect of moisture content upon compressive mechanical behavior of concrete under impact loading was studied. The axial rapid compressive loading tests of over 50 specimens with five different saturations were exe...The effect of moisture content upon compressive mechanical behavior of concrete under impact loading was studied. The axial rapid compressive loading tests of over 50 specimens with five different saturations were executed. The technique "split Hopkinson pressure bar"(SHPB) was used. The impact velocity was 10 m/s with corresponding strain rate of 50 s-1. The compressive behavior of materials was measured in terms of stress-strain curves, dynamic compressive strength, dynamic increase factor(DIF) and critical strain at a maximum stress. The data obtained from test indicate that both ascending and descending portions of stress-stain curves are affected by moisture content. However, the effect is noted to be more significant in ascending portion of the stress-strain curves. Dynamic compressive strength is higher at lower moisture content and weaker at higher moisture content.Furthermore, under nearly saturated condition, an increase in compressive strength can be found. The effect of moisture content on the average DIF of concrete is not significant. The critical compressive strain of concrete does not change with moisture content.展开更多
基金Project(2013CB036004)supported by the National Basic Research Program of ChinaProject(51378510)supported by the National Natural Science Foundation of China
文摘Rock burst is a kind of geological disaster in rock excavation of high stress areas.To evaluate intensity of rock burst,the maximum shear stress,uniaxial compressive strength,uniaxial tensile strength and rock elastic energy index were selected as input factors,and burst pit depth as output factor.The rock burst prediction model was proposed according to the genetic algorithms and extreme learning machine.The effect of structural surface was taken into consideration.Based on the engineering examples of tunnels,the observed and collected data were divided into the training set,validation set and prediction set.The training set and validation set were used to train and optimize the model.Parameter optimization results are presented.The hidden layer node was450,and the fitness of the predictions was 0.0197 under the optimal combination of the input weight and offset vector.Then,the optimized model is tested with the prediction set.Results show that the proposed model is effective.The maximum relative error is4.71%,and the average relative error is 3.20%,which proves that the model has practical value in the relative engineering.
基金Project(50979032)supported by the National Natural Science Foundation of China
文摘The effect of moisture content upon compressive mechanical behavior of concrete under impact loading was studied. The axial rapid compressive loading tests of over 50 specimens with five different saturations were executed. The technique "split Hopkinson pressure bar"(SHPB) was used. The impact velocity was 10 m/s with corresponding strain rate of 50 s-1. The compressive behavior of materials was measured in terms of stress-strain curves, dynamic compressive strength, dynamic increase factor(DIF) and critical strain at a maximum stress. The data obtained from test indicate that both ascending and descending portions of stress-stain curves are affected by moisture content. However, the effect is noted to be more significant in ascending portion of the stress-strain curves. Dynamic compressive strength is higher at lower moisture content and weaker at higher moisture content.Furthermore, under nearly saturated condition, an increase in compressive strength can be found. The effect of moisture content on the average DIF of concrete is not significant. The critical compressive strain of concrete does not change with moisture content.
