Large complex 7A85 aluminum wing-body joint was forged employing isothermal forging process and its mechanical properties were studied.The tensile strength after forging is up to 587.5 MPa in longitudinal direction,15...Large complex 7A85 aluminum wing-body joint was forged employing isothermal forging process and its mechanical properties were studied.The tensile strength after forging is up to 587.5 MPa in longitudinal direction,15% higher than that using free forging.Moreover,the tensile strength of the forging is almost the same in three directions.Isothermal forging also performs well on overall fracture toughness,with a maximum value of 39.8 MPa·m1/2,and that of short transverse direction all reaches 36 MPa·m1/2 and above,with a maximum relative error of only 3.6%.The results indicate that the isothermal forging leads to better performance as well as higher uniformity in mechanical properties.展开更多
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
基金Project(2010CB731701) supported by the National Basic Research Program of ChinaProject(2012ZX04010-081) supported by National Science and Technology Major Program of China
文摘Large complex 7A85 aluminum wing-body joint was forged employing isothermal forging process and its mechanical properties were studied.The tensile strength after forging is up to 587.5 MPa in longitudinal direction,15% higher than that using free forging.Moreover,the tensile strength of the forging is almost the same in three directions.Isothermal forging also performs well on overall fracture toughness,with a maximum value of 39.8 MPa·m1/2,and that of short transverse direction all reaches 36 MPa·m1/2 and above,with a maximum relative error of only 3.6%.The results indicate that the isothermal forging leads to better performance as well as higher uniformity in mechanical properties.
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.
