初始弹性侧移刚度比对框支配筋砌块砌体剪力墙结构的薄弱层位置、弹塑性变形性能和破坏形态的影响较大。
The value of lateral stiffness ratio has significant influence on the place of weak story, elastic-plastic distortion and failure characteristic.
本文根据液压胀形的特点，利用塑性变形原理，提出评定板材成形性能的液压胀形试验法。
According to the character of hydraulic bulge and the theory of plastic deformation, a testing method of hydraulic bulge to evaluate the forming property of sheet metals is put forward.
结果表明，BP神经网络用于材料超塑性变形后的力学性能及晶粒尺寸预测是可行的，其预测误差小于7%。
The results show that BP artificial neural network can be used in predicting mechanical properties and grain size of materials after superplastic forming and its predicting error is less than 7%.
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