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铝钨合金高温流变行为及神经网络本构关系模型

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采用Gleeble‐1500热模拟实验机研究铝钨合金在变形温度为450℃~540℃、应变速率为0.001 s-1~1 s-1下单道次压缩过程的高温流变行为。基于BP神经网络建立铝钨合金本构关系模型。在该模型中,输入变量为应变、应变速率和变形温度,输出变量为流变应力。与传统方法相比,该本构关系模型的测试数据可以为描述整个变形过程提供一个很好的代表性,也为开发铝钨合金本构关系提供方便和有效的途径。
High temperature flow behaviors and neural network based constitutive model of aluminum-tungsten alloy
The flow behaviors of the as‐extruded aluminum‐tungsten alloy were studied through single‐pass compression experi‐ments by using Gleeble1500 simulator within temperature range of 450℃ ~540℃ and strain rate range of 0.001s-1 ~1s-1 . And the constitutive relationship model for this alloy was successfully developed by using BP neural network . In the proposed model , the input variables are strain ,strain rate and temperature ,while the flow stress is the output variable .It was found that the es‐tablished constitutive relationship model could provide a good representation of the test data and better describe the whole defor‐ming process compared with that by the traditional method . Moreover , the suggested model is available to provide a convenient and effective way to develop the constitutive relationship for aluminum‐tungsten alloys .

aluminum-tungsten alloyflow behaviorconstitutive relationshipBP neural network

郭拉凤、张治民、李保成、薛勇

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中北大学 材料科学与工程学院,太原 030051

中北大学 机电工程学院,太原 030051

铝钨合金 流变行为 本构关系 BP神经网络

国家973计划前期专项资助项目山西省自然科学基金资助项目山西省研究生优秀创新资助项目

2012CB6268082013011022-420133098

2015

塑性工程学报
中国机械工程学会

塑性工程学报

CSTPCDCSCD北大核心
影响因子:0.46
ISSN:1007-2012
年,卷(期):2015.(1)
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