...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Journal of Mechanical Science and Technology >Estimation of flow curve and friction coefficient by means of a one-step ring test using a neural network coupled with FE simulations
【24h】

Estimation of flow curve and friction coefficient by means of a one-step ring test using a neural network coupled with FE simulations

机译：通过使用神经网络结合有限元模拟的一步环试验，估算流量曲线和摩擦系数

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

This paper is concerned with application of artificial neural network (ANN) to the ring compression test for simultaneous determination of the flow curve of the material and the friction factor. The developed ANN model was trained using data from 700 finite-element (FE) simulations of the ring test. The load curve of this test and the final internal diameter of the sample are the inputs for this ANN model and the outputs are the strength coefficient, strain hardening exponent and the friction factor. It was found that the outputs of the developed ANN model were in good agreement with the experimental results.
机译：本文涉及人工神经网络（ANN）在环压缩试验中同时确定材料流动曲线和摩擦系数的应用。使用来自环形测试的700个有限元（FE）模拟的数据训练了开发的ANN模型。该测试的载荷曲线和样品的最终内径是该ANN模型的输入，输出是强度系数，应变硬化指数和摩擦系数。发现所开发的人工神经网络模型的输出与实验结果非常吻合。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号