This paper presents the erosion results of the AISI H13 steel impinged by resin-bonded silica sand, using a testing rig that closely simulates the real blowing conditions during industrial core-making. Steel specimens...This paper presents the erosion results of the AISI H13 steel impinged by resin-bonded silica sand, using a testing rig that closely simulates the real blowing conditions during industrial core-making. Steel specimens were heat treated to obtain hardness of 294, 445 and 595 HV200 (29, 45 and 55 HRC). Erosion tests were carried out at impingement angles from 20° to 90° and air drag pressures of 1.38, 2.07 and 2.76 bar (20, 30 and 40 psi). The main results are summarized as follows:(i) The harder material, the lower erosion;(ii) the maximum erosion rate is at 30°;(iii) Little difference in erosion rate at impact angle of 60° and 90° for a constant pressure tested regardless of the hardness level;(iv) As the pressure increases, so does the erosion rate, being more sensitive for low impact angles. Finally, a differential form of the general erosion equation is applied on a practical core-making case to evaluate the erosion rate of the H13 steel at 30° and 90° impingement angles.展开更多
介绍了 BP 神经网络的基本原理,基于 Matlab 工具箱建立了预测光面爆破效果神经网络模型,从岩石力学性质、周边爆破参数两个方面对光面爆破效果进行分析和预测。为了加快神经网络模型的收敛速度,增强其跳出局部极小点的能力,采用了附加...介绍了 BP 神经网络的基本原理,基于 Matlab 工具箱建立了预测光面爆破效果神经网络模型,从岩石力学性质、周边爆破参数两个方面对光面爆破效果进行分析和预测。为了加快神经网络模型的收敛速度,增强其跳出局部极小点的能力,采用了附加动量法和自适应学习速率结合的方法对网络进行训练,利用该模型对光爆效果进行了预测,取得了很好的效果。展开更多
基金financially supported by NEMAK S.A. and Industria Meccanica Bassi Luigi&Co
文摘This paper presents the erosion results of the AISI H13 steel impinged by resin-bonded silica sand, using a testing rig that closely simulates the real blowing conditions during industrial core-making. Steel specimens were heat treated to obtain hardness of 294, 445 and 595 HV200 (29, 45 and 55 HRC). Erosion tests were carried out at impingement angles from 20° to 90° and air drag pressures of 1.38, 2.07 and 2.76 bar (20, 30 and 40 psi). The main results are summarized as follows:(i) The harder material, the lower erosion;(ii) the maximum erosion rate is at 30°;(iii) Little difference in erosion rate at impact angle of 60° and 90° for a constant pressure tested regardless of the hardness level;(iv) As the pressure increases, so does the erosion rate, being more sensitive for low impact angles. Finally, a differential form of the general erosion equation is applied on a practical core-making case to evaluate the erosion rate of the H13 steel at 30° and 90° impingement angles.
文摘介绍了 BP 神经网络的基本原理,基于 Matlab 工具箱建立了预测光面爆破效果神经网络模型,从岩石力学性质、周边爆破参数两个方面对光面爆破效果进行分析和预测。为了加快神经网络模型的收敛速度,增强其跳出局部极小点的能力,采用了附加动量法和自适应学习速率结合的方法对网络进行训练,利用该模型对光爆效果进行了预测,取得了很好的效果。
