摘要
对目前国内外常用规范进行归纳和总结,得到5种常用方法: ASME—B31G,DM方法,Wes-2805—97,CVDA-84和J积分方法.本文将BP神经网络和遗传算法相结合,得到一种新的神经网络,并将这种神经网络成功用于计算腐蚀管道的剩余强度和最大允许注水压力.通过示例分析,对7种常用规范和本文提出的改进的遗传神经网络方法进行了比较,得到下面结论:不同计算方法计算得到的剩余强度和最大允许注水压力相差较大, Wes-2805-97规范、 ASME—B31G规范、 CVDA-84规范等都比J积分方法计算得到的剩余强度和最大允许注水压力偏大、偏保守; DM断裂力学方法计算得到的剩余强度和最大允许注水压力比J积分偏小、偏危险; J积分方法和基于J积分方法的改进的遗传神经网络方法计算结果比较接近,比较适中,可以认为是计算剩余强度和最大允许注水压力较好的方法.
In this paper, common criterions about residual strength evaluation at home and abroad are generalized and seven methods are acquired, namely ASME-B31G, DM, Wes-2805-97,CVDA-84 and J integral methods. BP neural network are combined with genetic algorithm (GA) named by modified BP-GA methods to successfully predict residual strength and critical pressure of injecting corrosion pipelines. Examples are shown that calculation results of every kind of method have great difference and calculating values of Wes-2805-97 criterion, ASME-B31G criterion and CVDA-84 criterion fracture mechanics model are conservative and higher than those of J integral methods, while calculating values of DM fracture mechanics model are dangerous and less than those of J integral methods and calculating values of modified BP-GA methods are close and moderate to those of J integral methods. Therefore modified BP-GA methods and J integral methods are considered better methods to calculate residual strength and critical pressure of injecting corrosion pipelines.
出处
《力学学报》
EI
CSCD
北大核心
2004年第3期281-287,共7页
Chinese Journal of Theoretical and Applied Mechanics
