摘要
采用均匀设计的方法来优化安排试验,以水泥、石灰、碎石、风积砂为原材料进行试验研究,得到水泥石灰稳定风积砂的最佳含水量、最大干密度、无侧限抗压强度、回弹模量等指标,得到满足工程要求的最佳配合比为,水泥掺量900 g、石灰掺量1 000 g、碎石掺量3 000 g、风积砂掺量5 300 g。通过现场工业性试验和观测,结果表明:试验段水泥石灰稳定风积砂基层状况良好,且弯沉值满足有关的要求。将人工神经网络应用于水泥石灰稳定风积砂无侧限抗压强度的预测中,预测结果有较高的精度,同时对工程具有一定的指导意义。
Method by uniform design is used to posit majorized experiment, experimental investigation is carried out with raw materials of cement, lime, macadam and Aeolian, obtaining the target of optimal moisture content, maximum dry density, unconfined compression strength, modulus of resilience and so on for cement and lime stabilizing Aeolian soil, gaining the optimal mix for blending composition to meet project requirement is, cement is 900g,lime is 1000g,macadam is 3000g,Aeolian is 5300g. Tharough field engineering industrial experiment and observation, results indicate working section base is in good condition and flexure value can satisfy related demands. Artificial neural network is used in predicting unconfined compressive strength, obtaining higher precision in predicting outcome, which has some guiding significance for projects.
出处
《辽宁工程技术大学学报（自然科学版）》
EI
CAS
北大核心
2007年第3期366-368,共3页
Journal of Liaoning Technical University (Natural Science)
基金
辽宁省教育厅高等学校科学研究基金资助项目(2004D120)
关键词
风积砂土
均匀设计
路面基层
人工神经网络
无侧限抗压强度
预测
Aeolian soil
uniform design
road surface base
artificial neural network
unconfined compression strength： predicting
