黏粒含量与泥石流容重关系的PPR模型分析研究

现代矿业 ›› 2019, Vol. 35 ›› Issue (1): 60-64.

黏粒含量与泥石流容重关系的PPR模型分析研究

闫林，何建新，杨海华

新疆农业大学水利与土木工程学院

出版日期:2019-01-25 发布日期:2019-03-19
基金资助:
* 新疆水利水电重点学科基金项目（编号：XJXZ-2003-16）。

Study on the Relationship Between the Content of Clay Particles and the Density of Debris Flow Based on PPR Model

Yan Lin，He Jianxin，Yang Haihua

College of water conservancy and civil engineering,Xinjiang Agricultural University

Online:2019-01-25 Published:2019-03-19

摘要/Abstract

摘要： 通过投影寻踪回归分析法研究黏粒含量与泥石流容重之间的关系，结合泥石流动能机理和颗粒悬浮机理进行分析。结果表明：采用PPR单纯建模分析时，PPR模型和多项式模型的平均相对误差分别为5.3%和6.5%，在相对误差小于20%、15%、10%和5%时，PPR模型合格率相较于多项式模型分别提高了3.9%、10.6%、23%和24%。当采用PPR预留检验分析时，相较于多项式模型，建模分析组和预留检验组的合格率均有所提高。此外，黏粒含量与泥石流容重之间存在非线性相关，当黏粒含量小于6.78%时，泥石流容重随黏粒含量的增加而增大；当黏粒含量大于6.78%时，泥石流容重随着黏粒含量的增加而减小；当黏粒含量在6%~10%时，所形成的泥石流平均容重值最大，在2.05~2.20 g/cm3波动。PPR模型相较于多项式模型优势显著，其相对误差较小，回归拟合稳定，分析结果与泥石流动能机理和颗粒悬浮机理结论相吻合，进一步说明了PPR模型在兼容性和定量信息利用方面更具优越性。

关键词: 黏粒含量, 泥石流容重, 投影寻踪回归分析法, 泥石流动能机理, 颗粒悬浮机理

Abstract: This paper details the relationship between the content of clay particles and the density of debris flow by projection pursuit regression analysis, and the kinetic mechanism of debris flow and the mechanism of particle suspension were analyzed. The results show that the average relative error of PPR model and polynomial model is 5.3% and 6.5%, respectively when the PPR model is simple-modeled, when the relative error is less than 20%,15%,10% and 5%, the rate of the PPR model increases by 39%,10.6%,23% and 24%.When using PPR reservation test analysis, compared with the polynomial model, the qualification rate of the modeling analysis group and the reservation test group was improved. In addition, there is a non-linear correlation between the content of clay particles and the density of debris flow. When the content of clay particles is less than 6.78%, the density of debris flow increases with the increase of the content of clay particles, and when the content of clay is more than 6.78%, the density of debris flow decreases with the increase of the content of clay particles. When the clay content is between 6%~10%, the average bulk density of debris flow is the largest and fluctuates between 2.05~2.20 g/cm3. This paper proves that the PPR model has obvious advantages over the polynomial model, its relative error is smaller, the regression fitting is stable, the analysis result accords with the kinetic energy mechanism of debris flow and the conclusion of particle suspension mechanism, and further illustrates that PPR model has more advantages in compatibility and quantitative information utilization.

Key words: Clay content, Debris flow density, Projection pursuit regression analysis method, Kinetic energy mechanism of debris flow, Mechanism of particle suspension

闫林, 何建新, 杨海华. 黏粒含量与泥石流容重关系的PPR模型分析研究[J]. 现代矿业, 2019, 35(1): 60-64.

YAN Lin, HE Jian-Xin, YANG Hai-Hua. Study on the Relationship Between the Content of Clay Particles and the Density of Debris Flow Based on PPR Model[J]. Modern Mining, 2019, 35(1): 60-64.