详情

Ballast and Soil Performance Separation by Using Instrumented Geo-grid & Machine Learning

项目名称：	Ballast and Soil Performance Separation by Using Instrumented Geo-grid & Machine Learning
摘要：	To study how different combinations of ballast and soil yield the same tie displacement under the same load, a simple FEM track model was built with different combinations of ballast and soil moduli. The results show that it is possible for tracks with different combinations of moduli to have the same overall track displacement under the same load. However, the interface between the ballast and the soil does show very different stress-strain characteristics for different scenarios although the overall vertical track displacement might be similar. There is a clear dividing line between the track with higher subgrade modulus and the one with lower subgrade modulus no matter what the ballast condition might be. In another words, the vertical stress vs. horizontal strain relationship at the interface of ballast and subgrade together with the track modulus measurement might be able to separate the ballast and soil performances. To measure and further study the vertical stress and the horizontal stain at the ballast-soil interface, this research team is proposing to install instrumentations such as stress cells and strain gauges on geogrids, which are typically installed in between the ballast and soil to improve the track bearing capacity. The final objective of this research is to develop ballast and soil performance characterization algorithms based on the instrumented geogrid data (both in the lab and the field) by using supervised machine learning techniques including the Logistic Regressions (LR) and the Supporting Vector Machine (SVM).
状态：	Active
资金：	148299
资助组织：	Office of the Assistant Secretary for Research and Technology
管理组织：	Center for Integrated Asset Management for Multimodal Transportation Infrastructure Systems (CIAMTIS)
项目负责人：	Donnell, Eric T
执行机构：	Pennsylvania State University, University Park
主要研究人员：	Huang, Hai
开始时间：	20220201
预计完成日期：	20230831
主题领域：	Geotechnology；Railroads