Yunlong Guo

Mr. Yunlong Guo

Structural Engineering, Delft University of Technology, Delft, The Netherlands
orcid

Research Focus & Metrics

Academic Career Length

8Years (2019-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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7 June 2023 in Transportation Geotechnics
Verified
Journal Article
Open access
CSCan Shi
Can Shi
ZFZheng Fan
Zheng Fan
DCDavid P. Connolly
David P. Connolly
GJGuoqing Jing
Guoqing Jing
VMValeri Markine
Valeri Markine
Yunlong GuoYunlong Guo
Yunlong Guo

22 March 2022 in Sensors
Verified
Journal Article
Open access
PDF file
SWShilei Wang
Shilei Wang
GLGuixian Liu
Guixian Liu
Guoqing JingGuoqing Jing
Guoqing Jing
QFQiankuan Feng
Qiankuan Feng
HLHengbai Liu
Hengbai Liu
Yunlong GuoYunlong Guo
Yunlong Guo
In the past 20 years, many studies have been performed on ballast layer inspection and condition evaluation with ground penetrating radar (GPR). GPR is a non-destructive means that can reflect the ballast layer condition (fouling, moisture) by analysing the received signal variation. Even though GPR detection/inspection for ballast layers has become mature, some challenges still need to be stressed and solved, e.g., GPR indicator (for reflecting fouling level) development, quantitative evaluation for ballast fouling levels under diverse field conditions, rapid GPR inspection, and combining analysis of GPR results with other data (e.g., track stiffness, rail acceleration, etc.). Therefore, this paper summarised earlier studies on GPR application for ballast layer condition evaluation. How the GPR was used in the earlier studies was classified and discussed. In addition, how to correlate GPR results with ballast fouling level was also examined. Based on the summary, future developments can be seen, which is helpful for supplementing standards of ballast layer evaluation and maintenance.

1 August 2019 in Construction and Building Materials
Verified
Journal Article
Closed access
WJWenli Jia
Wenli Jia
VMValéri Markine
Valéri Markine
Yunlong GuoYunlong Guo
Yunlong Guo
GJGuoqing Jing
Guoqing Jing

27 August 2020 in Railway Engineering Science
Verified
Journal Article
Open access
PDF file
Yunlong GuoYunlong Guo
Yunlong Guo
CZChunfa Zhao
Chunfa Zhao
VMValéri Markine
Valéri Markine
CSCan Shi
Can Shi
Guoqing JingGuoqing Jing
Guoqing Jing
WZWanming Zhai
Wanming Zhai
To simulate ballast performance accurately and efficiently, the input in discrete element models should be carefully selected, including the contact model and applied particle shape. To study the effects of the contact model and applied particle shape on the ballast performance (shear strength and deformation), the direct shear test (DST) model and the large-scale process simulation test (LPST) model were developed on the basis of two types of contact models, namely the rolling resistance linear (RRL) model and the linear contact (LC) model. Particle shapes are differentiated by clumps. A clump is a sphere assembly for one ballast particle. The results show that compared with the typical LC model, the RRL method is more efficient and realistic to predict shear strength results of ballast assemblies in DSTs. In addition, the RRL contact model can also provide accurate vertical and lateral ballast deformation under the cyclic loading in LPSTs.

1 July 2020 in Construction and Building Materials
Verified
Journal Article
Closed access
Yunlong GuoYunlong Guo
Yunlong Guo
HFHAO FU
HAO FU
YQYu Qian
Yu Qian
VMValéri Markine
Valéri Markine
GJGuoqing Jing
Guoqing Jing

11 April 2022 in International Journal of Rail Transportation
Verified
Journal Article
Open access
Yunlong GuoYunlong Guo
Yunlong Guo
GLGuixian Liu
Guixian Liu
Guoqing JingGuoqing Jing
Guoqing Jing
JQJianjun Qu
Jianjun Qu
SWShilei Wang
Shilei Wang
WQWeile Qiang
Weile Qiang
Ground penetrating radar (GPR) has been applied for ballast layer inspection for two decades, mainly for the analysis of ballast layer fouling levels. However, some issues that affect the inspection quality remain unsolved, such as issues involving the GPR equipment quality (antenna) and the correlation between the GPR indicator and fouling index. With the aim of solving these two issues, in this paper, we investigated the difference between the results of two different antennas, the GPR data processing technique, indicators for the fouling level (by GPR signal processing) and the correlation between the indicators and fouling index (obtained by sieving). The results show that the antenna quality determines the inspection quality. The indicators can reflect the ballast layer fouling level, and they correlate the best with the fouling index (obtained by the percentage of particles passing through a 5 mm sieve size). This study is helpful for the future modification of railway ballast maintenance standards.