TY - JOUR
T1 - Probabilistic analysis of tunnel longitudinal performance based upon conditional random field simulation of soil properties
AU - Gong, Wenping
AU - Juang, C. Hsein
AU - Martin, James R.
AU - Tang, Huiming
AU - Wang, Qiangqing
AU - Huang, Hongwei
N1 - Publisher Copyright:
© 2017 Elsevier Ltd
PY - 2018/3
Y1 - 2018/3
N2 - Because of the inherent spatial variability of soil properties and the limited number of boreholes that can be afforded in a typical project, the soil properties at given geotechnical sites could not be known with certainty, which leads to an uncertainty in the predicted performance of a geotechnical system. For such uncertain system, probabilistic analysis is often used to assess its performance considering uncertainty. This paper presents a new framework for the probabilistic analysis of tunnel longitudinal performance. Within this framework, the conditional random field theory is adopted to simulate the spatial variation of soil properties along the tunnel longitudinal direction, in which the soil properties at borehole locations can be explicitly considered. Then, the tunnel longitudinal performance is analyzed with an advanced tunnel performance model, in which the influence of tunnel longitudinal behavior on the circumferential behavior of the tunnel cross section can be explicitly considered. With the aid of Monte Carlo simulation (MCS), tunnel longitudinal performance can readily be analyzed in a probabilistic manner; and, the variation of the tunnel performances (i.e., the structural safety and serviceability of the cross section) along the tunnel longitudinal direction could be assessed. The novelty and significance of this proposed framework, compared to the existing methods, are demonstrated through an illustrative example. Further, the influence of the borehole density (i.e., the number of boreholes per tunnel length) on the prediction of the tunnel longitudinal performance is analyzed through a parametric study.
AB - Because of the inherent spatial variability of soil properties and the limited number of boreholes that can be afforded in a typical project, the soil properties at given geotechnical sites could not be known with certainty, which leads to an uncertainty in the predicted performance of a geotechnical system. For such uncertain system, probabilistic analysis is often used to assess its performance considering uncertainty. This paper presents a new framework for the probabilistic analysis of tunnel longitudinal performance. Within this framework, the conditional random field theory is adopted to simulate the spatial variation of soil properties along the tunnel longitudinal direction, in which the soil properties at borehole locations can be explicitly considered. Then, the tunnel longitudinal performance is analyzed with an advanced tunnel performance model, in which the influence of tunnel longitudinal behavior on the circumferential behavior of the tunnel cross section can be explicitly considered. With the aid of Monte Carlo simulation (MCS), tunnel longitudinal performance can readily be analyzed in a probabilistic manner; and, the variation of the tunnel performances (i.e., the structural safety and serviceability of the cross section) along the tunnel longitudinal direction could be assessed. The novelty and significance of this proposed framework, compared to the existing methods, are demonstrated through an illustrative example. Further, the influence of the borehole density (i.e., the number of boreholes per tunnel length) on the prediction of the tunnel longitudinal performance is analyzed through a parametric study.
KW - Longitudinal performance
KW - Random field
KW - Shield tunnel
KW - Site characterization
KW - Spatial variation
UR - http://www.scopus.com/inward/record.url?scp=85040770760&partnerID=8YFLogxK
U2 - 10.1016/j.tust.2017.11.026
DO - 10.1016/j.tust.2017.11.026
M3 - 期刊論文
AN - SCOPUS:85040770760
SN - 0886-7798
VL - 73
SP - 1
EP - 14
JO - Tunnelling and Underground Space Technology
JF - Tunnelling and Underground Space Technology
ER -