Abstract

Pipeline safety faces a prevalent threat in mountainous areas due to landslides. The advent of landslides introduces the risk of pipeline leaks or ruptures, posing a significant threat to the environment, with the potential for casualties. Throughout the occurrence of landslides, uncertainties abound, yet few studies have addressed the incorporation of uncertainties in assessing pipeline safety. This work proposes a novel hybrid approach to the safety assessment for pipelines under landslides. The use of finite element analysis (FEA) models the pipeline under the action of landslides. The numerical outcomes, combined with unascertained measure theory (UMT), develop a multi-indicator unascertained measure (UM) matrix. Random forest (RF) algorithm is employed to determine the weight of indicators in the matrix. The hybrid application of set pair theory and the UM evaluation vector finally determine the pipeline safety degree and level. The proposed methodology has been well-validated through a case study on an in-service pipeline. The results indicate that the case pipeline safety degree is 2.777, 2.132, 3.132, 3.904, and 2.240, respectively. The corresponding safety level is III, II, III, IV, and II, respectively, which is consistent with the pipeline's actual condition. Different from the conventional safety assessment approach, the proposed methodology demonstrates the enhanced effectiveness, facilitating a more precise evaluation of the pipeline's safety condition.

References

1.
Marinos
,
V.
,
Stoumpos
,
G.
, and
Papazachos
,
C.
,
2019
, “
Landslide Hazard and Risk Assessment for a Natural Gas Pipeline Project: The Case of the Trans Adriatic Pipeline, Albania Section
,”
Geosciences
,
9
(
2
), p.
61
.10.3390/geosciences9020061
2.
Kozhaeva
,
K. V.
,
Azmetov
,
K. A.
, and
Pavlova
,
Z. K.
,
2022
, “
Analysis of the General Stability of Buried Pipelines in the Longitudinal Direction Taking Into Account the Peculiarities of Their Construction and Operation
,”
IOP Conf. Ser.: Earth Environ. Sci.
,
988
(
5
), p.
052001
.10.1088/1755-1315/988/5/052001
3.
Qin
,
G.
,
Huang
,
Y.
,
Wang
,
Y.
, and
Cheng
,
Y. F.
,
2023
, “
Pipeline Condition Assessment and Finite Element Modeling of Mechano-Electrochemical Interaction Between Corrosion Defects With Varied Orientations on Pipelines
,”
Tunn. Underground Space Technol.
,
136
, p.
105101
.10.1016/j.tust.2023.105101
4.
Liu
,
S.
,
Zhang
,
P.
,
Tang
,
Q.
,
Wu
,
S.
, and
Huang
,
Y.
,
2024
, “
A Novel Safety Early Warning Methodology for Pipelines Under Landslide Geological Hazard
,”
ASCE J. Pipeline Syst. Eng.
,
15
(
1
), p.
04023050
.10.1061/JPSEA2.PSENG-1529
5.
Alvarado-Franco
,
J. P.
,
Castro
,
D.
,
Estrada
,
N.
,
Caicedo
,
B.
,
Sánchez-Silva
,
M.
,
Camacho
,
L. A.
, and
Muñoz
,
F.
,
2017
, “
Quantitative-Mechanistic Model for Assessing Landslide Probability and Pipeline Failure Probability Due to Landslides
,”
Eng. Geol.
,
222
, pp.
212
224
.10.1016/j.enggeo.2017.04.005
6.
Katebi
,
M.
,
Maghoul
,
P.
, and
Blatz
,
J.
,
2019
, “
Numerical Analysis of Pipeline Response to Slow Landslides: Case Study
,”
Can. Geotech. J.
,
56
(
12
), pp.
1779
1788
.10.1139/cgj-2018-0457
7.
Holliday
,
C.
,
Young
,
A.
,
Funk
,
T.
, and
Murray
,
C.
,
2020
, “
The North Saskatchewan River Valley Landslide: Slope and Pipeline Condition Monitoring
,” ASME Paper No. IPC2020-9532.10.1115/IPC2020-9532
8.
Vasseghi
,
A.
,
Haghshenas
,
E.
,
Soroushian
,
A.
, and
Rakhshandeh
,
M.
,
2021
, “
Failure Analysis of a Natural Gas Pipeline Subjected to Landslide
,”
Eng. Fail. Anal.
,
119
, p.
105009
.10.1016/j.engfailanal.2020.105009
9.
Schwab
,
J. W.
,
Geertsema
,
M.
, and
Blais-Stevens
,
A.
,
2004
, “
The Khyex River Landslide of November 28, 2003, Prince Rupert British Columbia Canada
,”
Landslides
,
1
(
3
), pp.
243
246
.10.1007/s10346-004-0026-0
10.
Niu
,
C.
,
Zhang
,
H.
,
Liu
,
W.
,
Li
,
R.
, and
Hu
,
T.
,
2021
, “
Using a Fully Polarimetric SAR to Detect Landslide in Complex Surroundings: Case Study of 2015 Shenzhen Landslide
,”
ISPRS J. Photogramm. Remote Sens.
,
174
, pp.
56
67
.10.1016/j.isprsjprs.2021.01.022
11.
Cheng
,
Z.
,
Gong
,
W.
,
Tang
,
H.
,
Juang
,
C. H.
,
Deng
,
Q.
,
Chen
,
J.
, and
Ye
,
X.
,
2021
, “
UAV Photogrammetry-Based Remote Sensing and Preliminary Assessment of the Behavior of a Landslide in Guizhou, China
,”
Eng. Geol.
,
289
, p.
106172
.10.1016/j.enggeo.2021.106172
12.
Poma
,
P.
,
Usca
,
M.
,
Fdz-Polanco
,
M.
,
Garcia-Villacres
,
A.
, and
Toulkeridis
,
T.
,
2021
, “
Landslide and Environmental Risk From Oil Spill Due to the Rupture of SOTE and OCP Pipelines, San Rafael Falls, Amazon Basin, Ecuador
,”
Int. J. Adv. Sci. Eng. Inf. Technol.
,
11
(
4
), pp.
1558
1566
.10.18517/ijaseit.11.4.13727
13.
Zahid
,
U.
,
Godio
,
A.
, and
Mauro
,
S.
,
2020
, “
An Analytical Procedure for Modelling Pipeline-Landslide Interaction in Gas Pipelines
,”
J. Nat. Gas Sci. Eng.
,
81
, p.
103474
.10.1016/j.jngse.2020.103474
14.
Chaudhuri
,
C. H.
, and
Choudhury
,
D.
,
2020
, “
Buried Pipeline Subjected to Seismic Landslide: A Simplified Analytical Solution
,”
Soil Dyn. Earthquake Eng.
,
134
, p.
106155
.10.1016/j.soildyn.2020.106155
15.
Chaudhuri
,
C. H.
, and
Choudhury
,
D.
,
2021
, “
Semianalytical Solution for Buried Pipeline Subjected to Horizontal Transverse Ground Deformation
,”
ASCE, J. Pipeline Syst. Eng. Pract.
,
12
(
4
), p.
04021038
.10.1061/(ASCE)PS.1949-1204.0000541
16.
Calvetti
,
F.
,
Di Prisco
,
C.
, and
Nova
,
R.
,
2004
, “
Experimental and Numerical Analysis of Soil–Pipe Interaction
,”
ASCE J. Geotech. Geoenviron.
,
130
(
12
), pp.
1292
1299
.10.1061/(ASCE)1090-0241(2004)130:12(1292)
17.
Feng
,
W.
,
Huang
,
R.
,
Liu
,
J.
,
Xu
,
X.
, and
Luo
,
M.
,
2015
, “
Large-Scale Field Trial to Explore Landslide and Pipeline Interaction
,”
Soils Found.
,
55
(
6
), pp.
1466
1473
.10.1016/j.sandf.2015.10.011
18.
Kunert
,
H. G.
,
Otegui
,
J. L.
, and
Marquez
,
A.
,
2012
, “
Nonlinear FEM Strategies for Modeling Pipe–Soil Interaction
,”
Eng. Fail. Anal.
,
24
, pp.
46
56
.10.1016/j.engfailanal.2012.03.008
19.
Zhang
,
L.
,
Fang
,
M.
,
Pang
,
X.
,
Yan
,
X.
, and
Cao
,
Y.
,
2018
, “
Mechanical Behavior of Pipelines Subjecting to Horizontal Landslides Using a New Finite Element Model With Equivalent Boundary Springs
,”
Thin Walled Struct.
,
124
, pp.
501
513
.10.1016/j.tws.2017.12.019
20.
Liao
,
Y.
,
Liu
,
C.
,
Wang
,
T.
,
Xu
,
T.
,
Zhang
,
J.
, and
Ge
,
L.
,
2021
, “
Mechanical Behavior Analysis of Gas Pipeline With Defects Under Lateral Landslide
,”
Proc. Inst. Mech. Eng., Part C
,
235
(
23
), pp.
6752
6766
.10.1177/09544062211017161
21.
Fa-You
,
A.
,
Chen
,
T. H.
,
Yang
,
C.
,
Wu
,
Y. F.
, and
Yan
,
S. Q.
,
2023
, “
Study on Disaster Mechanism of Oil and Gas Pipeline Oblique Crossing Landslide
,”
Sustainability
,
15
(
4
), pp.
3012
3024
.10.3390/su15043012
22.
Wang
,
G.
,
1990
, “
Uncertainty Information and Its Mathematical Treatment
,”
J. Harbin Univ. Civ. Eng. Architect.
,
23
(
4
), pp.
1
9
.
23.
Liu
,
K.
,
Pang
,
Y.
,
Sun
,
G.
, and
Yao
,
L.
,
1999
, “
The Unascertained Measure Evaluation on a City's Environmental Quality
,”
Syst. Eng.-Theory Pract.
,
19
(
12
), pp.
3
5
.
24.
An
,
X.
,
Li
,
H.
,
Ojuri
,
O.
,
Wang
,
Z.
, and
Ding
,
J.
,
2018
, “
Identification and Prevention of Unbalanced Bids Using the Unascertained Model
,”
ASCE J. Constr. Eng. M.
, 144(11), p.
05018013
.10.1061/(ASCE)CO.1943-7862.0001563
25.
Li
,
Q.
, and
Li
,
W.
,
2021
, “
Availability Evaluation for Current Status of Old Industrial Area in China: From the Perspective of Sustainable Development
,”
Environ. Technol. Innovation
,
23
, p.
101743
.10.1016/j.eti.2021.101743
26.
Zheng
,
S. L.
,
Meng
,
Y. W.
,
Li
,
F. J.
,
Wang
,
C. H.
, and
Sun
,
S. Q.
,
2021
, “
Traffic Safety Evaluation Based on Unascertained Measure Model
,”
International Conference on Smart Transportation and City Engineering
, Chongqing, China, Nov. 10, pp.
432
438
.10.1117/12.2613687
27.
Li
,
M.
,
Nie
,
R.
,
Zhao
,
J.
,
Shen
,
J.
, and
Fu
,
Y.
,
2022
, “
Evaluation of Water Inrush Risk in Deep Mines Based on Variable Weight and Unascertained Measure Theories and GIS
,”
Shock Vib.
,
2022
, pp.
1
13
.10.1155/2022/9073554
28.
Zhang
,
G.
,
Wang
,
E.
,
Zhang
,
C.
,
Li
,
Z.
, and
Wang
,
D.
,
2022
, “
A Comprehensive Risk Assessment Method for Coal and Gas Outburst in Underground Coal Mines Based on Variable Weight Theory and Uncertainty Analysis
,”
Process Saf. Environ. Prot.
,
167
, pp.
97
111
.10.1016/j.psep.2022.08.065
29.
Sheng
,
K.
,
Lai
,
X.
,
Chen
,
Y.
, and
Jiang
,
J.
,
2021
, “
Risk Assessment of Urban Gas Pipeline Based on Different Unknown Measure Functions
,”
Tehnički vjesnik
,
28
(
5
), pp.
1605
1614
.10.17559/TV-20201021110548
30.
Cassidy
,
A. P.
, and
Deviney
,
F. A.
,
2014
, “
Calculating Feature Importance in Data Streams With Concept Drift Using Online Random Forest
,”
IEEE International Conference on Big Data (Big Data)
, Washington, DC, Oct. 27–30, pp.
23
28
.10.1109/BigData.2014.7004352
31.
Zheng
,
J. Y.
,
Zhang
,
B. J.
,
Liu
,
P. F.
, and
Wu
,
L. L.
,
2012
, “
Failure Analysis and Safety Evaluation of Buried Pipeline Due to Deflection of Landslide Process
,”
Eng. Fail. Anal
,.,
25
, pp.
156
168
.10.1016/j.engfailanal.2012.05.011
32.
Janitza
,
S.
, and
Hornung
,
R.
,
2018
, “
On the Overestimation of Random Forest's Out-of-Bag Error
,”
PloS One
,
13
(
8
), p.
e0201904
.10.1371/journal.pone.0201904
33.
Cen
,
H.
,
Huang
,
D.
,
Liu
,
Q.
,
Zong
,
Z.
, and
Tang
,
A.
,
2023
, “
Application Research on Risk Assessment of Municipal Pipeline Network Based on Random Forest Machine Learning Algorithm
,”
Water
,
15
(
10
), p.
1964
.10.3390/w15101964
34.
Fei
,
K.
, and
Zhang
,
J. W.
,
2010
,
Application of ABAQUS in Geotechnical Engineering
,
China Water Power Press
,
Beijing, China
.
You do not currently have access to this content.