A stochastic model for deterioration process of tunnel lining concrete in cold regions

2014 ◽  
pp. 5115-5120
Author(s):  
O Maruyama ◽  
A Sutoh ◽  
H Tanaka ◽  
T Satoh ◽  
H Nishi
Keyword(s):  
Stochastic Model ◽  
Tunnel Lining ◽  
Cold Regions ◽  
Deterioration Process

scholarly journals Development of a Stochastic Model for Predicting Wind-induced Damage to Wooden Houses in Snowy Cold Regions

2017 ◽  
Vol 42 (3) ◽  
pp. 89-99
Author(s):  
Sachiko YOSHIDA ◽  
Daisuke KONNO ◽  
Eri GAVANSKI ◽  
Yasushi UEMATSU
Keyword(s):  
Stochastic Model ◽  
Cold Regions

A stochastic model for the estimation of renewal periods of sharply curved metro rails

2016 ◽  
Vol 232 (2) ◽  
pp. 572-588 ◽  
Author(s):  
Wenfei Bai ◽  
Rengkui Liu ◽  
Quanxin Sun ◽  
Futian Wang ◽  
Peng Xu
Keyword(s):  
Life Expectancy ◽  
Stochastic Model ◽  
Weibull Distribution ◽  
Rail Wear ◽  
Deterioration Process ◽  
Factor Data ◽  
Inspection Data ◽  
Heterogeneous Factor ◽  
Common Defect

Rail wear is the most common defect that affects sharply curved metro rails, thus impacting their renewal periods. This article presents a stochastic model, based on a Weibull distribution, for the estimation of the renewal periods of sharply curved metro rails based on the analysis of the characteristics of rail wear. The model considers several heterogeneous factors to determine their effects on the deterioration process and is shown to be able to estimate the life expectancy of these rails in any wear state, as well as their remaining lives and renewal periods, with respect to these heterogeneous factors. The model is validated by a case study of the Beijing Metro, based on 10 years of rail wear inspection data and heterogeneous factor data of 200 sharp curves.

scholarly journals Study on the Progressive Deterioration of Tunnel Lining Structures in Cold Regions Experiencing Freeze–Thaw Cycles

2021 ◽  
Vol 11 (13) ◽  
pp. 5903
Author(s):  
Peng Xu ◽  
Yimin Wu ◽  
Le Huang ◽  
Kun Zhang
Keyword(s):  
Frost Damage ◽  
Tunnel Lining ◽  
Distribution Law ◽  
Cold Regions ◽  
Research Attention ◽  
Freeze Thaw ◽  
Progressive Deterioration ◽  
Structural Deterioration ◽  
Thaw Cycle ◽  
Freeze Thaw Cycle

The linings of tunnels in cold regions with long service lives usually have cracks, with parts of the structure peeling and falling off, which seriously threatens the tunnel safety and operation. The unsaturated freeze–thaw cycle of concrete, which is the main cause of structural deterioration, has not received much research attention. During the service life of tunnels in cold regions, unsaturated freeze–thaw cycles deteriorate the quality of the concrete, and its degree presents a gradual distribution in the circumferential and longitudinal directions. An experiment system was adopted to simulate the distribution of the progressive deterioration of tunnel lining concrete. The test results of the temperature field of the model show the distribution law of freeze–thaw cycles, and the gradual deterioration of the lining concrete was realized. Then, the bearing capacity of the model was tested after the progressive deterioration. The results show that the ultimate load of the model decreases with an increase in the number of freeze–thaw cycles. Finally, a numerical simulation was carried out to discuss the influence of the gradual deterioration of the lining. The gradual deterioration of lining concrete will encourage the gradual development of cracks, leading to serious cracking of the lining structure and even block spalling. Through this study, we hope to provide useful information for the prevention and control of tunnel frost damage in cold regions.

A Fruitful Stochastic Model

1964 ◽  
Vol 9 (7) ◽  
pp. 273-276
Author(s):  
ANATOL RAPOPORT
Keyword(s):  
Stochastic Model

A Stochastic Model for Evolution of Altruistic Genes

1996 ◽  
Vol 6 (4) ◽  
pp. 445-453 ◽  
Author(s):  
Roberta Donato
Keyword(s):  
Stochastic Model

A Stochastic Model for the Inheritance of the Cancer Proneness Phenotype

1987 ◽  
Vol 26 (03) ◽  
pp. 117-123
Author(s):  
P. Tautu ◽  
G. Wagner
Keyword(s):  
Stochastic Model ◽  
Gaussian Process ◽  
Covariance Function ◽  
Neoplastic Disease ◽  
Disease Phenotype ◽  
Probabilistic Representation ◽  
Temporal Behaviour ◽  
Continuous Trait ◽  
Continuous Parameter ◽  
Level Zero

SummaryA continuous parameter, stationary Gaussian process is introduced as a first approach to the probabilistic representation of the phenotype inheritance process. With some specific assumptions about the components of the covariance function, it may describe the temporal behaviour of the “cancer-proneness phenotype” (CPF) as a quantitative continuous trait. Upcrossing a fixed level (“threshold”) u and reaching level zero are the extremes of the Gaussian process considered; it is assumed that they might be interpreted as the transformation of CPF into a “neoplastic disease phenotype” or as the non-proneness to cancer, respectively.

Sign in / Sign up

Export Citation Format

Share Document