A probabilistic approach for predicting corrosion initiation time for RC Members considering effect of temperature and relative humidity

OPSEARCH ◽  
2008 ◽  
Vol 45 (3) ◽  
pp. 225-236
Author(s):  
A. Srividya ◽  
Satish B. Allampallewar
Keyword(s):  
Relative Humidity ◽  
Probabilistic Approach ◽  
Effect Of Temperature ◽  
Initiation Time ◽  
Corrosion Initiation ◽  
Corrosion Initiation Time

CORROSION INITIATION TIME FOR REINFORCED CONCRETE MEMBERS ALONG INDIAN COASTS: EFFECTS OF TEMPERATURE AND RELATIVE HUMIDITY — A PROBABILISTIC APPROACH

2008 ◽  
Vol 15 (06) ◽  
pp. 539-553
Author(s):  
SATISH B. ALLAMPALLEWAR ◽  
A. SRIVIDYA
Keyword(s):  
Diffusion Coefficient ◽  
Relative Humidity ◽  
Probabilistic Approach ◽  
Chloride Concentration ◽  
Threshold Value ◽  
Chloride Ingress ◽  
Initiation Time ◽  
Corrosion Initiation ◽  
Concrete Members ◽  
Corrosion Initiation Time

Corrosion initiation time of steel reinforcement for partially saturated concrete members subjected to chloride ingress is investigated at five places along Indian coasts using simplified probabilistic analysis and sensitivity of the parameters to reinforcement corrosion is studied. Previously proposed diffusion based chloride ingress model for constant surface chloride concentration and variable diffusion coefficient is used. Corrosion is initiated when the chloride concentration on steel reinforcement exceeds a threshold value. The various input parameters considered in the model are surface chloride concentration (Cs), chloride threshold value (Cth), Concrete cover (X), reference diffusion coefficient (Dref), age (t), reference age (tref), diffusion decay index (m) and monthly temperature and relative humidity correction factors f(T) and f(h) respectively; to reference diffusion coefficient. For prediction of corrosion initiation time temperature and relative humidity data collected by India metrological Department is used and all other parameters are assumed same. A large variation in corrosion initiation time is found and therefore it becomes necessary to consider the temperature and relative humidity data in a region. Life-365 considers fully saturated condition of concrete and thus underestimates the corrosion initiation time of a reinforced concrete member. The deterministic approach uses mean values of the parameters and provides a 50% probability of corrosion initiation but the probabilistic approach provides expected time of first corrosion for chosen risk of corrosion and also gives sensitivity of parameters to probability of corrosion. Corrosion initiation time in ascending order is found at Colaba, Kanyakumari, Santacruz, Chennai and Vishakhapatnam. Corrosion initiation time is useful for owner, designer, or to an organization to take decision in time of priority of repairs, repair strategy, corrosion protection in order to optimize maintenance planning and budgeting. Planned maintenance at the optimum time is the safest and most cost effective approach.

CORROSION INITIATION TIME OF REINFORCED CONCRETE STRUCTURES IN MARINE ENVIRONMENT — A PROBABILISTIC APPROACH

2008 ◽  
Vol 15 (02) ◽  
pp. 93-99
Author(s):  
A. SRIVIDYA ◽  
SATISH B. ALLAMPALLEWAR
Keyword(s):  
Probabilistic Approach ◽  
Chloride Concentration ◽  
Cost Effective ◽  
Threshold Value ◽  
Steel Reinforcement ◽  
Initiation Time ◽  
Expected Time ◽  
Corrosion Initiation ◽  
Cost Effective Approach ◽  
Corrosion Initiation Time

An approximate explicit method from literature to estimate the corrosion initiation time of steel reinforcement in concrete is developed to incorporate random variables which affect the diffusion rate. The method accounts for uncertainties of input parameters and predicate expected time of first corrosion for the chosen risk of corrosion and its variance. Method is also utilized to rank the sensitive parameters to initiate steel reinforcement corrosion. Corrosion is initiated when the chloride concentration on steel reinforcement exceeds a threshold value. Corrosion initiation time is useful for owner, designer, or to an organization to take decision in time of priority of repairs, repair strategy, corrosion protection in order to optimize maintenance planning and budgeting. Planned maintenance at the optimum time is the safest and most cost effective approach.

Corrosion initiation time of steel reinforcement in a chloride environment—A one dimensional solution

1997 ◽  
Vol 39 (4) ◽  
pp. 739-759 ◽  
Author(s):  
P. Arora ◽  
B.N. Popov ◽  
B. Haran ◽  
M. Ramasubramanian ◽  
S. Popova ◽  
...  
Keyword(s):  
Steel Reinforcement ◽  
Initiation Time ◽  
Dimensional Solution ◽  
One Dimensional ◽  
Corrosion Initiation ◽  
Corrosion Initiation Time ◽  
Chloride Environment

Probability Model of Corrosion Initiation Time of Steel in Concrete Structure in Chloride Environment

2011 ◽  
Vol 243-249 ◽  
pp. 5632-5636
Author(s):  
Ya Li Ma ◽  
Ai Lin Zhang
Keyword(s):  
Sensitivity Analysis ◽  
Probability Distribution ◽  
Probability Model ◽  
Chloride Concentration ◽  
Initiation Time ◽  
Distribution Law ◽  
Corrosion Initiation ◽  
Corrosion Initiation Time ◽  
Chloride Environment ◽  
Distribution Type

Probability distribution law of corrosion initiation time of steel in concrete under chloride environment is discussed. Based on the Fick’s second law, by Monte Carlo, frequency distribution, distribution type and probability density is analyzed. The statistic parameters of the factors influencing the probability distribution of corrosion initiation time are studied and the expression for sensitivity analysis of corrosion initiation time is deduced. By sensitivity analysis can know, corrosion initiation time is found to be more sensitive to cover than the diffusion coefficient, and more sensitive to surface chloride concentration than the critical chloride level. The analysis of the paper perfects the methods of predicting the corrosion initiation time.

Ensemble machine learning model for corrosion initiation time estimation of embedded steel reinforced self-compacting concrete

Measurement ◽  
2020 ◽  
Vol 165 ◽  
pp. 108141
Author(s):  
Babatunde Abiodun Salami ◽  
Syed Masiur Rahman ◽  
Tajudeen Adeyinka Oyehan ◽  
Mohammed Maslehuddin ◽  
Salah U. Al Dulaijan
Keyword(s):  
Machine Learning ◽  
Time Estimation ◽  
Learning Model ◽  
Initiation Time ◽  
Self Compacting Concrete ◽  
Corrosion Initiation ◽  
Ensemble Machine Learning ◽  
Machine Learning Model ◽  
Corrosion Initiation Time
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