This paper provides experimentally determined estimates of the scale of fluctuation of the principal variables employed in modeling chloride-induced corrosion for reinforced concrete; i.e., the surface chloride content (Cs) and apparent diffusion coefficient (Dapp). The estimation of the scale of fluctuation, θ, is based on the analysis of experimental data recorded on a bridge in South East Ireland prior to its extensive rehabilitation in 2007. In determining the scale of fluctuation the paper considers two commonly used methods; i.e., the maximum likelihood method and the autocorrelation curve-fitting method. The reliability of both methods is discussed. Introduction of the kriging statistical interpolation method is demonstrated to improve the reliability of the estimates of the scale of fluctuation. The results obtained from the analysis are compared with values in the literature proffered by other researchers. arabic 16 English 119
Omran Kenshel(1-2013)

Prediction of the present and future state of Reinforced Concrete (RC) structures suffering from chloride-induced corrosion is important if proper planning for inspection and maintenance is to be made. The majority of research studies have thus far focused on the diffusion process of chloride ions through the concrete cover, the time to corrosion initiation and on the prediction of the surface condition of the structure. However; practical evidence and theoretical analysis suggests that many structures can tolerate considerable corrosion damage without serious reduction to their load carrying capacity. Therefore, visual impression-based maintenance is not an optimum solution particularly when financial resources are limited. To support this notion, accurate models are needed to predict the deterioration rate of the structural load carrying capacity over time. This paper uses existing empirical RC deterioration models to predict the loss in the load carrying capacity of a typical RC T-beam using a reliability based approach. The approach takes into consideration the spatial variability of the deterioration parameters, thereby demonstrating the importance of its inclusion in any such analysis. arabic 13 English 97
Omran Kenshel(1-2009)

Estimating the service life of Reinforced Concrete (RC) bridge structures located in corrosive marine environments of a great importance to their owners/engineers. Traditionally, bridge owners/engineers relied more on subjective engineering judgment, e.g. visual inspection, in their estimation approach. However, because financial resources are often limited, rational calculation methods of estimation are needed to aid in making reliable and more accurate predictions of the service life of RC structures. This is in order to direct funds to bridges found to be the most critical. Criticality of the structure can be considered either from the Structural Capacity (i.e. Ultimate Limit State) or from Serviceability viewpoint whichever is adopted. This paper considers the service life of the structure only from the Structural Capacity viewpoint. Considering the great variability associated with the parameters involved in the estimation process, the probabilistic approach is most suited. The probabilistic modelling adopted here used Monte Carlo simulation technique to estimate the Reliability (i.e. Probability of Failure) of the structure under consideration. In this paper the authors used their own experimental data for the Correlation Length (CL) for the most important deterioration parameters. The CL is a parameter of the Correlation Function (CF) by which the spatial fluctuation of a certain deterioration parameter is described. The CL data used here were produced by analyzing 45 chloride profiles obtained from a 30 years old RC bridge located in a marine environment. The service life of the structure was predicted in terms of the load carrying capacity of an RC bridge beam girder. The analysis showed that the influence of SV is only evident if the reliability of the structure is governed by the Flexure failure rather than by the Shear failure. arabic 14 English 80
Omran Mohamed Saleh Kenshel(2-2021)

Estimating the Reliability (Probability of Failure) of Reinforced Concrete (RC) structures in marine environments has been of major concern among researchers in recent years. While General (uniform) corrosion affects the reinforcement by causing a uniform loss of its cross-sectional area, Pitting (localized) corrosion concentrates over small areas of the reinforcement. Many studies have focused on the effect of general corrosion, the effect of pitting corrosion on the structure reliability has not been fully investigated. Furthermore, due to the variability associated with the parameters involved in the reliability estimation of the corroded structure, this paper focuses on the effect of variability of pitting corrosion on the structure reliability. The analysis also takes into consideration the Spatial Variability (SV) of key deterioration parameters often neglected in previous studies. The authors have used their experimental data in modeling SV parameters of a specific deterioration parameter. The analysis adopted here used Monte Carlo (MC) simulation technique to construct a Spatial-Time Dependent model to estimate the girder reliability. The results showed that pitting corrosion potentially has a far more aggressive effect on the structure reliability than general corrosion and that pitting corrosion affects shear resistance far more severely than it would affect flexure resistance. The analysis showed that after 50 years of service, the reduction in the beam reliability due to pitting corrosion was 51% higher than that caused by general corrosion and that considering SV has caused the reliability predicted in terms of pitting corrosion to decrease by 12%. In the case of general corrosion, the decrease in beam reliability was only about 2% for the SV scenario.
Omran Kenshel, Mohamed Sulieman (12-2021)

The number of deteriorating bridges due to chloride-induced corrosion increases annually as does the cost of inspection, maintenance, repair and where necessary replacement. Meanwhile, budgets made available to bridge owners/managers for repair and maintenance of these bridges are reducing. To optimise and manage their budget spend, bridge owners/mangers need to rely more on rational decision making methods rather than on subjective engineering judgment. In this thesis, the author has developed a probabilistic- based model which aims to predict the lifetime performance of Reinforced Concrete (RC) structures exposed to chloride corrosive environment and consequently to optimise their lifetime management.
Omran Kenshel(11-2009)