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Aggressive marine environments and tidal conditions due to chloride ions attack and subsequent wetting and drying concrete, lead to excessive corrosion of reinforcing steel that creates destruction. Simulating behavior of corrosion can be effective in reducing the damage, regional investigations are necessary for durability-based design and evaluation of the models proposed for service-life prediction. In this paper Monte Carlo simulation use for service-life prediction of reinforced concrete structures in tidal zone. This study evaluates the influence of mean and standard deviation variations for each of the parameters that affect on the time of corrosion initiation. In tidal condition that studied in this paper, in the case of 10 mm convection depth with respect to non tidal zone, the service life of the structures decrease about 15 years. So it is found the effect of corrosion occurrence to standard deviation of concrete cover that must be noticed in constructions of marine structures.

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For structural reliability assessment or risk analysis of aging offshore steel structures, it is essential to have a probabilistic model, which contains specific statistical parameters, and predicts long term corrosion loss as a function of time. The aim of this study is to propose such model for offshore jacket platforms in the Persian Gulf. Field measurements for material loss due to uniform corrosion for submerged members in seawater have been collected and statistically analyzed to identify the probability density distribution function for dispersion and variation of corrosion loss value according to the passage of time. To predict the corrosion loss, two probabilistic models with different approaches and time dependent parameters are suggested, based on the statistical analysis results. For a comparative study, the application of aforementioned models on the reliability analysis of a simple plate structure is investigated. Prediction results, obtained from the proposed probabilistic models, are consistent well with filed measurements. 

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Marine vessels may cause accidental damage to the offshore platforms during uploading oil and gas production in the storm conditions or incorrect navigation by ship’s captain. This impact of sea-going vessels is source of local or global deformations in the offshore structures. In this research the reliability indexes of damaged members under vessels impact are estimated for a platform in the phase 19 of the South Pars using the first-order reliability method (FORM).Only deformation of structural members are considered as damage impact and energy dissipation during collision is not addressed in this research. The time consuming Monte Carlo simulation Method (MCS) and Important Sampling (I.S.) are used to verify the first-order reliability method because the limit state function in FORM is linear-zed by the Taylor series. At first, the wave force is applied into the safe structure, and reliability indexes are estimated for structural members. Then, in addition to the wave loads, the deformations caused by the assumed collision are also taken into account and structural reliability is estimated in the damaged state and corresponding results are compared with each other.  Finally, combinations of wave and current, wave directions, and damages scenarios in chord, vertical and horizontal bracing are considered and results are compared.

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Pipelines are widely used in transporting large quantities of oil and gas productions over long distances due to their efficiency, safety and low cost. Pipeline integrity is crucial for reliable pipeline operations, preventing expensive downtime, and failures resulting in leaking or spilling oil or gas content to the environment. In this paper, the influence of construction quality and corresponding uncertainties on the submarine pipelines integrity regarding the simultaneous effect of corrosion and bursting failure are investigated in a reliability analysis to predict critical failure year of the pipe. Also, sensitivity analysis is implemented to estimate how the important parameters affect the probability of failure using Monte Carlo simulation approach. Besides, consequences of failure also included in this study in terms of a ‘cost’ function considering post-failure inspection and repairs costs. Results illustrate that wall thickness is the dominant parameter in pipeline bursting. Also, allowable fabrication tolerances which are represented in DNV have an inherent probability of failure and it can be deteriorated by a degrading mechanism such as corrosion.

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Since various relationships have been presented to calculate the recession in the berm breakwater, the evaluation of these relationships in the form of probabilistic is one of the most basic topics in marine engineering. In this study, the failure probability or in complementary the reliability for recession of Shahid Beheshti port berm breakwater is investigated based on six models of Torum (2007), Moghim et al. (2011), Lykke Andersen et al. (2014), Moghim and Alizadeh (2014), Van Der Meer and Sigurdarson (2016) and Ehsani et al. (2020). Four methods of First-Order Reliability Method (FORM), Second-Order Reliability Method (SORM), Monte Carlo Simulation (MCS) and Importance Sampling (IS) are applied to obtained the failure probability and reliability index for breakwater at the maximum water depth and 100-year wave height. The results of the MCS show the highest failure probability belongs to Moghim et al. (2011) model with a value of about 0.69, and the lowest value possess to the Torum (2007) model with a value of about 0.29. In addition, Van der Meer and Sigurdarson (2016) and Moghim and Alizadeh (2014) models give the failure probabilities of 0.57 and 0.50 respectively and Likke Andersen et al. (2014) and Ehsani et al. (2020) models presented the failure probabilities of 0.42 and 0.38 respectively. According to these results, Ehsani et al. (2020) and Torum (2007) models which developed for Icelandic breakwaters have the lowest probability of failure. Furthermore, Models of Moghim et al. (2011) and Moghim and Alizadeh (2014) which presented for reshaping breakwaters have the highest probability of failure. Next, sensitivity analysis was performed and the impact of different variables on the probability of failure was investigated.