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CO₂ corrosion rate prediction is regarded as the backbone of materials selection in upstream hydrocarbon industry. This study aims to identify common types of errors in CO₂ rate calculation and to give guidelines on how to avoid them.

For the purpose of this study, 15 different “corrosion study and materials selection reports” carried out previously in upstream hydrocarbon industry were selected, and their predicted CO₂ corrosion rates were evaluated using various corrosion models. Errors captured in the original materials selection reports were categorized based on their type and nature.

The errors identified in the present study are classified into the following four main types: using inadequate or false data as the input to the model, failing to address factors which may have significant influence on corrosion rate, utilizing corrosion models beyond their validity range and utilizing a corrosion model for a specific set of input, where the model is considered to be inaccurate even though the input lies within the software’s range of validity.

This study is mainly based on the use of various corrosion models, and except few cases for which some actual field corrosion monitoring data were available, no laboratory tests were performed to verify the predicted data.

The paper provides a checklist of common types of errors in CO₂ corrosion rate prediction and the guidelines on how to avoid them.

CO₂ corrosion rate calculation is regarded as the backbone of materials selection in hydrocarbon industry. In this work, the source of errors in terms of corrosion modeling tool and human factors were identified.

This paper aims to study flow‐induced corrosion mechanisms for carbon steel in high‐velocity flowing seawater and to explain corrosive phenomena.

An overall mathematical model for flow‐induced corrosion of carbon steel in high‐velocity flow seawater was established in a rotating disk apparatus using both numerical simulation and test methods. By studying the impact of turbulent flow using the kinetic energy of a turbulent approach and the effects of the computational near‐wall hydrodynamic parameters on corrosion rates, corrosion behavior and mechanism are discussed here. It is applicable in order to understand in depth the synergistic effect mechanism of flow‐induced corrosion.

It was found that it is scientific and reasonable to investigate carbon steel corrosion through correlation of the near‐wall hydrodynamic parameters, which can accurately describe the influence of fluid flow on corrosion. The computational corrosion rates obtained by this model are in good agreement with measured corrosion data. It is shown that serious flow‐induced corrosion is caused by the synergistic effect between the corrosion electrochemical factor and the hydrodynamic factor, while the corrosion electrochemical factor plays a dominant role in flow‐induced corrosion.

The corrosion kinetics and mechanism of metals in a high‐velocity flowing medium is discussed here. These results will help those interested in flow‐induced corrosion to understand in depth the type of issue.

A significant part of Finnish concrete building stock is relatively young. Thus methods to adopt the existing building stock to climate change are needed. To plan and correctly timing the service actions there is a need to study the rates of different deterioration mechanisms. The reinforcement corrosion in Finnish outdoor exposed concrete structures is almost solely carbonation-induced corrosion. In former studies, it has been shown that active corrosion phase can also have a major effect on the total service life of the structure. The paper aims to discuss these issues.

In this study, the effect of climate change on predicted corrosion rate of concrete reinforcement in projected 2050 and 2100 climates compared to present climate were studied to consider adaptation methods for the climate change. The calculations are based on a corrosion propagation model, which takes into account four different climatic factors: wind-driven rain, temperature, relative humidity and solar radiation.

A significantly higher corrosion rates and thus faster corrosion-induced damage can be expected in the future climate. The increase in corrosion rate is the highest in the late autumn and winter because of the increasing amount of precipitation and weaker conditions for concrete structures to dry. In addition, the duration of high corrosion rate periods is increasing which may shorten the propagation phase. However, corrosion rate is highly dependent on the direction of the greatest climate load and the grade of sheltering which can be taken into account in service life calculations and while planning service actions.

There are different sources of error because of the uncertainties with both the used model and the climate change scenarios. That is why the results are discussed in more general way than comparing the actual numbers with each other.

The propagation model used in this study has not been used before in adaptation studies. The climate change effect on carbonation-induced corrosion has also been limited while the studies have focused on chloride-induced corrosion.

The purpose of this paper is to present a new model which combines the non-equidistant GM(1,1) model with GCHM_WBO (generalized contra-harmonic mean (GCHM); weakening buffer operator (WBO)). The authors use the model to solve the deadlock that for a large number of non-equidistant corrosion rate, it is difficult to establish a reasonable prediction model and improve the prediction accuracy.

This research consists of three parts: non-equidistant GM(1,1) model, GCHM_WBO operator, and the optimization of morphing parameter (contained in GCHM, control the intensity of the weakening operator). The methodology is explained as follows. First, the authors built a non-equidistant GM(1,1) model with GCHM_WBO weakened data, of which morphing parameter was randomly selected. Next, the authors calculated the error between prediction data of model and the real data, and adjusted the morphing parameter according to the error and property of GCHM. Then, the authors generated a new non-equidistant GM(1,1) based on new morphing parameter, and repeated the previous step until the termination condition was satisfied. Finally, the model with appropriate morphing parameter was used to implement the prediction of new data.

This paper finds a property of GCHM, which is a monotonic increasing function of morphing parameter in some specific conditions. Based on the property and the fixed point axiom of WBO, an algorithm was designed to search an appropriate morphing parameter. The appropriate morphing parameter was implemented for the purpose of improving the accuracy of the model. The model was applied to predict the corrosion rate of six steels at Guangzhou experimental station. The results showed that the proposed method can get more accuracy in prediction capability compared to the models with the original data and AWBO weakened data. The method is applicable to long-term forecasts in case of data scarcity.

Corrosion will cause huge economic loss to a country; therefore, it is important to judge the remaining useful life of a material or equipment; the foundation for judgement of which is the prediction of material corrosion rate. However, the prediction of corrosion rate is very difficult because of corrosion data’s features, such as small sample size, non-equidistant, etc. The proposed method can be used to implement long-term forecast of corrosion data with only one sample and non-equidistant samples.

This paper presented a model which combines the non-equidistant GM(1,1) model with GCHM_WBO to handle the problem of long-term forecasting of corrosion data. In the modelling process, the proposed morphing parameter searched through algorithm can improve the prediction accuracy of the model. Therefore, the model can provide effective and reliable result when data are of a small sample size and non-equidistant.

The paper aims to develop an intelligent anti-corrosion expert system based on browser/server (B/S) architecture to realize an intelligent corrosion management system.

The system is based on Java EE technology platform and model view controller (MVC) three-tier architecture development model. The authors used an extended three-dimensional interpolation model to predict corrosion rate, and the model is verified by cross-validation method. Additionally, MySQL is used to realize comprehensive data management.

The proposed anti-corrosion system thoroughly considers a full use of corrosion data, relevant corrosion prediction and efficient corrosion management in one system. Therefore, this system can achieve an accurate prediction of corrosion rate, risk evaluation, risk alert and expert suggestion for equipment in petrochemical plants.

Collectively, this present study has important ramifications for the more efficient and scientific management of corrosion data in enterprises and experts’ guidance in controlling corrosion status. At the same time, the digital management of corrosion data can provide a data support for related theoretical researches in corrosion field, and the intelligent system also offers examples in other fields to improve system by adding intelligence means.

The aim of this paper is to investigate the failure probability in an irregular area in pipeline (elbow) over its lifetime. The reliability analysis is performed by using of an enhanced first-order reliability method / second-order reliability method (FORM/SORM) and Monte Carlo simulation methods: a numerical model of a corroded pipeline elbow was developed by using finite element method; also, an empirical mechanical behavior model has been proposed. A numerical case with high, moderate and low corrosion rates was conducted to calculate the deferent reliability indexes. The found results can be used in an application case for managing an irregular area in pipeline lifetime. Hence, it is necessary to ensure a rigorous inspection for this part of a pipeline to avoid human and environmental disasters.

The present paper deals a methodology for estimating time-dependent reliability of a corroded pipeline elbow. Firstly, a numerical model of corroded elbow is proposed by using the finite element method. A mechanical behavior under the corrosion defect in time is studied, and an empirical model was also developed.

The result of this paper can be summarized as: a mechanical characterization of the material was carried out experimentally. A numerical model of a corroded pipeline elbow was developed by using the finite element method. An empirical mechanical behavior model has been developed. The reliability of a corroding pipe elbow can be significantly affected by corrosion and residual stress. A proportional relationship has been found between probability of failure and corrosion rate. The yield stress and pressure service have an important sensitivity factor.

Aiming to help Algerian gas and oil companies' decision makers, the present paper illustrates a methodology for estimating time-dependent reliability of a corroded pipeline elbow over its lifetime using numerical models by applying the finite element method. Firstly, a numerical model of a corroded pipe elbow was developed and coupled with an empirical mechanical behavior model, which is also proposed. A probabilistic is then developed to provide realistic corrosion parameters and time modeling, leading to the real impact on the lifetime of an elbow zone in pipeline. The reliability indexes and probability of failure for various corrosion rates with and without issued residual stress are computed using Monte Carlo simulation and FORM.

The purpose of this paper is to develop an equation for the synergistic corrosion of SRB and CO₂ based on the D-W model.

The bacterial types in the a and ß pipelines were studied by the most probable number method, and the corrosion morphology of L360 in pipeline water samples was studied by surface analysis. The corrosion rate of L360 was studied using the weight loss method. The gray correlation method was used to calculate the degree of correlation between the influencing factors of corrosion under the synergistic effect of CO₂ and SRB. The curve obtained from PIPESIM software and experiments data was then fitted using multiple non-linear regression method by MATLAB software.

The equation was used to predict the corrosion of the ß pipeline for verification, and it was found that seven out of ten excavation sites were within a 20% error range.

Using the gray correlation method, an equation that considers synergistic corrosion of SRB and CO₂ has been developed based on the D-W model. The equation could be used to predict the corrosion rate of shale gas gathering pipelines through SRB and CO₂ synergistic corrosion.

The purpose of this paper is to model the corrosion rate behavior for two ferrous materials, carbon steel AISI 1020 and stainless steel AISI 304, immersed in ferric sulfate and ferric chloride solutions using D-optimal design with response surface methodology.

Experimental design addresses two factors (concentration and contact time) with multilevel categories, in order to predict and compare the corrosion rates of the studied materials immersed in flocculants solutions. A corrosion rate of specimens was calculated from mass loss determinations.

The authors used a polynomial model to fit the experimental values, thereby predicting significantly higher corrosion rates in ferric chloride solutions, as compared to ferric sulfate.

The authors propose a high fidelity model of the corrosion rate of each carbon steel and stainless steel material using D-optimal design with a response surface method (RSM).

Reliable estimations of the extent of corrosion and time required to reach specific safety limits are crucial for assessing the reliability of aging reinforced concrete (RC) bridges. Engineers and decision-makers can use these figures to plan suitable inspection and maintenance operations.

Analytical, empirical and numerical approaches for estimating the service life of corroded RC structures were presented and compared. The concrete cover cracking times, which were predicted by the previously proposed analytical models, were compared with the experimentally obtained cracking times to identify the model/s for RC bridges. The shortcomings and limitations of the existing models are discussed.

The empirical models typically depend on the rate of corrosion, diameter of steel reinforcement and concrete cover depth and based on basic mathematical formula. In contrast, the analytical and numerical models contain the strength and stiffness properties of concrete as well as type of corrosion products and incorporate more complex mechanical factors. Four existing analytical models were analyzed and their performance was evaluated against existing experimental data in literature. All the considered analytical models were assumed thick-walled cylinder models. The maximum difference between observed cracking time from different test data and calculated cracking time using the developed models is 36.5%. The cracking times extend with increase in concrete cover and decrease with corrosion current density. The development of service life prediction models that considers factors such as heterogeneity of concrete, non-uniform corrosion along rebar, rust production rate and a more accurate representation of the corrosion accommodating region are some of the areas for further research.

Outcome of this paper partially bridge the gap between theory and practice, as it is the basis to estimate the serviceability of corrosion-affected RC structures and to propose maintenance and repair strategies for the structures. For structural design and evaluation, the crack-width criterion is the greatest practical importance, and structural engineers, operators and asset managers should pay close attention to it. Additionally, repair costs for corrosion-induced serviceability failures, particularly concrete cracking and spalling, are significantly higher than those for strength failures. Therefore, to optimize the maintenance cost of RC structures, it is essential to precisely forecast the serviceability of corrosion-affected concrete structures. The lifespan of RC structures may be extended by timely repairs. This helps stake holders to manage the resources.

In order to improve modeling of corrosion-induced cracking, important areas for future research were identified. Heterogeneity properties of concrete, concept of porous zone (accommodation effect of pores should be quantified), actual corrosion morphology (non-uniform corrosion along the length of rebar), interaction between sustain load and corrosions were not considered in existing models. Therefore, this work suggested for further researches should consider them as input and develop models which have best prediction capacity.

This work has positive impact on society and will not affect the quality of life. Predicting service life of structures is necessary for maintenance and repair strategy plans. Optimizing maintenance strategy is used to extend asset life, reduce asset failures, minimize repair cost, and improve health and safety for society.

The degree of accuracy and applicability of the existing service life prediction models used for RC were assessed by comparing the predicted cracking times with the experimentally obtained times reported in the literature. The shortcomings of the models were identified and areas where further research is required are recommended.

This paper aims to discover the mathematical model for Q235 carbon steel corrosion date acquired in the initial stage of atmospheric corrosion using electrical resistance probe.

In this paper, mathematical approaches are used to construct a classification model for atmospheric environmental elements and material corrosion rates.

Results of the experiment show that the corrosion data can be converted into corrosion depth for calculating corrosion rate to obtain corrosion kinetics model and conform corrosion acceleration phase. Combined with corresponding atmospheric environmental elements, a real time grade subdivision model for corrosion rate can be constructed.

These mathematical models constructed by real time corrosion data can be well used to research the characteristics about initial atmospheric corrosion of Q235 carbon steel.