Corrosion in Wet Oil Piping: Root Cause Failure Analysis,Mitigation and Neural Networking

This paper discusses the typical corrosion anomalies likely to occur in the wet oil system of a Floating Storage and Offloading Vessel (FPSO). The root causes and operational mitigations are identified. A neural network is proposed for capturing relationships within the large volume and diversity of data and hence permit effective modelling of corrosion and integrity of specific piping sections. Novel mitigations which can minimize severity of wall loss for flowing lines include; corrosion modelling of separator fluids and consequent pressure and temperature adjustments and calculated partition coefficients P derived from corrosion inhibitor (CI) injection and residual lab data for first-pass assessment of the effectiveness of CI injections, hence providing adequate inhibition.     

Root Cause Failure Analysis and Mitigation of Corrosion in Seawater Injection Piping

This paper illustrates the methodology for performing a root cause failure analysis of corrosion anomalies reported in the low pressure section of an FPSO seawater injection piping system. Specific practical actions are recommended for mitigating the identified root causes of failure. The primary root cause of failure is oxygen corrosion due to oxygen ingress at components upstream (u/s) and downstream (d/s) of the sulfate removal (SRM) pumps. Oxygen corrosion was worsened by underdeposit corrosion caused by unavailability of coarse straining of abstracted seawater. The secondary root causes are likely due to: deterioration of graphite-filled gaskets on the flanges; occasional bisulphite overdosing; incorrectly specified oxygen scavenger; non-optimized scavenger injection rates; incorrect risk assessment; and unavailability of hypochlorination of abstracted seawater. This paper recommends that the primary and secondary root causes should be further investigated and mitigated. The less difficult but big-impact mitigations which should reduce significantly the number and severity of reported anomalies include: modeling corrosion (based on dissolved oxygen concentration inputs) with predicted velocities (V) guiding operational adjustments within the target range 2 < V < 10 m/s and the predicted cumulative corrosion rates used to target and optimize inspection requirements; inspecting and testing each component u/s and d/s of the SRM pump, in order to identify locations of oxygen ingress; and checking deaeration performance especially possible leaks along the vacuum pump system. Results of KPIs should comply with the specified targets and be managed as part of the corrosion management system.     

管线钢在湿气介质中的H_2S/CO_2腐蚀行为研究

利用高温高压反应釜模拟高含硫气田H2S/CO2共存环境,在流动湿H2S/CO2介质中进行腐蚀实验,辅以SEM,EDS和XRD,探讨了湿气介质中高H2S分压对API-X52和API-X60管线钢H2S/CO2腐蚀行为的影响。两种钢在湿气介质中的腐蚀速率均随H2S分压的升高而增加,X60腐蚀速率略高于X52,随着H2S分压由0.15MPa增至2.0MPa,腐蚀形态由全面腐蚀趋向局部腐蚀,腐蚀过程由H2S控制,腐蚀产物以四方晶系的FeS1-x(Mackinawite)为主。X60钢表面出现氢鼓泡,内部发生氢致开裂。     

高温高压酸性气井油套管钢在超临界CO_2环境下的腐蚀行为

高温高压酸性气井腐蚀环境恶劣,油套管腐蚀、变形、破损等事故频繁发生,严重影响气井安全生产。为了解掌握油套管钢的腐蚀类型、严重程度及耐蚀性能,利用高温高压反应釜在模拟井底实际工况条件下研究了J55、N80、P110、13Cr、S13Cr 5种油套管材质的抗CO_2腐蚀性能,运用失重法、扫描电镜(SEM)和能谱分析等技术,重点分析了腐蚀速率、腐蚀产物膜形貌和腐蚀产物膜成分。结果表明:在本试验测试范围内,J55、N80、P110钢在90℃时腐蚀速率为最大,然后随温度升高而降低,属于极严重腐蚀;13Cr、S13Cr钢的腐蚀速率随温度的升高不断增大,在150℃达到最大值;5种材料的平均腐蚀速率随CO_2分压的增大呈先上升后下降的趋势;碳钢材质腐蚀类型主要为均匀腐蚀+局部腐蚀,含Cr钢材质腐蚀类型主要为均匀腐蚀;碳钢CO_2腐蚀产物膜主要成分为FeCO_3,同时夹杂有少量的Fe_3C和铁的氧化物或铁单质;13Cr和S13Cr钢CO_2腐蚀产物膜的主要成分为晶态FeCO_3和非晶态的Cr(OH)_3,此外,还含有少量的Fe或Cr的氧化物、碳化物和单质Fe等。     

燃煤烟气中SO3的产生与转化及其抑制对策探讨

燃煤烟气中高浓度SO3的存在,不仅使烟囱出口出现“蓝烟”现象,而且会对锅炉系统造成腐蚀和污染,严重影响机组运行.针对这一现象,探讨了烟气中SO3的发生机理和SO3在锅炉系统各环节的产生与转化过程,并提出了目前抑制燃煤烟气中SO3生成和排放的几个方向,为抑制SO3生成和排放提供解决思路.     

N80油管钢在CO_2/H_2S水介质中的腐蚀研究

油田设施受产出水和CO2/H2S腐蚀严重.以长庆某天然气井产出水为腐蚀介质,采用失重法研究了不同腐蚀影响因素对N80钢的作用规律.结果表明,随着介质温度的升高,腐蚀速率先增加后降低,并在60℃时达到最大;Cl-的影响与温度具有基本相似的规律,在Cl-含量为30 g/L时腐蚀速率最大;随着pH值的增大,腐蚀速率持续减小,并在pH值为8.0左右时达到最低;随着CO:分压的增大,腐蚀速率呈单调增大趋势;随着H2S分压的增大,腐蚀速率先下降后又缓慢升高.     

Double Glow Plasma Surface Alloying Process Modeling Using Artificial Neural Networks

A model is developed for predicting the correlation between processing parameters and the technical target of double glow by applying artificial neural network (ANN). The input parameters of the neural network (NN) are source voltage, workpiece voltage, working pressure and distance between source electrode and workpiece. The output of the NN model is three important technical targets, namely the gross element content, the thickness of surface alloying layer and the absorpticm rate (the ratio of the mass loss of source materials to the increasing mass of workpiece) in the processing of double glow plasma surface alloying. The processing parameters and technical target are then used as a training set for an artificial neural network. The model is based on multiplayer feedforward neural network. A very good performance of the neural network is achieved and the calculated results are in good agreement with the experimental ones.     

Stress corrosion failure of high-pressure gas pipeline

Incidents of failure due to corrosion/stress corrosion cracking of high-pressure gas pipelines in Pakistan have been observed to occur after about 15–20 years of service. The present paper constitutes the failure analysis of an 18-inch diameter electric resistance-welded gas pipeline. The failure was characterized, on the basis of all the available evidence and the metallurgical examination carried out on the ruptured pipe, as a stress corrosion failure that had initiated at a longitudinal ‘stress raiser’. This stress raiser, which was essentially a manufacturing defect, constituted a longitudinal ‘step’ on the pipe surface that had resulted from the faulty trimming/shaving of the weld flash. The findings of this study, thus, emphasize the need for the care that must be taken during the shaving-off of the weld flash.     

天然气外输管材腐蚀适应性分析

针对我国西部某油田的一气田地面天然气处理及外输系统存在的腐蚀问题,重点对管道内外腐蚀环境进行调查,对系统内腐蚀性物质的来源和性质进行分析化验,以明确系统的腐蚀的原因和机理。在此基础上,对该气田地面天然气处理及外输系统腐蚀缓解措施进行分析和研究。结果表明:无残酸返排的天然气外输管线属于中度腐蚀程度,需加以关注;而有残酸返排的管线属于严重或极严重腐蚀程度,应采取防腐蚀措施。     

Erosion–corrosion of preoxidised Incoloy 800H in fluidised bed environments: effects of temperature,velocity, and exposure time

Abstract

The effects of preoxidation as a potential protective measure for alloys exposed to erosion–corrosion have been evaluated for Incoloy 800H in laboratory simulated fluidised bed conditions. The performance of the specimens after exposure to such environments was estimated from weight change data, electron microscopy, and X-ray diffraction patterns. The results showed that, in ‘corrosion dominated’ conditions, i.e. at relatively high temperatures and low velocities, preoxidation was successful in reducing the erosion–corrosion of the underlying alloy. However, when the velocity was increased and the temperature decreased, preoxidation afforded only some short term protection to the alloy. In these more ‘erosion–corrosion dominated’ regimes, preoxidation delayed the incubation period for erosion–corrosion of the alloy, but, once the scale was removed, the erosion–corrosion rates were similar to those of the non-preoxidised alloys. The effects of temperature, velocity, and exposure time are discussed for the preoxidised and non-preoxidised alloys. Comparisons are made between the results of the present and other erosion–corrosion studies, to explain the distinctive pattern of alloy wastage in these environments.

MST/1432     

High-temperature corrosion of superalloys

The performance of gas turbines has been improved by the development of alloys with progressively increasing high-temperature capabilities. While both strength and corrosion resistance are important, the strength requirements have a higher priority, and alloy developments which led to higher strengths also had the effect of reducing the corrosion resistance, particularly with nickel-base alloys. The most important form of corrosion is the accelerated oxidation which takes place when the air or fuel is contaminated with certain impurities, of which alkali metal salts are the most important. This type of attack is generally known as ‘hot corrosion’. Two different forms of hot corrosion have been distinguished. Type I, which is present over a temperature range of about 800–950°C, and type II, which is present over the range 700–800°C. Both processes involve an incubation period, an initiation step, and a propagation stage. Most attention has been given to the propagation stage but, from a technical point of view, the initiation step is the most important process. Mechanisms suggested include the salt fluxing model, the electrochemical model, and the sulphidation–oxidation model. Both the practical and theoretical aspects of the problem will be reviewed.     

减二线馏分油中炼厂常用钢材的动态冲刷腐蚀行为

为了更好地解决炼厂在流动条件下减二线馏分油对管路的腐蚀问题,研究了流动条件下Q235碳钢和Cr5Mo合金钢的耐环烷酸和硫冲刷腐蚀性能,并与炼厂常用钢材渗铝碳钢和304不锈钢进行比较。结果表明:Cr5Mo钢的腐蚀速率明显小于Q235钢的,酸值越大两者的腐蚀差别越明显(酸值>5 mg KOH/g);随着酸值和硫含量的增大,Q235钢腐蚀速率有明显增大的趋势; Cr5Mo钢的腐蚀速率随着酸值的增大基本保持不变,甚至有一定的下降;相比于Q235(腐蚀速率6.3 mm/a)和Cr5Mo钢(腐蚀速率1.5 mm/a),渗铝碳钢和304不锈钢表现出优异的耐冲刷腐蚀性能,渗铝碳钢腐蚀速率为0.2 mm/a,而304不锈钢几乎没有失重。     

Insight into atmospheric corrosion evolution of mild steel in a simulated coastal atmosphere

The corrosion behavior of mild steel in a simulated coastal atmosphere environment has been investigated by the indoor accelerated wet/dry cyclic corrosion acceleration test(CCT),scanning electron microscopy(SEM),Raman spectroscopy and electrochemical measurements.During the CCT test of 60 cycles,the evolution of logarithmic(corrosion rate)vs.logarithmic(CCT cycles)presents a turning point at the 5th cycle,presenting a tendency to increase first and then decrease to gradually stabilize as the CCT cycle prolonged.Before the 5th cycle,γ-FeOOH and β-FeOOH and Fe3O4 were detected,respectively.And then,α-FeOOH as a new chemical composition was detected in the subsequent corrosion cycles.It is found that,after long term corrosion,the rust separated into a relatively dense inner layer rich with α-FeOOH and a loose outer layer rich with γ-FeOOH,both of which have poor electrical conductivity.The rapid increase of corrosion rate in the early stage since reducible corrosion products are involved in the reduction process of the cathode which promotes the dissolution of the anodic metal substrate.Afterward,as the rust layer thickens,the resistance of the rust increases,and the aggressive ions diffusion is blocked,gradually suppressing the electrochemical corrosion process.At last,when the composition and distribution of the rust layer remain stable,the corrosion presents a fluctuating speed around a certain value during the cracking and self-repairing process of the rust layer.     

模拟沿海大气环境下铝合金搭接件电偶腐蚀行为研究

铝合金搭接结构材料2A12与螺栓材料ML30CrMnSiA因存在电位差,在沿海潮湿的大气环境中服役时会发生电偶腐蚀。采用自制实验装置模拟沿海大气环境,通过电化学极化曲线测试法分别测量铝合金材料和螺栓材料在0.5mm厚液膜下的边界值,运用数值仿真软件BEASY对搭接件表面偶合后的电位、电流密度分布及腐蚀速率进行模拟计算。研究结果表明,铝合金板2A12与螺栓搭接后作为偶对阳极电位正移:与螺栓直接接触的位置,阳极极化程度最高,电偶腐蚀速率最大;随与螺栓距离增大,铝合金板的电偶腐蚀速率向两侧递减。     

Book Reviews

‘Early’ creep-fatigue crack growth rates have been measured in complex-cycle large single edge notched bend feature-specimen tests on a 1¼ CrMoV turbine casting steel at 550°C. Crack propagation rates initially accelerate with increasing distance below the stress concentration to a peak value. The depth at which this maximum occurs depends on the notch geometry and the magnitude of any superimposed primary loading. ‘Early’ creep-fatigue crack growth rates are dependent on crack size, notch root strain range and any creep damage accumulated due to primary and secondary loading.     

长北气田某气井油管腐蚀速率增大原因

长北气田油管整体腐蚀速率缓慢,但某气井在多臂井径检测中发现,该油管局部腐蚀速率增大,远远大于整个气田的油管腐蚀速率和该井前期的腐蚀速率.进行了水质、气质组分分析、多臂井径检测和腐蚀挂片等试验,分别对腐蚀挂片的宏观形貌及腐蚀产物进行了分析,并结合油管的腐蚀程度和腐蚀情况,对该井油管腐蚀速率突然加快的原因及腐蚀机理进行了分...     

Neural Network Mapping of Corrosion Induced Chemical Elements Degradation in Aircraft Aluminum

A neural network (NN) model is developed for the analysis and prediction of the mapping between degradation of chemical elements and electrochemical parameters during the corrosion process. The input parameters to the neural network model are alloy composition, electrochemical parameters, and corrosion time. The output parameters are the degradation of chemical elements in AA 2024-T3 material. The NN is trained with the data obtained from Energy Dispersive X-ray Spectrometry (EDS) on corroded specimens. A very good performance of the neural network is achieved after training and validation with the experimental data. After validating the NN model, simulations were carried out to obtain the trends in element degradation with varying pH values, and the results showed correct trends. The preliminary results obtained demonstrate that through a comprehensive study, a better corrosion resistant material can be designed by controlling the degradation of the chemical elements during the corrosion process through neural network methods.     

Effect of tin addition on corrosion behavior of a low-alloy steel in simulated costal-industrial atmosphere

The effect of tin addition on the atmospheric corrosion behavior of a low-alloy steel in simulated coastal-industrial atmosphere has been investigated by indoor wet/dry cyclic corrosion test (CCT). The results indicate that tin addition can obviously make the steel substrate more resistant to atmospheric corrosion by suppressing the cathodic H⁺ reduction reaction, and but tin addition is not of obvious beneficial effect when the steel is covered with a thicker rust layer during long-term corrosion process. The reason lies in the fact that the presence of un-reduced H⁺ can lower the electrolyte pH value and lead to a loose and porous rust layer on tin-containing steel sample than that on tin-free steel sample. In addition, the 120 CCT cycles corrosion process of the two steels can be divided into three stages. Both the tin-free and tin-containing steels show an increasing corrosion rate during the initial corrosion stage and then exhibit a decreasing corrosion rate during the second and third corrosion stages. Moreover, tin addition makes the tin-containing steel rust layer have a higher amount of α-FeOOH and lower amount of γ-FeOOH and Fe₃O₄ than the tin-free steel rust layer.     

Elimination of Surface Defects in High Tensile Steel for Wheel Rim Application

One of the important applications of high tensile steel grades is in wheel rims by the automotive industry. High tensile steel facilitates vehicle weight reduction under the ‘Go Green’ initiative. Along with weight reduction, in recent times, the surface quality requirement of steels for wheel rim applications has also gained a significant focus, and in many cases, it is becoming the cause of rejection at the customers’ processing line. It is known that owing to chemistry requirements such high strength steel grades generally show peritectic behavior during solidification and are prone to surface defects. Tata Steel India produces several wheel rim grades of varying strength levels. In one such high manganese and micro-alloyed peritectic steel grade, the rejection by the customer on account of surface defects was a major concern. The defects consisted of typical longitudinal cracks of varying dimensions along with the unique defects in transverse direction named tear marks on the surface of 100-mm-thick plates rolled from 215-mm-thick slab. In subsequent stages, these plates were processed into rim profiles through hot working by the wheel customer. The paper highlights how systematic study led to arrive at root causes and helped redesign steel chemistry to ensure zero rejection for surface quality without affecting mechanical property requirements.     

Using fuzzy analytic hierarchy process and particle swarm optimisation for balanced and defective supply chain problems considering WEEE/RoHS directives

This research explored problems concerning production and delivery in a green supply chain, and constructed an optimal mathematical model to provide solutions. This model incorporates WEEE and RoHS in EU directives for the selection of green partners when establishing a supply chain. The weight of each component is calculated by fuzzy analytic hierarchy process (fuzzy AHP). Previous studies suggested that a supply chain is a balanced system, however, in actual practice, there may be processing damages or delivering losses. Thus, such a supply chain with production loss is known as a ‘defective supply chain’. This research analysed the defective supply chain system to discuss its supplier selection, production, and distribution. It developed an optimal mathematical model for both balanced and defective models, and adopted particle swarm optimisation (PSO) to obtain solutions for both models. Finally, case studies for both models with quality solutions were discussed to confirm the efficiency and effectiveness of the proposed approach.