Study of corrosion resistrance of pipeline API 5L X42 using green inhibitor bawang dayak (<i>Eleutherine americanna Merr.</i>) in 1M HCl

Azmi, Muhammad Fikri; Soedarsono, Johny Wahyuadi

doi:10.1088/1755-1315/105/1/012061

Cited by 10 publications

(9 citation statements)

References 7 publications

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“…When value is around − 20 kJmol −1 or less negative, then the interaction is only electrostatic then the adsorption is considered as physisorption. On the other hand, when value is equal or more negative than − 40 kJmol −1 , then the interaction is associated with charge transfer, i.e., chemisorption (Azmi and Soedarsono 2018 ; Verma et al 2018b ). The values of in Table 4 indicate that the adsorption in this study is actually physicochemical, as the values in both acidic media lie between − 20 kJmol −1 and − 40 kJmol −1 .…”

Section: Resultsmentioning

confidence: 99%

Novel use of kitchen waste: protection of boiler quality steel from corrosion in acidic media using onion waste

Pal

Das

2022

Chem. Pap.

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An eco-friendly approach to inhibit the corrosion of boiler quality (BQ) steel by onion waste in acidic media was investigated. The extract from onion peel was characterized using the conventional extraction method and was characterized using HPLC. The efficacy of the onion peel extract (OPE) as a green corrosion inhibitor was studied using the weight loss method and a variety of electrochemical techniques, including open-circuit potential (OCP), potentiodynamic polarization (PDP), and electrochemical impedance spectroscopy (EIS). The Tafel polarization revealed that at 200 mg L −1 of onion peel extract (OPE), corrosion current density was reduced maximum in both 1 (M) HCl and 0.5 (M) H 2 SO 4 media. From the electrochemical impedance spectroscopy studies, the maximum inhibition efficiencies of 91.30% and 90.71% were found at 200 mg L −1 in 1 (M) HCl and 0.5 (M) H 2 SO 4 , respectively. The Langmuir isotherm was determined to be the best-fitting model, and the thermodynamic parameter, such as free energy , was computed, which indicated the physisorption of OPE onto the BQ surface. In theoretical investigations, density functional theory DFT was used to determine the adsorption efficiency and reactive sites of the OPE molecule by exploring various quantum chemical parameters. Supplementary Information The online version contains supplementary material available at 10.1007/s11696-022-02549-7.

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Section: Resultsmentioning

confidence: 99%

Novel use of kitchen waste: protection of boiler quality steel from corrosion in acidic media using onion waste

Pal

Das

2022

Chem. Pap.

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“…The maximum efficiency of inhibition, i.e., 84.5% occurred when the concentration of 1000 ppm inhibitor is added to 1M HCl. At 1000 ppm, the corrosion current density of steel decreased to 81635 μA, and solution resistance increased to 748 Ω. Bawang Dayak's extract inhibited the isothermic Langmuir mode, which will generally control the process of charge transfer on the steel interface of the API 5L X42 [90]. Another extract of Brassica oleracea demonstrated outstanding mixed-type corrosion prevention properties in acidic conditions, i.e., 0.5M H 2 SO 4 of pipeline steel corrosion.…”

Section: Oil and Gas Sectormentioning

confidence: 98%

Green Corrosion Inhibitors for Technological Applications

Kumar

2021

Theory and Applications of Green Corrosion Inhibitors

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Corrosion is an inevitable fact of day-to-day life, and however, because of its technological, economic, and aesthetic significance, it always receives much attention. Most of the corrosion inhibitors are environmentally harmful and toxic synthetic chemicals. In view of the toxicity of the inhibitors, the search for an eco-friendly and non-toxic corrosion inhibitor is of great interest. Green corrosion inhibitors are of concern because of increased awareness and improvements in regulations related to the environment because of their toxicity, restrict regular corrosion inhibitors. The extracts of natural products contain compounds having oxygen, carbon, nitrogen and sulfur. Such elements facilitate compounds to absorb on the surface of metal, forming a protective film to prevent corrosion. The main purpose of this chapter is to provide a comprehensive study of technological applications of green corrosion inhibitors in different industries, such as reinforced concrete, coating, aircraft, oil and gas, acid pickling, and water industry.

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“…Without RCA, the business impact of material loss consumes the company's time and finances, especially in the oil and gas (O&G) industry. Some mitigation strategies have been implemented, including using a green corrosion inhibitor [8][9][10][11], failure analysis (FA) [12], and Risk-Based Inspection (RBI) based on AI [6]. Amongst the strategies, the blending implementation of FA and AI is critical to preventing uncertainty-induced risk.…”

Section: Literature Review and Problem Statementmentioning

confidence: 99%

Risk analysis of Ex-spool 16” mol: an insight of machine learning and experimental result

Aditiyawarman

Soedarsono

Kaban

et al. 2022

EEJET

Self Cite

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The paper reports the development of a Risk-Based Inspection (RBI)-Machine Learning perspective. The Optical Emission Spectrometry (OES), Tensile and Hardness Test, Scanning Electron Microscope (SEM), Energy Dispersive X-Ray Spectroscopy (EDS), Sulfate Reducing Bacteria Check, and X-Ray Diffraction (XRD) was used to analyze the root cause of the pipeline’s failure. Corrosion attack shows at the cross-section microstructure based on SEM results. Carbon, Manganese, Phosphorous, and sulfur’s chemical composition is dramatically lower than the standard API 5L Grade X42. Siderite and hematite dominate the composition of the corroded area as a result of CO2 dissolving in water. In contrast, hematite is generated due to the pipe and outdoor atmosphere reaction. Severe local wall thinning of the sand abrasion causes the degradation of the material’s mechanical properties and increases the corrosion rate. This result amplifies by the development of Machine Learning (ML) of Pearson Multicollinear Matrix and Supervised ML (Random Forest, Support Vector Machine, and Linear Regression) to estimate the corrosion degradation of the material. The source of datasets provided by ILI inspection includes the calculated PoF Remaining Useful Life (RuL) as input data, while Probability of Failure (PoF) prediction serves as output data. The Random Forest shows superior predictions of 92.18 %, with the lowest validation loss of 0.0316. The modeling result confirms the experimental outcome. This work demonstrates the implementation strategy to reduce the analysis time, minimize human bias, and serve as a reliable reference tool and guideline to maintain the integrity of the subsea pipelines.

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Study of corrosion resistrance of pipeline API 5L X42 using green inhibitor bawang dayak (Eleutherine americanna Merr.) in 1M HCl

Cited by 10 publications

References 7 publications

Novel use of kitchen waste: protection of boiler quality steel from corrosion in acidic media using onion waste

Novel use of kitchen waste: protection of boiler quality steel from corrosion in acidic media using onion waste

Green Corrosion Inhibitors for Technological Applications

Risk analysis of Ex-spool 16” mol: an insight of machine learning and experimental result

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