Fabrication of biochar-based superhydrophobic coating on steel substrate and its UV resistance, anti-scaling, and corrosion resistance performance DOI Creative Commons
M. E. Mohamed, Adel Ouannas, E. Khamis

et al.

Scientific Reports, Journal Year: 2023, Volume and Issue: 13(1)

Published: June 10, 2023

In this study, we report an eco-friendly and facile process for the synthesis of biochar, BC, a cobalt-biochar nanocomposite, Co-BC, using rice straw biomass. We constructed two superhydrophobic coatings on steel substrates potentiostatic electrodeposition nickel-modified Ni@BC, nickel modified by Ni@Co-BC, then, these were soaked in ethanolic stearic acid solution. Fourier transform infrared spectroscopy showed that acid-grafted Ni@BC coating, Ni@BC@SA, Ni@Co-BC composite, Ni@Co-BC@SA, well grafted surface. Scanning electron microscopy revealed have nanoscale features. Atomic force results Ni@Co-BC@SA coat had higher roughness than resulting superhydrophobicity. The water contact angles Ni@BC@SA 161° 165°, respectively, while values sliding both 3.0° 1.0°, respectively. Quantitative estimation scale inhibition efficiency coating exhibited greater compared to coating. Additionally, demonstrated improved corrosion resistance, UV mechanical abrasion chemical stability These highlight superior performance its potential as highly effective durable substrates.

Language: Английский

Autopilot control unmanned aerial vehicle system for sewage defect detection using deep learning DOI Creative Commons
Binay Kumar Pandey, Digvijay Pandey, Kameshwar Sahani

et al.

Engineering Reports, Journal Year: 2024, Volume and Issue: unknown

Published: Jan. 29, 2024

Abstract This work proposes the use of an unmanned aerial vehicle (UAV) with autopilot to identify defects present in municipal sewerage pipes. The framework also includes effective control mechanism that can direct flight path a UAV within sewer line. Both these breakthroughs have been addressed throughout this work. UAV's camera proved useful sewage inspection, providing important contextual data helped analyze line's internal condition. A plethora information for understanding inner functioning and extracting interior visual details be obtained from camera‐recorded imagery if defect is present. In case inspections, nevertheless, impact false negative significantly higher than positive. One trickiest parts procedure identifying defective pipelines negatives. order get rid outcome or positive outcome, guided image filter (GIF) implemented proposed method during pre‐processing stage. Afterwards, algorithms Gabor transform (GT) stroke width (SWT) were used obtain features UAV‐captured surveillance image. camera's then classified as “defective” “not defective” using by Weighted Naive Bayes Classifier (WNBC). Next, images lines captured are analyzed speed‐up robust (SURF) deep learning different types defects. As result, methodology achieved more favorable outcomes prior existing approaches terms following metrics: mean PSNR (71.854), MSE (0.0618), RMSE (0.2485), SSIM (98.71%), accuracy (98.372), specificity (97.837%), precision (93.296%), recall (94.255%), F1‐score (93.773%), processing time (35.43 min).

Language: Английский

Citations

132

Computational and experimental studies on the corrosion inhibition performance of an aerial extract of Cnicus Benedictus weed on the acidic corrosion of mild steel DOI
Abhinay Thakur, Savaş Kaya, Ashraf S. Abousalem

et al.

Process Safety and Environmental Protection, Journal Year: 2022, Volume and Issue: 161, P. 801 - 818

Published: March 30, 2022

Language: Английский

Citations

116

Advances in corrosion growth modeling for oil and gas pipelines: A review DOI
Haonan Ma, Weidong Zhang, Yao Wang

et al.

Process Safety and Environmental Protection, Journal Year: 2022, Volume and Issue: 171, P. 71 - 86

Published: Dec. 27, 2022

Language: Английский

Citations

71

Sulfur-doped graphitic carbon nitride (S-g-C3N4) as an efficient corrosion inhibitor for X65 pipeline steel in CO2- saturated 3.5% NaCl solution: Electrochemical, XPS and Nanoindentation Studies DOI
Valentine Chikaodili Anadebe, Vitalis Ikenna Chukwuike, Vinoth Kumar Selvaraj

et al.

Process Safety and Environmental Protection, Journal Year: 2022, Volume and Issue: 164, P. 715 - 728

Published: June 28, 2022

Language: Английский

Citations

62

A review of risk-based decision-making models for microbiologically influenced corrosion (MIC) in offshore pipelines DOI
Mohammad Yazdi, Faisal Khan, Rouzbeh Abbassi

et al.

Reliability Engineering & System Safety, Journal Year: 2022, Volume and Issue: 223, P. 108474 - 108474

Published: March 16, 2022

Language: Английский

Citations

56

A CNN-based transfer learning method for leakage detection of pipeline under multiple working conditions with AE signals DOI
Pengqian Liu,

Changhang Xu,

Jing Xie

et al.

Process Safety and Environmental Protection, Journal Year: 2022, Volume and Issue: 170, P. 1161 - 1172

Published: Dec. 24, 2022

Language: Английский

Citations

50

Optimization of the corrosion inhibition performance of 2-mercaptobenzothiazole for carbon steel in HCl media using response surface methodology DOI
Soroush Ahmadi, Azizollah Khormali

Fuel, Journal Year: 2023, Volume and Issue: 357, P. 129783 - 129783

Published: Sept. 12, 2023

Language: Английский

Citations

41

Evaluating the adsorption and corrosion inhibition capabilities of Pyridinium - P - Toluene Sulphonate on MS in 1 M HCl medium: An experimental and theoretical study DOI
Humira Assad, Suresh Kumar, Sourav Kr. Saha

et al.

Inorganic Chemistry Communications, Journal Year: 2023, Volume and Issue: 153, P. 110817 - 110817

Published: May 10, 2023

Language: Английский

Citations

31

INTEGRATING ADVANCED TECHNOLOGIES IN CORROSION AND INSPECTION MANAGEMENT FOR OIL AND GAS OPERATIONS DOI Creative Commons

Patrick Oputa Odili,

Cosmas Dominic Daudu,

Adedayo Adefemi

et al.

Engineering Science & Technology Journal, Journal Year: 2024, Volume and Issue: 5(2), P. 597 - 611

Published: Feb. 25, 2024

The oil and gas industry is witnessing a paradigm shift in corrosion detection, inspection methodologies, maintenance practices due to the integration of advanced technologies. This paper explores how cutting-edge technologies, including artificial intelligence (AI), robotics, Internet Things (IoT), are revolutionizing management operations. AI-powered algorithms enable predictive by analyzing vast datasets identify patterns predict equipment failure. Robotics plays pivotal role remote inspection, offering unprecedented access critical infrastructure while minimizing human risk. Additionally, IoT sensors provide real-time monitoring rates, temperature, pressure, facilitating proactive enhancing asset integrity management. deep dive into technologies reveals their synergistic impact on management, processes, strategies industry. By leveraging AI, IoT, operators can optimize performance, extend lifespan, minimize downtime, ultimately operational efficiency ensuring regulatory compliance. Through case studies examples, this illustrates practical application optimization. Furthermore, it discusses challenges opportunities associated with these highlighting need for data standardization, cybersecurity measures, workforce upskilling. As sector embraces digital transformation, adoption poised drive significant improvements reliability, safety, environmental stewardship. underscores importance embracing innovation address unlock new sustainable operations sector. Keywords: Advanced Technologies, Corrosion, Inspection, Management, Oil Gas.

Language: Английский

Citations

14

Optimizing wastewater treatment through artificial intelligence: recent advances and future prospects DOI Creative Commons
Mudita Nagpal,

Miran Ahmad Siddique,

Khushi Sharma

et al.

Water Science & Technology, Journal Year: 2024, Volume and Issue: 90(3), P. 731 - 757

Published: July 26, 2024

Artificial intelligence (AI) is increasingly being applied to wastewater treatment enhance efficiency, improve processes, and optimize resource utilization. This review focuses on objectives, advantages, outputs, major findings of various AI models in the three key aspects: prediction removal efficiency for both organic inorganic pollutants, real-time monitoring essential water quality parameters (such as pH, COD, BOD, turbidity, TDS, conductivity), fault detection processes equipment integral treatment. The accuracy (

Language: Английский

Citations

11