Investigating the impact of fatty acid profiles on biodiesel lubricity using artificial intelligence techniques

Cleaner Engineering and Technology, Год журнала: 2025, Номер unknown, С. 100913 - 100913

Опубликована: Фев. 1, 2025

Язык: Английский

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Residual strength prediction of corroded pipelines based on physics-informed machine learning and domain generalization

npj Materials Degradation, Год журнала: 2025, Номер 9(1)

Опубликована: Фев. 14, 2025

Язык: Английский

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State-of-the-art progress on artificial intelligence and machine learning in accessing molecular coordination and adsorption of corrosion inhibitors

Applied Physics Reviews, Год журнала: 2025, Номер 12(1)

Опубликована: Янв. 6, 2025

Artificial intelligence (AI) and machine learning (ML) have attracted the interest of research community in recent years. ML has found applications various areas, especially where relevant data that could be used for algorithm training retraining are available. In this review article, been discussed relation to its corrosion science, monitoring control. tools techniques, structure modeling methods, were thoroughly discussed. Furthermore, detailed inhibitor design/modeling coupled with associated limitations future perspectives reported.

Язык: Английский

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A study of creep rupture life prediction for P91 steel with machine learning method: model selection and sensitivity analysis

International Journal of Pressure Vessels and Piping, Год журнала: 2025, Номер unknown, С. 105494 - 105494

Опубликована: Март 1, 2025

Язык: Английский

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An Adaptive Grid Generation Approach to Pipeline Leakage Rapid Localization Based on Time Reversal

Sensors, Год журнала: 2025, Номер 25(6), С. 1753 - 1753

Опубликована: Март 12, 2025

Gas pipeline leakage will result in casualties and property losses if not detected time. Conventional localization methods usually rely on dense grid distribution, leading to high computational costs. This study proposes a time-reversal-based adaptive generation approach enhance efficiency localization. The method introduces resolution adjustment parameter optimize captured signals, allowing for concentration areas based energy distribution. Based this principle, three steps—including signal computation, conventional TR computation the grids—are introduced. Then, an experimental is conducted 55.8 m PVC with piezoceramic transducers, capturing negative pressure wave signals from four points. results demonstrate that proposed maintains comparable accuracy while reducing number of grids time only 0.6% 2.4% those required by uniform methods, respectively. findings offers computationally efficient accurate solution real-time monitoring.

Язык: Английский

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Intelligent Control Strategy for Coal to Ethylene Glycol Wastewater Emission Reduction based on Dynamic Simulation and Reinforcement Learning

Process Safety and Environmental Protection, Год журнала: 2024, Номер unknown

Опубликована: Дек. 1, 2024

Язык: Английский

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