Settling velocity of microplastics in turbulent open-channel flow

The Science of The Total Environment, Год журнала: 2024, Номер 946, С. 174179 - 174179

Опубликована: Июнь 24, 2024

Язык: Английский

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Interpretable machine learning reveals transport of aged microplastics in porous media: Multiple factors co-effect

Water Research, Год журнала: 2025, Номер 274, С. 123129 - 123129

Опубликована: Янв. 12, 2025

Язык: Английский

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Machine learning-supported determination for site-specific natural background values of soil heavy metals

Journal of Hazardous Materials, Год журнала: 2025, Номер 487, С. 137276 - 137276

Опубликована: Янв. 18, 2025

Язык: Английский

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Centrifugal microfluidic chip for multi-stage sorting and detection of microplastics at micron scale

Analytica Chimica Acta, Год журнала: 2025, Номер 1351, С. 343883 - 343883

Опубликована: Март 5, 2025

Язык: Английский

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Microplastic pollution in Taihu lake: Spatial distribution from the lake inlet to the lake centre and vertical stratification in the water column

Environmental Pollution, Год журнала: 2024, Номер 363, С. 125102 - 125102

Опубликована: Окт. 10, 2024

Язык: Английский

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Towards better predicting the settling velocity of film-shaped microplastics based on experiment and simulation data

Marine Pollution Bulletin, Год журнала: 2024, Номер 203, С. 116493 - 116493

Опубликована: Май 16, 2024

Язык: Английский

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Principles, Challenges, and optimization of Indigenous Microalgae-Bacteria consortium for sustainable swine wastewater treatment

Bioresource Technology, Год журнала: 2024, Номер 406, С. 131055 - 131055

Опубликована: Июнь 27, 2024

Язык: Английский

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Tracing the Footprint of Microplastics: Transport Mechanism, Degradation, and Remediation in Marine Environment

Water Air & Soil Pollution, Год журнала: 2025, Номер 236(2)

Опубликована: Янв. 24, 2025

Язык: Английский

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Abundance of microplastics in a typical urban wetland in China: Association with occurrence and carbon storage

Journal of Hazardous Materials, Год журнала: 2025, Номер 488, С. 137451 - 137451

Опубликована: Янв. 30, 2025

Язык: Английский

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Machine learning-based prediction for airflow velocity in unpressured water-conveyance tunnels

Physics of Fluids, Год журнала: 2025, Номер 37(2)

Опубликована: Фев. 1, 2025

Spillway and drainage tunnels have an open-channel flow pattern when operating under unpressured condition, above which air is driven resisted by water flow, wall friction, pressure difference. Unpressured present many airflow-related safety environmental issues, including fluctuation, gate vibration, shaft cover blow-off, odor emission; therefore, it valuable to study predict their airflow velocity. Given the difficulty in accurate prediction of velocity complicated influences hydraulic, structural, boundary parameters, this focuses on establishing high-performance models understanding importance independent coupled each parameter using machine learning. It found that Froude number, ratio free-surface width unwetted perimeter, relative ventilation area, tunnel length are four key parameters. By these parameters input combination, learning can well tunnels, achieving significantly higher performance than existing empirical theoretical models. Among models, built Random Forest XGBoost demonstrate best with R2 ≥ 0.911. The interpretability analysis reveals highest number increases generally result enhancement plays a dominant role ≤11.5, continuous increase exhibits marginal effect. area close importances, either promoting To help researchers engineers unfamiliar easily accurately GPlearn algorithm employed establish explicit expressions, validated good 0.900.

Язык: Английский

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