The response characteristics and stability evaluation of vegetated slope under strong wind DOI Creative Commons
Yanlin Liu, Fei Wang,

Feng Ji

et al.

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: Nov. 23, 2024

As one of the major geological disasters in southeastern China, typhoon-induced vegetation slope instability causes significant loss life and property each year. Despite criticality this issue, response mechanism vegetated slopes to wind loading terms soil deformation stability still remains unclear. This research conducted field investigations on 330 historical landslides Yongjia County, Zhejiang Province, analyzing their spatiotemporal distribution developmental characteristics establish a conceptual model. The influence conditions dynamic parameters strength were subsequently determined through numerical simulations using FLAC3D software, model tests, direct shear tests. results show that: (1) is significantly affected by speed. At forces ≤ 12 (hurricane: 32.7-36.9 m/s), plays positive role enhancing stability. ≥ 13 (typhoon: 37.0-41.4 exerts negative under combined action strong loads. (2) Based experimentally evolution parameters, formula c (v, w) was fitted express variation cohesion with speed (v) moisture content (w). (3) optimized evaluation demonstrates increased sensitivity compared traditional model, resulting 17.88% increase sliding force 10.62-11.64% anti-sliding force. accounts for both indirect effects slopes. findings are expected enhance assessment winds facilitate development more accurate machine learning statistical models future.

Language: Английский

Review of smoothed particle hydrodynamics modeling of fluid flows in porous media with a focus on hydraulic, coastal, and ocean engineering applications DOI
Min Luo,

Xiujia Su,

Ehsan Kazemi

et al.

Physics of Fluids, Journal Year: 2025, Volume and Issue: 37(2)

Published: Feb. 1, 2025

A comprehensive review is conducted on the application of Lagrangian mesh-free methods for simulating flows in various types porous media, ranging from fixed structures like coastal breakwaters to deformable and transportable media. Deformable media refer soil that may deform under influence currents waves, while involve processes such as sediment transport scour around hydraulic, coastal, ocean structures. This addresses problem dimensionality, governing equations, domain discretization schemes, interaction mechanisms, applications. The literature analysis reveals numerical techniques have been employed model complex between fluid solid phases, not all are physically or mathematically justifiable. However, some approaches significantly advanced modeling process over past two decades. Based these findings, a framework proposed guide construction models flow interactions with natural engineered It highlights effective approaches: (i) Three-dimensional (3D) pore-scale microscopic through large-sized particles using coupled smoothed particle hydrodynamics (SPH) discrete element method (DEM), (ii) two-dimensional (2D) macroscopic small-sized mixture theory SPH. mixture-theory-based particularly large-scale simulations SPH-DEM coupling enable precise fluid–solid interactions. serves researchers developing simulate engineering

Language: Английский

Citations

1

Wave energy evolution: Knowledge structure, advancements, challenges and future opportunities DOI
Ali Azam, Ammar Ahmed,

Minyi Yi

et al.

Renewable and Sustainable Energy Reviews, Journal Year: 2024, Volume and Issue: 205, P. 114880 - 114880

Published: Aug. 27, 2024

Language: Английский

Citations

7

Data-Driven Models for Significant Wave Height Forecasting: Comparative Analysis of Machine Learning Techniques DOI Creative Commons
Ahmet Durap

Results in Engineering, Journal Year: 2024, Volume and Issue: unknown, P. 103573 - 103573

Published: Dec. 1, 2024

Language: Английский

Citations

4

Advancing flood risk assessment: Multitemporal SAR-based flood inventory generation using transfer learning and hybrid fuzzy-AHP-machine learning for flood susceptibility mapping in the Mahananda River Basin DOI Creative Commons
Chiranjit Singha, Satiprasad Sahoo,

Alireza Bahrami Mahtaj

et al.

Journal of Environmental Management, Journal Year: 2025, Volume and Issue: 380, P. 124972 - 124972

Published: March 23, 2025

The Mahananda River basin, located in Eastern India, faces escalating flood risks due to its complex hydrology and geomorphology, threatening socioeconomic environmental stability. This study presents a novel approach susceptibility (FS) mapping updates the region's inventory. Multitemporal Sentinel-1 (S1) SAR images (2020-2022) were processed using U-Net transfer learning model generate water body frequency map, which was integrated with Global Flood Dataset (2000-2018) refined through grid-based classification create an updated Eleven geospatial layers, including elevation, slope, soil moisture, precipitation, type, NDVI, Land Use Cover (LULC), wind speed, drainage density, runoff, used as conditioning factors (FCFs) develop hybrid FS approach. integrates Fuzzy Analytic Hierarchy Process (FuzzyAHP) six machine (ML) algorithms models FuzzyAHP-RF, FuzzyAHP-XGB, FuzzyAHP-GBM, FuzzyAHP-avNNet, FuzzyAHP-AdaBoost, FuzzyAHP-PLS. Future trends (1990-2030) projected CMIP6 data under SSP2-4.5 SSP5-8.5 scenarios MIROC6 EC-Earth3 ensembles. SHAP algorithm identified LULC, type most influential FCFs, contributing over 60 % susceptibility. Results show that 31.10 of basin is highly susceptible flooding, western regions at greatest risk low elevation high density. projections indicate 30.69 area will remain vulnerable, slight increase SSP5-8.5. Among models, FuzzyAHP-XGB achieved highest accuracy (AUC = 0.970), outperforming FuzzyAHP-GBM 0.968) FuzzyAHP-RF 0.965). experimental results showed proposed can provide spatially well-distributed inventory derived from freely available remote sensing (RS) datasets robust framework for long-term assessment ML techniques. These findings offer critical insights improving management mitigation strategies basin.

Language: Английский

Citations

0

Assessing climate change and human impacts on runoff and hydrological droughts in the Yellow River Basin using a machine learning-enhanced hydrological modeling approach DOI
Lei Wang,

Li Yi,

Asim Biswas

et al.

Journal of Environmental Management, Journal Year: 2025, Volume and Issue: 380, P. 125091 - 125091

Published: March 28, 2025

Language: Английский

Citations

0

Steady streaming in front of Jarlan-type perforated caisson breakwaters DOI
Siamak Mohammadi, Abbas Yeganeh‐Bakhtiary

Ocean Engineering, Journal Year: 2025, Volume and Issue: 329, P. 121075 - 121075

Published: April 7, 2025

Language: Английский

Citations

0

A Bibliometric Analysis of Trends in Rainfall-Runoff Modeling Techniques for Urban Flood Mitigation (2005-2024) DOI Creative Commons

Abd. Rakhim Nanda,

Nurnawaty Nurnawaty,

Amrullah Mansida

et al.

Results in Engineering, Journal Year: 2025, Volume and Issue: unknown, P. 104927 - 104927

Published: April 1, 2025

Language: Английский

Citations

0

Coastal Disaster Assessment and Response DOI Creative Commons
Deniz Velioglu Sogut

Journal of Marine Science and Engineering, Journal Year: 2025, Volume and Issue: 13(4), P. 780 - 780

Published: April 14, 2025

Coastal communities have become increasingly susceptible to natural hazards over the past few decades, largely due effects of climate change [...]

Language: Английский

Citations

0

Analysis of spatiotemporal evolution characteristics and recovery patterns of mangrove forests in China since 1978 DOI Creative Commons

Minduan Xu,

Zhipan Wang,

Yinyu Liang

et al.

Ecological Indicators, Journal Year: 2024, Volume and Issue: 169, P. 112882 - 112882

Published: Dec. 1, 2024

Language: Английский

Citations

3

Study of tropical cyclone wave characteristics based on a hybrid track clustering method DOI
Jiaqian Li, Zhuxiao Shao, Bingchen Liang

et al.

Ocean & Coastal Management, Journal Year: 2024, Volume and Issue: 259, P. 107448 - 107448

Published: Oct. 21, 2024

Language: Английский

Citations

2