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State of the Art of CFD-DEM Coupled Modeling and Its Application in Turbulent Flow-Induced Soil Erosion

Jun Xu - Nama Orang; Fei Wang - Nama Orang; Ruth Abegaz - Nama Orang;

Fluid–soil interaction plays a pivotal role in various geotechnical engineering applications, as it significantly influences processes such as erosion, sediment transport, and soil stability. Modeling fluid–soil particle interactions in these contexts presents substantial challenges due to the inherent complexity of the interactions occurring across multiple characteristic scales. The primary challenge lies in the vast disparities in magnitude between these scales, which demand sophisticated modeling techniques to accurately capture the intricate dynamics involved. Coupled fluid–soil particle models have emerged as essential tools for understanding the mechanisms underlying fluid–soil interactions. Among these, the CFD-DEM (computational fluid dynamics–discrete element method) approach has gained significant attention. This method provides an effective compromise between high-resolution sub-particle fluid modeling and coarser mesh-based techniques for fluids and particles. By doing so, CFD-DEM facilitates large-scale simulations while maintaining computational efficiency, making it a promising solution for studying fluid–soil interactions in complex geotechnical scenarios. This review highlights the application of CFD-DEM models in geotechnical engineering, with a specific focus on soil erosion processes and the critical role of turbulent flow. It explores various fluid–soil particle interaction computational mechanisms and their implications for erosion dynamics, emphasizing several key aspects, including the following: laminar vs. turbulent flow models: understanding the distinctions between flow regimes is critical for accurately predicting fluid-induced soil particle movement. Shear stress effects: the influence of flow-induced shear stress on the detachment of soil particles is analyzed, particularly in erosion-prone environments. Sediment transport mechanisms: factors such as particle size, density, and water velocity are examined for their roles in governing sediment transport. Knowledge gaps and future directions: these involve identifying unresolved issues in current fluid–soil interaction models, with an emphasis on improving the accuracy and scalability of CFD-DEM simulations. By delving into these aspects, the review aims to advance the understanding of fluid–soil interactions and provide insights into optimizing modeling techniques for geotechnical engineering applications. It also outlines future research directions to bridge existing knowledge gaps, emphasizing the importance of integrating advanced turbulence modeling and computational strategies to enhance the predictive capabilities of fluid–soil interaction frameworks.


Ketersediaan
#
Perpustakaan BIG (Eksternal Harddisk) 550
371
Tersedia
Informasi Detail
Judul Seri
Geosciences
No. Panggil
550
Penerbit
Switzerland : MPDI., 2025
Deskripsi Fisik
20 hlm PDF, 875 KB
Bahasa
Inggris
ISBN/ISSN
2076-3263
Klasifikasi
550
Tipe Isi
text
Tipe Media
-
Tipe Pembawa
online resource
Edisi
Vol.15, Issue 1, January 2025
Subjek
soil erosion
computational fluid dynamics
discrete element method
CFDDEM coupling
geotechnical engineering
Info Detail Spesifik
Geosciences
Pernyataan Tanggungjawab
-
Versi lain/terkait

Tidak tersedia versi lain

Lampiran Berkas
  • State of the Art of CFD-DEM Coupled Modeling and Its Application in Turbulent Flow-Induced Soil Erosion
    Fluid–soil interaction plays a pivotal role in various geotechnical engineering applications, as it significantly influences processes such as erosion, sediment transport, and soil stability. Modeling fluid–soil particle interactions in these contexts presents substantial challenges due to the inherent complexity of the interactions occurring across multiple characteristic scales. The primary challenge lies in the vast disparities in magnitude between these scales, which demand sophisticated modeling techniques to accurately capture the intricate dynamics involved. Coupled fluid–soil particle models have emerged as essential tools for understanding the mechanisms underlying fluid–soil interactions. Among these, the CFD-DEM (computational fluid dynamics–discrete element method) approach has gained significant attention. This method provides an effective compromise between high-resolution sub-particle fluid modeling and coarser mesh-based techniques for fluids and particles. By doing so, CFD-DEM facilitates large-scale simulations while maintaining computational efficiency, making it a promising solution for studying fluid–soil interactions in complex geotechnical scenarios. This review highlights the application of CFD-DEM models in geotechnical engineering, with a specific focus on soil erosion processes and the critical role of turbulent flow. It explores various fluid–soil particle interaction computational mechanisms and their implications for erosion dynamics, emphasizing several key aspects, including the following: laminar vs. turbulent flow models: understanding the distinctions between flow regimes is critical for accurately predicting fluid-induced soil particle movement. Shear stress effects: the influence of flow-induced shear stress on the detachment of soil particles is analyzed, particularly in erosion-prone environments. Sediment transport mechanisms: factors such as particle size, density, and water velocity are examined for their roles in governing sediment transport. Knowledge gaps and future directions: these involve identifying unresolved issues in current fluid–soil interaction models, with an emphasis on improving the accuracy and scalability of CFD-DEM simulations. By delving into these aspects, the review aims to advance the understanding of fluid–soil interactions and provide insights into optimizing modeling techniques for geotechnical engineering applications. It also outlines future research directions to bridge existing knowledge gaps, emphasizing the importance of integrating advanced turbulence modeling and computational strategies to enhance the predictive capabilities of fluid–soil interaction frameworks.
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