See discussions, stats, and author profiles for this publication at: https://www.researchgate.net/publication/388324098 CFD Simulations for Filter Layer Optimization: Sensitivity Analysis of Flow Velocity, Particle Size, Roughness, and Particle Rate ArticleinRevista de Gestão Social e Ambiental · January 2025 DOI: 10.24857/rgsa.v19n1-107 CITATIONS 0 READS 102 7 authors, including: Daiane Francisca do Nascimento Silva Federal University of Pernambuco 56 PUBLICATIONS5 CITATIONS SEE PROFILE Antonio Celso Antonino Federal University of Pernambuco 35 PUBLICATIONS148 CITATIONS SEE PROFILE Daniel Milian Perez Federal University of Pernambuco 109 PUBLICATIONS119 CITATIONS SEE PROFILE Yaicel Ge Proenza Federal University of Pernambuco 62 PUBLICATIONS162 CITATIONS SEE PROFILE All content following this page was uploaded by Daiane Francisca do Nascimento Silva on 23 January 2025. The user has requested enhancement of the downloaded file.
Rev. Gest. Soc. Ambient. | Miami | v.19.n.1 | p.1-21 | e010677 | 2025. 1 RGSA – Revista de Gestão Social e Ambiental ISSN: 1981-982X Submission date: 10/1/2024 Acceptance date: 12/2/2024 DOI: https://doi.org/10.24857/rgsa.v19n1-107 Organization: Interinstitutional Scientific Committee Chief Editor: Ana Carolina Messias de Souza Ferreira da Costa Assessment: Double Blind Review pelo SEER/OJS CFD SIMULATIONS FOR FILTER LAYER OPTIMIZATION: SENSITIVITY ANALYSIS OF FLOW VELOCITY, PARTICLE SIZE, ROUGHNESS, AND PARTICLE RATE Daiane Francisca do Nascimento Silva 1 João Victor de Barros Felix 2 Jean Firmino Cardoso 3 Abel Gámez Rodríguez 4 Yaicel Ge Proenza 5 Daniel Milian Pérez 6 Antonio Celso Dantas Antonino 7 ABSTRACT Objective: The objective of this study is to examine the sensitivity of particle retention processes in artificial porous media to variations in fluid injection velocity, particle size, injection rate, and surface roughness. Similarly, this investigation contributes to the understanding of the mechanisms governing particle transport and retention, as well as supports the optimization of filtration systems across various applications. Theoretical Framework: The research builds upon the established theories of porous media flow, particle transport, and interfacial phenomena, particularly focusing on the application of Computational Fluid Dynamics (CFD) simulations to the study of particulate matter retention in water. Method: In this work, a sensitivity analysis was conducted using a computational model implemented in ANSYSCFX software, which allows for the study of water-particle mixture percolation in artificial porous media. The main parameters analyzed included flow velocity, particle size, surface roughness, and injection rate. Prior to simulations, X-ray computed tomography (μCT-XR) was employed to obtain detailed geometric information of the porous media, which was used to generate realistic computational models. Results and Discussion: The results obtained revealed article retention in porous media is influenced by flow velocity, particle size, and media roughness. Higher velocities and larger particles promote deposition. In the discussion section, these results are contextualized in light of the theoretical framework, highlighting the implications and relationships identified. Possible discrepancies and limitations of the study are also considered in this section. Research Implications: These findings provide valuable insights to understand the limits of applicability of computational CFD when applied to the optimization of barrier and filter construction which have significant implications for various applications, such as water filtration, soil contamination, and reservoir engineering. 1 Universidade Federal de Pernambuco, Recife, Pernambuco, Brazil. E-mail: daiane.francisc[email protected] Orcid: https://orcid.org/0000-0002-1057-7335 2 Universidade Federal de Pernambuco, Recife, Pernambuco, Brazil. E-mail:
[email protected] Orcid: https://orcid.org/0009-0007-6016-2705 3 Universidade Federal de Pernambuco, Recife, Pernambuco, Brazil. E-mail: [email protected] Orcid: https://orcid.org/0000-0001-6092-713X 4 Universidade Federal de Pernambuco, Recife, Pernambuco, Brazil. E-mail: abel.rodr[email protected] Orcid: https://orcid.org/0000-0002-1584-6768 5 Universidade Federal de Pernambuco, Recife, Pernambuco, Brazil. E-mail: yaicel.gepr[email protected] Orcid: https://orcid.org/0000-0003-3894-8326 6 Universidade Federal de Pernambuco, Recife, Pernambuco, Brazil. E-mail: [email protected]r Orcid: https://orcid.org/0000-0002-3172-0508 7 Universidade Federal de Pernambuco, Recife, Pernambuco, Brazil. E-mail:
[email protected] Orcid: https://orcid.org/0000-0002-4120-9404
CFD Simulations for Filter Layer Optimization: Sensitivity Analysis of Flow Velocity, Particle Size, Roughness, and Particle Rate ___________________________________________________________________________ Rev. Gest. Soc. Ambient. | Miami | v.19.n.1 | p.1-21 | e010677 | 2025. 2 Originality/Value: This study contributes to the literature by providing valuable insights about key factors influencing particle retention. The relevance and value of this research are evident in the potential application of CFD simulations, which, through sensitivity analyses, provide valuable understanding about optimizing filter design and mitigating water contamination. Keywords: Particle Retention, Water Filtration, Surface Deposition, Pollutant Transport, Pouros Media, Zirconia Particle. SIMULAÇÕES CFD PARA OTIMIZAÇÃO DE CAMADAS FILTRANTES: ANÁLISE DE SENSIBILIDADE DA VELOCIDADE DO FLUXO, TAMANHO DE PARTÍCULA, RUGOSIDADE E TAXA DE INJEÇÃO DE PARTÍCULAS RESUMO Objetivo: O objetivo deste estudo é examinar a sensibilidade dos processos de retenção de partículas em meios porosos artificiais a variações na velocidade de injeção de fluido, tamanho das partículas, taxa de injeção e rugosidade da superfície. Da mesma forma, esta investigação contribui para a compreensão dos mecanismos que governam o transporte e a retenção de partículas, bem como suporta a otimização de sistemas de filtração em diversas aplicações. Referencial Teórico: A pesquisa se baseia nas teorias estabelecidas de escoamento em meios porosos, transporte de partículas e fenômenos interfaciais, com foco particular na aplicação de simulações de Fuidodinâmica Computacional (CFD) ao estudo da retenção de material particulado em água. Método: Neste trabalho, uma análise de sensibilidade foi conduzida utilizando um modelo computacional implementado no software ANSYS-CFX, que permite o estudo da percolação da mistura água-partícula em meios porosos artificiais. Os principais parâmetros analisados incluíram velocidade do fluxo, tamanho das partículas, rugosidade da superfície e taxa de injeção. Antes das simulações, tomografia computadorizada de raios-X (μCTXR) foi empregada para obter informações geométricas detalhadas dos meios porosos, que foram utilizadas para gerar modelos computacionais realistas. Resultados e Discussão: Os resultados obtidos revelaram que a retenção de partículas em meios porosos é influenciada pela velocidade do fluxo, tamanho de partícula e rugosidade do meio. Velocidades mais altas e partículas maiores favorecem a deposição. Na seção de discussão, esses resultados são contextualizados à luz do referencial teórico, destacando as implicações e relações identificadas. Possíveis discrepâncias e limitações do estudo também são consideradas nesta seção. Implicações da Pesquisa: Esses resultados fornecem insights valiosos para compreender os limites de aplicabilidade das simulações de CFD quando aplicadas à otimização de barreiras e construção de filtros, o que tem implicações significativas para diversas aplicações, como filtração de água, contaminação do solo e engenharia de reservatórios. Originalidade/Valor: Este estudo contribui para a literatura ao fornecer insights valiosos sobre os principais fatores que influenciam a retenção de partículas. A relevância e o valor desta pesquisa são evidenciados pela apresentação de simulações de CFD, que, através de análises de sensibilidade, fornecem um valioso entendimento sobre a otimização do projeto de filtros e a mitigação da contaminação da água. Palavras-chave: Retenção de Partículas, Filtração de Água, Deposição Superficial, Transporte de Poluentes, Meios Porosos, Partícula de Zircônia. SIMULACIONES CFD PARA LA OPTIMIZACIÓN DE ESTRATOS FILTRANTES: ANÁLISIS DE SENSIBILIDAD DE LA VELOCIDAD DEL FLUJO, TAMAÑO DE PARTÍCULA, RUGOSIDAD Y TASA DE PARTÍCULAS RESUMEN Objetivo: El objetivo de este estudio es examinar la sensibilidad de los procesos de retención de partículas en medios porosos artificiales a variaciones en la velocidad de inyección de fluido, tamaño de partículas, tasa de
CFD Simulations for Filter Layer Optimization: Sensitivity Analysis of Flow Velocity, Particle Size, Roughness, and Particle Rate ___________________________________________________________________________ Rev. Gest. Soc. Ambient. | Miami | v.19.n.1 | p.1-21 | e010677 | 2025. 3 inyección y rugosidad superficial. De igual manera, esta investigación contribuye a la comprensión de los mecanismos que gobiernan el transporte y la retención de partículas, así como apoya la optimización de sistemas de filtración en diversas aplicaciones. Marco Teórico: La investigación se basa en las teorías establecidas de flujo en medios porosos, transporte de partículas y fenómenos interfaciales, con un enfoque particular en la aplicación de simulaciones de Dinámica de Fluidos Computacional (CFD) al estudio de la retención de material particulado en agua. Método: En este trabajo, se realizó un análisis de sensibilidad utilizando un modelo computacional implementado en el software ANSYS-CFX, que permite el estudio de la percolación de la mezcla agua-partícula en medios porosos artificiales. Los principales parámetros analizados incluyeron velocidad del flujo, tamaño de partículas, rugosidad superficial y tasa de inyección. Antes de las simulaciones, se empleó tomografía computarizada de rayos X (μCT-XR) para obtener información geométrica detallada de los medios porosos, la cual se utilizó para generar modelos computacionales realistas. Resultados y Discusión: Los resultados obtenidos revelaron que la retención de partículas en medios porosos está influenciada por la velocidad del flujo, el tamaño de partícula y la rugosidad del medio. Velocidades más altas y partículas más grandes favorecen la deposición. En la sección de discusión, estos resultados se contextualizan a la luz del marco teórico, destacando las implicaciones y relaciones identificadas. También se consideran posibles discrepancias y limitaciones del estudio en esta sección. Implicaciones de la Investigación: Estos resultados proporcionan valiosos conocimientos para comprender los límites de aplicabilidad de las simulaciones de CFD cuando se aplican a la optimización de barreras y construcción de filtros, lo que tiene implicaciones significativas para diversas aplicaciones, como la filtración de agua, la contaminación del suelo y la ingeniería de reservorios. Originalidad/Valor: Este estudio contribuye a la literatura proporcionando valiosos conocimientos sobre los factores clave que influyen en la retención de partículas. La relevancia y el valor de esta investigación se evidencian por la presentación de simulaciones de CFD como herramienta para optimizar filtros y barreras reactivas permeables en la prevención y remediación de la contaminación de recursos hídricos. Palabras clave: Retención de Partículas, Filtración de Agua, Deposición Superficial, Transporte de Contaminantes, Medios Porosos, Partícula de Zirconio. RGSA adota a Licença de Atribuição CC BY do Creative Commons (https://creativecommons.org/licenses/by/4.0/). 1 INTRODUCTION Understanding particle movement through porous media is fundamental for ensuring water quality, managing water resources, optimizing industrial processes, and preventing soil contamination. The transport of water and pollutants in porous media is governed by the principles of hydrodynamics and hydrology (Frippiat & Holeyman, 2008; Lee & Jung, 2022). In essence, porous media consist of a solid matrix (e.g., soil, rock) with void spaces between the particles, called pores (Ling et al., 2021; Leal et al., 2023). Water and pollutants can move within these pores through physical and chemical processes, which depend primarily on the
CFD Simulations for Filter Layer Optimization: Sensitivity Analysis of Flow Velocity, Particle Size, Roughness, and Particle Rate ___________________________________________________________________________ Rev. Gest. Soc. Ambient. | Miami | v.19.n.1 | p.1-21 | e010677 | 2025. 4 characteristics of the porous medium and the properties of the water and pollutants (Nielsen et al., 1997). In this context, Computational Fluid Dynamics (CFD) simulations play a crucial role in analyzing particle transport and retention processes in porous media (Tu et al., 2013). These simulations allow for a detailed analysis of fluid and particle behavior, considering input parameters such as flow velocity, particle size and injection rate, and surface characteristics of the porous medium (Tu et al., 2013; Afzali et al., 2022; Li, et al., 2023). By providing insights into flow patterns and microscopic interactions in particle retention within porous media, CFD simulations contribute to optimizing engineering designs, remediation strategies, and industrial process improvements, resulting in significant advancements in research and development (Tu et al., 2013; Afzali et al., 2022; Li et al., 2023; Elrahmani et al., 2023). Some studies on particle retention in porous media using CFD simulation approaches can be found in the literature, among which Sadeghnejad et al. (2022) investigated the clogging of porous structures using CFD simulations. Applying the Euler-Lagrange approach, the authors observed that particle size and adhesion forces exert a predominant influence on permeability through clogging mechanisms, rather than surface deposition. They also highlighted that particle retention reaches its maximum at a critical velocity. This study, being one of the most recent in this area, opens up a range of questions regarding the sensitivity of particle retention processes to variations in input parameters. The present study aims to investigate the sensitivity of particle retention processes in artificial porous media composed of glass beads to variations in the input parameters of fluid injection velocity, particle size and injection rate, and surface roughness of the glass beads. 2 THEORETICAL FRAMEWORK According to Nielsen et al., 1997, porous media are composed of a solid matrix (e.g., soil, rock) with void spaces between the particles, termed pores. Water and pollutants can migrate within these pores through physical and chemical processes, primarily dependent on the characteristics of the porous medium and the properties of the water and pollutants. Water transport through porous media is referred to as porous flow. This process involves the passage of water through pores and channels under the influence of hydraulic pressure gradients. Hydraulic pressure is a measure of the energy associated with water, dependent on the height of the water column above a reference point and its properties. Water
CFD Simulations for Filter Layer Optimization: Sensitivity Analysis of Flow Velocity, Particle Size, Roughness, and Particle Rate ___________________________________________________________________________ Rev. Gest. Soc. Ambient. | Miami | v.19.n.1 | p.1-21 | e010677 | 2025. 5 flows from a high-pressure point to a low-pressure point, following the laws of fluid motion, such as Darcy's law and the Navier-Stokes equations (Nielsen et al., 1997; Hariti et al., 2020). Darcy's law states that the flow of water through a porous medium is directly proportional to the permeability of the porous medium, and inversely proportional to the hydraulic pressure gradient and viscosity of water. Therefore, the greater the hydraulic pressure difference between two points in the porous medium, the greater the flow between them, provided that the medium is sufficiently permeable to allow the fluid to pass more easily (Wang et al., 2022). This permeability depends on the characteristics of the solid matrix and the void spaces between the particles of the medium (Nielsen et al., 1997; Guha, 2008; White, 2009; Hariti et al., 2020; Wang et al., 2022). Two primary mechanisms govern the transport of suspended particles in porous media: advection and diffusion (Bear, 1988; Sahimi, 1995). The interplay of these mechanisms determines the transport pattern of suspended particles in porous media. The complexity of this transport is influenced by the characteristics of the porous medium, as well as the properties of the suspended particles (such as size, shape, and charge) and the flow conditions of the water (such as velocity and direction) (McDowell-Boyer et al., 1986; Bear, 1988; Sahimi, 1995; Deng et al., 2022). Advection refers to the transport of suspended particles along with the flow of water through the porous medium. This transport occurs due to the velocity differences between the water and the particles, and as the water flows through the pores of the material, it drags the suspended particles in its direction, similar to the transport of objects carried by river currents (McDowell-Boyer et al., 1986; Bear, 1988; Sahimi, 1995; Deng et al., 2022; Monga et al., 2023). The diffusion occurs due to the random motion of suspended particles, resulting in their spreading in all directions. Diffusion is particularly significant for small particles, which are more affected by thermal motion and collisions with other particles and water molecules. Diffusion tends to spread suspended particles throughout the porous medium (Bear, 1988; Sahimi, 1995; Deng et al., 2022; Ren et al., 2022; Monga et al., 2023). Filter layers are designed to remove unwanted particles and impurities from water, allowing only clean water to pass through the pores. According to Nan et al. (2023), various hydrodynamic and physicochemical processes play a crucial role in generating retained particles in porous media, both saturated and unsaturated. The main mechanisms governing particle retention are surface deposition, clogging, and sieving. Surface forces, such as van der Waals and electrostatic forces, are responsible for the adhesion and agglomeration of particles on the matrix surface. Clogging occurs when multiple
CFD Simulations for Filter Layer Optimization: Sensitivity Analysis of Flow Velocity, Particle Size, Roughness, and Particle Rate ___________________________________________________________________________ Rev. Gest. Soc. Ambient. | Miami | v.19.n.1 | p.1-21 | e010677 | 2025. 6 particles form a bridge or arch at the pore throats. Sieving occurs when particles block pore throats that are smaller than their diameters. These mechanisms are illustrated in Figure 1. Factors such as flow velocity, initial particle concentration, particle size and polydispersity, ionic strength, and surface heterogeneity (roughness and wettability) govern the magnitude of particle retention in porous media (Lin et al., 2021; Sadeghnejad et al., 2022). Figure 1 Processes of particle retention in porous media. Source: YE et al., 2019. Mechanism of Suspended Kaolinite Particle Clogging in Porous Media During Managed Aquifer Recharge. Groundwater, v. 57, n. 5, 2019. CFD simulation is a numerical technique used to model and analyze the behavior of fluids, such as liquids and gases, and their interactions with solid structures (Tu et al., 2013). It allows for the solution of the fundamental equations governing fluid motion, such as the conservation equations of mass, momentum, and energy, using computational methods to predict flow behavior under different conditions (Tu et al., 2013; Spurin et al., 2023; Zheng et al., 2023). This approach offers several advantages, including cost savings, as it eliminates the need for physical experiments, reducing the costs associated with building models and laboratory testing. Additionally, it provides flexibility to simulate a wide range of conditions and scenarios, enabling a more comprehensive analysis of fluid behavior under different boundary conditions, geometries, and operating parameters. The speed of obtaining results is another advantage, as simulations can be run on high-performance computers, accelerating the design and optimization process of fluid dynamic systems (Tu et al., 2013; Sadeghnejad et al., 2022; Nan et al., 2023; Dhar et al., 2024). In the current context, the importance of CFD simulations in studying transport phenomena and particle retention in porous media is emphasized (Tu et al., 2013). These
CFD Simulations for Filter Layer Optimization: Sensitivity Analysis of Flow Velocity, Particle Size, Roughness, and Particle Rate ___________________________________________________________________________ Rev. Gest. Soc. Ambient. | Miami | v.19.n.1 | p.1-21 | e010677 | 2025. 7 simulations enable a thorough analysis of fluid and particle behavior, considering variables such as flow velocity and porous media geometry (Tu et al., 2013; Afzali et al., 2022; Li et al., 2023). By providing insights into flow patterns and microscopic interactions during particle retention in porous media, they contribute to the optimization of engineering designs, remediation strategies, and industrial process improvements, resulting in substantial advancements in research and development. For this purpose, mass, energy and momentum balance equations are calculated for each particle throughout its trajectory in the medium. (Tu et al., 2013; Afzali et al., 2022; Li et al., 2023; Elrahmani et al., 2023). 3 METHODOLOGY For this study, three artificial porous media, referred to as reference columns, were constructed and scanned using X-rays micro-CT (μCT-XR) to generate a representative geometric model. These models were then meshed to enable simulations. Standard conditions of velocity, particle size, particle rate, and porous media surface roughness were established for the simulations, and these were then varied to study sensitivity. Each of these methodological steps is better described in the subsequent subtopics. Building upon the previous work of Silva et al. (2024), this study extends the investigation into porous media applied to filtration systems. The reference columns were assembled in an acrylic cylinder using glass pebbles as a solid matrix. The regular surface of glass pebbles ensures that, as they have well-defined and connected voids, the medium presents absolute porosity equal to the effective porosity, important for porosimetry methods based on column saturation. Of the three constructed reference columns, one was filled with 3 mm pebbles (CF3), another with 4 mm pebbles (CF4), and the third was filled with a 50:50 volumetric mixture of 3 mm and 4 mm pebbles (CFM). The reference columns are shown in Figure 2. The reference columns CF3, CF4, and CFM exhibited porosities of 37.14%, 39.51%, and 37.55%, respectively. These porosity values were obtained from helium gas porosimetry measurements as reported in Silva et al. (2024).
CFD Simulations for Filter Layer Optimization: Sensitivity Analysis of Flow Velocity, Particle Size, Roughness, and Particle Rate ___________________________________________________________________________ Rev. Gest. Soc. Ambient. | Miami | v.19.n.1 | p.1-21 | e010677 | 2025. 8 Figure 2 Studied reference columns. Tomographic images were acquired using a third-generation μCT-XR system, model NIKON XT H 225 ST. These images were obtained based on the attenuation of X-ray beams incident on a sample located between the source and the detector. The scanning conditions were as follows: voltage of 200 kV, current of 90 μA, a 0.5 mm Copper (Cu) filter, and a resolution of 25 μm. Tomographic projections were reconstructed using the CTPro 3D XT 3.03 software (Nikon Metrology, 2015). The initial stage of the geometric model generation process involves the reconstruction of tomographic images and subsequent extraction of surfaces to form a three-dimensional (3D) model in STL format, facilitated by the 3D Viewer plugin within the ImageJ 1.54f software (Ferreira and Rasband, 2012). STL files encode geometric data by defining surfaces through triangular facets. Each facet is characterized by a unit normal vector, orthogonal to its corresponding triangle with a magnitude of 1.0, and delineated by the coordinates of its three vertices. Hence, for every facet, a total of 12 numerical values are stored: three for the normal vector and nine for the coordinates of the vertices (Szilvśi-Nagy and Mátyási, 2003). This representation ensures the accurate preservation of surface topology and geometric details essential for subsequent computational analyses and simulations. As an additional benefit, this file format can be loaded into the Ansys Discovery SpaceClaim software (ANSYS, 2023). Using the latter, the model with triangular facets is transformed into a solid body (Figure 3a). Following this transformation, repair tools are applied to identify gaps, missing faces, extra or duplicated edges, among other issues in the solid body. Finally, the glass bead column is enclosed within a cylinder with dimensions equivalent to those of the inner wall of the PVC column, and a Boolean subtraction operation
CFD Simulations for Filter Layer Optimization: Sensitivity Analysis of Flow Velocity, Particle Size, Roughness, and Particle Rate ___________________________________________________________________________ Rev. Gest. Soc. Ambient. | Miami | v.19.n.1 | p.1-21 | e010677 | 2025. 15 Consequently, particle retention is primarily attributed to adhesive forces, which are influenced by particle mass and velocity. Altering particle size affects both these parameters, with extremes (lower velocity with higher mass and vice versa) significantly impacting retention. The higher retention of 15 µm particles suggests that their specific mass-volume-diameter ratio enhances adhesive interactions within the porous medium. Figure 8 Particle retention graph in reference columns CF3 (a), CF4 (b) and CFM (c) from the zirconia particle size variation. (a) (b) (c) In contrast to what has been observed so far, roughness (Figure 9) did not present significant alterations to establish a dependency relationship with the particle retention rate, while it is clear that increasing surface roughness can directly impact particle retention. Although the results do not indicate a significant sensitivity of the CFD simulations to this
CFD Simulations for Filter Layer Optimization: Sensitivity Analysis of Flow Velocity, Particle Size, Roughness, and Particle Rate ___________________________________________________________________________ Rev. Gest. Soc. Ambient. | Miami | v.19.n.1 | p.1-21 | e010677 | 2025. 16 parameter, it is premature to conclude that there is no sensitivity. Therefore, further studies are warranted. This includes increasing the range of input values as well as investigating the impact of particle sizes on different surface roughness. Figure 9 Particle retention graph in reference columns CF3 (a), CF4 (b) and CFM (c) from the surface roughness variation. (a) (b) (c) Finally, the particle rate (Figure 10) showed a direct proportionality in zirconia retention, similar to the relationship observed in the variation of velocities. The sensitivity to this parameter is linked to the pattern whereby the more particles are injected into the medium, the more particles are retained. An additional factor contributing to this behavior is particleparticle retention, wherein particles adhering to the porous matrix walls can act as nucleation sites for further particle deposition, forming filter cakes. The agglomeration of these filter cakes
CFD Simulations for Filter Layer Optimization: Sensitivity Analysis of Flow Velocity, Particle Size, Roughness, and Particle Rate ___________________________________________________________________________ Rev. Gest. Soc. Ambient. | Miami | v.19.n.1 | p.1-21 | e010677 | 2025. 17 can subsequently obstruct pore throats, leading to the retention of additional particles via a clogging mechanism (inner blocking showed in Figure 1). Figure 10 Particle retention graph in reference columns CF3 (a), CF4 (b) and CFM (c) from the particle injection rate variation. (a) (b) (c) 5 CONCLUSION The study observed the factors influencing particle retention (clogging) within porous media. Our findings demonstrate that: (1) particle retention decreases with increasing flow velocity, as predicted by theoretical models, (2) both very small (5 μm) and very large (20 μm) particles exhibit lower retention rates compared to intermediate sizes. This could be attributed to factors such as low inertia for smaller particles and increased mass and potential for bridging for larger particles, (3) surprisingly, surface roughness did not significantly influence particle
CFD Simulations for Filter Layer Optimization: Sensitivity Analysis of Flow Velocity, Particle Size, Roughness, and Particle Rate ___________________________________________________________________________ Rev. Gest. Soc. Ambient. | Miami | v.19.n.1 | p.1-21 | e010677 | 2025. 18 retention in this study, (4) increasing the particle injection rate directly correlates with increased particle retention. Furthermore, the study observed preferential flow paths within the porous media that remain consistent despite variations in simulation parameters. These findings provide valuable insights to understand the limits of applicability of computational fluid dynamics simulations when applied to the optimization of barrier and filter construction which have significant implications for various applications, such as water filtration, soil contamination, and reservoir engineering. This study provides a foundational understanding of the factors influencing clogging. Further research could explore the combined effects of these factors, investigate the impact of different particle shapes and distributions, and refine the understanding of preferential flow paths and their influence on clogging dynamics and the filter life-time. ACKNOWLEDGEMENTS This research was partially supported by the Fundação de Amparo à Ciência e Tecnologia de Pernambuco (FACEPE), project numbers: IBPG-1064-3.09/22 and BFP-0146-3.09/23 and the Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), project number: 465764/2014-2 Observatório Nacional da Dinâmica da Água e de Carbono no Bioma Caatinga (ONDACBC). The authors also acknowledge CNPq for supporting this research through the Productivity Fellowship granted to Antonio Celso Dantas Antonino. REFERENCES Afzali, S., Rezaei, N., Zendehboudi, S., Chatzis, I. (2022). Computational fluid dynamic simulation of multi-phase flow in fractured porous media during water-alternating-gas injection process. Journal of Hydrology, 610, 127852. https://doi.org/10.1016/j.jhydrol.2022.127852 Ansys, Team. (2023). Ansys CFX-Solver Theory Guide, Release 2023 R1. ANSYS, Inc., 2023b. Bear, J. (1988). Dynamics of fluids in porous media. New York: Dover. Deng, H., Gharasoo, M., Zhang, L., Dai, Z., Hajizadeh, A., Peters, C. A., Soulaine, C., Thullner, M., Cappellen, P. V. (2022). A perspective on applied geochemistry in porous media: Reactive transport modeling of geochemical dynamics and the interplay with flow phenomena and physical alteration. Applied Geochemistry, 146, 105445. https://doi.org/10.1016/j.apgeochem.2022.105445
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