Optimizing Sustainable Biofilter Performance by Modeling Velocity Profiles Through a 3D-Printed Porous Media
Faculty Mentor
Francisco Cubas Suazo
Location
Russell Union Room 2052
Type of Research
Proposed
Session Format
Oral Presentation
College
Allen E. Paulson College of Engineering & Computing
Department
Civil Engineering
Abstract
As low-impact development tools, biofilters rely on biological and physical processes to retain and degrade pollutants from diffuse nonpoint source pollution, which makes routine maintenance essential to sustain their treatment efficiency over time. In practice, current biofilters require routine monitoring and maintenance to sustain optimal flow through the filtration media, often leading to high operational costs or even costly replacement of clogged and failed filters. To address this limitation, this research focuses on sustainable biofilters that require low intervention while still maintaining treatment efficiency of the filter by using a novel 3D-printed media that can be reused and whose accumulated biomass can be recovered for future applications. Unfortunately, there is no current information on the resulting flow regimes and their impact on the performance of 3D printed media filters. To overcome this uncertainty, this study will first determine velocity profiles through the filter media using digital modeling to decide the minimum and maximum velocities needed to maintain an adequate flow. Results, combined with velocity percentage reduction calculations, will then produce an outcome of optimized design criteria for the biofilters. Additionally, by correlating porous media buildup to biofilter geometry, velocity profiles will define optimal parameters of operation leading to higher performance outcomes. Results from this approach will help determine media replacement timelines by minimizing operational costs. Overall, this work demonstrates that integrating digital modeling with percentage reduction analysis yields a clear velocity window for reliable biofilter operation, thus advancing the design of low maintenance, self-sustaining filtration systems for long-term environmental calculations.
Program Description
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Start Date
4-23-2026 10:00 AM
End Date
4-23-2026 10:15 AM
Recommended Citation
Wolfe, Helena M., "Optimizing Sustainable Biofilter Performance by Modeling Velocity Profiles Through a 3D-Printed Porous Media" (2026). GS4 Student Scholars Symposium. 13.
https://digitalcommons.georgiasouthern.edu/research_symposium/2026/2026/13
Optimizing Sustainable Biofilter Performance by Modeling Velocity Profiles Through a 3D-Printed Porous Media
Russell Union Room 2052
As low-impact development tools, biofilters rely on biological and physical processes to retain and degrade pollutants from diffuse nonpoint source pollution, which makes routine maintenance essential to sustain their treatment efficiency over time. In practice, current biofilters require routine monitoring and maintenance to sustain optimal flow through the filtration media, often leading to high operational costs or even costly replacement of clogged and failed filters. To address this limitation, this research focuses on sustainable biofilters that require low intervention while still maintaining treatment efficiency of the filter by using a novel 3D-printed media that can be reused and whose accumulated biomass can be recovered for future applications. Unfortunately, there is no current information on the resulting flow regimes and their impact on the performance of 3D printed media filters. To overcome this uncertainty, this study will first determine velocity profiles through the filter media using digital modeling to decide the minimum and maximum velocities needed to maintain an adequate flow. Results, combined with velocity percentage reduction calculations, will then produce an outcome of optimized design criteria for the biofilters. Additionally, by correlating porous media buildup to biofilter geometry, velocity profiles will define optimal parameters of operation leading to higher performance outcomes. Results from this approach will help determine media replacement timelines by minimizing operational costs. Overall, this work demonstrates that integrating digital modeling with percentage reduction analysis yields a clear velocity window for reliable biofilter operation, thus advancing the design of low maintenance, self-sustaining filtration systems for long-term environmental calculations.