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    Hydrodynamic optimization of full-scale aeration tanks using field measurements and computational fluid dynamics modeling
    (Aip Publishing, 2025) Celik, Damla Yilmaz; Yilmaz, Naz; Sibil, Rahim; Aras, Egemen; Vaheddoost, Babak
    Improving energy efficiency and operational performance in wastewater treatment plants largely relies on precise hydrodynamic analysis. In this context, field-based studies are essential for understanding system behavior under real operational conditions. This study was conducted at a full-scale wastewater treatment plant, where flow dynamics in the aeration tank were evaluated through extensive field measurements and computational fluid dynamics modeling. Data were collected from 98 locations across 15 different depth levels using an Acoustic Doppler Current Profiler and a Hach FH950 velocity meter. The numerical model was initially validated with the help of experimental field data, enabling an accurate assessment of flow characteristics at varying depths. Results revealed that the low-velocity zones and non-uniform velocity distributions negatively affect system performance. It is also concluded that the inlet and outlet positions disturb the favorable circulation patterns and flow uniformity. Geometric optimization strategies were implemented to develop solutions, which led to a more uniform velocity distribution and improved hydraulic efficiency. By integrating detailed field measurements with numerical modeling, this study provides a comprehensive understanding of aeration tank hydrodynamics and offers practical design recommendations for improving overall system performance.
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    Refinement of field-measured velocity profiles via CFD comparison: A case study on single-phase flow in aeration tanks
    (Elsevier Sci Ltd, 2026) Celik, Damla Yilmaz; Vaheddoost, Babak; Aras, Egemen; Sibil, Rahim
    The accuracy of field measurements obtained from aeration tanks is of critically important for the validation of Computational Fluid Dynamics (CFD) models. In many cases, the employed validation metrics serve as a fundamental keystone for evaluating both the credibility of experimental data and the accuracy of numerical simulations. In this study, a novel data refinement approach is developed to assess the physical plausibility of velocity measurements collected from a full-scale aeration tank. Unlike conventional validation approaches, the CFD model is utilized as a reference framework within a reverse-approach perspective to evaluate the reliability of field data. Measurement points affected by acoustic noise, surface sludge interference, and turbulence near static structures were identified and excluded through curve-fitting and statistical filtering techniques. Velocity data obtained with the help of an Acoustic Doppler Current Profiler (ADCP) across six lateral and 53 vertical layers were evaluated using the Coefficient of Determination (R2), Relative Error (RE), and Performance Index (PI) metrics. The maximum-elimination combined with polynomial fitting notably enhanced the model accuracy, reducing RE from -123 % to 20 %, increasing R2 from 0.054 to 0.96, and improving PI from 2.6 to 1.16. As a result, the refined dataset provided a more consistent and realistic representation of the flow structure and established a robust observational basis for the future calibration.