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Start date: 2020Subject: search.filters.subject.Computational Fluid Dynamics

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    Item type:Publication,
    Physics-Guided CFD–ML Framework for Sustainable Classical Wire Coating with Power-Law Fluids
    (2026-07-01)
    Nabudda, Kriengkrai
    ;
    Poungthong, Pongthep
    ;
    Ritthong, Wirote
    ;
    Elumalai, P. V.
    This study presents an integrated Computational Fluid Dynamics (CFD) and machine learning framework for analyzing and optimizing classical wire coating processes involving non-Newtonian power-law fluids. A two-dimensional axisymmetric CFD model was developed in ANSYS Fluent 2024R1 to investigate the effects of the power-law index (n = 0.3–1.0) on flow, pressure, temperature, and density fields under non-isothermal conditions. A Latin Hypercube Sampling-based Design of Experiments was coupled with surrogate modelling and Sobol sensitivity analysis to evaluate process performance and identify optimal operating conditions. The results showed that velocity distributions were highly dependent on fluid rheology, with shear-thinning fluids producing broader plug-like flow regions and more uniform velocity profiles. In contrast, pressure, temperature, and density fields exhibited limited sensitivity to variations in the power-law index. Optimization indicated that low power-law indices, moderate pressure gradients, and low-to-moderate wire speeds maximize coating thickness while minimizing material loss. Ridge Polynomial Regression achieved excellent predictive accuracy for all response variables (R<sup>2</sup> > 0.995). Sensitivity analysis revealed that the initial die gap is the dominant factor governing coating thickness, whereas material loss is influenced by combined effects of die geometry, fluid rheology, and wire speed. The proposed framework provides an efficient tool for process optimization and material conservation in industrial wire coating applications.
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    Evaluation and improvement of ventilation systemreduceinside low-costparticle contaminationautomation line to
    (2020-02-28)
    Puangburee, Lamai
    ;
    Busayaporn, Wutthikrai
    ;
    Kaewbumrung, Mongkol
    ;
    Thongsri, Jatuporn
    A Low-Cost Automation (LCA) line, a group of machines to manufacture hard disk drive’s components located inside a clean room of factory, faces the problem of particle contamination caused by an improper ventilation system. To solve this problem, Computational Fluid Dynamics (CFD) has been implemented to evaluate airflow and simulate solutions to improve the ventilation system of the LCA. By using actual operating conditions collected at the factory and Fluent CFD software, the simulation showed that airflow patterns in such areas were substandard. For example, the large areas of recirculation zone with air velocities lower than 0.2 m/s such as Fan Filter Units’ conveyor and Work Area. The low ve-locity of the airflow can cause particle contamination and leads to low-quality production. To reduce the particle contamination, we suggested novel solutions based on the CFD results by increasing the momen-tum source (S<inf>m</inf>) and/or redesigning the LCA’s model especially extending its height of cover. The increasing of S<inf>m</inf> can be simply implemented by increasing the air-condition power to the optimal values accord-ing to the calculation leading to a reduction in recir-culation areas. In addition, extending the height of the LCA’s cover also improved the air velocities in the critical areas to meet the factory’s standard.