Development of a digital twin framework for hybrid adsorption-ultrafiltration systems in drinking water treatment
Yazarlar (3)
Doç. Dr. Dilek GÜMÜŞ Sinop Üniversitesi, Türkiye
Doç. Dr. Alper Alver Aksaray Üniversitesi, Türkiye
Prof. Dr. Feryal Akbal Ondokuz Mayıs Üniversitesi, Türkiye
| Makale Türü | Özgün Makale (SSCI, AHCI, SCI, SCI-Exp dergilerinde yayınlanan tam makale) | ||
| Dergi Adı | Process Safety and Environmental Protection (Q1) | ||
| Dergi ISSN | 0957-5820 Dergi Bilgileri (2026) | ||
| Dergi Tarandığı Indeksler | SCI-Expanded | ||
| Makale Dili | Türkçe | Basım Tarihi | 01-2026 |
| Cilt / Sayı / Sayfa | 205 / 1 / 108182–0 | DOI | 10.1016/j.psep.2025.108182 |
| Makale Linki | https://doi.org/10.1016/j.psep.2025.108182 | ||
| UAK Araştırma Alanları |
Su Kirliliği ve Kontrolü
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| Özet |
| A data-driven digital twin was developed to address the ongoing challenges of humic acid removal and membrane fouling in hybrid adsorption-ultrafiltration (UF) systems used for drinking water treatment. Natural organic matter, particularly humic substances, continues to pose operational challenges in membrane-based processes, leading to irreversible fouling and flux reduction. The digital twin incorporates eXtreme Gradient Boosting (XGBoost) models combined with SHapley Additive exPlanations (SHAP) to forecast key performance indicators such as dissolved organic carbon (DOC), UV254 absorbance, specific UV absorbance (SUVA), and membrane fouling percentage under various hydraulic and chemical loading conditions. The UF-only model showed the highest accuracy, with R2 values of 0.98 for DOC, 0.99 for UV254, 0.80 for SUVA, and 0.99 for fouling. The hybrid GAC-UF model also performed … |
| Anahtar Kelimeler |
| Adsorption | Digital twin | Humic acid | Machine learning | Membrane fouling | Ultrafiltration |
Science Direct
Development of a digital twin framework for hybrid adsorption-ultrafiltration systems in drinking water treatment
BM Sürdürülebilir Kalkınma Amaçları
| Atıf Sayıları | |
| Web of Science | 7 |
| Google Scholar | 9 |