Latent heat thermal energy storage: Metal foam configuration and deep learning-based process predictions
Yazarlar (4)
Dr. Öğr. Üyesi Emrehan Gürsoy Kardemir Karabük Iron Steel Industry Trade & Co. Inc., Türkiye
Doç. Dr. Mehmet GÜRDAL Kastamonu Üniversitesi, Türkiye
Dr. Öğr. Üyesi Muhammed TAN Kastamonu Üniversitesi, Türkiye
Engin Gedik Karabük Üniversitesi, Türkiye
| Makale Türü | Özgün Makale (SSCI, AHCI, SCI, SCI-Exp dergilerinde yayınlanan tam makale) | ||
| Dergi Adı | Journal of Energy Storage (Q1) | ||
| Dergi ISSN | 2352-152X Wos Dergi Scopus Dergi | ||
| Dergi Tarandığı Indeksler | SCI-Expanded | ||
| Makale Dili | İngilizce | Basım Tarihi | 09-2025 |
| Cilt / Sayı / Sayfa | 130 / 1 / 117361–0 | DOI | 10.1016/j.est.2025.117361 |
| Makale Linki | https://doi.org/10.1016/j.est.2025.117361 | ||
| Özet |
| This study investigates the effects of different metal foam (MF) configurations on the performance of latent heat thermal energy storage (LHTES) systems. Two distinct MF materials, aluminum (Al) and copper (Cu) were analyzed with varying porosity (ε=0.90–0.95) and pore density (ω=10–20 PPI) values to optimize the melting and energy storage characteristics of phase change materials (PCMs). A validated computational fluid dynamics (CFD) model using the enthalpy-porosity method (EPM) was implemented and a deep learning approach integrating long short-term memory (LSTM) networks and self-attention mechanisms was employed to optimize key parameters. The findings indicate that placing Cu MF near the heat source reduced the melting time by 28.2%, increased the total stored energy by 3.39%, and a solid phase state of 17% is observed in the Al MF case. Due to Cu's high thermal conductivity (401 W … |
| Anahtar Kelimeler |
| Enthalpy | Latent heat thermal energy storage | Machine learning | Metal foam | Phase change materials | Python |
Science Direct
Latent heat thermal energy storage: Metal foam configuration and deep learning-based process predictions
BM Sürdürülebilir Kalkınma Amaçları
| Atıf Sayıları | |
| Web of Science | 3 |
| Scopus | 4 |
| Google Scholar | 4 |