Работы, цитирующие эту работу

Работ: 4

Работа: Artificial neural network-based optimization of heat absorption process of phase change materials in a novel-designed finned-plate latent heat storage system

1. Optimizing novel thermal energy storage systems: Enhancing melting efficiency with tubes, stands, and advanced machine learning techniques

   Ahmad Almadhor, Ali Basem, Pradeep Kumar Singh +7

   СтатьяPhase Change Materials ResearchJournal of Energy Storage2025Цитирований: 5

   ABIABI:AkademIndex/openalex/2025.article.000117

2. Heat absorption/release efficiency betterment of phase change material inside a shell-and-tube latent heat storage system under six different conditions of tube and fins

   Peng Duan, Azher M. Abed, Rishabh Chaturvedi +4

   СтатьяPhase Change Materials ResearchJournal of Energy Storage2024Цитирований: 3

   ABIABI:AkademIndex/openalex/2024.article.000259

3. Advanced latent thermal energy storage design featuring three dividers: Optimizing multi-enclosure system with ANN-driven models and hybrid phase change material integration

   Zhonghong Li, Lin Wu, Mohamed Shaban +7

   СтатьяPhase Change Materials ResearchJournal of Energy Storage2025Цитирований: 1

   ABIABI:AkademIndex/openalex/2025.article.000381

4. Improving energy absorption capacity in a thermal energy storage system for domestic heating applications using an integrated machine learning/numerical approach

   Xianzhi Tang, Xin Sun, Sinan Q. Salih +7

   СтатьяPhase Change Materials ResearchApplied Thermal Engineering2025Цитирований: 1

   ABIABI:AkademIndex/openalex/2025.article.001117