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All Journal Rotasi ENGINEERING Jurnal Pendidikan Teknologi dan Kejuruan Jurnal Abdimas Sangkabira Automotive Experiences Advance Sustainable Science, Engineering and Technology (ASSET)
Bisrul Hapis Tambunan, Bisrul Hapis
Jurusan Teknik Mesin, Universitas Negeri Medan, Jl. William Iskandar, Medan
Aerospace Engineering Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering Social Sciences

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Journal : Advance Sustainable Science, Engineering and Technology (ASSET)

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Stratification and Charging Efficiency in Compact Thermal Storage Under Variable Flow Conditions: An AI-Assisted Simulation Study Simanjuntak, Janter P.; Daryanto, Eka; Tambunan, Bisrul Hapis; Silaban, Robert; Sinaga, Denny Haryanto; Zainon, Mohd Zamri; Muhammad Ibrahim
Advance Sustainable Science Engineering and Technology Vol. 8 No. 1 (2026): November - January
Publisher : Science and Technology Research Centre Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/asset.v8i1.2031

Abstract

Thermal Energy Storage (TES) systems are essential for managing low-grade heat in renewable energy applications. This study evaluates the impact of flow rate and heating power on thermal stratification and efficiency within a 30-liter TES unit. Using an AI-assisted simulation framework, the system's performance was analyzed across varying flow rates (0.3–0.9 LPM) and heater capacities (1.5–2.0 kW). Results indicate that lower flow rates (0.3–1.2 LPM) effectively preserve stratification, whereas higher rates induce thermal mixing. While charging efficiency generally decreases as target temperatures rise, it improves significantly with higher heater power. Notably, the configuration using a 0.7 LPM flow rate and 2.0 kW heater achieved a peak efficiency of 78% while maintaining stable thermal layering. This research demonstrates how AI-driven modeling can optimize charging behavior, providing critical insights for the design and thermal management of compact TES systems in low-grade heat applications.
Co-Authors Abdi Hanra Sebayang Denny Haryanto Sinaga DINA AMPERA Efendi, Hidir Eka Daryanto, Eka Harwin Saptoadi Himsar Ambarita Idroas, Mohamad Yusof Masudie, Ahmad Matondang, Zulkifl Mochamad Syamsiro Muhammad Ibrahim Riduwan Riduwan, Riduwan Robert Silaban Simanjuntak, Janter P. Simanjuntak, Janter Pangaduan siregar, Ridho Filandow Syahreza, Dina Sarah Tulus Burhanuddin Sitorus Yul Ifda Tanjung, Yul Ifda Zainon, Mohamad Zamri Zainon, Mohd Zamri Zulkifli, Nurin Wahidah Binti Mohd