Experimental validation of a novel modelling technique for packed bed thermal storage systems containing non-spherical phase change material capsules
Bibliographic record
Abstract
• Introduces a novel simulation technique for packed bed thermal storage systems using non-spherical phase change material capsules. • Combines detailed 2D simulations of a single capsule with a 1D finite volume model to simulate the entire PCM-PBS system efficiently. • Reduces computational resources required for iterative design while maintaining model accuracy. • Experimental validation performed using a PCM-PBS setup with cylindrical capsules containing stearic acid. • Demonstrates strong agreement between simulated results and experimental data, offering a practical tool for improving system performance in energy storage applications. This work presents a novel modeling technique for non-spherical capsule-shaped latent heat packed bed storage (PBS) systems aiming for resource efficiency in iterative optimization and design. The current simulation methods for such systems are resource-intensive and not suitable for iterative design. To address this, it is proposed to combine an efficient approach of detailed simulations of a single capsule during the phase change process with a one-dimensional (1D) model. Finite element simulations are used to capture local phenomena and characterize heat transfer rates from the capsules. The resulting heat flux dataset is integrated into a finite volume model to simulate the entire PCM-PBS system effectively. By combining these approaches, the computational resources needed are significantly reduced while maintaining accuracy. Experimental validation was conducted using a PCM-PBS setup with steel cans containing stearic acid and water as the heat transfer fluid. The results were able to reproduce the temperature history measured at four locations within the packed bed as well as the outlet temperature and total energy remove from the system during discharge for six separate experiments. These confirm the effectiveness of this simulation technique and provide validation. It addresses a knowledge gap in both experimental and numerical aspects, offering potential improvements in charge/discharge rate, energy density, and cost-effectiveness of PCM-PBS systems.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".