Solar flat plate collectors with internally grooved absorber tubes for enhanced efficiency: Application of eXplainable artificial intelligence using cooperative game theory-based Shapley values

This study investigates the impact of grooved absorber tubes on the efficiency of solar flat plate collectors (SFPCs). Conducted in Vellore, India, it compares plain tubes (case 1) with grooved tubes (cases 2 and 3) using water and glycol-water mixtures. Results show that grooved tubes significantly improved efficiency, particularly with glycol-water mixtures. Efficiency increased by up to 12 % in transient flow conditions and by 8 %–20 % across various flow rates compared to plain tubes. A 5 % increase in solar radiation led to a 7 % rise in effectiveness. Heat removal factors ranged from 0.66 to 0.69 for water and 0.76–0.78 for glycol-water. Case 2 exhibited the highest efficiency under transient flow, while case 1 had the lowest under laminar flow conditions. These findings suggest that grooved tubes significantly enhance SFPC performance. Three machine learning approaches—AdaBoost, K-Nearest Neighbors, and Tweedie regression—were employed for model prediction, utilizing SHapley Additive exPlanations for interpretability. The AdaBoost model outperformed with an MAE of 0.0150, MSE of 0.0003, RMSE of 0.0175, and R2 of 0.8494. Key features identified by the model included groove pitch, ambient and glass plate temperatures, and solar radiation. These findings offer insights into enhancing SFPC efficiency through absorber unit adjustments.

Authors

Publication Details

Journal
Case Studies in Thermal Engineering
Published
2025-02-18
DOI
https://doi.org/10.1016/j.csite.2025.105912
Citations
8
Primary Topic
Solar Thermal and Photovoltaic Systems
Type
article
Field-Weighted Citation Impact
2.91
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Solar flat plate collectors with internally grooved absorber tubes for enhanced efficiency: Application of eXplainable artificial intelligence using cooperative game theory-based Shapley values

Prabhakar Sharma, L. Chilambarasan, K.V. Sharma, Y. Raja Sekhar et al.
8 citations
Case Studies in Thermal Engineering
Solar Thermal and Photovoltaic Systems
2.91
article

Solar flat plate collectors with internally grooved absorber tubes for enhanced efficiency: Application of eXplainable artificial intelligence using cooperative game theory-based Shapley values

Prabhakar Sharma, L. Chilambarasan, K.V. Sharma, Y. Raja Sekhar, Seshathiri Dhanasekaran, Praveen Kumar Kanti, Prabhu Paramasivam
article en
8 citations

Abstract

This study investigates the impact of grooved absorber tubes on the efficiency of solar flat plate collectors (SFPCs). Conducted in Vellore, India, it compares plain tubes (case 1) with grooved tubes (cases 2 and 3) using water and glycol-water mixtures. Results show that grooved tubes significantly improved efficiency, particularly with glycol-water mixtures. Efficiency increased by up to 12 % in transient flow conditions and by 8 %–20 % across various flow rates compared to plain tubes. A 5 % increase in solar radiation led to a 7 % rise in effectiveness. Heat removal factors ranged from 0.66 to 0.69 for water and 0.76–0.78 for glycol-water. Case 2 exhibited the highest efficiency under transient flow, while case 1 had the lowest under laminar flow conditions. These findings suggest that grooved tubes significantly enhance SFPC performance. Three machine learning approaches—AdaBoost, K-Nearest Neighbors, and Tweedie regression—were employed for model prediction, utilizing SHapley Additive exPlanations for interpretability. The AdaBoost model outperformed with an MAE of 0.0150, MSE of 0.0003, RMSE of 0.0175, and R2 of 0.8494. Key features identified by the model included groove pitch, ambient and glass plate temperatures, and solar radiation. These findings offer insights into enhancing SFPC efficiency through absorber unit adjustments.

Case Studies in Thermal EngineeringVol. 68
Affordable and clean energy
Openalex Percentile: Top 9%
Solar Thermal and Photovoltaic Systems
2.91
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.