Is this project an undergraduate, graduate, or faculty project?
Undergraduate
Project Type
group
Campus
Daytona Beach
Authors' Class Standing
Quinten Acchione, Senior Spencer Marinac Tristan Bagar
Lead Presenter's Name
Quinten Acchione
Lead Presenter's College
DB College of Engineering
Faculty Mentor Name
Mark Ricklick
Abstract
This study investigates the thermal performance of supercritical carbon dioxide (sCO₂) in a counterflow heat exchanger with water as the secondary working fluid. The primary objective is to evaluate heat transfer behavior and assess the accuracy of predictive modeling for both fluid streams. An experimental test rig was developed to physically evaluate multiple operating conditions, including variations in inlet temperatures, pressures, and mass flow rates for both sCO₂ and water. The experimental data was then compared against results from a Python-based simulation solver to validate model predictions. The results show strong agreement between the experimental and simulated heat transfer coefficients on the sCO₂ side, indicating that the numerical model effectively captures the thermophysical behavior of sCO₂ under the tested conditions. However, discrepancies were observed on the water side, where experimental results deviated from simulation predictions. This inconsistency is attributed primarily to unaccounted heat losses in the experimental setup, which reduced the accuracy of the measured water side heat transfer. Overall, the findings demonstrate that while the simulation model is reliable for predicting sCO₂ heat transfer performance, improvements to the experimental setup, particularly minimizing heat leakage, are necessary for accurate validation on the water side. Thus far, this work highlights the importance of accounting for system-level losses in experimental heat exchanger studies and supports the continued use of coupled experimental and computational approaches for evaluating advanced thermal systems. Future work will focus on incorporating surface roughness profiles into the Python-based model to determine the optimal heat exchanger roughness distribution required to achieve a uniform temperature profile and minimize thermal pinching.
Did this research project receive funding support (Spark, SURF, Research Abroad, Student Internal Grants, Collaborative, Climbing, or Ignite Grants) from the Office of Undergraduate Research?
No
Performance of a Supercritical CO2 Counterflow Heat Exchanger
This study investigates the thermal performance of supercritical carbon dioxide (sCO₂) in a counterflow heat exchanger with water as the secondary working fluid. The primary objective is to evaluate heat transfer behavior and assess the accuracy of predictive modeling for both fluid streams. An experimental test rig was developed to physically evaluate multiple operating conditions, including variations in inlet temperatures, pressures, and mass flow rates for both sCO₂ and water. The experimental data was then compared against results from a Python-based simulation solver to validate model predictions. The results show strong agreement between the experimental and simulated heat transfer coefficients on the sCO₂ side, indicating that the numerical model effectively captures the thermophysical behavior of sCO₂ under the tested conditions. However, discrepancies were observed on the water side, where experimental results deviated from simulation predictions. This inconsistency is attributed primarily to unaccounted heat losses in the experimental setup, which reduced the accuracy of the measured water side heat transfer. Overall, the findings demonstrate that while the simulation model is reliable for predicting sCO₂ heat transfer performance, improvements to the experimental setup, particularly minimizing heat leakage, are necessary for accurate validation on the water side. Thus far, this work highlights the importance of accounting for system-level losses in experimental heat exchanger studies and supports the continued use of coupled experimental and computational approaches for evaluating advanced thermal systems. Future work will focus on incorporating surface roughness profiles into the Python-based model to determine the optimal heat exchanger roughness distribution required to achieve a uniform temperature profile and minimize thermal pinching.