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Fluid mechanics model studies often utilize scaled-down systems to predict fluid behavior in full-scale environments, such as river flows, dam spillways, and structures interacting with open surfaces. Maintaining Froude number similarity in river models is crucial, as it replicates surface flow features like wave patterns and velocities.
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Performance Prediction and Optimization of Nanofluid-Based PV/T Using Numerical Simulation and Response Surface

Sreehari Sreekumar1, Supriya Chakrabarti2, Neil Hewitt1

  • 1Centre for Sustainable Technologies (CST), Belfast School of Architecture and the Built Environment, Ulster University, Belfast BT15 1ED, Northern Ireland, UK.

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Summary
This summary is machine-generated.

This study optimized a photovoltaic/thermal (PV/T) system using MXene/water nanofluid. The research identified optimal operating parameters to maximize both energy and exergy efficiency for enhanced performance.

Keywords:
ANOVACFDnanofluidoptimizationresponse surface method

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Area of Science:

  • Renewable Energy Systems
  • Nanofluids
  • Heat Transfer

Background:

  • Photovoltaic/thermal (PV/T) systems offer combined electricity and heat generation.
  • MXene/water nanofluids show promise as advanced heat transfer fluids (HTFs) for PV/T systems.
  • Optimizing operating parameters is crucial for maximizing PV/T system efficiency.

Purpose of the Study:

  • To numerically investigate the performance of a PV/T system using MXene/water nanofluid.
  • To analyze the impact of operating parameters on thermal, electrical, and exergy efficiencies.
  • To optimize the system for maximum energy and exergy efficiency using response surface methodology.

Main Methods:

  • Numerical simulation using ANSYS Fluent®.
  • Development of a predictive model using response surface methodology (RSM).
  • Analysis of Variance (ANOVA) to determine parameter significance.

Main Results:

  • Nanofluid mass flow rate significantly impacts thermal efficiency.
  • Incident solar radiation greatly influences electrical efficiency and exergy efficiencies.
  • Optimized parameters include mass flow rate (71.84 kgh-1), mass fraction (0.2 wt%), incident radiation (581 Wm-2), and inlet temperature (20 °C).

Conclusions:

  • The study successfully optimized a PV/T system with MXene/water nanofluid.
  • Maximum predicted overall energy efficiency reached 81.67%, and exergy efficiency reached 18.6%.
  • The developed model provides a valuable tool for designing and enhancing similar PV/T systems.