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The addition of Computational Fluid Dynamics (CFDComputational Fluid Dynamics (CFD)) in renewable energyRenewable energy has improved the optimizationOptimization and efficiency of energy conversion procedures. As the demand for sustainable energy sources grows, CFDComputational Fluid Dynamics (CFD) plays a vital role in investigating fluid–structure interactions (FSI), turbulence modeling, and heat transfer systems in renewable energy systemsRenewable energy systems. Efficient wave energy convertersWave Energy Converter (WEC) (WECsWave Energy Converter (WEC)) are vital, with CFDComputational Fluid Dynamics (CFD) playing a key role in their design and optimizationOptimization. This chapter examines CFDComputational Fluid Dynamics (CFD)’s application in modeling hydrodynamic performance in oscillating water columnsOscillating Water Column (OWC) (OWCsOscillating Water Column (OWC)) and other WECWave Energy Converter (WEC) technologies as well as its critical role in nuclear reactor safety, especially in analyzing high-temperature variations and mitigating thermal stripingThermal striping risks in liquid–metal-cooled reactors. This chapter explores the applications of CFDComputational Fluid Dynamics (CFD) in different renewable energyRenewable energy domains, with a focus on wind energy, solar thermal systems, and WECsWave Energy Converter (WEC). Cutting-edge numerical techniques, such as unsteady Reynolds-averaged Navier–Stokes (URANS), large eddy simulation (LES), direct numerical simulation (DNS), turbulence-coherent structure analysis, and smoothed particle hydrodynamics (SPH), will be discussed to highlight their usefulness in modeling complex flow dynamics. The chapter also examines the role of artificial intelligence (AIArtificial Intelligence (AI)) in improving CFDComputational Fluid Dynamics (CFD)-based energy simulations, aiding predictive analysisPredictive analysis and optimization mainly in nuclear reactor safety and performance improvement. Furthermore, case studies indicating CFDComputational Fluid Dynamics (CFD) applications in wind turbine aerodynamics, solar panel cooling optimizationOptimization, thermal stripingThermal striping mitigation in nuclear reactors, and wave energyWave energy extraction will be presented. Challenges for instance computational costs, turbulence modeling limits, and environmental uncertainties will be critically analyzed, together with potential solutions including hybrid computational methods.

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Advancing Energy Systems with CFD from Renewable Technologies to Nuclear Reactor Safety

  • 章节

  • 发表日期：

    2026年

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  • Mohsin Raza,
  • Zahid Kumail,
  • Tahsin Nawaz,
  • Syed Zia Uddin

摘要

The addition of Computational Fluid Dynamics (CFDComputational Fluid Dynamics (CFD)) in renewable energyRenewable energy has improved the optimizationOptimization and efficiency of energy conversion procedures. As the demand for sustainable energy sources grows, CFDComputational Fluid Dynamics (CFD) plays a vital role in investigating fluid–structure interactions (FSI), turbulence modeling, and heat transfer systems in renewable energy systemsRenewable energy systems. Efficient wave energy convertersWave Energy Converter (WEC) (WECsWave Energy Converter (WEC)) are vital, with CFDComputational Fluid Dynamics (CFD) playing a key role in their design and optimizationOptimization. This chapter examines CFDComputational Fluid Dynamics (CFD)’s application in modeling hydrodynamic performance in oscillating water columnsOscillating Water Column (OWC) (OWCsOscillating Water Column (OWC)) and other WECWave Energy Converter (WEC) technologies as well as its critical role in nuclear reactor safety, especially in analyzing high-temperature variations and mitigating thermal stripingThermal striping risks in liquid–metal-cooled reactors. This chapter explores the applications of CFDComputational Fluid Dynamics (CFD) in different renewable energyRenewable energy domains, with a focus on wind energy, solar thermal systems, and WECsWave Energy Converter (WEC). Cutting-edge numerical techniques, such as unsteady Reynolds-averaged Navier–Stokes (URANS), large eddy simulation (LES), direct numerical simulation (DNS), turbulence-coherent structure analysis, and smoothed particle hydrodynamics (SPH), will be discussed to highlight their usefulness in modeling complex flow dynamics. The chapter also examines the role of artificial intelligence (AIArtificial Intelligence (AI)) in improving CFDComputational Fluid Dynamics (CFD)-based energy simulations, aiding predictive analysisPredictive analysis and optimization mainly in nuclear reactor safety and performance improvement. Furthermore, case studies indicating CFDComputational Fluid Dynamics (CFD) applications in wind turbine aerodynamics, solar panel cooling optimizationOptimization, thermal stripingThermal striping mitigation in nuclear reactors, and wave energyWave energy extraction will be presented. Challenges for instance computational costs, turbulence modeling limits, and environmental uncertainties will be critically analyzed, together with potential solutions including hybrid computational methods.