Abstract This review critically examines state-of-the-art numerical methodologies for the simulation of wind turbines, offering a rigorous exploration of their theoretical foundations, practical implementations, and comparative performance. It begins by establishing a contextual framework through the classification of wind turbines, with particular focus on vertical axis configurations and emerging hybrid designs. The core of the study delves into advanced computational techniques encompassing computational fluid dynamics (CFD), finite element analysis (FEA), and fully coupled CFD-FEA frameworks used to resolve aerodynamic, structural, and fluid–structure interaction phenomena with high fidelity. The paper systematically analyzes turbulence modeling strategies, from industry-standard Reynolds-averaged Navier–Stokes (RANS) models to high-resolution large eddy simulation (LES) and hybrid detached eddy simulation (DES) approaches, evaluating their capabilities in capturing unsteady flow structures, vortex dynamics, and wake interactions. Additionally, reduced-order models such as the actuator line method (ALM) and actuator disk method (ADM) are assessed for their scalability in large wind farm simulations. Detailed discussions cover geometry generation, mesh refinement techniques, solver configuration, and post-processing analytics, offering best practices for ensuring numerical stability, accuracy, and validation. Through a comparative synthesis of these methods, the paper provides deep insights into their trade-offs in terms of computational cost, physical realism, and practical applicability, ultimately guiding the selection and optimization of simulation strategies for advanced wind energy system design and performance evaluation.
Building similarity graph...
Analyzing shared references across papers
Loading...
Mahmoud Hassan
Ain Shams University
Ibrahim A. Elsherif
Military Technical College
Mohamed A. El-latif
Military Technical College
Beni-Suef University Journal of Basic and Applied Sciences
Military Technical College
Building similarity graph...
Analyzing shared references across papers
Loading...
Hassan et al. (Thu,) studied this question.
synapsesocial.com/papers/68bb3edf2b87ece8dc956f07 — DOI: https://doi.org/10.1186/s43088-025-00680-4