Anupam Dewan

Darrieus vertical-axis wind turbines (VAWTs) offer an attractive alternative to traditional horizontal-axis wind turbines (HAWTs). However, the poor self-starting performance of Darrieus wind turbines remains a significant limitation that needs improvement. The present study investigates design modifications to improve the self-starting performance of a Darrieus wind turbine. An unsteady Reynolds-Averaged Navier–Stokes (URANS) investigation was performed by utilising the SST k–ω turbulence model to evaluate the performance and flow physics of a double-Darrieus turbine incorporating a NACA 0021 aerofoil and 70%, 60% and 50% cut-ratio J-blade derived from the same aerofoil. A detailed investigation of changes in torque and pressure coefficients resulting from the design modifications was performed. The results indicate an improvement in the power coefficient at low tip speed ratios. An average power coefficient improvement of more than 100% was observed for a tip speed ratio of 1.5 with an inlet velocity of 9 m/s. The present findings suggest that the addition of a second rotor (J-blades) not only improves self-starting performance but also improves the performance of the base turbine at low tip speed ratios. Furthermore, geometric modification of the Darrieus turbine can provide a promising solution to its self-starting issue without the need for an external source of starting torque.

The world is undergoing simultaneous digital and energy revolutions. Rising energy demand, together with rapid expansion of digital infrastructure, is reshaping the relevance and design priorities of modern renewable energy systems. Among these, wind energy remains a major renewable resource, with continuous developments in turbine design, simulation, control, and deployment strategies. This perspective highlights the co-evolution of wind turbine research and computational infrastructure, particularly in the context of artificial intelligence, graphics processing units, application-specific integrated circuits, and high-performance computing. It briefly reviews wind turbine simulation approaches, from early analytical models to modern high-fidelity large-eddy simulations. The article also discusses system-level improvements and policy measures required to support renewable energy integration, grid planning, and sustainable digital growth. This perspective argues that wind-energy development and AI infrastructure are undergoing a mutually reinforced co-evolution, linking advances in computational methods and hardware with AI-enabled wind-system design while creating new requirements for renewable generation, grid integration, and energy-system planning. Overall, it emphasizes the need for coordinated energy and computing strategies to address future decarbonization challenges.

Swirling flows underpin engineering systems, yet their dominant instability—the precessing vortex-core (PVC) associated with vortex-breakdown—can cause detrimental flame wrinkling, pressure oscillations, and increased pollutant formation. This work examines how swirler centerbody (CB) geometry alters PVC dynamics in a nonreacting, isothermal swirl-combustor. Unsteady Reynolds-averaged Navier–Stokes (URANS) simulations with shear-stress-transport (SST) k–ω model are performed for double-bullet and cylindrical CBs, with grid-independence and validation against reported measurements. PVC characteristics are extracted using two-point cross-spectral analysis of axial-velocity fluctuations near inner shear layer, time-domain signals for persistence, and low-pressure isosurfaces for associated vortex-core (VC) visualization. Both configurations exhibit a dominant m=1 correlated oscillatory component. Double-bullet case shows a strong PVC at ≈122 Hz, whereas cylindrical CB shifts it to ≈25 Hz and substantially attenuates the oscillation. Low-pressure isosurfaces show a clear asymmetric single-helical VC in double-bullet case, while cylindrical-CB case possesses a more symmetric near-swirler core with a weakly asymmetric downstream extension, i.e., deformed single-helical VC. The resolved fluctuations remain largely persistent in both cases. Further, the weak persistent response in cylindrical CB case is not fully explained by expected eigenmode-based suppression/intermittency. Accordingly, eigenmode-based interpretation here appears to be sensitive to mean-flow linearization and turbulence model used in URANS for predicting mean-flow topology; therefore, PVC behavior deduced from linear eigenmodes and mean-flow state should be interpreted here only qualitatively.

This work presents an analysis of wake dynamics of vertical-axis wind turbines (VAWTs), employing the actuator line model in conjunction with large eddy simulation. Three turbine configurations—a straight-bladed turbine and two helical-bladed turbines with 90° and 180° twists—are investigated under a tip-speed ratio of 4.5 for the turbulence intensity of 0.5% and 5%. This study focuses on quantifying wake recovery mechanisms, turbulence characteristics, and energy redistribution using velocity fields, transport mechanisms, and modal decomposition. The results show that increasing the helical angle leads to earlier vortex breakdown, shorter near-wake regions, and faster streamwise velocity recovery. Helical turbines induce significant vertical velocity components and exhibit enhanced lateral and vertical turbulent transports, which accelerate wake mixing. Proper orthogonal decomposition analysis reveals that the first mode captures more than 99% of the streamwise energy in all cases, while energy distribution across higher modes increases with helical angle, especially in the vertical component. This redistribution is attributed to reduced dynamic stall intensity in the helical configurations. Furthermore, a shift in the dominant frequency of the temporal modes indicates that vortex shedding becomes less intense and more spread out with increased blade helicity. The findings highlight the aerodynamic advantages of helical VAWTs, particularly in enabling denser turbine arrays.