Low-Reynolds-number flows are susceptible to premature boundary-layer separation and stall, which can substantially reduce the aerodynamic efficiency of small blades. In this study, a variable-section twisted blade, designated FX-01, is investigated using computational fluid dynamics with the correlation-based Transition SST model. The blade incorporates a smooth spanwise transition between two cambered airfoil sections, together with linearly varying chord and twist distributions. Its aerodynamic performance is compared with those of two full-span reference blades over a range of prescribed global blade angles and freestream velocities. The numerical method is assessed against published low-Reynolds-number experimental data for a finite-span NACA4412 model. At V = 8 m/s, FX-01 achieves a maximum lift-to-drag ratio of approximately 9.1 at a prescribed global blade angle of α_g = 15°, compared with approximately 8.85 and 6.42 for the NACA4412 and NACA4418 reference blades, respectively. At α_g = 15°, FX-01 reaches a maximum lift-to-drag ratio of approximately 13.06 at V = 28 m/s. This peak value is 5.0% and 25.1% higher than the respective maximum values of the NACA4412 and NACA4418 reference blades over the investigated velocity range. The flow-field visualizations indicate that FX-01 produces a smoother spanwise pressure distribution and a less concentrated low-speed region in the displayed wake under the investigated conditions. Within the limitations of the steady-RANS framework, the results indicate that the coordinated spanwise variation in airfoil section, chord, and twist is associated with favorable predicted aerodynamic efficiency for the stationary finite-span blade under the investigated low-Reynolds-number conditions.

The incorporation of hybrid nanomaterials and fiber architectures into fiber-optic biosensors has proven to be effective in improving sensing performance. This study developed a plasmonic biosensor using a tapered multimode fiber (MMF)–multicore fiber (MCF)–MMF structure functionalized with a nanocomposite of gold nanoparticles (AuNPs), tungsten disulfide quantum dots (WS₂-QDs), and multi-walled carbon nanotubes (MWCNTs) for selective triclosan detection. Combining WS₂-QDs and MWCNTs with AuNPs leverages their individual advantages, creating an active sensing interface with abundant analyte-binding sites, thereby substantially improving responsiveness. The composite-modified structure also promotes higher-order mode generation, which is critical for sensitivity enhancement. When optically excited, the periodic plasmonic geometry produces strong evanescent fields that intensify interactions between the immobilized nanocomposite and target molecules. Transmission spectroscopy demonstrated that the biosensor achieved a detection limit of 3.87 µM within the 0–40 µM range. These results show that the strategic combination of WS₂-QDs and MWCNTs with AuNPs significantly amplifies localized surface plasmon resonance (LSPR) effects. This architecture offers a promising approach for developing sensitive fiber-optic biosensors, particularly for environmental monitoring of agents like triclosan.