Jian Guo Zhou

High-Reynolds-number cavity flow with obstacles plays a critical role in many engineering applications; however, the underlying mechanisms governing vortex evolution and turbulence characteristics remain poorly understood. This study investigates the dynamic evolution of flow structures in a square cavity across Reynolds numbers ranging from Re = 1 × 105 to 7 × 105 using high-resolution particle image velocimetry. Results show that the primary vortex exhibits a multi-stage migration, moving from the wall toward the cavity center and stabilizing as Reynolds number increases, while the secondary vortex on the right side of the obstacle strengthens up to Re = 2.5 × 105 and diminishes at higher Reynolds numbers. At Re = 7 × 105, the primary vortex dominates the flow field, suppressing secondary vortices and concentrating over 68% of the total positive vorticity. Proper orthogonal decomposition reveals that energy becomes increasingly localized in low-order, large-scale structures, with the first 50 modes capturing approximately 59% of the total turbulent kinetic energy at Re = 2.5 × 105. Velocity analysis indicates a significant reduction in extremely high-speed regions with increasing Reynolds number, and the skewness coefficient in the primary vortex core exceeds 1, reflecting strong intermittent pulsations. These findings provide quantitative insight into the multi-scale interactions and self-organization of turbulence in high-Reynolds-number cavity flows with obstacles, offering guidance for flow control and mixing optimization in engineering applications.

Waterborne diseases and antimicrobial resistance (AMR) pose mounting public health threats across sub‐Saharan Africa, particularly in rapidly urbanising regions dependent on untreated or poorly treated surface waters. This study applied shotgun metagenomic sequencing to characterise microbial communities, virulence factors and antibiotic resistance genes (ARGs) in water samples collected from Lake Victoria, River Wigwa, Dunga Water Treatment Plant, Nyalenda Wastewater Stabilisation Ponds and the tap water outlet in post‐treatment supply pipe in Kisumu city (Kenya). Bacterial taxa dominated all metagenomes, with 121 classes represented. Cyanobacteria, particularly Planktothrix , were highly abundant in lake and tap water, whereas wastewater and river samples exhibited greater taxonomic diversity. Major human pathogens, including Pseudomonas aeruginosa , Klebsiella pneumoniae , Escherichia coli , Acinetobacter baumannii and Bacillus cereus /anthracis , were detected in nearly all samples, with unexpectedly high prevalence in tap water. Viral indicators of faecal contamination (adenoviruses, enteroviruses and torque teno viruses) corroborated widespread wastewater influence. Functional gene profiling revealed a rich resistome comprising aminoglycoside‐modifying enzymes, β‐lactamases, vancomycin‐resistance operons and disinfectant‐resistance determinants. The highest ARG and virulence gene frequencies occurred in tap and treatment‐plant water, suggesting that incomplete disinfection and biofilm persistence promote the proliferation and exchange of ARGs between environmental and pathogenic taxa. In contrast, Lake Victoria water exhibited lower ARG abundance, reflecting natural self‐purification processes. These findings underscore the inadequate water treatment and open wastewater systems create ecological ‘hotspots’ for ARG selection and horizontal gene transfer. Metagenomic surveillance integrated into One Health frameworks can enhance risk forecasting and guide interventions to mitigate AMR emergence and dissemination in freshwater systems serving over 35 million people across the Lake Victoria basin.

Wetting and drying processes in shallow‐water flows remain challenging to simulate accurately, especially over complex terrain where conventional methods often struggle to maintain stability and precision. To address this gap, a discrete Boltzmann model is developed in this study, incorporating an effective wetting and drying treatment to precisely capture the dynamics of wet–dry boundaries across intricate terrain. The model's performance is evaluated through six benchmark tests, including three one‐dimensional (1D) and three two‐dimensional (2D) cases: (a) flow in a straight channel with a triangular bed obstacle; (b) propagation of one‐dimensional tidal waves across a varying sloped bed; (c) dam‐break flow over non‐uniform terrain with two elevation steps; (d) 2D dam‐break in an L‐shaped channel; (e) 2D dam‐break flow through a contracting channel; and (f) 2D flooding over terrain with three mounds. The numerical results align well with analytical solutions, previously published computational results, and experimental data. Furthermore, the study highlights the critical role of the wetting threshold water depth in determining both accuracy and numerical stability. An excessively high threshold could result in imprecise predictions of wet–dry transitions, while a threshold set too low may cause numerical instability. Therefore, the appropriate selection of this parameter is essential for obtaining reliable and consistent simulations.

To address the challenge of modal characterization of complex turbulent structures in high Reynolds number cavity flow, this study integrates the time integration contribution-dynamic mode decomposition (TIC-DMD) and sparsity-promoting DMD (SPDMD) as multi-scale analysis methods. Utilizing particle image velocimetry experimental data (Re = 5 × 105 and Re = 2 × 106), it comprehensively analyzes the dynamic characteristics and modal reconstruction performance of high Reynolds number cavity flow. The findings show that the TIC-DMD effectively extracts the dominant vortex structures through a time-domain energy integration mechanism. At Re = 5 × 105, it achieves 61.02% reduction in reconstruction error compared to SPDMD when using a high modal number (N = 246), significantly enhancing its ability to capture multi-scale turbulence. In addition, the SPDMD suppresses noise interference through sparsity constraints, achieving a reconstruction error of 0.0593 with a low modal number (N = 7), a 75.79% improvement over the standard DMD. Both methods' first-order modes consistently and stably reconstruct the dominant vortex structures of the flow field, while the standard DMD suffers from mode fragmentation due to noise sensitivity. Further analysis reveals that SPDMD excels at low modal numbers, whereas TIC-DMD offers superior stability and accuracy in flow field reconstruction as the modal number increases, particularly for high Reynolds number flows. The modal analysis framework developed in this study introduces a novel paradigm for modeling complex flows. The framework proposes to integrate experimental data with the large eddy simulation benchmark database, thereby advancing engineering applications in high Reynolds number flow control.

This study experimentally investigates lid-driven cavity flow at high Reynolds numbers (Re = 3 × 105–1 × 106) using particle image velocimetry. The spatial distribution of root mean square (RMS) velocity, turbulent kinetic energy dissipation rate, and the Smagorinsky constant is analyzed to reveal key turbulence characteristics. The results show that: (1) the RMS velocity increases significantly in the near-wall region with Reynolds number, reaching a peak of 0.43 m/s on the downstream near-wall surface at Re = 1 × 106, while remaining below 0.1 m/s in the core region due to flow stability suppressing turbulence fluctuations; (2) the turbulent kinetic energy dissipation rate exhibits significant spatial nonuniformity near the wall with a peak value of 0.6 at Re = 1 × 106; as the Reynolds number increases, high dissipation regions extend further into the cavity interior and evolve into multiscale fragmented structures; (3) the Smagorinsky constant is close to zero near the cavity wall, gradually increases with distance from the wall, reaches a maximum, and then decreases to zero at the cavity center. As the Reynolds number increases, the overall Smagorinsky constant increases with a more significant rise in its maximum value at higher Reynolds numbers, indicating stronger eddy viscosity. These findings provide experimental insights for improving the nonuniform parameterization in eddy viscosity models for large-eddy simulations.

A novel single MRT-featured lattice Boltzmann method (SmrtLBM) is introduced. The intricate algorithm of the multiple-relaxation-time (MRT) collision operator is reimagined and distilled into a streamlined, single-relaxation-time-like scheme. This innovation preserves the simplicity and efficiency of the conventional single-relaxation-time approach while inheriting the enhanced stability characteristic of the MRT techniques, making it a powerful tool for simulating complex fluid flows. Rigorous numerical testing on cavity flows demonstrates that SmrtLBM accurately captures complex flow characteristics, even in challenging high Reynolds number regimes where precision and stability are crucial. Compared to the traditional single-relaxation-time lattice Boltzmann method, this model offers superior stability and accurate solutions for difficult flows. The SmrtLBM marks a breakthrough in complex fluid simulation through a simple method, offering a new level of efficiency and reliability in tackling challenging flow problems.

Wind effects on wave overtopping over a fully impermeable vertical sea wall were studied numerically using the open-source computational fluid dynamics library OpenFoam. A pressure gradient correction term was incorporated in the momentum equations. In recent studies, it was found that, in the absence of wind, an increase in wave steepness results in a reduction of wave overtopping. This is related to the instability of the standing wave formed at the front of a vertical structure. Such instability was noticed in the range of steepness 0.285–0.443 from previous physical experiments for a regular wave interacting with a vertical structure. The existence of this regime was confirmed in the current study. It was also found that the stability of the standing wave determines the shape and volume of the overshooting jet, which has a strong effect on wave overtopping. When the wind is relatively weak (e.g. a wind speed of 10 m/s) it is unable to alter the overshooting jet very much, meaning a weak wind effect on wave overtopping. When the wind is strong (e.g. a wind speed of 30 m/s) it completely deforms the overshooting jet resulting in overtopping discharge almost three times that without wind.