Sourav Sarkar

The two-dimensional unsteady laminar flow past a slotted cylinder facilitated with fluid injection is studied to examine the mixing behavior between upstream air and the fluid injected from the cylinder-slots for different slot angular positions (0°–90°). Additionally, wake dynamics and the resulting variations in key hydrodynamic quantities resulting from fluid–fluid interaction are analyzed. Simulations are primarily conducted for an injected fluid and air velocity ratio (Vr) of 1, with additional cases up to 3 to assess the impact of injection momentum. Pressure, velocity, and vorticity contours are used to analyze wake dynamics, while mass-fraction and mixture-fraction fields are examined to check mixing characteristics. Furthermore, the recurrence quantification analysis (RQA) is used to understand the underlying flow dynamics. For Vr=1, two distinct wake characteristics are identified. At low injection angles (0°–20°), the wake remains symmetric with the absence of vortex shedding, resulting in minimal lift and drag. Beyond 20°, vortex shedding emerges for all configurations. For 0°–20° cases, the flow exhibits a narrow mixing layer and high downstream mass-fraction variance, indicating weak mixing. Mixing is enhanced at higher injection angles (60°–90°), as indicated by a wider mixing layer and the lowest downstream variance. However, intensified vortex shedding for 60°–90° cases leads to stronger wake oscillations and higher hydrodynamic forces. RQA of the lift coefficient shows stable equilibrium at low injection angles, transitioning to periodic dynamics at higher angles. Despite the few dynamical variations, similar mixing and hydrodynamic trends persist for all velocity ratios considered.

Efficient particle sorting in microfluidic systems is vital for advancements in biomedical diagnostics and industrial applications. This study numerically investigates particle migration and passive sorting in symmetric serpentine microchannels, leveraging inertial and centrifugal forces for label-free, high-throughput separation. Using a two-dimensional numerical model, particle dynamics were analyzed across varying flow rates, diameter ratios (1.2, 1.5, and 2), and channel configurations. The optimized serpentine geometry achieved particle separation efficiencies exceeding 95% and throughput greater than 99%.A novel scaling framework was developed to predict the minimum number of channel loops required for efficient sorting. Additionally, the robustness of the proposed scaling framework is demonstrated by its consistency with findings from previous studies, which exhibit the same trend as predicted by the scaling laws, underscoring the universality and reliability of the model. Additionally, the study revealed the significant influence of density ratio (α) on sorting efficiency, where higher α values enhanced separation through amplified hydrodynamic forces. Optimal flow rates tailored to particle sizes were identified, enabling the formation of focused particle streaks for precise sorting. However, efficiency declined beyond these thresholds due to particle entrapment in micro-vortices or boundary layers. This work provides valuable insights and design principles for developing compact, cost-effective microfluidic systems, with broad applications in biomedical fields like cell sorting and pathogen detection, as well as industrial processes requiring precise particle handlin

Efficient cooling is vital for the performance and reliability of modern systems such as electronics, nuclear reactors, and industrial equipment. Jet impingement cooling is widely used for its high local heat transfer rates. Accurate estimation of convective heat transfer coefficient (CHTC) is essential for design, simulation, and control of thermal systems. However, estimating spatially varying CHTCs from limited and noisy temperature data poses a challenging inverse problem. This study presents a physics-informed neural network (PINN) framework to estimate both averaged and spatially varying CHTCs at the fluid-solid interface in a jet impingement setup at Reynolds number 5000. The model uses sparse and noisy temperature data from within the solid and embeds the transient heat conduction equation along with boundary and initial conditions into its loss function. This enables inference of unknown boundary parameters without explicit modeling of the fluid domain. Validation is performed using synthetic temperature data from high-fidelity conjugate heat transfer (CHT) simulations. The framework is tested under various additive Gaussian noise levels (up to 30 percent) and sampling rates 0.25 to 4.0 per second. For noise levels up to 10% and sampling rates of 0.5 per second or higher, estimated CHTCs match CHT-derived benchmarks with relative errors below 8 percent. Even under high-noise scenarios, the framework maintains predictive accuracy when time resolution is sufficient. These results highlight the method's robustness to noise and sparse data, offering a scalable alternative to traditional inverse methods, experimental measurements, or full CHT modeling for estimating boundary thermal parameters in real-world cooling applications.

Efficient particle sorting in microfluidic systems is vital for advancements in biomedical diagnostics and industrial applications. This study numerically investigates particle migration and passive sorting in symmetric serpentine microchannels, leveraging inertial and centrifugal forces for label-free, high-throughput separation. Using a two-dimensional numerical model, particle dynamics were analyzed across varying flow rates, diameter ratios (1.2, 1.5, and 2), and channel configurations. The optimized serpentine geometry achieved particle separation efficiencies exceeding 95% and throughput greater than 99%. A novel scaling framework was developed to predict the minimum number of channel loops required for efficient sorting. Additionally, the robustness of the proposed scaling framework is demonstrated by its consistency with findings from previous studies, which exhibit the same trend as predicted by the scaling laws, underscoring the universality and reliability of the model. Additionally, the study revealed the significant influence of density ratio (α) on sorting efficiency, where higher α values enhanced separation through amplified hydrodynamic forces. Optimal flow rates tailored to particle sizes were identified, enabling the formation of focused particle streaks for precise sorting. However, efficiency declined beyond these thresholds due to particle entrapment in micro-vortices or boundary layers. This work provides valuable insights and design principles for developing compact, cost-effective microfluidic systems, with broad applications in biomedical fields like cell sorting and pathogen detection, as well as industrial processes requiring precise particle handling.

Bioaerosols produced within the respiratory system play an important role in respiratory disease transmission. These include infectious diseases such as common cold, influenza, tuberculosis, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) among several others. It is, therefore, of immense interest to understand how bioaerosols are produced within the respiratory system. This has not been extensively investigated. The present study computationally investigates how bioaerosols are produced in a model respiratory tract due to hydrodynamic interactions between breathed air and a thin mucus layer, which lines the inner surface of the tract. It is observed that Kelvin–Helmholtz instability is established in the thin mucus layer due to associated fluid dynamics. This induces interfacial surface waves which fragment forming bioaerosols under certain conditions. A regime map is created—based on pertinent dimensionless parameters—to enable identification of such conditions. Analysis indicates that bioaerosols may be produced even under normal breathing conditions, contrary to expectations, depending on mucus rheology and thickness of the mucus layer. This is possible during medical conditions as well as during some treatment protocols. However, such bioaerosols are observed to be larger (∼O(100)μm) and are produced in less numbers (∼100), as compared to those produced under coughing conditions. Treatment protocols and therapeutic strategies may be suitably devised based on these findings.