Over the past several decades, multiple methods have been developed to relate fluid dynamic forces on submerged bodies to the surrounding volumetric flow fields. These approaches ranging from force partitioning methods using divergence-free filters based on potential flow, to reciprocal-theorem-based techniques connecting actual flows to auxiliary viscous potential fields, to impulse and vorticity-moment methods grounded in global momentum conservation offer different perspectives for identifying links between flow features and hydrodynamic forces. In this work, we present a unifying mechanistic framework that integrates these seemingly disparate approaches under a single methodological umbrella, enabling consistent interpretation and comparison of their predictions. The framework is validated and demonstrated across canonical vortex-dominated flows, including two-dimensional and oscillating cylinders, oscillating spheres, prolate spheroids, and carangiform swimmers, highlighting its versatility and diagnostic power for analyzing complex hydrodynamic interactions.

Compared to the canonical problem of the turbulent boundary layer over a flat surface, the flow interaction with a wavy surface presents additional complexities, such as modified patterns of flow separation and reattachment, which enhance turbulence intensity and mixing. By inducing optimal interactions between the flow and the wavy surface, it is possible to enhance the efficiency and performance of aerospace systems and improve mixing in various engineering and environmental applications. Notable examples of wavy surfaces include Rayleigh waves, such as those found in dolphin skin and water waves. Research on dolphin skin suggests that elastic waves can be leveraged to reduce drag using either passive or active flow control techniques, and wind-wave interaction is a key process in shaping environmental flow. Numerous experimental and simulation studies have been conducted on wind-water interfaces, where the tangential motion of surface particles follows the direction of wave propagation. However, the same level of understanding is not available for Rayleigh waves, in which the tangential motion of surface particles follows retrograde motion, contrary to gravity waves. This study explores such a problem using a direct numerical simulation (DNS) of turbulent Couette flows over wavy Rayleigh surfaces with a wave age of 7.55 and material properties. We analyze the turbulence flow characteristics in proximity to compliant surfaces to identify unique near-surface flow patterns near surface elastic waves compared to those observed in water waves. These insights can potentially inform the future design of surface actuators and contribute to the development of non-local techniques for flow control.

Our sense of smell enables us to navigate a vast space of chemically diverse odour molecules. This task is accomplished by the combinatorial activation of approximately 400 odorant G protein-coupled receptors encoded in the human genome. How odorants are recognized by odorant receptors remains unclear. Here we provide mechanistic insight into how an odorant binds to a human odorant receptor. Using cryo-electron microscopy, we determined the structure of the active human odorant receptor OR51E2 bound to the fatty acid propionate. Propionate is bound within an occluded pocket in OR51E2 and makes specific contacts critical to receptor activation. Mutation of the odorant-binding pocket in OR51E2 alters the recognition spectrum for fatty acids of varying chain length, suggesting that odorant selectivity is controlled by tight packing interactions between an odorant and an odorant receptor. Molecular dynamics simulations demonstrate that propionate-induced conformational changes in extracellular loop 3 activate OR51E2. Together, our studies provide a high-resolution view of chemical recognition of an odorant by a vertebrate odorant receptor, providing insight into how this large family of G protein-coupled receptors enables our olfactory sense.

Droplet and drop penetration through a woven fabric surface highly relies on the surface’s geometrical and wetting properties. In addition, the inertia of the incident drop can substantially change the drop penetration dynamics by causing the breakup of a large drop and the transmission of many smaller droplets. This mechanism is present in cloth face masks and could affect their outward protection effectiveness during routine coughing, sneezing, or speaking. A numerical model is employed to study drops’ impact on the simplest one-layer woven fabric wherein adaptive mesh refinement (AMR) and the moment-of-fluid method are used to capture the complex interface separating the drop from the surrounding gas and woven fabric. The roles of pore size, hydrophobicity of the materials and impact momentum of the drop are investigated. The results are further used to find a “drop-fabric” relation based on the Weber number for different fabric-woven structures to describe transmitted droplets’ size and velocity distributions. An immediate application of the presented research is the quantification of the fabric mesh weave’s role in preventing the spread of respiratory diseases such as COVID-19.

This research aims to investigate the causal flow dynamics associated with the metachronal swimming mode used by krill, along with its correlation to the force generation exhibited by these fascinating creatures. Krill, which possess five legs distributed along their body, propel themselves by coordinating the movement of their legs and body. Our study seeks to comprehend the synchronized paddling motion of these legs and its role in generating two primary types of hydrodynamic forces: kinematic forces resulting from the inertia of the flow and vortex-induced forces originating from vorticity produced by the legs. We will closely examine how the specific kinematic parameters of metachronal swimming influence the contribution of these two forces. Additionally, we will show the impact of the coordinated opening and closure of the interior legs during metachronal swimming in enhancing wake dynamics and better hydrodynamic force generation. Employing a combined immersed body method-boundary element method approach for simulations and flow analysis, the study uses a reciprocal theorem to unify various force partitioning methods and demonstrate its effectiveness in analyzing force contributions..

Fillets on leading edges (LE) of turbine blades alter flow patterns and change the loss profile. A bidirectional flow impulse turbine utilized for harnessing wave energy is introduced and computational fluid dynamics (CFD) was used to perform various analysis. In the present work, fillets of different radii on the leading and trailing edges of both the rotor blade (RB) and guide vane (GV) are modified to study the change in overall performance. After an appropriate gird convergence study, ANSYS-CFX 16.0 solver is used for solving the Reynolds averaged Navier-Stokes (RANS) equations incorporating the k-ω-SST turbulence closure model. The numerical investigations were performed using the high-resolution scheme with the convergence criteria of 10−6 to produce unwavering results. The results show that the boundary layer near the endwall creates flow blockage and losses. Also, the increase in pressure drop due to the thickening of the boundary layers (BLs) across the blade/vane leads to a depletion in the overall performance of the turbine. The rotor and guide vane filleted turbine experience higher losses than the base model due to the radial pressure gradient that is explained with post-processed figures. The concept of fillet shapes has been applied to gas turbines and which improves the performance of the turbine due to a reduction in the secondary flow losses occurring inside the turbine and the same concept has been applied to wave energy air turbine to check its performance based on the losses present across the turbine passage.

Oscillating water columns (OWC) are widely used devices for the extraction of wave energy through self -rectifying impulse air turbines. To improve the performance of any turbo-machinery, guide vanes (GV) play an essential role in deciding turbine characteristics in terms of efficiency and torque. The concept of filleting is used in the GVs of bidirectional impulse turbine (BDI) with five different types of GV fillets for different radii, and the performance was analyzed. The numerical simulation was done using the commercial code ANSYS CFX 16.2, which solves the three-dimensional Reynolds-Averaged Navier-Stokes equation by finite volume explicit Runge-Kutta scheme with the k-ω SST closure model. There is a close agreement between the experimental and the numerical model. The detailed flow physics of filleted GVs have been included in the present work, and it was found that the efficiency increases at higher flow coefficients.