Drag of suction cup tags on swimming animals: Modeling and measurement

Bio‐logging tags are widely used to study the behavior and movements of marine mammals with the tacit assumption of little impact to the animal. However, tags on fast‐swimming animals generate substantial hydrodynamic forces potentially affecting behavior and energetics adversely, or promoting early removal of the tag. In this work, hydrodynamic loading of three novel tag housing designs are compared over a range of swimming speeds using computational fluid dynamics (CFD). Results from CFD simulation were verified using tag models in a water flume with close agreement. Drag forces were reduced by minimizing geometric disruptions to the flow around the housing, while lift forces were reduced by minimizing the frontal cross‐sectional area of the housing and holding the tag close to the attachment surface. Hydrodynamic tag design resulted in an experimentally measured 60% drag force reduction in 5.6 m/s flow. For all housing designs, off‐axis flow increased the magnitude of the force on the tag. Experimental work with a common dolphin (Delphinus delphis) cadaver indicates that the suction cups used to attach the types of tags described here provide sufficient attachment force to resist failure to predicted forces at swimming speeds of up to 10 m/s.     

A computational fluid dynamics (CFD) based method for assessing the hydrodynamic impact of animal borne data loggers on host marine mammals

Animal‐borne data loggers (ABDLs) or “tags” are regularly used to elucidate animal ecology and physiology, but current literature highlights the need to assess associated deleterious impacts including increased resistive force to motion. Previous studies have used computational fluid dynamics (CFD) to estimate this impact, but many suffer limitations (e.g., inaccurate turbulence modeling, neglecting boundary layer transition, neglecting added mass effects, and analyzing the ABDL in isolation from the animal). A novel CFD‐based method is presented in which a “tag impact envelope” is defined utilizing simulations with and without transition modeling to define upper and lower drag limits, respectively, and added mass coefficients are found via simulations with sinusoidally varying inlet velocity, with modified Navier‐Stokes conservation of momentum equations enforcing a shift to the animal's noninertial reference frame. The method generates coefficients for calculating total resistive force for any velocity and acceleration combination, and is validated against theory for a prolate spheroid. An example case shows ABDL drag impact on a harp seal of 11.21%–16.24%, with negligible influence on added mass. By considering the effects of added mass and boundary layer transition, the approach presented is an enhancement to the CFD‐based ABDL impact assessment methods previously applied by researchers.     

Membrane-based actuation for high-speed single molecule force spectroscopy studies using AFM

Atomic force microscopy (AFM)-based dynamic force spectroscopy of single molecular interactions involves characterizing unbinding/unfolding force distributions over a range of pulling speeds. Owing to their size and stiffness, AFM cantilevers are adversely affected by hydrodynamic forces, especially at pulling speeds >10 μm/s, when the viscous drag becomes comparable to the unbinding/unfolding forces. To circumvent these adverse effects, we have fabricated polymer-based membranes capable of actuating commercial AFM cantilevers at speeds ≥100 μm/s with minimal viscous drag effects. We have used FLUENT^®, a computational fluid dynamics (CFD) software, to simulate high-speed pulling and fast actuation of AFM cantilevers and membranes in different experimental configurations. The simulation results support the experimental findings on a variety of commercial AFM cantilevers and predict significant reduction in drag forces when membrane actuators are used. Unbinding force experiments involving human antibodies using these membranes demonstrate that it is possible to achieve bond loading rates ≥10⁶ pN/s, an order of magnitude greater than that reported with commercial AFM cantilevers and systems.     

A non‐invasive dolphin telemetry tag: Computer design and numerical flow simulation

The impact of devices attached to animals remains a challenge in telemetry studies of dolphins. It was hypothesized that the hydrodynamic design of a tag could provide stable attachment to the dorsal fin by means of resultant hydrodynamic force appearing when a dolphin is swimming. To verify this hypothesis the computer fluid dynamics (CFD) study of tag performance was carried out. A virtual model presenting authentic geometry of a dolphin with tag attached to the dorsal fin was constructed. The same model without tag was used as a reference object to calculate tag impact as regards drag, lift, and moments coefficients. Flow around the models was simulated for the range of velocities as well as the ranges of pitch and yaw angles. It was shown that in 33 of 35 CFD scenarios the streamlined shape of a tag generates the lift force that facilitates keeping a tag attached to the fin. Throughout the set of calculations the tag‐associated drag coefficient does not exceed 4%, which indicates low impact. Data obtained present a baseline for the further development of non‐invasive dolphin telemetry tags.     

Unsteady Motion, Finite Reynolds Numbers, and Wall Effect on Vorticella convallaria Contribute Contraction Force Greater than the Stokes Drag

Contraction of Vorticella convallaria, a sessile ciliated protozoan, is completed within a few milliseconds and results in a retraction of its cell body toward the substratum by coiling its stalk. Previous studies have modeled the cell body as a sphere and assumed a drag force that satisfies Stokes' law. However, the contraction-induced flow of the medium is transient and bounded by the substrate, and the maximum Reynolds number is larger than unity. Thus, calculations of contractile force from the drag force are incomplete. In this study, we analyzed fluid flow during contraction by the particle tracking velocimetry and computational fluid dynamics simulations to estimate the contractile force. Particle paths show that the induced flow is limited by the substrate. Simulation-based force estimates suggest that the combined effect of the flow unsteadiness, the finite Reynolds number, and the substrate comprises 35% of the total force. The work done in the early stage of contraction and the maximum power output are similar regardless of the medium viscosity. These results suggest that, during the initial development of force, V. convallaria uses a common mechanism for performing mechanical work irrespective of viscous loading conditions.     

Estimating maximal force output of cetaceans using axial locomotor muscle morphology

Cetaceans span a large range of body sizes and include species with the largest known locomotor muscles. To date, force output and thrust production have only been directly measured in the common bottlenose dolphin (Tursiops truncatus), although thrust forces have been hydrodynamically modeled for some whales. In this study, two metrics of epaxial muscle size—cross‐sectional area (CSA) and mass—were used to estimate force output for 22 species (n = 83 specimens) ranging in size from bottlenose dolphins to blue whales (Balaenoptera musculus). Relative to total body length (TL), maximum force output estimated based upon both muscle CSA (TL^{1.56 ± 0.05}) and mass (TL^{2.64 ± 0.07}) scaled at rates lower than those predicted by geometric scaling, suggesting relative force output decreases with increasing body size in cetaceans. Estimated maximal force outputs were compared to both published drag forces and to the breaking strengths of commercial fishing lines known to entangle whales. The breaking strengths of these lines are within the same order of magnitude, and in some cases, exceed the estimated maximal force output of whales. These results suggest that while powerful animals, large whales may be unable to break the extremely strong fishing line used today.     

Cells in 3D matrices under interstitial flow: Effects of extracellular matrix alignment on cell shear stress and drag forces

Interstitial flow is an important regulator of various cell behaviors both in vitro and in vivo, yet the forces that fluid flow imposes on cells embedded in a 3D extracellular matrix (ECM), and the effects of matrix architecture on those forces, are not well understood. Here, we demonstrate how fiber alignment can affect the shear and pressure forces on the cell and ECM. Using computational fluid dynamics simulations, we show that while the solutions of the Brinkman equation accurately estimate the average fluid shear stress and the drag forces on a cell within a 3D fibrous medium, the distribution of shear stress on the cellular surface as well as the peak shear stresses remain intimately related to the pericellular fiber architecture and cannot be estimated using bulk-averaged properties. We demonstrate that perpendicular fiber alignment of the ECM yields lower shear stress and pressure forces on the cells and higher stresses on the ECM, leading to decreased permeability, while parallel fiber alignment leads to higher stresses on cells and increased permeability, as compared to a cubic lattice arrangement. The Spielman–Goren permeability relationships for fibrous media agreed well with CFD simulations of flow with explicitly considered fibers. These results suggest that the experimentally observed active remodeling of ECM fibers by fibroblasts under interstitial flow to a perpendicular alignment could serve to decrease the shear and drag forces on the cell.     

Validation tool for traction force microscopy

Traction force microscopy (TFM) is commonly used to estimate cells' traction forces from the deformation that they cause on their substrate. The accuracy of TFM highly depends on the computational methods used to measure the deformation of the substrate and estimate the forces, and also on the specifics of the experimental set-up. Computer simulations can be used to evaluate the effect of both the computational methods and the experimental set-up without the need to perform numerous experiments. Here, we present one such TFM simulator that addresses several limitations of the existing ones. As a proof of principle, we recreate a TFM experimental set-up, and apply a classic 2D TFM algorithm to recover the forces. In summary, our simulator provides a valuable tool to study the performance, refine experimentally, and guide the extraction of biological conclusions from TFM experiments.     

Morphologic and Aerodynamic Considerations Regarding the Plumed Seeds of Tragopogon pratensis and Their Implications for Seed Dispersal

Tragopogon pratensis is a small herbaceous plant that uses wind as the dispersal vector for its seeds. The seeds are attached to parachutes that increase the aerodynamic drag force and increase the total distance travelled. Our hypothesis is that evolution has carefully tuned the air permeability of the seeds to operate in the most convenient fluid dynamic regime. To achieve final permeability, the primary and secondary fibres of the pappus have evolved with complex weaving; this maximises the drag force (i.e., the drag coefficient), and the pappus operates in an “optimal” state. We used computational fluid dynamics (CFD) simulations to compute the seed drag coefficient and compare it with data obtained from drop experiments. The permeability of the parachute was estimated from microscope images. Our simulations reveal three flow regimes in which the parachute can operate according to its permeability. These flow regimes impact the stability of the parachute and its drag coefficient. From the permeability measurements and drop experiments, we show how the seeds operate very close to the optimal case. The porosity of the textile appears to be an appropriate solution to achieve a lightweight structure that allows a low terminal velocity, a stable flight and a very efficient parachute for the velocity at which it operates.     

Aerodynamic study of different cyclist positions: CFD analysis and full-scale wind-tunnel tests

Three different cyclist positions were evaluated with Computational Fluid Dynamics (CFD) and wind-tunnel experiments were used to provide reliable data to evaluate the accuracy of the CFD simulations. Specific features of this study are: (1) both steady Reynolds-averaged Navier–Stokes (RANS) and unsteady flow modelling, with more advanced turbulence modelling techniques (Large-Eddy Simulation – LES), were evaluated; (2) the boundary layer on the cyclist’s surface was resolved entirely with low-Reynolds number modelling, instead of modelling it with wall functions; (3) apart from drag measurements, also surface pressure measurements on the cyclist’s body were performed in the wind-tunnel experiment, which provided the basis for a more detailed evaluation of the predicted flow field by CFD. The results show that the simulated and measured drag areas differed about 11% (RANS) and 7% (LES), which is considered to be a close agreement in CFD studies. A fair agreement with wind-tunnel data was obtained for the predicted surface pressures, especially with LES. Despite the higher accuracy of LES, its much higher computational cost could make RANS more attractive for practical use in some situations. CFD is found to be a valuable tool to evaluate the drag of different cyclist positions and to investigate the influence of small adjustments in the cyclist’s position. A strong advantage of CFD is that detailed flow field information is obtained, which cannot easily be obtained from wind-tunnel tests. This detailed information allows more insight in the causes of the drag force and provides better guidance for position improvements.     

Striped dolphins and short‐beaked common dolphins in the Gulf of Corinth,Greece: Abundance estimates from dorsal fin photographs

Capture‐recapture methods relying on dorsal fin natural markings have never been applied successfully to striped dolphins, Stenella coeruleoalba, and were rarely used to assess abundance of short‐beaked common dolphins, Delphinus delphis. We used digital photo‐identification to obtain abundance estimates of striped and common dolphins living in mixed groups in the Gulf of Corinth, Greece. The proportion of either species was calculated based on the relative number of photographs of adult animals showing relevant portions of their body during conspicuous surfacings. Striped dolphins and common dolphins averaged 95.0% and 3.2% of all individuals, respectively. Animals showing intermediate pigmentation accounted for another 1.8%. Striped dolphin numbers were relatively high, with a point estimate of 835 animals (95% CI = 631–1,106). Common dolphins numbers were low (point estimate 28 animals; 95% CI = 11–73) and individuals were scattered within striped dolphin groups, indicating that this common dolphin population may be nonviable. Within a semiclosed Gulf exposed to considerable anthropogenic impact, the future of both dolphin species is of concern due to their suspected geographic isolation and restricted extent of occurrence. Information provided here can be used to inform timely conservation efforts.     

Nonkinetic modeling of the mechanical unfolding of multimodular proteins: theory and experiments

We introduce and discuss a novel approach called back-calculation for analyzing force spectroscopy experiments on multimodular proteins. The relationship between the histograms of the unfolding forces for different peaks, corresponding to a different number of not-yet-unfolded protein modules, is exploited in such a manner that the sole distribution of the forces for one unfolding peak can be used to predict the unfolding forces for other peaks. The scheme is based on a bootstrap prediction method and does not rely on any specific kinetic model for multimodular unfolding. It is tested and validated in both theoretical/computational contexts (based on stochastic simulations) and atomic force microscopy experiments on (GB1)₈ multimodular protein constructs. The prediction accuracy is so high that the predicted average unfolding forces corresponding to each peak for the GB1 construct are within only 5 pN of the averaged directly-measured values. Experimental data are also used to illustrate how the limitations of standard kinetic models can be aptly circumvented by the proposed approach.     

Influence of surface penetration on measured fluid force on a hand model

The purpose of this study was to quantify the effect of wave drag due to surface penetration on drag and lift forces (C_d and C_l) acting on a hand model. The values of C_d and C_l had been acquired to gain the hydrodynamic characteristics of the swimmer's hand and predict force on the swimmer's hand. These values have also been used to benchmark computational fluid dynamics analysis. Because the previous studies used a hand/forearm model which penetrated the water's surface, the values of C_d and C_l include the effect of the surface wave on the model. Wave formation causes pressure differences between the frontal and rear sides of a surface-penetrating model as a result of depressions and elevations in the water's surface. This may be considered as wave drag due to surface penetration. Fluid forces due to wave drag on the forearm should not be included in the measured C_d and C_l of a swimmer's hand that does not sweep near the water's surface. Two hand/forearm models are compared, one with the hand rigidly connected to the forearm. The other model was constructed to isolate the fluid forces acting on the hand from the influence of wave drag on the forearm. The measurements showed that the effect of wave drag on the hand model caused large increases in the values of C_d, up to 46–98% with lesser increases in C_l of 2–12% depending on the hand orientation. The present study provides an improved method to determine the values of C_d and C_l that eliminates the effect of wave drag on a hand/forearm model by isolating the measurement of fluid forces on the forearm of the hand/forearm model in order to separately acquire the forces on the hand.     

Force-based analysis of multidimensional energy landscapes: application of dynamic force spectroscopy and steered molecular dynamics simulations to an antibody fragment-peptide complex

Multidimensional energy landscapes are an intrinsic property of proteins and define their dynamic behavior as well as their response to external stimuli. In order to explore the energy landscape and its implications on the dynamic function of proteins dynamic force spectroscopy and steered molecular dynamics (SMD) simulations have proved to be important tools. In this study, these techniques have been employed to analyze the influence of the direction of the probing forces on the complex of an antibody fragment with its peptide antigen. Using an atomic force microscope, experiments were performed where the attachment points of the 12 amino acid long peptide antigen were varied. These measurements yielded clearly distinguishable basal dissociation rates and potential widths, proving that the direction of the applied force determines the unbinding pathway. Complementary atomistic SMD simulations were performed, which also show that the unbinding pathways of the system are dependent on the pulling direction. However, the main barrier to be crossed was independent of the pulling direction and is represented by a backbone hydrogen bond between Gly^H-H40 of the antibody fragment and Glu^Oε-6_peptide of the peptide. For each pulling direction, the observed barriers can be correlated with the rupture of specific interactions, which stabilize the bound complex. Furthermore, although the SMD simulations were performed at loading rates exceeding the experimental rates by orders of magnitude due to computational limitations, a detailed comparison of the barriers that were overcome in the SMD simulations with the data obtained from the atomic force microscope unbinding experiments show excellent agreement.     

Turbulence model choice for the calculation of drag forces when using the CFD method

The aim of this work is to specify which model of turbulence is the most adapted in order to predict the drag forces that a swimmer encounters during his movement in the fluid environment. For this, a Computational Fluid Dynamics (CFD) analysis has been undertaken with a commercial CFD code (Fluent^®). The problem was modelled as 3D and in steady hydrodynamic state. The 3D geometry of the swimmer was created by means of a complete laser scanning of the swimmer’s body contour. Two turbulence models were tested, namely the standard k–ε model with a specific treatment of the fluid flow area near the swimmer’s body contour, and the standard k–ω model. The comparison of numerical results with experimental measurements of drag forces shows that the standard k–ω model accurately predicts the drag forces while the standard k–ε model underestimates their values. The standard k–ω model also enabled to capture the vortex structures developing at the swimmer’s back and buttocks in underwater swimming; the same vortices had been visualized by flow visualization experiments carried out at the INSEP (National Institute for Sport and Physical Education in Paris) with the French national swimming team.     

Computational fluid dynamics simulation improves the design and characterization of a plug-flow-type scale-down reactor for microbial cultivation processes

The scale-up of bioprocesses remains one of the major obstacles in the biotechnology industry. Scale-down bioreactors have been identified as valuable tools to investigate the heterogeneities observed in large-scale tanks at the laboratory scale. Additionally, computational fluid dynamics (CFD) simulations can be used to gain information about fluid flow in tanks used for production. Here, we present the rational design and comprehensive characterization of a scale-down setup, in which a flexible and modular plug-flow reactor was connected to a stirred-tank bioreactor. With the help of CFD using the realizable k-ε model, the mixing time difference between a 20 and 4000 L bioreactor was evaluated and used as scale-down criterion. CFD simulations using a shear stress transport (SST) k-ω turbulence model were used to characterize the plug-flow reactor in more detail, and the model was verified using experiments. Additionally, the model was used to simulate conditions where experiments technically could not be performed due to sensor limitations. Nevertheless, verification is difficult in this case as well. This was the first time a scale-down setup was tested on high-cell-density Escherichia coli cultivations to produce industrially relevant antigen-binding fragments (Fab). Biomass yield was reduced by 11% and specific product yield was reduced by 20% during the scale-down cultivations. Additionally, the intracellular Fab fraction was increased by using the setup. The flexibility of the introduced scale-down setup in combination with CFD simulations makes it a valuable tool for investigating scale effects at the laboratory scale. More information about the large scale is still necessary to further refine the setup and to speed up bioprocess scale-up in the future.     

Computational fluid dynamics analysis of cyclist aerodynamics: Performance of different turbulence-modelling and boundary-layer modelling approaches

This study aims at assessing the accuracy of computational fluid dynamics (CFD) for applications in sports aerodynamics, for example for drag predictions of swimmers, cyclists or skiers, by evaluating the applied numerical modelling techniques by means of detailed validation experiments. In this study, a wind-tunnel experiment on a scale model of a cyclist (scale 1:2) is presented. Apart from three-component forces and moments, also high-resolution surface pressure measurements on the scale model’s surface, i.e. at 115 locations, are performed to provide detailed information on the flow field. These data are used to compare the performance of different turbulence-modelling techniques, such as steady Reynolds-averaged Navier–Stokes (RANS), with several k–ε and k–ω turbulence models, and unsteady large-eddy simulation (LES), and also boundary-layer modelling techniques, namely wall functions and low-Reynolds number modelling (LRNM). The commercial CFD code Fluent 6.3 is used for the simulations. The RANS shear-stress transport (SST) k–ω model shows the best overall performance, followed by the more computationally expensive LES. Furthermore, LRNM is clearly preferred over wall functions to model the boundary layer. This study showed that there are more accurate alternatives for evaluating flow around bluff bodies with CFD than the standard k–ε model combined with wall functions, which is often used in CFD studies in sports.     

CFD predicted pH gradients in lactic acid bacteria cultivations

The formation of pH gradients in a 700 L batch fermentation of Streptococcus thermophilus was studied using multi-position pH measurements and computational fluid dynamics (CFD) modeling. To this end, a dynamic, kinetic model of S. thermophilus and a pH correlation were integrated into a validated one-phase CFD model, and a dynamic CFD simulation was performed. First, the fluid dynamics of the CFD model were validated with NaOH tracer pulse mixing experiments. Mixing experiments and simulations were performed whereas multiple pH sensors, which were placed vertically at different locations in the bioreactor, captured the response. A mixing time of about 46 s to reach 95% homogeneity was measured and predicted at an impeller speed of 242 rpm. The CFD simulation of the S. thermophilus fermentation captured the experimentally observed pH gradients between a pH of 5.9 and 6.3, which occurred during the exponential growth phase. A pH higher than 7 was predicted in the vicinity of the base solution inlet. Biomass growth, lactic acid production, and substrate consumption matched the experimental observations. Moreover, the biokinetic results obtained from the CFD simulation were similar to a single-compartment simulation, for which a homogeneous distribution of the pH was assumed. This indicates no influence of pH gradients on growth in the studied bioreactor. This study verified that the pH gradients during a fermentation in the pilot-scale bioreactor could be accurately predicted using a coupled simulation of a biokinetic and a CFD model. To support the understanding and optimization of industrial-scale processes, future biokinetic CFD studies need to assess multiple types of environmental gradients, like pH, substrate, and dissolved oxygen, especially at industrial scale.     

Errors in power-law estimations of inflow rates for intracranial aneurysm CFD

Patient-specific inflow rates are rarely available for computational fluid dynamics (CFD) studies of intracranial aneurysms. Instead, inflow rates are often estimated from parent artery diameters via power laws, i.e. Q ∝ Dⁿ, reflecting adaptation of conduit arteries to demanded flow. The present study aimed to validate the accuracy of these power laws. Internal carotid artery (ICA) flow rates were measured from 25 ICA aneurysm patients via 2D phase contrast MRI. ICA diameters, derived from 3D segmentation of rotational angiograms, were used to estimate inflow rates via power laws from the aneurysm CFD literature assuming the same inlet wall shear stress (WSS) (n = 3), velocity (n = 2) or flow rate (n = 0) for all cases. To illustrate the potential impact of errors in flow rate estimates, pulsatile CFD was carried out for four cases having large errors for at least one power law. Flow rates estimated by n = 3 and n = 0 power laws had significant (p < 0.01) mean biases of −22% to +32%, respectively, but with individual errors ranging from −78% to +120%. The n = 2 power law had no significant bias, but had non-negligible individual errors of −58% to +71%. CFD showed similarly large errors for time-averaged sac WSS; however, these were reduced after normalizing by parent artery WSS. High frequency WSS fluctuations, evident in 2/4 aneurysms, were also sensitive to inflow rate errors. Care should therefore be exercised in the interpretation of aneurysm CFD studies that rely on power law estimates of inflow rates, especially if absolute (vs. normalized) WSS, or WSS instabilities, are of interest.     

A computationally efficient strategy to estimate muscle forces in a finite element musculoskeletal model of the lower limb

Concurrent multiscale simulation strategies are required in computational biomechanics to study the interdependence between body scales. However, detailed finite element models rarely include muscle recruitment due to the computational burden of both the finite element method and the optimization strategies widely used to estimate muscle forces. The aim of this study was twofold: first, to develop a computationally efficient muscle force prediction strategy based on proportional-integral-derivative (PID) controllers to track gait and chair rise experimental joint motion with a finite element musculoskeletal model of the lower limb, including a deformable knee representation with 12 degrees of freedom; and, second, to demonstrate that the inclusion of joint-level deformability affects muscle force estimation by using two different knee models and comparing muscle forces between the two solutions. The PID control strategy tracked experimental hip, knee, and ankle flexion/extension with root mean square errors below 1°, and estimated muscle, contact and ligament forces in good agreement with previous results and electromyography signals. Differences up to 11% and 20% in the vasti and biceps femoris forces, respectively, were observed between the two knee models, which might be attributed to a combination of differing joint contact geometry, ligament behavior, joint kinematics, and muscle moment arms. The tracking strategy developed in this study addressed the inevitable tradeoff between computational cost and model detail in musculoskeletal simulations and can be used with finite element musculoskeletal models to efficiently estimate the interdependence between muscle forces and tissue deformation.