Flow Measurements Research Articles

Assessment of 4D flow MRI for quantification of left-to-right shunt in pediatric patients with ventricular septal defect: comparison with right heart catheterization

ObjectivesThe percentage of shunt fraction significantly impacts the management of patients with congenital shunts, influencing strategic choices such as surgical or interventional procedures. This study compared the estimated shunt fraction (the ratio of pulmonary-to-systemic flow, Qp/Qs) for quantifying the left-to-right shunt in children with ventricular septal defect (VSD) using heart catheterization, four-dimensional (4D) flow, and two-dimensional (2D) flow magnetic resonance imaging (MRI). The goal was to establish a non-invasive and reliable measurement ratio between pulmonary and systemic blood flow in these patients.MethodsBetween July 2022 and June 2023, patients scheduled to undergo invasive right heart catheterization were included in this study. MRI was performed one hour before the catheterization procedure. The correlation of shunt fraction was assessed between all methods after calculating the Qp/Qs ratio from 2D and 4D flow MRI and catheterization.ResultsA total of 24 patients (aged 3–15 years, eight females) were ultimately included in the study. The Qp/Qs ratios obtained from 4D flow had a robust correlation (correlation coefficient r = 0.962) compared to those obtained during catheterization. Cardiac catheterization recorded the mean shunt fraction at 1.499 ± 0.396, while 4D flow measured it at 1.403 ± 0.344, with no significant difference between the two techniques. Moreover, there was a reasonable correlation (r = 0.894) between 2D flow measurements of Qp/Qs and the results obtained from catheterization, with a mean shunt fraction of 1.326 ± 0.283.Conclusion4D flow MRI has the potential to be a non-invasive method for accurately measuring the left-to-right shunt in children with VSD.

Bayesian Reconstruction of 3D Particle Positions in High-Seeding Density Flows

Abstract Measuring particles' three-dimensional (3D) positions using multi-camera images in fluid dynamics is critical for resolving spatiotemporally complex flows like turbulence and mixing. However, current methods are prone to errors due to camera noise, optical configuration and experimental setup limitations, and high seeding density, which compound to create fake measurements (ghost particles) and add noise and error to velocity estimations. We introduce a Bayesian Volumetric Reconstruction (BVR) method, addressing these challenges by using probability theory to estimate uncertainties in particle position predictions. Our method assumes a uniform distribution of particles within the reconstruction volume and employs a model mapping particle positions to observed camera images. We utilize variational inference with a modified loss function to determine the posterior distribution over particle positions. Key features include a penalty term to reduce ghost particles, provision of uncertainty bounds, and scalability through subsampling. In tests with synthetic data and four cameras, BVR achieved 95% accuracy with less than 3% ghost particles and an RMS error under 0.3 pixels at a density of 0.1 particles per pixel (ppp). This shows 57% to 97% less ghost particles and 1.3 to 2 times lower RMS error than standard MART and IPR reconstructions. In an experimental Poiseuille flow measurement, our method closely matched the theoretical solution. Additionally, in a complex cerebral aneurysm basilar tip geometry flow experiment, our reconstructions were dense and consistent with observed flow patterns. Our BVR method effectively reconstructs particle positions in complex 3D flows, particularly in situations with high particle image densities and camera distortions. It distinguishes itself by providing quantifiable uncertainty estimates and scaling efficiently for larger image dimensions, making it applicable across a range of fluid flow scenarios.

Adaptation of stomatal conductance, photosynthesis and water-use efficiency at shoot and canopy scales in adjacent stands of Dacrycarpus dacrydioides and Podocarpus totara.

We tested an approach to estimate daily canopy net photosynthesis, A, based on estimates of transpiration, E, using measurements of sap flow and water-use efficiency, ω, by measuring δ13C in CO2 respired from shoots in the canopies of two conifers (Podocarpaceae) native to New Zealand. The trees were planted in adjacent 20-year-old stands with the same soil and environmental conditions. Leaf area index was lower for Dacrycarpus dacrydioides (1.34m2m-2) than for Podocarpus totara (2.01m2m-2) but mean (± standard error) stem diameters were the same at 152±21mm for D. dacrydioides and 154±25mm for P. totara. Over a 28-day period, daily A (per unit ground area) ranged almost five-fold but there were no significant differences between species (mean 2.73±1.02 gC m-2 d-1). This was attributable to higher daily values of E (2.63±0.83mm d-1) and lower ω (1.35±0.53 gC kg H2O-1) for D. dacrydioides compared with lower E (1.82±0.72mm d-1) and higher ω (1.90±0.77 gC kg H2O-1) for P. totara. We attributed this to higher nitrogen availability and nitrogen concentration per unit foliage area, Na, and greater exposure to irradiance in the D. dacrydioides canopy compared with P. totara. Our findings support earlier observations that D. dacrydioides is more adapted to sites with poor drainage. In contrast, the high retention of leaf area and maintaining low rates of transpiration by P. totara, resulting in higher water-use efficiency, is an adaptive response to survival in dry conditions. Our findings show that physiological adjustments for two species adapted to different environments led to similar canopy photosynthesis rates when the trees were grown in the same conditions. We demonstrated consistency between whole-tree and more intensive shoot-scale measurements, confirming that integrated approaches are appropriate for comparative estimates of carbon uptake in stands with different species.

Adaptive Clutter Filtering for Speckle Decorrelation-Based Blood Flow Measurements

Adaptive Clutter Filtering for Speckle Decorrelation-Based Blood Flow Measurements

Using Lorentz force flowmeter to measure the narrow channel flow that mimics lead-bismuth cooled reactors

ABSTRACT LFF (Lorentz Force Flowmeter) as a new non-contact electromagnetic flowmeter, can adapt to high temperature, strong corrosion, and other factors, which is suitable for measuring the flow of lead-bismuth eutectic (LBE) commonly used in the nuclear industry. This article designs a narrow channel with fuel rod gap characteristics and conducts simulation measurement experiments on the laboratory GaInSn loop using the Halbach-type LFF. The experimental results indicate that the accuracy of the Halbach-type LFF in measuring the flow rate of this specially shaped narrow channel can meet industrial requirement, and it is more flexible compared to Faraday flowmeter. This paper explores the way forward for real-time, on-line, accurate measurement of narrow flow in LBE cooled reactors in the nuclear industry by LFF.

Collateral flow and pulsatility during large vessel occlusions: insights from a quantitative in vitro study

Acute ischemic stroke caused by large vessel occlusions is being increasingly treated with neurovascular interventions. The hemodynamics within the collateral system of the circle of Willis (CoW) hemodynamics play a fundamental role in therapy success. However, transient in vivo data on pathological collateral flow during large vessel occlusions are not available. Moreover, there are no flow models that accurately simulate the hemodynamic conditions in the CoW during large vessel occlusions. We used a circulatory loop to generate highly reproducible cerebrovascular-like flows and pressures and used non-invasive flow visualization and high-resolution flow and pressure measurements to acquire detailed, time-dependent hemodynamics inside an anatomical phantom of the CoW. After calibrating a physiological reference case, we induced occlusions in the 1. middle cerebral artery, 2. terminal carotid artery, and 3. basilar artery; and measured the left posterior communicating artery flow. Mean arterial pressure and pulse pressure remained unchanged in the different occlusion cases compared to the physiological reference case, while total cerebral flow decreased by up to 19%. In all three occlusion cases, reversed flow was found in the left posterior communicating artery compared to the reference case with different flow magnitudes and pulsatility index values. The experimental results were compared with clinical findings, demonstrating the capability of this realistic cerebrovascular flow setup. This novel cerebrovascular flow setup opens the possibility for investigating different topics of neurovascular interventions under various clinical conditions in controlled preclinical laboratory studies.

Unveiling Turbulent Flow Dynamics in Blind-Tee Pipelines: Enhancing Fluid Mixing in Subsea Pipeline Systems

Blind tees, as important junctions, are widely used in offshore oil and gas transportation systems to improve mixing flow conditions and measurement accuracies in curved pipes. Despite the significance of blind tees, their unsteady flow characteristics and mixing mechanisms in turbulent flow regimes are not clearly established. Therefore, in this study, Unsteady Reynolds-Averaged Navier–Stokes (URANS) simulations, coupled with Explicit Algebraic Reynolds Stress Model (EARSM), are employed to explore the complex turbulent flow characteristics within blind-tee pipes. Firstly, the statistical flow features are investigated based on the time-averaged results, and the swirl dissipation analysis reveals an intense dissipative process occurring within blind tees, surpassing conventional elbows in swirling intensity. Then, the instantaneous flow characteristics are investigated through time and frequency domain analysis, uncovering the oscillatory patterns and elucidating the mechanisms behind unsteady secondary flow motions. In a 2D-length blind tee, a nondimensional dominant frequency of oscillation (Stbt = 0.0361) is identified, highlighting the significant correlation between dominant frequencies inside and downstream of the plugged section, which emphasizes the critical role of the plugged structure in these unsteady motions. Finally, a power spectra analysis is conducted to explore the influence of blind-tee structures, indicating that the blind-tee length of lbt = 2D enhances the flow-mixing conditions by amplifying the oscillation intensities of secondary flow motions.

Wavelet Cross-Correlation Signal Processing for Two-Phase Flow Control System in Oil Well Production

An algorithm based on continuous measurement of multiphase flows of oil well production has been designed to improve the efficiency of the technical control of oil production processes in the field. Separation-free, non-contact measurement of multiphase flows of oil well products allows increasing the efficiency of managing oil production processes in the field. Monitoring the current density using radioisotope measuring transducers (RMTs) allows obtaining information about the structure of the flow in the form of the distribution of gas inclusions and the speed of movement of liquid and gas in a two-phase flow. Fluid velocity measurement is based on digital processing of RMT signals, applying a continuous or discrete undecimated wavelet transform to them, and assessing the cross-correlation of wavelet coefficients in individual subspaces of the wavelet decomposition. The cross-correlation coefficients of two RMT signals located at a base distance, calculated in the subspaces of the wavelet decomposition, characterize the speed of movement of gas bubbles of different sizes in a vertical pipe. The measurement assumes that the velocity of the liquid phase of the oil flow in a vertical pipe mainly corresponds to the velocity of small bubbles. This speed should be determined by the maximum cross-correlation of wavelet coefficients in the corresponding decomposition subspace. Computer modeling made it possible to evaluate the characteristics of the algorithm for controlling the speed of liquid movement in the gas–liquid flow of oil well products and determine the mass flow rate of the liquid and the relative value of the gas content. The implementation of the algorithm in a multi-channel version of the device allows monitoring an entire cluster of wells in the field.

Assessing Coriolis meter performance in multicomponent carbon dioxide-rich mixtures

Accurate flow measurement plays a pivotal role in monitoring CO2 flows across the CCS value chain. This not only bolsters the overall business model of the CCS industry, but also ensures adherence to environmental legislations and regulatory requirements. Unlike other industrial process fluids, such as water, oil & natural gas, it is unclear whether current commercially available metering technologies can meet the requisite accuracy levels, specifically the ±2.5 % recommended within the EU/UK European Trading Scheme for CO2 mass transfer. Accordingly, the aim of this work was to gain a comprehensive understanding of CO2 flow measurement within the context of CCS transport conditions. Firstly, GERG-2008 equation of state was implemented on REFPROP v10 to predict the optimal transport conditions for CO2-rich mixtures and to understand the influence of non-condensable gas impurities in CCS flow operations. Then, a dedicated laboratory-scale gravimetric flow facility was designed and used to evaluate the performance of a Coriolis flow meter under gas, liquid, and supercritical flow conditions. The results indicate that the impurities have a relatively minor impact on the measurement performance of the meter, with maximum mean absolute measurement errors of 0.25 %, 0.12 %, and 0.28 % observed in gas, liquid, and supercritical CO2 flow conditions, respectively. The findings support the use of Coriolis metering technology as a reliable option for CCS metering, underscoring its suitability for accurate measurements in single-phase CO2 transport applications.

Flow measurement in microfluidic chips through optical trapping and deep learning

Flow measurement in microfluidic chips through optical trapping and deep learning

Dissecting the vascular-cognitive nexus: energetic vs. conventional hemodynamic parameters.

Blood pressure or flow measurements have been associated withvascular health and cognitive function. We proposed that energetic hemodynamic parameters may provide a more nuanced understanding and stronger correlation with cognitive function, in comparisons with conventional aortic and carotid pressure and flow parameters. The study comprised 1858 participants, in whom we assessed cognitive function via MoCA method, and measured central aortic and carotid pressure and flow waveforms. In addition to various pressure and flow parameters, we calculated energetic hemodynamic parameters through integration of pressure multiplying flow with respect to time. Energetic hemodynamic parameters, particularly aortic and carotid mean and pulsatile energy and pulsatility index (PI), were significantly associated with MoCA score more than any aortic and carotid pressure and flow parameters, after adjusting for age, sex, education, depression score, heart rate, BMI, HDL-cholesterol, and glucose levels. MoCA exhibited a strong positive relationship with carotid mean energy (standardized beta = 0.053, P = 0.0253) and a negative relationship with carotid energy PI (standardized beta = -0.093, P = 0.0002), exceeding the association with all traditional pressure- or flow-based parameters. Aortic pressure reflection coefficient at the aorto-carotid junction was positively correlated with mean carotid energy and negatively correlated with PI. Aortic characteristic impedance positively correlated with carotid energy PI but not mean energy. Our research indicates that energetic hemodynamic parameters, particularly carotid mean energy and carotid energy PI, have a stronger association with MoCA scores than traditional pressure- or flow-based metrics. This correlation with cognitive function is notably influenced by the properties of the aorto-carotid interface.

Dissecting the vascular-cognitive nexus: energetic vs. conventional hemodynamic parameters.

Blood pressure or flow measurements have been associated withvascular health and cognitive function. We proposed that energetic hemodynamic parameters may provide a more nuanced understanding and stronger correlation with cognitive function, in comparisons with conventional aortic and carotid pressure and flow parameters. The study comprised 1858 participants, in whom we assessed cognitive function via MoCA method, and measured central aortic and carotid pressure and flow waveforms. In addition to various pressure and flow parameters, we calculated energetic hemodynamic parameters through integration of pressure multiplying flow with respect to time. Energetic hemodynamic parameters, particularly aortic and carotid mean and pulsatile energy and pulsatility index (PI), were significantly associated with MoCA score more than any aortic and carotid pressure and flow parameters, after adjusting for age, sex, education, depression score, heart rate, BMI, HDL-cholesterol, and glucose levels. MoCA exhibited a strong positive relationship with carotid mean energy (standardized beta = 0.053, P = 0.0253) and a negative relationship with carotid energy PI (standardized beta = -0.093, P = 0.0002), exceeding the association with all traditional pressure- or flow-based parameters. Aortic pressure reflection coefficient at the aorto-carotid junction was positively correlated with mean carotid energy and negatively correlated with PI. Aortic characteristic impedance positively correlated with carotid energy PI but not mean energy. Our research indicates that energetic hemodynamic parameters, particularly carotid mean energy and carotid energy PI, have a stronger association with MoCA scores than traditional pressure- or flow-based metrics. This correlation with cognitive function is notably influenced by the properties of the aorto-carotid interface.

Analysis of the Flow Structure inside an Oscillating Sessile Drops in a Shear Flow Using Double-Helix 3D Particle Tracking Velocimetry and Adaptive Optics

The motion and particularly the detachment mechanism of sessile drops in an air-shear-flow is highly relevant for many technical applications. For instance, water drops in fuel cells can block the oxygen transport and thus lower the overall efficiency. Hence, a deeper understanding of the drop detachment mechanism could facilitate efficiency optimisations. Nonetheless, until now only simplified models exist for predicting the critical velocity that do not take into account the mutual interaction of the air and the liquid via the non-rigid interface. One reason for this is the lack of knowledge of the flow inside the oscillating drop. In this contribution, we present the first three-dimensional flow measurements in oscillating sessile drops in shear flow. Time-averaged flow measurements were conducted for different Reynolds numbers. Furthermore, the phase-averaged flow field was measured. The measurements were conducted with a novel 3D-PTV method, which offers scanless three-dimensional flow measurements with a single optical access for a measurement volume that covers about 90 % of the drop volume. Moreover, we present a novel technique for conducting flow measurements through fluctuating gas-liquid interfaces based on adaptive optics. We demonstrate that this technique enables the correction of a systematic error corresponding to the magnitude of the first drop eigenfrequency, which seems to play an important role in the detachment mechanism of drops. The results give new insights about the fluid mechanics of sessile drops and thus may help in the optimisation of drop removal in e. g. fuel cells.

Assessing The Potential Of PIV Data To Resolve Hidden Frequency Scales

The present work investigates the performance of an advection-based flow reconstruction model to increase the temporal resolution of PIV measurements recorded in a turbulent, planar jet. Using a semi-Lagrangian technique in combination with Rapid Distortion Theory, a modified trajectory tracking procedure is implemented. The method introduces a specification for a two-dimensional convective velocity based on the least squares minimization of the linearized advection equation, in contrast to the previously introduced one-dimensional mean velocity profile outlined in Vocke et al. (2023). The new implementation is based on local flow measurements, making it well-suited towards streamwise heterogeneity and spatially developing flows. With this, the flow at some unknown time can be estimated from the know flow measurements at the forward and backward time. Spectral analysis illustrates the model's proficiency in recovering spatiotemporal information far exceeding the Nyquist frequency, with spectral reconstruction errors of less than 5% for the most extreme case. It is demonstrated that the spectral content can be estimated at least two orders of magnitude beyond the sampling frequency of the original recording. Improved performance compared to alternative methods is demonstrated with only minor impact on computational time. This indicates the approach may be used as a tool for experimental researchers a) having no access to a high-speed PIV or b) with high-speed PIV to increase the spectral resolution even further.

Artificial Intelligence Techniques for the Hydrodynamic Characterization of Two-Phase Liquid–Gas Flows: An Overview and Bibliometric Analysis

Accurately and instantly estimating the hydrodynamic characteristics in two-phase liquid–gas flow is crucial for industries like oil, gas, and other multiphase flow sectors to reduce costs and emissions, boost efficiency, and enhance operational safety. This type of flow involves constant slippage between gas and liquid phases caused by a deformable interface, resulting in changes in gas volumetric fraction and the creation of structures known as flow patterns. Empirical and numerical methods used for prediction often result in significant inaccuracies during scale-up processes. Different methodologies based on artificial intelligence (AI) are currently being applied to predict hydrodynamic characteristics in two-phase liquid–gas flow, which was corroborated with the bibliometric analysis where AI techniques were found to have been applied in flow pattern recognition, volumetric fraction determination for each fluid, and pressure gradient estimation. The results revealed that a total of 178 keywords in 70 articles, 29 of which reached the threshold (machine learning, flow pattern, two-phase flow, artificial intelligence, and neural networks as the high predominance), were published mainly in Flow Measurement and Instrumentation. This journal has the highest number of published articles related to the studied topic, with nine articles. The most relevant author is Efteknari-Zadeh, E, from the Institute of Optics and Quantum Electronics.

Spatiotemporal Filter Velocimetry With Arbitrary-Shaped Measurement Region For Accurate Measurement In The Vicinity Of A Boundary

Viscous stress at a boundary or an interface is a source of drag acting on a body or a fluid particle and therefore its measurement is of great importance for understanding the motion of the body or the fluid particle. In this study, spatiotemporal filter velocimetry (SFV: Hosokawa & Tomiyama, 2012) is extended to arbitrary quadrilateral measurement areas fitted to an interface shape for accurate measurement of flow about a deformed drop, and it is applied to flows about single drops of glycerol-water solution falling in stagnant silicon oil under clean and contaminated conditions. Figure 1 shows the trajectories of tracer particles and the measured velocity distributions. No separation is observed for the spherical and ellipsoidal drops. On the other hand, the stagnant region is observed in the dimple region of the tail of the cap drop. These results clearly indicate that the flow about the deformed drop is successfully measured by SFV with arbitrary quadrilateral measurement areas. Figure 2 shows the trajectories of tracer particles and the measured velocity distributions of single ellipsoidal drops in clean and contaminated systems. Triton X-100 was used as the surfactant and its concentration C in the drop ranges from 0.0 to 0.1 mol/m3 . The drop tail becomes flat and then slightly dimpled shape, and the internal circulation becomes weak as C increases. The internal circulation remains even at the high surfactant concentration condition under which the internal circulation in single spherical drop is fully damped (Hosokawa et al., 2017). We also evaluate interfacial velocity, interfacial shear stresses, the Marangoni stress and surfactant concentration at the interface from measured velocity distributions in the vicinity of the interface. As a result, we confirmed that SFV enables us to measure velocity distribution about a single deformed drop and enables us to evaluate interfacial velocity, interfacial shear stresses, the Marangoni stress and surfactant concentration at the interface.

Three-Dimensional Measurements Of Deformable Oil Droplets In Turbulence

This work introduces an experimental facility designed to generate turbulence with a high energy dissipation rate of up to 0.3 m^2/s^3 , sufficient to induce deformation and fragmentation of oil droplets. The turbulence is produced by opposing arrays consisting of 24 jet streams in total, each with Reynolds numbers ranging from 12,000 to 50,000. Flow regimes are determined using 3D Particle Tracking Velocimetry (PTV) conducted in the center of the octagonal test section. The statistical analysis of the turbulence reveals a nearly homogeneous and isotropic nature. A 3D imaging system, equipped with six high-speed cameras, allows for the reconstruction of droplets using the multiple algebraic reconstruction technique algorithm, fostering both visualization and quantification of interface deformation. Additionally, the system enables the tracking of the breakup process. The presented setup is able to couple the measurements of the droplet shapes with surrounding turbulence in 3D dproplet topology reconstruction coupled with surrounding flow measurements. We demonstrate the capability of our imaging system and reconstruction methods for multiphase flow studies with an example of full 3D droplet topology reconstruction coupled with surrounding flow measurements.

Towards Time-Resolved Multi-Property Measurements By Single-Frequency FRS

The filtered Rayleigh scattering technique (FRS), extended by the method of frequency scanning, has historically been limited to time-averaged multi-property flow measurements. In our recently published work, we present a concept that potentially enables the combined measurement of time-resolved pressure, temperature and three-component (3C) velocity fields. It is based on the observation of the region of interest from six perspectives and a single excitation frequency. This work summarizes and expands on a follow-up publication that experimentally verifies this concept on an aspirated circular duct flow. For this purpose, the results obtained from single-frequency data processing are compared with reference pressures, temperatures and corresponding LDA velocity measurements. Overall, a very good agreement is found for all operating points with accuracies of 3.4% in pressure, 1.3% in temperature and ±2 m/s in axial velocity. Concerning precision, a newly developed multistage evaluation procedure enables values for pressure, temperature and velocity as low as 3 hPa, 2.2 K and 1.7 m/s. In a second flow configuration, an axial swirler is introduced into the duct. The resulting secondary flow structure and deformation of the axial velocity field caused by swirler geometry and support are very well captured with the single-frequency analysis. A closing discussion on the implementation challenges of a single-frequency multi-property FRS instrument with pulsed laser radiation reveals significant obstacles to overcome. Due the considerable optimization potential identified, chances are high that true time-resolved multi-property measurements by FRS will become a reality.

Feasibility Study For Large Scale Thermal Convective Flow Measurements In Building Physics

The Department of Building Physics / Energy-efficient Buildings at the Rheinland-Pfälzische Technische Universität Kaiserslautern-Landau is about to put a novel research-building into commission, the “Small House III”. Among other measurement equipment, a system for volumetric, large-scale, high-resolution flow velocity measurement should be utilized. In this paper, requirements for such a system are detailed, a suitable measurement system is proposed and a feasibility study for the verification of the system requirements is conducted. To this end, a tailored system for large-scale Lagrangian particle tracking (“Shake-the-Box”) is applied to thermal convective flow measurements above an electric radiator close to a wall. As a result, it is found that the designed volumetric velocity measurement system is capable of successfully operating in the design environment without minimal disturbance of the low-speed convection flow. . After a relatively short setup time (about 5 hours, including camera setup, calibration and self-calibration) up to 10000 images at 50 Hz (200 seconds) have been recorded continuously. Shake-the-Box results show a decline of the number of tracked particles from initially 48000 to about 8000 (with a half-life span of about 100 seconds for the helium filled soap bubbles used for seeding). Applying fine scale reconstruction (data assimilation), a vector spacing of 4 mm could be achieved for instantaneous volumetric velocity snapshots. Averaging resulted in a 2 mm vector spacing with an average of 3300 particles per bin and 410 particles per bin for 1 mm vector spacing (with 75% bin overlap). Weaker particles could only be detected in front of a black background. Using a white background (default background for later applications), weak particles could not be detected as well, so the number of detected particles and the measurement volume decreased slightly compared to the black background. Overall, the feasibility study successfully confirmed the readiness of the measurement system for the intended use for “Small House III” measurements.

LED-based PIV Of A Particle-Laden Turbulent Free-Surface

An experimental method is proposed to study dispersed two-phase flows at an airwater interface, a family of flows of practical significance in environmental and industrial settings. The applicability of this technique is demonstrated through the study of a lightly-deformed turbulent free-surface laden with floating particles (`floaters'). A low-mean turbulent flow is generated in a turbulence box actuated by a 10×10 synthetic jet array. Using LEDs and a single camera, free-surface flow measurements are carried out by Particle Image Velocimetry (PIV) simultaneously with Lagrangian tracking of the floaters, allowing the potential to characterise the coupling between the floater dynamics and the (sub)surface flow. Discrimination of the dispersed and continuous phases is carried out based on size. Individual floaters and clusters of floaters are successfully tracked throughout the field of view while they navigate through elongated and circular regions of high and low vorticity, characteristic features typically observed when a subsurface turbulent flow interacts with a free surface. Preliminary results of the floater-fluid interactions are presented to highlight the potential of this technique to better our understanding of floaterladen turbulent free surfaces.