arXiv subjects

Pavlos P. Vlachos

Publications and source records attributed to Pavlos P. Vlachos.

At least 19 recordsLinked to original sources

arXiv2026

Mixing Performance of Toroidal Ring Mixers: Effects of Flow Rate Ratios and Geometric Asymmetry

Microfluidic mixing is important for nanoparticle fabrication, where rapid contact between the solvent and nonsolvent streams is needed to control the formation process. Various micromixer geometries have been developed and analyzed to improve mixing efficiency. However, for toroidal micromixers, the role of flow rate ratio and geometric asymmetry has not been examined in detail. In this study, the mixing process of two toroidal micromixer designs is investigated, namely symmetric and asymmetric, with emphasis on the impact of flow rate ratio and geometric asymmetry during the mixing of miscible fluids. Numerical simulations are carried out to examine the mixing behavior of these toroidal micromixers for different flow rates and flow rate ratios. High-fidelity numerical simulations are performed using the stabilized finite element method. The concentration and velocity fields are used to examine how the chamber asymmetry can affect the mixing performance. Experiments are also conducted to provide a validation for the numerical results. We demonstrate that the asymmetric toroidal mixer design generally improves the mixing over the conventional design, especially at low to moderate total flow rates. The results obtained show that improved mixing can be achieved without changing the overall mixer size.

physics.flu-dyn↗

arXiv2026

Bayesian Aneurysm Growth Detection via Surface Displacement Modeling

Clinical decisions for unruptured intracranial aneurysms depend on detecting growth on follow-up magnetic resonance angiography (MRA). Growth is typically judged from manual 2D diameters on few slices, which vary across clinicians and frequently miss subtle 3D change. Even with 3D segmentations, apparent differences can reflect resolution, segmentation, surface processing, or registration mismatch rather than true growth; most criteria remain heuristic and binary. We show that a Bayesian displacement-based model using the surrounding vessel as an internal reference achieves strong discrimination of aneurysm growth (AUC 0.86-0.87) and improves agreement with expert labels (Cohen's kappa up to 0.66 vs. 0.35 for volumetric criteria), while providing calibrated posterior probabilities with uncertainty bounds. The method registers baseline and follow-up surfaces, computes normal-directed displacements, and summarizes change as the difference between mean aneurysm displacement and mean displacement on the surrounding non-aneurysmal vessel segment. The vessel segment serves as an internal control for imaging and processing variability, assuming negligible structural change over the surveillance interval. We evaluate two cohorts spanning time-of-flight and contrast-enhanced longitudinal MRA studies: a public dataset labeled from neuroradiologist-provided measurements and an institutional dataset labeled by senior and junior raters. Performance is preserved when training on lower-expertise labels, indicating robustness to label variability. Calibrated probabilities may aid clinical decision-making in borderline cases, where high uncertainty can motivate repeat imaging. This framework provides interpretable probabilistic growth assessment from longitudinal MRA, reduces dependence on clinician expertise, and supports cross-center surveillance across scanners and angiography sequences.

physics.med-ph↗

arXiv2026

VAST: Vascular Flow Analysis and Segmentation for Intracranial 4D Flow MRI

Four-dimensional (4D) Flow MRI can noninvasively measure cerebrovascular hemodynamics but remains underused clinically because current workflows rely on manual vessel segmentation and yield velocity fields sensitive to noise, artifacts, and phase aliasing. We present VAST (Vascular Flow Analysis and Segmentation), an automated, unsupervised pipeline for intracranial 4D Flow MRI that couples vessel segmentation with physics-informed velocity reconstruction. VAST derives vessel masks directly from complex 4D Flow data by iteratively fusing magnitude- and phase-based background statistics. It then reconstructs velocities via continuity-constrained phase unwrapping, outlier correction, and low-rank denoising to reduce noise and aliasing while promoting mass-consistent flow fields, with processing completing in minutes per case on a standard CPU. We validate VAST on synthetic data from an internal carotid artery aneurysm model across SNR = 2-20 and severe phase wrapping (up to five-fold), on in vitro Poiseuille flow, and on an in vivo internal carotid aneurysm dataset. In synthetic benchmarks, VAST maintains near quarter-voxel surface accuracy and reduces velocity root-mean-square error by up to fourfold under the most degraded conditions. In vitro, it segments the channel within approximately half a voxel of expert annotations and reduces velocity error by 39% (unwrapped) and 77% (aliased). In vivo, VAST closely matches expert time-of-flight masks and lowers divergence residuals by about 30%, indicating a more self-consistent intracranial flow field. By automating processing and enforcing basic flow physics, VAST helps move intracranial 4D Flow MRI toward routine quantitative use in cerebrovascular assessment.

eess.IV↗

arXiv2026

Effect of Electric Charge on Biotherapeutic Transport, Binding and Absorption: A Computational Study

This study explores the effects of electric charge on the dynamics of drug transport and absorption in subcutaneous injections of monoclonal antibodies (mAbs). We develop a novel mathematical and computational model, based on the Nernst-Planck equations and porous media flow theory, to investigate the complex interactions between mAbs and charged species in subcutaneous tissue. The model enables us to study short-term transport dynamics and long-term binding and absorption for two mAbs with different electric properties. We examine the influence of buffer pH, body mass index, injection depth, and formulation concentration on drug distribution and compare our numerical results with experimental data from the literature.

cs.CE↗

arXiv2021

Direct estimation of global longitudinal strain from echocardiograms using a logarithm-scaled Fourier magnitude correlation

We present a new method for measuring global longitudinal strain and global longitudinal strain rate from 2D echocardiograms using a logarithmic-transform correlation (LTC) method. In contrast to traditional echocardiography strain analysis, our approach does not require cardiac chamber segmentation and regularization. The algorithm was benchmarked against two conventional strain analysis methods using synthetic left ventricle ultrasound images. Measurement error was assessed as a function of contrast-to-noise ratio (CNR) using mean absolute error and root-mean-square error and showed better agreement to the ground truth for strain($R^2$ = 0.91) and strain rate($R^2$ = 0.85) as compared to conventional algorithms (strain($R^2$ = 0.7), strain rate($R^2$ = 0.7)). Also, our method was unaffected by CNR. A 200% increase in strain measurement accuracy was observed compared to the conventional algorithms. Subsequently, we tested the method using a 54-subject clinical cohort (20 subjects diseased with cardiomyopathy, 34 healthy controls). Our method distinguished between normal and abnormal left ventricular function with an AUC = 0.85, a 10% improvement over the conventional GLS algorithms.

physics.med-ph↗

arXiv2021

Shock generated vorticity in spark discharges

Spark discharges induce a complex flow field consisting of a shock wave at early times (~ 1 $μ$ s), a pair of vortex rings, and a hot gas kernel. The vortex rings entrain ambient gas into the hot gas kernel and control its cooling and expansion. In this work, we investigate the shock wave's contribution in producing the vortex ring vorticity. We analyze high-speed (700 kHz) schlieren images of the shock wave for a range of electrical energies to measure the shock properties and estimate shock velocity and curvature. These measurements are combined with a model to calculate the vorticity generated. The measurements show that the highest vorticity is generated near the peak shock curvature location, and the shock curvature and strength increase with electrical energy deposited. A comparison of the vorticity estimated from the model to vorticity measurements from stereoscopic particle image velocimetry shows the results to be statistically equivalent. This suggests that the shock curvature and velocity contribute to the vortex rings induced by spark discharges.

physics.flu-dyn↗

arXiv2020

Meta-Uncertainty for Particle Image Velocimetry

Uncertainty quantification for Particle Image Velocimetry (PIV) is critical for comparing flow fields with Computational Fluid Dynamics (CFD) results, and model design and validation. However, PIV features a complex measurement chain with coupled, non-linear error sources, and quantifying the uncertainty is challenging. Multiple assessments show that none of the current methods can reliably measure the actual uncertainty across a wide range of experiments. Because the current methods differ in assumptions regarding the measurement process and calculation procedures, it is not clear which method is best to use for an experiment. To address this issue, we propose a method to estimate an uncertainty method's sensitivity and reliability, termed the Meta-Uncertainty. The novel approach is automated, local, and instantaneous, and based on perturbation of the recorded particle images. We developed an image perturbation scheme based on adding random unmatched particles to the interrogation window pair considering the signal-to-noise (SNR) of the correlation plane. Each uncertainty scheme's response to several trials of random particle addition is used to estimate a reliability metric, defined as the rate of change of the inter-quartile range (IQR) of the uncertainties with increasing levels of particle addition. We also propose applying the meta-uncertainty as a weighting metric to combine uncertainty estimates from individual schemes, based on ideas from the consensus forecasting literature. We use PIV measurements across a range of canonical flows to assess the performance of the uncertainty schemes.The results show that the combined uncertainty method outperforms the individual methods, and establish the meta-uncertainty as a useful reliability assessment tool for PIV uncertainty quantification.

physics.flu-dyn↗

arXiv2020

Unsupervised Segmentation of B-Mode Echocardiograms

We present a method for unsupervised segmentation of echocardiograms (echo). The method uses an iterative Dijkstra's algorithm, a strategic node selection, and a novel cost matrix formulation based on intensity peak prominence and is thus termed the "Prominence Iterative Dijkstra's" algorithm, or ProID. Although the current analysis focuses on the left ventricle (LV), ProID is applicable to all four heart chambers. ProID was tested using artificial echo images representing five different systems. Results showed accurate LV contours and volume estimations as compared to the ground-truth for all systems. Subsequently, ProID was used to analyze a clinical cohort of 66 pediatric patients, including both normal and diseased hearts. Output segmentations, end-diastolic, end-systolic volumes, and ejection fraction (EF) were compared against manual segmentations from two expert readers. ProID maintained an average Dice similarity score of 0.93 when comparing against manual segmentation. Comparing the two expert readers, the manual segmentations maintained a score of 0.93, which increased to 0.95 when they used ProID. Thus, ProID successfully reduced the inter-operator variability across the two expert readers. Overall, this work demonstrates that ProID yields accurate boundaries across all age groups, disease states, and echo platforms with low computation cost, thereby establishing its clinical usefulness.

eess.IV↗

arXiv2020

Filamentary Surface Plasma Discharge Flow Length and Time Scales

Nanosecond Surface Dielectric Barrier Discharge (ns-SDBDs) are a class of plasma actuators that utilize a high-voltage pulse of nanosecond duration between two surface-mounted electrodes to create an electrical breakdown of air, along with rapid heating. These actuators usually produce multiple filaments when operated at high pulse frequencies, and the rapid heating leads to the formation of shock waves and complex flow fields. In this work we replicate a single filament of the ns-SDBDs and characterize the induced flow using velocity measurements from particle image velocimetry and density measurements from background-oriented schlieren. The discharge is produced by a high voltage electrical pulse between two copper electrodes on an acrylic base. A hot gas kernel characterizes the flow field formed close to the electrodes that expands and cools over time and a vortex ring that propagates away from the surface while entraining cold ambient fluid. The gas density deficit inside the kernel displays a power-law decay over time. Based on the observations, we develop a simplified theoretical model based on vortex-driven cooling and perform a scaling analysis to obtain the induced flow length and time scales. The results show that the cooling process's time scales correspond to a circulation-based time scale of the vortex ring, and the length scale of the kernel corresponds to the vortex ring radius. These findings can guide the choice of optimal filament spacing and pulse frequencies in the design, deployment, and operation of nanosecond surface dielectric barrier discharges (ns-SDBDs) for flow control.

physics.flu-dyn↗

arXiv2020

Vortex rings drive entrainment and cooling in flow induced by a spark discharge

Spark plasma discharges induce vortex rings and a hot gas kernel. We develop a model to describe the late stage of the spark induced flow and the role of the vortex rings in the entrainment of cold ambient gas and the cooling of the hot gas kernel. The model is tested in a plasma-induced flow, using density and velocity measurements obtained from simultaneous stereoscopic particle image velocimetry (S-PIV) and background oriented schlieren (BOS). We show that the spatial distribution of the hot kernel follows the motion of the vortex rings, whose radial expansion increases with the electrical energy deposited during the spark discharge. The vortex ring cooling model establishes that entrainment in the convective cooling regime is induced by the vortex rings and governs the cooling of the hot gas kernel, and the rate of cooling increases with the electrical energy deposited during the spark discharge.

physics.flu-dyn↗

arXiv2019

To Seal or Not To Seal

When an object impacts the free surface of a liquid, it ejects a splash curtain upwards and creates an air cavity below the free surface. As the object descends into the liquid, the air cavity eventually closes under the action of hydrostatic pressure (deep seal). In contrast, the surface curtain may splash outwards or dome over and close, creating a surface seal. In this paper we experimentally investigate how the splash curtain dynamics are governed by the interplay of cavity pressure difference, gravity, and surface tension and how they control the occurrence, or not, of surface seal. Based on the experimental observations and measurements, we develop an analytical model to describe the trajectory and dynamics of the splash curtain. The model enables us to reveal the scaling relationship for the dimensionless surface seal time and discover the existence of a critical dimensionless number that predicts the occurrence of surface seal. This scaling indicates that the most significant parameter governing the occurrence of surface seal is the velocity of the airflow rushing into the cavity. This is in contrast to the current understanding which considers the impact velocity as the determinant parameter.

physics.flu-dyn↗

arXiv2019

Uncertainty-based pressure field reconstruction from PIV/PTV flow measurements with generalized least-squares

A novel uncertainty-based pressure reconstruction method is proposed to evaluate the instantaneous pressure fields from velocity fields measured using particle image velocimetry (PIV) or particle tracking velocimetry (PTV). First, the pressure gradient fields are calculated from velocity fields, while the local and instantaneous pressure gradient uncertainty is estimated from the velocity uncertainty using a linear-transformation based algorithm. The pressure field is then reconstructed by solving an overdetermined linear system which involves the pressure gradients and boundary conditions. This linear system is solved with generalized least-squares (GLS) which incorporates the previously estimated variances and covariances of the pressure gradient errors as inverse weights to optimize the reconstructed pressure field. The method was validated with synthetic velocity fields of a 2D pulsatile flow and the results show significantly improved pressure accuracy with an error reduction of as much as 250% compared to the existing baseline method of solving the pressure Poisson equation (PPE). The GLS was more robust to the velocity errors and provides greater improvement with spatially correlated velocity errors. For experimental validation, the volumetric pressure fields were evaluated from a laminar pipe flow velocity field measured using 3D PTV. The GLS reduced the median absolute pressure errors by as much as 96%.

physics.flu-dyn↗

arXiv2019

Volumetric Particle Tracking Velocimetry (PTV) Uncertainty Quantification

We introduce the first comprehensive approach to determine the uncertainty in volumetric Particle Tracking Velocimetry (PTV) measurements. Volumetric PTV is a state-of-the-art non-invasive flow measurement technique, which measures the velocity field by recording successive snapshots of the tracer particle motion using a multi-camera set-up. The measurement chain involves reconstructing the three-dimensional particle positions by a triangulation process using the calibrated camera mapping functions. The non-linear combination of the elemental error sources during the iterative self-calibration correction and particle reconstruction steps increases the complexity of the task. Here, we first estimate the uncertainty in the particle image location, which we model as a combination of the particle position estimation uncertainty and the reprojection error uncertainty. The latter is obtained by a gaussian fit to the histogram of disparity estimates within a sub-volume. Next, we determine the uncertainty in the camera calibration coefficients. As a final step the previous two uncertainties are combined using an uncertainty propagation through the volumetric reconstruction process. The uncertainty in the velocity vector is directly obtained as a function of the reconstructed particle position uncertainty. The framework is tested with synthetic vortex ring images. The results show good agreement between the predicted and the expected RMS uncertainty values. The prediction is consistent for seeding densities tested in the range of 0.01 to 0.1 particles per pixel. Finally, the methodology is also successfully validated for an experimental test case of laminar pipe flow velocity profile measurement where the predicted uncertainty is within 17% of the RMS error value.

physics.flu-dyn↗

arXiv2019

A Wavelet Approach for the Estimation of Left Ventricular Early Filling Wave Propagation Velocity from Color-M-Mode Echocardiograms

Objective: This work evaluates a new approach for calculating the left-ventricular (LV) early filling propagation velocity (VP) from color M-Mode (CMM) echocardiograms using wavelet analysis. Unlike current approaches, the method requires no assumptions, user inputs, or heuristic conventions. Background: Current methods for measuring VP using CMM echocardiography do not account for the spatiotemporal variation of the filling wave propagation velocity. They are instead confined by empirical assumptions and user inputs that significantly hinder the accuracy of VP, subsequently limiting its clinical utility. Methods: We evaluated three methods for measuring LV early filling VP: conventional VP, the strength of propagation (VS), and VP determined from the most energetically important wave (Peak-VW), using 125 patients (Group A) with normal filling (n=50), impaired relaxation (n=25), pseudonormal filling (n=25) and restrictive filling (n=25), and in 69 patients (Group B) with normal (n=32), dilated (n=15), and hypertrophic ventricles (n=22). Results: Peak-VW most accurately distinguished normal left ventricles from diseased ones. Specifically, for Group A which spanned the stages of diastolic function, using receiver operator characteristics (ROC) and measuring their corresponding area under the curve (AUC), the AUC for Peak-VW was 0.92, versus 0.62 for conventional VP, 0.63 for VS and 0.58 for intraventricular pressure difference (IVPD). These correspond to a 50-70% improvement in classification ability. Similar improvements were found using Group B. Conclusion: A new determination of the LV early filling using wavelet analysis, Peak-VW, may provide a more accurate evaluation of diastolic function than the standard method of determining Vp and enable better diagnostic classification of patients suffering with diastolic dysfunction.

physics.med-ph↗

arXiv2019

Uncertainty amplification due to density/refractive-index gradients in volumetric PTV and BOS experiments

We theoretically analyze the effect of density/refractive-index gradients on the measurement precision of Volumetric Particle Tracking Velocimetry (V-PTV) and Background Oriented Schlieren (BOS) experiments by deriving the Cramer-Rao lower bound (CRLB) for the 2D centroid estimation process. A model is derived for the diffraction limited image of a particle or dot viewed through a medium containing density gradients that includes the effect of various experimental parameters such as the particle depth, viewing direction and f-number. Using the model we show that non-linearities in the density gradient field lead to blurring of the particle/dot image. This blurring amplifies the effect of image noise on the centroid estimation process, leading to an increase in the CRLB and a decrease in the measurement precision. The ratio of position uncertainties of a dot in the reference and gradient images is a function of the ratio of the dot diameters and dot intensities. We term this parameter the Amplification Ratio (AR), and we propose a methodology for estimating the position uncertainties in tracking-based BOS measurements. The theoretical predictions of the particle/dot position estimation variance from the CRLB are compared to ray tracing simulations with good agreement. The uncertainty amplification is also demonstrated on experimental BOS images of flow induced by a spark discharge, where we show that regions of high amplification ratio correspond to regions of density gradients. This analysis elucidates the dependence of the position error on density and refractive-index gradient induced distortion parameters, provides a methodology for accounting its effect on uncertainty quantification and provides a framework for optimizing experiment design.

physics.flu-dyn↗

arXiv2019

Uncertainty Quantification in density estimation from Background Oriented Schlieren (BOS) measurements

We present an uncertainty quantification methodology for density estimation from Background Oriented Schlieren (BOS) measurements, in order to provide local, instantaneous, a-posteriori uncertainty bounds on each density measurement in the field of view. Displacement uncertainty quantification algorithms from cross-correlation based Particle Image Velocimetry (PIV) are used to estimate the uncertainty in the dot pattern displacements obtained from cross-correlation for BOS and assess their feasibility. In order to propagate the displacement uncertainty through the density integration procedure, we also develop a novel methodology via the Poisson solver using sparse linear operators. Testing the method using synthetic images of a Gaussian density field showed agreement between the propagated density uncertainties and the true uncertainty. Subsequently the methodology is experimentally demonstrated for supersonic flow over a wedge, showing that regions with sharp changes in density lead to an increase in density uncertainty throughout the field of view, even in regions without these sharp changes. The uncertainty propagation is influenced by the density integration scheme, and for the Poisson solver the density uncertainty increases monotonically on moving away from the regions where the Dirichlet boundary conditions are specified.

physics.flu-dyn↗

arXiv2019

4D-Flow MRI Pressure Estimation Using Velocity Measurement-Error based Weighted Least-Squares

This work introduces a 4D-flow magnetic resonance imaging (MRI) pressure reconstruction method which employs weighted least-squares (WLS) for pressure integration. Pressure gradients are calculated from the velocity fields, and velocity errors are estimated from the velocity divergence for incompressible flow. Pressure gradient errors are estimated by propagating the velocity errors through Navier-Stokes momentum equation. A weight matrix is generated based on the pressure gradient errors, then employed for pressure reconstruction. The pressure reconstruction method was demonstrated and analyzed using synthetic velocity fields as well as Poiseuille flow measured using in vitro 4D-flow MRI. Performance of the proposed WLS method was compared to the method of solving the pressure Poisson equation which has been the primary method used in the previous studies. Error analysis indicated that the proposed method is more robust to velocity measurement errors. Improvement on pressure results was found to be more significant for the cases with spatially-varying velocity error level, with reductions in error ranging from 50% to over 200%. Finally, the method was applied to flow in a patient-specific cerebral aneurysm. Validation was performed with in vitro flow data collected using Particle Tracking Velocimetry (PTV) and Shake the Box (STB) method, and in vivo flow measurement obtained using 4D-flow MRI. Pressure calculated by WLS, as opposed to the Poisson equation, was more consistent with the flow structures and showed better agreement between the in vivo and in vitro data. These results suggest the utility of WLS method to obtain reliable pressure field from clinical flow measurement data.

physics.flu-dyn↗

arXiv2019

Flow field evolution and entrainment in a free surface plunging jet

We investigate ambient fluid entrainment and near-field flow characteristics of a free surface plunging jet for five Reynolds numbers ranging from 3000 to 10000 using time-resolved stereo particle image velocimetry (SPIV). We present time-averaged velocities, RMS velocity fluctuations, mean entrainment and unsteady flow features and compare them with previous studies on free jets. We find that plunging jets have a smaller potential core length, and earlier decay of the mean centerline velocity. The peak RMS velocity fluctuations occur at a location significantly upstream compared to the free jets reported in the literature. Near-field ambient fluid entrainment of plunging jets is measured for the first time and is found to be considerably higher than free jets in the low Reynolds number range. For the plunging jet case at Re = 3000, faster jet decay, higher levels of turbulent intensity in the near-field, and augmented mass entrainment result from strong primary vortices that give the turbulent/non-turbulent interface (TNTI) its convoluted shape which facilitates both bulk entrapment of ambient fluid and small scale nibbling because of larger surface area. These primary vortices occur right below the free surface and disintegrate into secondary structures at axial locations that are upstream compared to those of free jets. At higher Reynolds numbers, primary vortices are smaller in size, weak in swirling strength, and disintegrate prematurely, resulting in suppressed mixing and reduced entrainment efficiency.

physics.flu-dyn↗