4.5 Article

Stereo-particle image velocimetry uncertainty quantification

Journal

MEASUREMENT SCIENCE AND TECHNOLOGY
Volume 28, Issue 1, Pages -

Publisher

IOP PUBLISHING LTD
DOI: 10.1088/1361-6501/28/1/015301

Keywords

particle image velocimetry; PIV; stereo-PIV; uncertainty

Funding

  1. National Science Foundation [PoLS-1205642, CBET-1336038, IDBR-1152304]

Ask authors/readers for more resources

Particle image velocimetry (PIV) measurements are subject to multiple elemental error sources and thus estimating overall measurement uncertainty is challenging. Recent advances have led to a posteriori uncertainty estimation methods for planar two-component PIV. However, no complete methodology exists for uncertainty quantification in stereo PIV. In the current work, a comprehensive framework is presented to quantify the uncertainty stemming from stereo registration error and combine it with the underlying planar velocity uncertainties. The disparity in particle locations of the dewarped images is used to estimate the positional uncertainty of the world coordinate system, which is then propagated to the uncertainty in the calibration mapping function coefficients. Next, the calibration uncertainty is combined with the planar uncertainty fields of the individual cameras through an uncertainty propagation equation and uncertainty estimates are obtained for all three velocity components. The methodology was tested with synthetic stereo PIV data for different light sheet thicknesses, with and without registration error, and also validated with an experimental vortex ring case from 2014 PIV challenge. Thorough sensitivity analysis was performed to assess the relative impact of the various parameters to the overall uncertainty. The results suggest that in absence of any disparity, the stereo PIV uncertainty prediction method is more sensitive to the planar uncertainty estimates than to the angle uncertainty, although the latter is not negligible for non-zero disparity. Overall the presented uncertainty quantification framework showed excellent agreement between the error and uncertainty RMS values for both the synthetic and the experimental data and demonstrated reliable uncertainty prediction coverage. This stereo PIV uncertainty quantification framework provides the first comprehensive treatment on the subject and potentially lays foundations applicable to volumetric PIV measurements.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.5
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

Article Computer Science, Interdisciplinary Applications

Modeling Bias Error in 4D Flow MRI Velocity Measurements

Sean M. Rothenberger, Jiacheng Zhang, Melissa C. Brindise, Susanne Schnell, Michael Markl, Pavlos P. Vlachos, Vitaliy L. Rayz

Summary: We present a model to estimate the bias error of 4D flow MRI velocity measurements, accounting for intra-voxel velocity distribution and partial volume effects. The model accurately estimates the bias error in voxels not affected by partial volume effects, and can help plan 4D flow MRI scans.

IEEE TRANSACTIONS ON MEDICAL IMAGING (2022)

Article Engineering, Multidisciplinary

Uncertainty of PIV/PTV based Eulerian pressure estimation using velocity uncertainty

Jiacheng Zhang, Sayantan Bhattacharya, Pavlos P. Vlachos

Summary: This work presents a method to estimate the uncertainty of pressure fields reconstructed from PIV/PTV measurements. The method propagates the uncertainty of the velocity vectors through the pressure reconstruction. The method has been validated through tests on synthetic velocity fields and experimental flow fields, showing high accuracy in capturing the effects of velocity noise, autocorrelation, and pressure gradient integration methods on pressure errors.

MEASUREMENT SCIENCE AND TECHNOLOGY (2022)

Article Engineering, Biomedical

Automated Peak Prominence-Based Iterative Dijkstra's Algorithm for Segmentation of B-Mode Echocardiograms

Melissa C. Brindise, Brett A. Meyers, Shelby Kutty, Pavlos P. Vlachos

Summary: This article presents a user-initialized, automated left ventricle segmentation method for echocardiograms, named ProID. The method achieved accurate segmentation results with low computational cost across different systems. Clinical analysis on a cohort of 66 pediatric patients demonstrated the accuracy and stability of ProID.

IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING (2022)

Article Mechanics

Spatiotemporal measurement of concentration-dependent diffusion coefficient

Adib Ahmadzadegan, Jiacheng Zhang, Arezoo M. Ardekani, Pavlos P. Vlachos

Summary: This paper introduces a method to measure the concentration-dependent diffusion coefficient using a sequence of concentration images. The method utilizes spatial and temporal information and numerically solves Fick's second law to measure the diffusion coefficient. The method makes no assumptions and outperforms existing methods in estimating spatiotemporal changes and concentration-dependent diffusion.

PHYSICS OF FLUIDS (2022)

Article Engineering, Biomedical

Wall Shear Stress Estimation for 4D Flow MRI Using Navier-Stokes Equation Correction

Jiacheng Zhang, Sean M. Rothenberger, Melissa C. Brindise, Michael Markl, Vitaliy L. Rayz, Pavlos P. Vlachos

Summary: This study introduces a novel method for estimating wall shear stress (WSS) using 4D flow MRI, which improves the accuracy of WSS estimation by correcting velocity gradient estimation. The method was tested on synthetic and in vivo data, and compared to the state-of-the-art method. The proposed method showed significant improvement in WSS accuracy and its potential for predicting cardiovascular diseases.

ANNALS OF BIOMEDICAL ENGINEERING (2022)

Article Chemistry, Multidisciplinary

Assessment of Cavitation Intensity in Accelerating Syringes of Spring-Driven Autoinjectors

Javad Eshraghi, Jean-Christophe Veilleux, Galen Shi, David Collins, Arezoo M. Ardekani, Pavlos P. Vlachos

Summary: Cavitation is an undesirable phenomenon that may occur in certain types of autoinjectors, potentially causing damage to the device container and protein drug molecules. By analyzing the potential effects of cavitation on autoinjectors, it was found that design parameters have an impact on the severity of cavitation, providing valuable data insights.

PHARMACEUTICAL RESEARCH (2022)

Article Engineering, Biomedical

Automated Layer Identification Method for Skin Tissue Histology Images

Melissa C. Brindise, Kevin Buno, Luis Solorio, Pavlos P. Vlachos

Summary: We propose a novel automated method for identifying tissue layers in histology images. The method incorporates coarse boundary identification and refinement steps to accurately segment different layers. Experimental results show that our method is robust across different histology stains.

ANNALS OF BIOMEDICAL ENGINEERING (2023)

Article Engineering, Biomedical

Multi-feature-Based Robust Cell Tracking

Brian H. Jun, Adib Ahmadzadegan, Arezoo M. Ardekani, Luis Solorio, Pavlos P. Vlachos

Summary: This study presents a feature-based cell tracking algorithm that can automatically detect and track cells in time-lapse images. By using advanced image processing techniques and adaptive thresholding, the algorithm can handle cell feature changes and achieves high detection and tracking accuracy.

ANNALS OF BIOMEDICAL ENGINEERING (2023)

Article Engineering, Biomedical

Modeling large-volume subcutaneous injection of monoclonal antibodies with anisotropic porohyperelastic models and data-driven tissue layer

Mario de Lucio, Yu Leng, Atharva Hans, Ilias Bilionis, Melissa Brindise, Arezoo M. Ardekani, Pavlos P. Vlachos, Hector Gomez

Summary: Subcutaneous injection of therapeutic monoclonal antibodies (mAbs) is a rapidly growing field in the pharmaceutical industry. This study presents a large-deformation poroelastic model to understand high-dose, high-speed subcutaneous injection. The anisotropy of subcutaneous tissue and the multi-layer structure of the skin tissue are considered. The impact of handheld autoinjectors on injection dynamics for different patient forces is analyzed. The simulations highlight the importance of the large deformation approach in modeling large injection volumes and provide insights into the mechanics and transport processes in subcutaneous injections of mAbs.

JOURNAL OF THE MECHANICAL BEHAVIOR OF BIOMEDICAL MATERIALS (2023)

Article Chemistry, Multidisciplinary

Mechanistic Computational Modeling of Implantable, Bioresorbable Drug Release Systems

Patrick A. Giolando, Kelsey Hopkins, Barrett F. Davis, Nicole Vike, Adib Ahmadzadegan, Arezoo M. Ardekani, Pavlos P. Vlachos, Joseph V. Rispoli, Luis Solorio, Tamara L. Kinzer-Ursem

Summary: Implantable, bioresorbable drug delivery systems provide a patient-tailored drug dosage with increased patient compliance. Mechanistic mathematical modeling accelerates the design of release systems by predicting physical anomalies and short- and long-term drug release profiles. This study investigates the impact of various parameters on drug release and offers new insight into the design process for tailored release systems.

ADVANCED MATERIALS (2023)

Article Pharmacology & Pharmacy

Hydrodynamic considerations for spring-driven autoinjector design

Xiaoxu Zhong, Jean-Christophe Veilleux, Galen Huaiqiu Shi, David S. Collins, Pavlos Vlachos, Arezoo M. Ardekani

Summary: In recent years, significant progress has been made in the studies of spring-driven autoinjectors, leading to an improved understanding of its interactions with tissue and therapeutic proteins. Simulation tools have enhanced the prediction of performance, while this paper addresses critical hydrodynamic considerations and presents a framework for optimizing design. This work is valuable to the pharmaceutic industry as it provides insights into device development and improving patient outcomes.

INTERNATIONAL JOURNAL OF PHARMACEUTICS (2023)

Article Mechanics

Particle Image micro-Rheology (PIR) using displacement probability density function

Adib Ahmadzadegan, Harsa Mitra, Pavlos P. Vlachos, Arezoo M. Ardekani

Summary: We propose a novel method called particle image rheometry (PIR) to measure the rheological properties of fluids using the Brownian motion of suspended particles. PIR estimates the particle ensemble mean square displacement (MSD) from the temporal evolution of the displacement probability density function (PDF). Our evaluations show that PIR achieves a lower error than existing methods, with less than 1% error in passive microrheology measurements.

JOURNAL OF RHEOLOGY (2023)

Article Biology

Complex hemolymph circulation patterns in grasshopper wings

Mary K. Salcedo, Brian H. Jun, John J. Socha, Naomi E. Pierce, Pavlos P. Vlachos, Stacey A. Combes

Summary: Research shows that the circulation system, respiration system, and nervous system of insects extend into their wings, playing a critical role in supplying nutrients and maintaining wing function. High-speed fluorescent microscopy and particle tracking reveals dynamic flow patterns in every vein of grasshopper wings, with three different flow behaviors: pulsatile, aperiodic, and leaky. Study of the wing circulatory system provides valuable insights into the hemodynamics necessary for sustaining wing health and insect flight.

COMMUNICATIONS BIOLOGY (2023)

Article Computer Science, Interdisciplinary Applications

Automatic 4D Flow MRI Segmentation Using the Standardized Difference of Means Velocity

Sean M. Rothenberger, Neal M. Patel, Jiacheng Zhang, Susanne Schnell, Bruce A. Craig, Sameer A. Ansari, Michael Markl, Pavlos P. Vlachos, Vitaliy L. Rayz

Summary: We propose an automatic segmentation method for 4D flow MRI based on SDM velocity. The SDM velocity quantifies the net flow effects in each voxel, and vessel segmentation is performed using an F-test. We compare the SDM algorithm with PCD and CNN segmentation methods, and the results demonstrate its robustness and accuracy in identifying vessel surfaces.

IEEE TRANSACTIONS ON MEDICAL IMAGING (2023)

Article Multidisciplinary Sciences

A multi-modality approach for enhancing 4D flow magnetic resonance imaging via sparse representation

Jiacheng Zhang, Melissa C. Brindise, Sean M. Rothenberger, Michael Markl, Vitaliy L. Rayz, Pavlos P. Vlachos

Summary: This study evaluates and applies a multi-modality approach to improve blood flow measurements and hemodynamic analysis in cerebral aneurysms using 4D flow MRI. The method reconstructs the flow field and calculates the pressure using sparse representation, leading to enhanced accuracy of the measurements.

JOURNAL OF THE ROYAL SOCIETY INTERFACE (2022)

No Data Available