Time-resolved Flow Research Articles

Aortic and mitral flow quantification using dynamic valve tracking and machine learning: Prospective study assessing static and dynamic plane repeatability, variability and agreement.

BackgroundBlood flow is a crucial measurement in the assessment of heart valve disease. Time-resolved flow using magnetic resonance imaging (4 D flow MRI) can provide a comprehensive assessment of heart valve hemodynamics but it relies in manual plane analysis. In this study, we aimed to demonstrate the feasibility of automate the detection and tracking of aortic and mitral valve planes to assess blood flow from 4 D flow MRI.MethodsIn this prospective study, a total of n = 106 subjects were enrolled: 19 patients with mitral disease, 65 aortic disease patients and 22 healthy controls. Machine learning was employed to detect aortic and mitral location and motion in a cine three-chamber plane and a perpendicular projection was co-registered to the 4 D flow MRI dataset to quantify flow volume, regurgitant fraction, and a peak velocity. Static and dynamic plane association and agreement were evaluated. Intra- and inter-observer, and scan-rescan reproducibility were also assessed.ResultsAortic regurgitant fraction was elevated in aortic valve disease patients as compared with controls and mitral valve disease patients (p < 0.05). Similarly, mitral regurgitant fraction was higher in mitral valve patients (p < 0.05). Both aortic and mitral total flow were high in aortic patients. Static and dynamic were good (r > 0.6, p < 0.005) for aortic total flow and peak velocity, and mitral peak velocity and regurgitant fraction. All measurements showed good inter- and intra-observer, and scan-rescan reproducibility.ConclusionWe demonstrated that aortic and mitral hemodynamics can efficiently be quantified from 4 D flow MRI using assisted valve detection with machine learning.

Luminescent Nanomaterials (II).

In this review, we focus on sensing techniques and biological applications of various luminescent nanoparticles including quantum dot (QD), up-conversion nanoparticles (UCNPs) following the previous chapter. Fluorescent phenomena can be regulated or shifted by interaction between biological targets and luminescence probes depending on their distance, which is so-called Fӧrster resonance energy transfer (FRET). QD-based FRET technique, which has been widely applied as a bioanalytical tool, is described. We discuss time-resolved fluorescence (TRF) imaging and flow cytometry technique, using photoluminescent nanoparticles with unique properties for effectively improving selectivity and sensitivity. Based on these techniques, bioanalytical and biomedical application, bioimaging with QD, UCNPs, and Euripium-activated luminescent nanoprobes are covered. Combination of optical property of these luminescent nanoparticles with special functions such as drug delivery, photothermal therapy (PTT), and photodynamic therapy (PDT) is also described.

Influence on Sensitivity Enhancement of Expansion Tube Window in Multi-Pass Laser Absorption Spectroscopy and Time-Resolved Flow Diagnostics

Influence on Sensitivity Enhancement of Expansion Tube Window in Multi-Pass Laser Absorption Spectroscopy and Time-Resolved Flow Diagnostics

Computational fluid dynamics simulation of time-resolved blood flow in Budd-Chiari syndrome with inferior vena cava stenosis and its implication for postoperative efficacy assessment

BackgroundThis study aimed to adopt computational fluid dynamics to simulate the blood flow dynamics in inferior vena cava stenosis based on time-dependent patient-specific models of Budd-Chiari syndrome as well as a normal model. It could offer valuable references for a retrospective insight into the underlying mechanisms of Budd-Chiari syndrome pathogenesis as well as more accurate evaluation of postoperative efficacy. MethodsThree-dimensional inferior vena cava models of Budd-Chiari syndrome patient-specific (preoperative and postoperative) and normal morphology model were reconstructed as per magnetic resonance images using Simpleware. Moreover, computational fluid dynamics of time-resolved inferior vena cava blood flow were simulated using actual patient-specific measurements to reflect time-dependent flow rates. FindingsThe assessment of the preoperative model revealed the dramatic variations of hemodynamic parameters of the stenotic inferior vena cava. Moreover, the comparison of the preoperative and postoperative models with the normal model as benchmark showed that postoperative hemodynamic parameters were markedly ameliorated via stenting, with the attenuation of overall velocity and wall shear stress, and the increase of pressure. However, the comparative analysis of the patient-specific simulations revealed that some postoperative hemodynamic profiles still bore some resemblance to the preoperative ones, indicating potential risks of restenosis. InterpretationComputational fluid dynamics simulation of time-resolved blood flow could reveal the tight correlation between the hemodynamic characteristics and the pathological mechanisms of inferior vena cava stenosis. Furthermore, such time-resolved hemodynamic profiles could provide a quantitative approach to diagnosis, operative regimen and postoperative evaluation of Budd-Chiari syndrome with inferior vena cava stenosis.

Particle–fluid–wall interaction of inertial spherical particles in a turbulent boundary layer

Abstract

Volumetric measurement of turbulence and flow topology in an asymmetric diffuser

Three-dimensional particle tracking velocimetry is used to characterize the time-resolved turbulent flow in an asymmetric diffuser. The measurements cover the full diffuser and show that the separated flow consists of large-scale structures with a Strouhal number smaller than 0.03. Three large vortices are identified; two vortices originate from the wall with the largest diverging angle and the third vortex from the neighboring diverging wall.

Lifetime encoding in flow cytometry for bead-based sensing of biomolecular interaction

To demonstrate the potential of time-resolved flow cytometry (FCM) for bioanalysis, clinical diagnostics, and optically encoded bead-based assays, we performed a proof-of-principle study to detect biomolecular interactions utilizing fluorescence lifetime (LT)-encoded micron-sized polymer beads bearing target-specific bioligands and a recently developed prototype lifetime flow cytometer (LT-FCM setup). This instrument is equipped with a single excitation light source and different fluorescence detectors, one operated in the photon-counting mode for time-resolved measurements of fluorescence decays and three detectors for conventional intensity measurements in different spectral windows. First, discrimination of bead-bound biomolecules was demonstrated in the time domain exemplarily for two targets, Streptavidin (SAv) and the tumor marker human chorionic gonadotropin (HCG). In a second step, the determination of biomolecule concentration levels was addressed representatively for the inflammation-related biomarker tumor necrosis factor (TNF-α) utilizing fluorescence intensity measurements in a second channel of the LT-FCM instrument. Our results underline the applicability of LT-FCM in the time domain for measurements of biomolecular interactions in suspension assays. In the future, the combination of spectral and LT encoding and multiplexing and the expansion of the time scale from the lower nanosecond range to the longer nanosecond and the microsecond region is expected to provide many distinguishable codes. This enables an increasing degree of multiplexing which could be attractive for high throughput screening applications.

Exploring the signature of distributed pressure measurements on non-slender delta wings during axial and vertical gusts

For a broad range of aerodynamic bodies, vortex structures arising from perturbations such as gusts cause characteristic surface pressure signatures that are coupled to the observed aerodynamic loads. The present study evaluates the extent to which sparsely measured pressure signatures can be used to identify the spatio-temporal evolution of vortex structures and, specifically, their relationship to the bulk aerodynamic loads. A non-slender delta wing experiencing axial and vertical gusts under various initial stall conditions is selected as a test case. Time-resolved loads, distributed surface pressures, and time-resolved flow fields (particle image velocimetry) are collected for a wide range of parameters in a towing-tank facility. By linearly mapping the sparse pressure data to the aerodynamic loads, the spatio-temporal relation of loads and pressure can be extracted. The static mapping coefficients are determined through linear regression at each incidence angle as well as for an angle-independent (aggregate) case. Despite slightly larger errors when compared to the angle-specific fits, the aggregate method maintains a good fit quality over all angles of attack and thereby provides a robust pressure-load mapping. Thus, the existence of a common mechanism across gusts and angles of attack is identified despite the stark differences in flow conditions, i.e., light vs deep dynamic stall. In addition, the lasso regularization used in the study provides valuable insight into sensor reduction. The distribution of fewer regression predictors indicates specific pressure ports that capture the footprint of dominant flow features and thereby suggest sensitive locations for future clusters of sensors.

Unsteady Flow Interactions Between a High- and Low-Pressure Turbine

Abstract This paper presents the unsteady flow interactions between an engine-representative high-pressure turbine (HPT) and low-pressure turbine (LPT) stage, connected by a turbine center frame (TCF) duct with nonturning struts. The setup was tested at the high-speed two-spool test turbine facility at the Institute for Thermal Turbomachinery and Machine Dynamics at Graz University of Technology and includes relevant purge and turbine rotor tip leakage flows. Due to the complexity of such a test, the unsteady component interactions in an HPT–TCF–LPT module have not received much attention in the past and require additional analysis to determine new approaches for further performance improvements on the system level. The flow downstream of an HPT is highly unsteady and dominated by stator–rotor interactions, which affect the flow behavior through the downstream TCF and LPT. To capture the unsteady flow structures, time-resolved aerodynamic measurements were carried out with a fast-response aerodynamic pressure probe (FRAPP) at three different measurement planes. In this paper, the time-resolved and phase-averaged flow fields with respect to the HPT and LPT trigger are studied. Since the two rotors are uncorrelated, the applied method allows the identification of the flow structures induced by either of them. Upstream of the LPT stage, the HPT flow structures evolving through the TCF duct dominate the flow fields. Downstream of the LPT stage, the flow is affected by both the HPT and the LPT secondary flow structures. The interactions between the various stator rows and the two rotors are detected by means of time-space plots and modal decomposition. To describe the fluctuations induced by both rotors, particularly the rotor–rotor interaction, the rotor synchronic averaging (RSA) is used to analyze the flow field downstream of the LPT. This paper highlights the need to account for the HPT-induced unsteady mechanisms in addition to the LPT flow structures and the interaction of both to arrive at improved LPT designs.

Data-driven order reduction and velocity field reconstruction using neural networks: The case of a turbulent boundary layer

We present a data-driven methodology to achieve the identification of coherent structure dynamics and system order reduction of an experimental turbulent boundary layer flow. The flow is characterized using time-resolved optical flow particle image velocimetry, leading to dense velocity fields that can be used both to monitor the overall dynamics of the flow and to define as many local visual sensors as needed. A Proper Orthogonal Decomposition (POD) is first applied to define a reduced-order system. A non-linear mapping between the local upstream sensors (inputs sensors) and the full-field dynamics (POD coefficients) as outputs is sought using an optimal focused time-delay Artificial Neural Network (ANN). The choices of sensors, ANN architecture, and training parameters are shown to play a critical role. It is verified that a shallow ANN, with the proper sensor memory size, can lead to a satisfying full-field dynamics identification, coherent structure reconstruction, and system order reduction of this turbulent flow.

The impact of the third O2 addition reaction network on ignition delay times of neo-pentane

We studied the oxidation of neo-pentane by combining experiments, theoretical calculations, and mechanistic developments to elucidate the impact of the 3rd O2 addition reaction network on ignition delay time predictions. The experiments are based on photoionization mass spectrometry in jet-stirred and time-resolved flow reactors allowing for sensitive detection of the keto-hydroperoxide (KHP) and keto-dihydroperoxide (KDHP) intermediates. With neo-pentane exhibiting a unique symmetric molecular structure, which consequently results only in single KHP and KDHP isomers, theoretical calculations of ionization and fragment appearance energies and of absolute photoionization cross sections enabled the unambiguous identification and quantification of the KHP intermediate. Its temperature and time-resolved profiles together with calculated and experimentally observed KHP-to-KDHP signal ratios were compared to simulation results based on a newly developed mechanism that describes the 3rd O2 addition reaction network. A satisfactory agreement has been observed between the experimental data points and the simulation results, thus adding confidence to the model's overall performance. Finally, this mechanism was used to predict ignition delay times reported previously in shock tube and rapid compression machine experiments (J. Bugler et al., Combust. Flame 163 (2016) 138–156). While the model accurately reproduces the experimental data, simulations with and without the 3rd O2 addition reaction network included reveal only a negligible effect on the predicted ignition delay times at 10 and 20 atm. According to model calculations, low temperatures and high pressures promote the importance of the 3rd O2 addition reactions.

Analysis of Interaction Between Oscillating Jet Issuing from a Fluidic Oscillator and a Crossflow

In the present study, numerical simulation was conducted to study both the internal and external flows of a fluidic oscillator in a quiescent environment and with a crossflow. Unsteady Reynolds-averaged Navier–Stokes analysis was used to evaluate the flow field. The blowing ratio was varied to understand the interaction between the free stream and the oscillating jet. Results for the time-averaged and the time-resolved flow fields were presented. The outlet velocity from the oscillator was not affected by the freestream flow for the tested three blowing ratios. Q criterion was used to evaluate the interaction of turbulent vortical structures from the fluidic oscillator with the crossflow. It was observed that two counter-rotating vortices and ring-like vortices were the important flow features of the external flow. As blowing ratio increases, the counter-rotating vortices become more asymmetric, move further from the wall, and are more spread.

Phase-consistent dynamic mode decomposition from multiple overlapping spatial domains

Dynamic mode decomposition (DMD) provides a principled approach to extract physically interpretable spatial modes from time-resolved flow field data, along with a linear model for how the amplitudes of these modes evolve in time. Recently, DMD has been extended to work with more realistic data that is under-resolved either in time or space, or with data collected in the same spatial domain over multiple independent time windows. In this work, we develop an extension to DMD to synthesize globally consistent modes from velocity fields collected independently in multiple partially overlapping spatial domains. We propose a tractable optimization to identify modes that span multiple windows and align their phases to be consistent in the overlapping regions. First, we demonstrate this approach on data from direct numerical simulation, where it is possible to split the data into overlapping domains and benchmark against ground-truth modes. We consider the laminar flow past a cylinder as an example with distinct frequencies, along with the spatially developing mixing layer, which exhibits a frequency spectrum that evolves continuously as the measurement window moves downstream. Next, we analyze experimental velocity fields from PIV in six overlapping domains in the wake of a cross-flow turbine. On the numerical examples, we demonstrate the robustness of this approach to increasing measurement noise and decreasing size of the overlap regions. In all cases, it is possible to obtain a phase-aligned, composite reconstruction of the full time-resolved flow field from the phase-consistent modes over the entire domain.

100 kHz PLEET velocimetry in a Mach-6 Ludwieg tube.

Picosecond laser electronic-excitation tagging (PLEET) was demonstrated in a Mach-6 Ludwieg tube at a repetition rate of 100 kHz using a 1064 nm, 100 ps burst-mode laser. The system performance of high-speed velocimetry in unseeded air and nitrogen Mach-6 flows at a static pressure in the range of 5-20 torr were evaluated. Based on time-resolved freestream flow measurements and computational fluid dynamics (CFD) calculations, we concluded that the measurement uncertainty of 100 kHz PLEET measurement for Mach 6 freestream flow condition is ∼1%. The measured velocity profiles with a cone-model agreed well with the CFD computations upstream and downstream of the shockwave; downstream of the shockwave the discrepancy between the CFD and experimental measurement could be attributed to a slight nonzero angle of attack (AoA) or flow unsteadiness. Our results show the potential of utilizing 100 kHz PLEET velocimetry for understanding real-time dynamics of turbulent hypersonic flows and provide the capability of collecting sufficient data across fewer tests in large hypersonic ground test facilities.

Time-resolved reconstruction of turbulent flows using linear stochastic estimation and sequential data assimilation

The present work concentrates on the reconstruction of the time-resolved turbulent flows from probe signals and low sampling rate flow fields using linear stochastic estimation (LSE) and sequential data assimilation (DA). The separated and reattached flow over a blunt plate is used as the benchmark configuration. Experimental data are acquired with a microphone array (34 probes) installed on the plate surface to capture the pressure fluctuation at a sampling rate 1000 Hz, and with planar particle image velocimetry (PIV) measuring the two-dimensional two-component (2D2C) velocity fields synchronized with the microphones at 1 Hz. LSE is conducted first to estimate the raw temporal sequence of the flow field from PIV and microphone data. This temporal sequence then serves as the observations for the DA process based on continuous adjoint formulation for the flow field correction and pressure determination. The LSE results show that an appropriate size of proper orthogonal decomposition (POD) database should be evaluated considering the combined error induced by the truncation of the mapping function M, the size of the POD database, and the scaling of the model coefficient for the compensation of M truncation. Subsequently, the LSE reconstructions using the POD database of size Nt = 100 are employed as the observations in the DA process. The mean flow field is recovered quite well, while the normal Reynolds stress also has a significant improvement compared to large-eddy simulation. The temporal variation of the LSE reconstruction is significantly improved, and the resultant fluctuating pressure coefficient distribution agrees reasonably well with the microphone measurement.

In Vitro Assessment of Flow Variability in an Intracranial Aneurysm Model Using 4D Flow MRI and Tomographic PIV.

Aneurysm rupture has been suggested to be related to aneurysm geometry, morphology, and complex flow activity; therefore, understanding aneurysm-specific hemodynamics is crucial. 4D Flow MRI has beenshown to be a feasible tool for assessing hemodynamics in intracranial aneurysms with high spatial resolution. However, it requires averaging over multiple heartbeats and cannot account for cycle-to-cycle hemodynamics variations. This study aimed to assess cycle-to-cycle flow dynamics variations in a patient-specific intracranial aneurysm model using tomographic particle image velocimetry (tomo-PIV) at a high image rate under pulsatile flow conditions. Time-resolved and time-averaged velocity flow fields within the aneurysm sac and estimations of wall shear stress (WSS) were compared with those from 4D Flow MRI. A one-way ANOVA showed a significant difference between cardiac cycles (p value < 0.0001); however, differences were not significant after PIV temporal and spatial resolution was matched to that of MRI (p value 0.9727). This comparison showed the spatial resolution to be the main contributor to assess cycle-to-cycle variability. Furthermore, the comparison with 4D Flow MRI between velocity components, streamlines, and estimated WSS showed good qualitative and quantitative agreement. This study showed the feasibility of patient-specific in-vitro experiments using tomo-PIV to assess 4D Flow MRI with high repeatability in the measurements.

Time-Resolved Flow Field Analysis of Effusion Cooling System With Representative Swirling Main Flow

Abstract Film-cooling jets behavior in a combustor chamber is deeply affected by swirling flow interactions and unsteadiness; on the other hand, the jets behavior has a direct impact on different phenomena such as cooling capabilities and ignition. For these reasons, an in-depth characterization of the film-cooling flows in the presence of a swirling main flow and demands dedicated time-resolved analyses. The experimental setup consists of a nonreactive single-sector linear combustor simulator installed in an open-loop wind tunnel. It is equipped with a swirler and a multiperforated plate to simulate the effusion cooling system of the liner. The rig is scaled with respect to the engine configuration to increase spatial resolution and to reduce the characteristic frequencies of the unsteady phenomena. Time-resolved particle image velocimetry (TRPIV) was exploited for the investigation testing different values of liner pressure drop. In addition, numerical investigations were carried out to gain a deeper insight of the behavior highlighted by the experiments and to assess the capability of computational fluid dynamics (CFD) in predicting the flow physics. In this work, the stress-blended eddy simulation (SBES) approach implemented in ansys fluent was adopted. Oscillations of the jets and intermittent interactions of the mainstream with the wall of the liner and hence with the film development have been investigated in detail. The results demonstrate how an unsteady analysis of the flow structures that characterize the jets, the turbulent mixing of coolant flows, and the interaction between mainstream and cooling jets is strictly necessary to have a complete knowledge of the behavior of the coolant, which in turn affects combustor operability and life time.

Jet Oscillation Frequency Characterization of a Sweeping Jet Actuator

The time-resolved flow field of a spatially oscillating jet emitted by a sweeping jet (SWJ) actuator is investigated numerically using three-dimensional Reynolds-averaged Navier–Stokes (3D-URANS) equations. Numerical simulations are performed for a range of mass flow rates providing flow conditions varying from incompressible to subsonic compressible flows. After a detailed mesh study, the computational domain is represented using two million hexagonal control volumes. The jet oscillation frequency is predicted by analyzing velocity time histories at the actuator exit, and a linear relationship between the jet oscillation frequency and time-averaged exit nozzle Mach number is found ( f = 511.22 M + 46.618 , R² = 0.97). The results of our numerical model are compared with data from the literature, and a good agreement is found. In addition, we confirmed that the Strouhal number is almost constant with the Mach number for the subsonic oscillating jet and has an average value of St = 0.0131. The 3D-URANS model that we presented here provides a computationally inexpensive yet accurate alternative to the researchers to investigate jet oscillation characteristics.

Flow interactions on supersonic projectiles in transitional ballistic regimes

A projectile moving in the transitional/intermediate ballistic regime encounters many complex flow phenomena as the flow field contains two blast waves and several flow interfaces. The aerodynamic characteristics of the projectile are highly influenced by the interaction of the projectile with the surrounding flow field. The present study aims to experimentally visualize the flow structures associated with a moving projectile in the immediate vicinity of the launch tube (transitional/intermediate ballistic regime). In this work, the main focus is to investigate three significant phenomena which normally occur in the transitional ballistic regime and have significant effects on the aerodynamic characteristics of the projectile. These are the moving projectile-standing shock interaction termed as unsteady shock diffraction, shock generation due to the transition in the relative projectile Mach number and the moving projectile-moving shock interaction known as the projectile overtaking phenomenon. Experiments are carried out with projectiles of various configurations for various projectile Mach numbers. The flow field is visualized using time-resolved schlieren and shadowgraph flow visualization techniques. The experiments could capture several interesting features of projectile-flow interactions such as the unsteady shock diffraction, shock generation and overtaking phenomenon in various flow regimes through visualization and quantification of the images using image processing techniques.

Time-resolved fluorescence resonance energy transfer-based lateral flow immunoassay using a raspberry-type europium particle and a single membrane for the detection of cardiac troponin I

Herein, we report a novel lateral flow immunoassay (LFIA) system for detecting cardiac troponin I (cTnI) in serum using the time-resolved fluorescence resonance energy transfer (TR-FRET) technique and the fusion 5 membrane. The fusion 5 membrane is used as a strip for LFIA, and it is constructed without additional matrices (such as a sample or conjugation pad). Although this strategy for constructing the LFIA strip is quite simple and cost-effective, LFIA is still not suitable for the analysis of biomarkers that require high sensitivity, such as cTnI. Therefore, the highly sensitive TR-FRET technique is integrated with a fusion 5 membrane-based LFIA strip. To accomplish this, a microparticle covered with europium chelate-contained silica nanoparticles is synthesized as a raspberry-type particle and used as a fluorescence donor. A gold nanorod (GNR) is used as a fluorescence acceptor particle. In the TR-FRET-based LFIA system, the competitive immunoassay should be performed to satisfy the condition required for the FRET phenomenon to occur. Therefore, the fluorescence signal is proportional to the cTnI concentration, ensuring a quantitative analysis of cTnI can be accomplished by measuring the fluorescence signal between the raspberry-type europium particles and GNR. Using the developed TR-FRET-based LFIA system, sensitive detection of cTnI is successfully achieved with a limit of detection of 97 pg/mL in human serum. Moreover, because the result can be obtained using one matrix (the fusion 5 membrane), the developed LFIA system can be employed in cTnI diagnosis with a simple manufacturing process.