Flow Velocity Estimation Research Articles

Semi-Empirical Estimation of Dean Flow Velocity in Curved Microchannels

Curved and spiral microfluidic channels are widely used in particle and cell sorting applications. However, the average Dean velocity of secondary vortices which is an important design parameter in these devices cannot be estimated precisely with the current knowledge in the field. In this paper, we used co-flows of dyed liquids in curved microchannels with different radii of curvatures and monitored the lateral displacement of fluids using optical microscopy. A quantitative Switching Index parameter was then introduced to calculate the average Dean velocity in these channels. Additionally, we developed a validated numerical model to expand our investigations to elucidating the effects of channel hydraulic diameter, width, and height as well as fluid kinematic viscosity on Dean velocity. Accordingly, a non-dimensional comprehensive correlation was developed based on our numerical model and validated against experimental results. The proposed correlation can be used extensively for the design of curved microchannels for manipulation of fluids, particles, and biological substances in spiral microfluidic devices.

Surf beat-induced overwash during Typhoon Haiyan deposited two distinct sediment assemblages on the carbonate coast of Hernani, Samar, central Philippines

Wave set-up steepened and accentuated the storm surge during Typhoon Haiyan in November 2013 resulting in bore-like flooding with surge heights of 7m and flow velocities reaching 5ms−1 on the open-sea coastal plain near Hernani. This study investigates two distinct sediment assemblages left behind by the coastal flooding associated with this surge. The first assemblage consists of numerous coastal boulders that now occupy the reef flat, and the second pertains to a laterally extensive sand sheet that blanketed the coastal plain up to ~300m inland. The majority of the boulders has b axes between 1 and 2m, weigh no >10t, and were originally submerged on the reef edge. The boulders found more landwards of the reef edge were potentially lying loosely on the reef flat prior to Haiyan. In contrast, the coarse carbonate sand sheet starts at ~10m inland of the current shoreline and has a maximum thickness of 10cm and gradually thins to 3mm at ~300m inland. The Haiyan sand contains moderate concentrations of foraminifera (Amphistegina spp., Baculogypsina sphaerulata, and Peneroplis spp.) that were both abraded and unaltered, pointing to a reef flat and beach source for the sand. Sediment transport inverse modeling complements previous flow velocity estimates using numerical modeling, which altogether indicate sustained high-velocity overland flow despite the presence of coral reefs and mangroves as natural defenses to extreme waves.

Regional-scale analysis of karst underground flow deduced from tracing experiments: examples from carbonate aquifers in Malaga province, southern Spain

Tracer concentration data from field experiments conducted in several carbonate aquifers (Malaga province, southern Spain) were analyzed following a dual approach based on the graphical evaluation method (GEM) and solute transport modeling to decipher flow mechanisms in karst systems at regional scale. The results show that conduit system geometry and flow conditions are the principal factors influencing tracer migration through the examined karst flow routes. Solute transport is mainly controlled by longitudinal advection and dispersion throughout the conduit length, but also by flow partitioning between mobile and immobile fluid phases, while the matrix diffusion process appears to be less relevant. The simulation of tracer breakthrough curves (BTCs) suggests that diffuse and concentrated flow through the unsaturated zone can have equivalent transport properties under extreme recharge, with high flow velocities and efficient mixing due to the high hydraulic gradients generated. Tracer mobilization within the saturated zone under low flow conditions mainly depends on the hydrodynamics (rather than on the karst conduit development), which promote a lower longitudinal advection and retardation in the tracer migration, resulting in a marked tailing effect of BTCs. The analytical advection-dispersion equation better approximates the effective flow velocity and longitudinal dispersion estimations provided by the GEM, while the non-equilibrium transport model achieves a better adjustment of most asymmetric and long-tailed BTCs. The assessment of karst underground flow properties from tracing tests at regional scale can aid design of groundwater management and protection strategies, particularly in large hydrogeological systems (i.e. transboundary carbonate aquifers) and/or in poorly investigated ones.

Vector flow imaging techniques: An innovative ultrasonographic technique for the study of blood flow.

Doppler ultrasonography is routinely used to identify abnormal blood flow. Nevertheless, conventional Doppler can be used to determine only the axial component of blood flow velocity and is angle dependent. A new method of multidimensional angle-independent estimation of flow velocity, called Vector Flow Imaging (VFI), has been proposed. It quantitatively evaluates the true velocity vector's amplitude and direction at any location into a vessel and displays a more intuitive depiction of the flow movements. High frame rate VFI, based on plane wave imaging, allows a detailed dynamic visualization of complex flow by showing even transient events, otherwise undetectable. © 2017 Wiley Periodicals, Inc. J Clin Ultrasound 45:582-588, 2017.

Interpreting flash flood palaeoflow parameters from antidunes and gravel lenses: An example from Montserrat, West Indies

AbstractThe wavelength of stationary water‐surface waves and their associated antidune bedforms are related to the mean velocity and depth of formative flow. In past published sand‐bed flume experiments, it was found that lens structures were preserved during antidune growth and change, and the dimension of the lenses was empirically related to antidune wavelength, and thus could be used to estimate flow velocity and depth. This study is the first to compare observations of formative flow conditions and resulting sedimentary structures in a natural setting, testing the previously published relationship at a field‐scale. Trains of stationary and upstream migrating water‐surface waves were prevalent during the flash flood in October 2012 in the Belham Valley, Montserrat, West Indies. Wave positions and wavelengths were assessed at 900 sec intervals through the daylight hours of the event within a monitored reach. The wave data indicate flow depths up to 1·3 m and velocity up to 3·6 m sec−1. Sedimentary structures formed by antidune growth and change were preserved in the event deposit. These structures include lenses of clast‐supported gravel and massive sand, with varying internal architecture. The lenses and associated low‐angle strata are comparable to sand‐bed structures formed from stationary and upstream migrating waves in flume experiments, confirming the diagnostic value of these structures. Using mean lens length in the event deposit underestimated peak flow conditions during the flood and implied that the lenses were preserved during waning flow.

A hybrid method of debris flow velocity estimation based on empirical equation

A hybrid method of debris flow velocity estimation based on empirical equation

Evaluation of multiple tracer methods to estimate low groundwater flow velocities

Four different tracer methods were used to estimate groundwater flow velocity at a multiple-well site in the saturated alluvium south of Yucca Mountain, Nevada: (1) two single-well tracer tests with different rest or “shut-in” periods, (2) a cross-hole tracer test with an extended flow interruption, (3) a comparison of two tracer decay curves in an injection borehole with and without pumping of a downgradient well, and (4) a natural-gradient tracer test. Such tracer methods are potentially very useful for estimating groundwater velocities when hydraulic gradients are flat (and hence uncertain) and also when water level and hydraulic conductivity data are sparse, both of which were the case at this test location. The purpose of the study was to evaluate the first three methods for their ability to provide reasonable estimates of relatively low groundwater flow velocities in such low-hydraulic-gradient environments. The natural-gradient method is generally considered to be the most robust and direct method, so it was used to provide a “ground truth” velocity estimate. However, this method usually requires several wells, so it is often not practical in systems with large depths to groundwater and correspondingly high well installation costs. The fact that a successful natural gradient test was conducted at the test location offered a unique opportunity to compare the flow velocity estimates obtained by the more easily deployed and lower risk methods with the ground-truth natural-gradient method. The groundwater flow velocity estimates from the four methods agreed very well with each other, suggesting that the first three methods all provided reasonably good estimates of groundwater flow velocity at the site. The advantages and disadvantages of the different methods, as well as some of the uncertainties associated with them are discussed.

From Surface Flow Velocity Measurements to Discharge Assessment by the Entropy Theory

A new methodology for estimating the discharge starting from the monitoring of surface flow velocity, usurf, is proposed. The approach, based on the entropy theory, involves the actual location of maximum flow velocity, umax, which may occur below the water surface (dip phenomena), affecting the shape of velocity profile. The method identifies the two-dimensional velocity distribution in the cross-sectional flow area, just sampling usurf and applying an iterative procedure to estimate both the dip and umax. Five gage sites, for which a large velocity dataset is available, are used as a case study. Results show that the method is accurate in simulating the depth-averaged velocities along the verticals and the mean flow velocity with an error, on average, lower than 12% and 6%, respectively. The comparison with the velocity index method for the estimation of the mean flow velocity using the measured usurf, demonstrates that the method proposed here is more accurate mainly for rivers with a lower aspect ratio where secondary currents are expected. Moreover, the dip assessment is found more representative of the actual location of maximum flow velocity with respect to the one estimated by a different entropy approach. In terms of discharge, the errors do not exceed 3% for high floods, showing the good potentiality of the method to be used for the monitoring of these events.

Analysis of the Seepage Due to the Thawing of Permafrost, Considering the Gradient of the Impermeable Layer

Topographical deformation due to global warming has become a serious problem. However, scientific studies have not been sufficiently conducted to understand the mechanisms. Solifluction, a gradual mass movement related to freeze-thaw processes, is known as a typical topographical deformation. The purpose of this study is to simulate the solifluction process considering the seepage influence, and then establish a predictive numerical model. The authors adopted the Finite Volume Method (FVM) and Dupuit's assumption in order to precisely simulate the seepage flow. Consequently, according to this study, the authors suggested to adopt a non-linear assumption for appropriate estimation of seepage flow velocity.

Ultrasound Imaging Velocimetry: a review

Whole-field velocity measurement techniques based on ultrasound imaging (a.k.a. ‘ultrasound imaging velocimetry’ or ‘echo-PIV’) have received significant attention from the fluid mechanics community in the last decade, in particular because of their ability to obtain velocity fields in flows that elude characterisation by conventional optical methods. In this review, an overview is given of the history, typical components and challenges of these techniques. The basic principles of ultrasound image formation are summarised, as well as various techniques to estimate flow velocities; the emphasis is on correlation-based techniques. Examples are given for a wide range of applications, including in vivo cardiovascular flow measurements, the characterisation of sediment transport and the characterisation of complex non-Newtonian fluids. To conclude, future opportunities are identified. These encompass not just optimisation of the accuracy and dynamic range, but also extension to other application areas.

Application of entropic approach to estimate the mean flow velocity and Manning roughness coefficient in a high-curvature flume

The entropy-based approach allows the estimation of the mean flow velocity in open channel flow by using the maximum flow velocity. The linear relationship between the mean velocity, umax, and the mean flow velocity, um, through the dimensionless parameter Φ(M), has been verified both in natural rivers and in laboratory channels. Recently, the authors of this study investigated the reliability of the entropy-based formula in a straight channel and under different bed and side-walls' roughness conditions. The present study aims to further validate the entropy-based approach and to explore the effectiveness of entropy-based formula in high curvature channels. Results show that as the effect of the downstream variation of the channel's curvature the value of the parameter Φ(M) varies along the bend. When the bed deformation is evident, the variation of the parameter Φ(M) is strongly reduced compared to that obtained in absence of bed deformation. Results also show that the Manning's roughness coefficients determined through entropy-based formula are in agreement with those estimated by applying other literature's expressions but, unlike the latter, through the parameter Φ(M) the entropy-based formula could account for the effects due to the advective momentum transport by cross-circulation along the strongly curved reaches of the channel.

Correlation Between Cerebral Blood Flow Velocities Measured By Magnetic Resonance and Transcranial Doppler Ultrasound in Children with Sickle Cell Anemia

BackgroundTranscranial Doppler (TCD) ultrasonography is the standard stroke screening test for children with sickle cell anemia (SCA). However, approximately 10% of children have inadequate ultrasonographic windows for a successful TCD study, and some clinical sites may lack the equipment or personnel to perform TCDs in children. Magnetic resonance imaging (MRI) techniques can also measure blood flow velocities and could substitute for TCD in these clinical scenarios. We tested the hypothesis that MRI-derived middle cerebral artery (MCA) blood flow velocities would correlate with TCD-derived MCA blood flow velocities in children with SCA.MethodsChildren age 6 years and up with SCA at their baseline state of health underwent TCD and MRI as part of a prospective clinical study. Imaging TCD of the bilateral MCAs to determine time-average mean of maximum blood flow velocities (TCD-CBFV) were performed using clinical ultrasound equipment. MRIs were performed at 3T without sedation. MRI cerebral time-averaged mean blood flow velocities (MR-CBFV) were measured in the MCAs using phase contrast sequences without cardiac cycle gating to shorten acquisition time and reduce ghosting artifacts. TCD- and MR-CBFV of each hemisphere were compared. Silent cerebral infarctions (SCIs) were categorized as present or absent in each hemisphere. Non-parametric tests were used with a level of significance of <0.05. Statistics were performed in SPSS version 21.ResultsTwenty hemispheres from 15 children had both TCD-CBFV and MR-CBFV measurements. Median age was 9 years (IQR 6.25-10). In these children, two hemispheres had unobtainable TCDs due to skull thickness, and eight hemispheres had MR-CBFV excluded due to patient motion or poor positioning. The median TCD-CBFV was 116 cm/sec (IQR 90.25-124) and none of the included hemispheres had arterial stenosis or TCD-CBFV in the conditional or abnormal range. Eight included hemispheres were from children receiving chronic blood transfusion therapy for primary or secondary stroke prevention. There was a linear relationship between TCD-CBFV and MR-CBFV (Spearman correlation, ρ=0.781, p<0.001, Figure) although MR-CBFV values were lower than TCD-CBFV values (median difference 32.6%, IQR 26.7-42.8). When evaluating only the children not receiving chronic transfusion therapy, MR-CBFV was significantly higher in 8 hemispheres without SCIs (median 80 cm/sec, IQR 77.8-87.8) than in 4 hemispheres with SCIs (median 60 cm/sec, IQR 44.6-72.3, p=0.004). In a multivariate model adjusting for age, MR-CBFV continued to be associated with presence of SCIs (p=0.036). There was no significant difference in TCD-CBFV when analyzed by SCI status (p=0.2), consistent with published studies of TCD-CBFV and SCIs.ConclusionsIn this small cohort of children with SCA, MR-CBFV correlated significantly with TCD-CBFV, but MR-CBFV values were approximately 30% lower than TCD-CBFV. This may be due to the method of acquiring MR-CBFV via non-gated methodology, which is known to produce lower blood flow velocity estimates. Further work is needed to determine a threshold for high-risk MR-CBFV values before this modality could be used as a substitute for TCD screening. Lower MR-CBFV was associated with SCIs, suggesting a potential role for MR-CBFV in predicting SCI risk. The relationship between MR-CBFV and SCIs should be explored further. [Display omitted] DisclosuresHulbert:Pfizer, Inc.: Other: spouse employment. Fields:NeuroPhage Pharmaceuticals: Equity Ownership, Membership on an entity's Board of Directors or advisory committees.

Flow velocity estimation using a fish-shaped lateral line probe with product-moment correlation features and a neural network

Environmental studies on fish require measurements of highly turbulent flows in both the laboratory and in the field. A fish-shaped bioinspired flow measuring device is applied in conjunction with data processing workflow which leverages the interactions between the body and the surrounding flow field for velocity estimation in turbulent flows. Our objective is to develop a robust velocity estimation methodology relevant for studies of fish behavior using a bioinspired fish-shaped artificial lateral line probe (LLP). We show that the device is capable of covering the range of flow velocities from 0 to 1.5m/s. Three different sets of experiments performed in a closed flow tunnel, a model vertical slot fishway and laboratory open channel flume were collected and combined to provide time-averaged flow velocity and LLP measurements under fully turbulent flow conditions. Based on the experimental results, a signal processing workflow using Pearson product-moment correlation coefficient (PCC) features in conjunction with an artificial neural network (ANN) is presented. Using PCC features provides a simple data fusion methodology exploiting the use of the LLP's as a simultaneous collocated sensing array. In this work we show that (1) the PCC-ANN workflow provides the first LLP velocity estimator without repeated calibration across the full span of 0–1.5m/s, (2) using all pressure sensors results in the best performance with R2=0.917, but requires a PCC feature matrix of 55 dimensions and (3) a stepwise reduction of the PCC feature matrix allows for the use of as few as 11 dimensions, and results in R2=0.911, indicating that a modest reduction in LLP velocity estimation performance can be gained by a large reduction in dimensionality. A surprising finding was that after stepwise reduction, the best performing sensor pair combinations were not the expected pitot-like anteroposterior couples spanning from nose to body. Instead, it was found that optimal velocity estimation using the LLP exploited a network of sensor pairs. It is shown that the LLP can be implemented similar to an ADV for highly turbulent flows over the range of 0–1.5m/s, and in addition provides body-centric pressure distributions which may aid in the interpretation of fish hydrodynamic preferences in future environmental studies.

Estimating Retinal Blood Flow Velocities by Optical Coherence Tomography.

While optical coherence tomography (OCT) angiography has been considered to evaluate retinal capillary blood flow instead of fluorescein angiography, the reflectance pattern of blood vessels on structural OCT might also provide retinal capillary flow data in the absence of fluorescein angiography. This potential has been insufficiently explored, despite promising data concerning a possible relationship between the reflectance pattern of blood vessels and their perfusion velocity in a laboratory setting. To evaluate the potential of retinal blood flow velocity estimation by structural OCT. Cross-sectional observational study conducted from June to November 2015 at a tertiary clinical referral center. Sixty arteries (the superior and inferior temporal arteries) from 30 eyes of 30 patients (17 female, 13 male) were included in the study. Based on the intraluminal contrast patterns of retinal arteries on OCT, 3 independent graders categorized the blood flow velocities as low, medium, or high. These results and the results from a software-based intraluminal contrast analysis were compared with the retinal blood flow velocities measured by video fluorescein angiography. Among the 30 eyes of 30 patients (mean [SD] age, 72.6 [12.3] years; 17 female, 13 male), 15 were controls without retinal occlusion, 6 had a branch retinal artery occlusion, and 9 had a central retinal artery occlusion. When discriminating between low flow velocities and medium or high flow velocities, the graders' sensitivity ranged from 88.2% to 100% (grader 1: 88.2%; 95% CI, 63.6%-98.5%; grader 2: 88.2%; 95% CI, 63.6%-98.5%; and grader 3: 100%; 95% CI, 69.8%-100%) and their specificity ranged from 97.6% to 100% (grader 1: 100%; 95% CI, 87.7%-100%; grader 2: 97.6%; 95% CI, 87.4%-99.9%; and grader 3: 100%; 95% CI, 87.7%-100%). The κ coefficients of the comparison between the 3 graders and the angiography were 0.77 (95% CI, 0.60-0.93; P < .001), 0.64 (95% CI, 0.44-0.83; P < .001), and 0.87 (95% CI, 0.74-0.99; P < .001). In the computer-based assessment, the contrast reduction of the intraluminal pattern could be numerically expressed in a specific coefficient in the model (I2, describing the angular change of the backscattering intensity in the model), which presented nonoverlapping intervals between low flow velocities and medium or high flow velocities (mean [SD] I2, 0.3 [5.3], 20.4 [6.4], and 21.7 [4.0], respectively). This study suggests that a low retinal blood flow velocity reflects in a visually distinct contrast reduction of the intraluminal pattern of retinal vessels on OCT. Larger studies are required to assess the clinical benefits.

Spread-Spectrum Beamforming and Clutter Filtering for Plane-Wave Color Doppler Imaging.

Plane-wave imaging is desirable for its ability to achieve high frame rates, allowing the capture of fast dynamic events and continuous Doppler data. In most implementations of plane-wave imaging, multiple low-resolution images from different plane wave tilt angles are compounded to form a single high-resolution image, thereby reducing the frame rate. Compounding improves the lateral beam profile in the high-resolution image, but it also acts as a low-pass filter in slow time that causes attenuation and aliasing of signals with high Doppler shifts. This paper introduces a spread-spectrum color Doppler imaging method that produces high-resolution images without the use of compounding, thereby eliminating the tradeoff between beam quality, maximum unaliased Doppler frequency, and frame rate. The method uses a long, random sequence of transmit angles rather than a linear sweep of plane wave directions. The random angle sequence randomizes the phase of off-focus (clutter) signals, thereby spreading the clutter power in the Doppler spectrum, while keeping the spectrum of the in-focus signal intact. The ensemble of randomly tilted low-resolution frames also acts as the Doppler ensemble, so it can be much longer than a conventional linear sweep, thereby improving beam formation while also making the slow-time Doppler sampling frequency equal to the pulse repetition frequency. Experiments performed using a carotid artery phantom with constant flow demonstrate that the spread-spectrum method more accurately measures the parabolic flow profile of the vessel and outperforms conventional plane-wave Doppler in both contrast resolution and estimation of high flow velocities. The spread-spectrum method is expected to be valuable for Doppler applications that require measurement of high velocities at high frame rates.

Substantiation of debris flow velocity from super-elevation: a numerical approach

The use of super-elevations that a forced vortex flow leaves on the valley walls of a curved flume is a plausible approach toward estimating debris flow velocities in earthquake-induced geo-hazard studies. The centrifugal force of a speeding flow is responsible for a higher flow depth on the outer bend. However, in reality, a flow is not steady, and only the highest flow-marks are left at the outer and inner bends of the flow, which can lead to an inaccurate estimation of the actual velocity. Seeing the real scenario of the field, a series of numerical flume tests using smoothed particle hydrodynamics (SPH) is conducted to validate the estimation of debris flow velocities from flow-marks. Velocities estimated from flow-marks are lower than real velocities near the source region, but they converge to real velocities as the distance to the source increases. Based on several simulations, a best-fit line is proposed for adjusting debris flow velocity from mud-marks, and it is used to estimate flow velocities of the well-documented debris event called “Shiraito river debris flow,” which happened near the rim of the Hakone Crater, Kanagawa Prefecture, Japan, ensuing from the 1923 Great Kanto earthquake.

Micro Radar Surface Velocimetry for Hydrologic Signal Processing Using a Bandpass Filtering Approach

The collection of hydrological data is particularly important for the utilization and management of water resources, water conservation, and flood control. Most of the hydrological observation operations should be conducted manually and are time-consuming, strenuous, dangerous, and have low precision. In this study, the shortcomings of the manual observations are overcome and the uncertainties related to the radar-based flow velocity estimations by a sensor in the radar surface current meter are explored. This includes an automatic observation feature and analyses are conducted using the radar signals that are received by the instruments for the real-time observation of the signals. In this study, experiments were conducted at the Water Resources Planning Institute (WRPI) of the Water Resources Agency, Ministry of Economic Affairs, Taiwan and the surface velocity was estimated using the conventional fast Fourier transform (FFT), wavelet transform (WT), and a bandpass filter. The experimental results after signal processing using the bandpass filter were precise, when the tilt angle ranged between 20 and 40 degrees. The 10.525 GHz radar surface current meter adopted in this study is suitable for a tilt angle of 20–40 degrees; the measurement error will be relatively large if the tilt angle is less than 20 degrees or more than 40 degrees.

Transfer Matrices Analysis of FRP Pipelines Stability

A fluid-pipe interaction model is derived for estimation of critical flow velocities causing instability in multi-layered filament wound FRP pipelines resting on elastic supports. The model takes into account the anisotropic properties of the pipe’s material, the elastic properties of the pipeline’s supports and flow parameters. Using the motion equation, transfer matrices are derived for the pipeline’s spans and supports. A representative example is solved and discussed.

Flow field sensing with bio-inspired artificial hair cell arrays

The hair cell is a biological sensor that uses microscopic hair-like structures to detect delicate motions of surrounding fluid. Inspired by this principle, an artificial hair cell (AHC) sensory method based on bio-membrane transducers is developed for airflow sensing. One-dimensional arrays built from modular AHC units measure local velocity at different points in a flow profile. Each of the AHC units uses thinly extruded glass fibers as mechanical receptors of air velocity. Hair vibrations are converted to current via hydrogel-supported (lipid bilayers) by virtue of their mechanosensitive properties. The AHC outputs are combined into one channel, requiring a demultiplexing operation to recover individual hair cell information. This is achieved by tuning each AHC hair length to a unique frequency response and recovering individual sensor information based on the frequency content of the signal. The method is entitled tuned frequency response encoding (TFRE). When several AHC units are excited simultaneously by an airflow, the resulting signal is a superposition of each sensor's individual response. The excitation at each sensor is reconstructed from the frequencies that appear in the combined output. This technique was inspired by how organisms use hair cells with tuned responses to mechanically process flow stimuli. It takes advantage of a novel AHC's high signal-to-noise ratio (compared to other membrane-based AHCs) and linear output response to flow velocity. Initial tests with linear arrays of three AHCs show success in estimating the shape of the velocity profile from an air source that varies in position and intensity. However, temporal variations in some cases in membrane size affect sensitivity properties and make accurate flow velocity estimation difficult. Nevertheless, under stable conditions, the measured velocity profiles match closely with theoretical predictions. The implementation of the array sensing method demonstrates the sensory capability of bilayer-based AHC arrays, but highlights the difficulties of achieving consistent performance with biomolecular materials.

Is dynamic cerebral autoregulation measurement using transcranial Doppler ultrasound reproducible in the presence of high concentration oxygen and carbon dioxide?

Reliability of cerebral blood flow velocity (CBFV) and dynamic cerebral autoregulation estimates (expressed as autoregulation index: ARI) using spontaneous fluctuations in blood pressure (BP) has been demonstrated. However, reliability during co-administration of O2 and CO2 is unknown. Bilateral CBFV (using transcranial Doppler), BP and RR interval recordings were performed in healthy volunteers (seven males, four females, age: 54 ± 10 years) on two occasions over 9 ± 4 d. Four 5 min recordings were made whilst breathing air (A), then 5%CO2 (C), 80%O2 (O) and mixed O2 + CO2 (M), in random order. CBFV was recorded; ARI was calculated using transfer function analysis. Precision was quantified as within-visit standard error of measurement (SEM) and the coefficient of variation (CV). CBFV and ARI estimates with A (SEM: 3.85 & 0.87; CV: 7.5% & 17.8%, respectively) were comparable to a previous reproducibility study. The SEM and CV with C and O were similar, though higher values were noted with M; Bland–Altman plots indicated no significant bias across all gases for CBFV and ARI (bias <0.06 cm s−1 and <0.05, respectively). Thus, transcranial-Doppler-ultrasound-estimated CBFV and ARI during inhalation of O2 and CO2 have acceptable levels of reproducibility and can be used to study the effect of these gases on cerebral haemodynamics.