Velocity Gradient Research Articles

Right parasternal view in dobutamine stress echocardiography for aortic stenosis assessment.

Dobutamine stress echocardiography is an integral part of the evaluation of aortic stenosis (AS) severity in low-gradient AS. In transthoracic echocardiography, in 20% of the patients, the highest aortic valve peak transvalvular velocity and mean gradient are achieved with continuous wave Doppler, from the suprasternal or right parasternal view. We present a case of a 79-year-old-male, with low-gradient aortic stenosis, where the highest peak aortic valve velocity and mean gradient, were consistently obtained from the right parasternal view, during all stages of a dobutamine stress echocardiogram. Use of the right parasternal view was important in avoiding overestimation of aortic valve area and underestimation of aortic valve mean gradients and therefore AS severity at rest. Furthermore, it correctly identified significant increase of aortic valve mean gradients during stress and therefore confirmed the diagnosis of severe AS. This case report highlights the importance of routinely attempting right parasternal view, in patients undergoing stress echocardiography to ensure the maximum possible aortic valve gradient is obtained.

Surface pressure reconstruction from LPT data with boundary conforming grids

Abstract The coupling between fluid-structure interactions is governed by the pressure distribution over the interaction surface between the fluid and solid domains. The capabilities of non-intrusive optical techniques, such as particle image velocimetry and Lagrangian particle tracking (LPT), have been proven to provide accurate velocity and acceleration information within the flow field while simultaneously tracking the corresponding structural deformations. However, scattered data from LPT measurements are typically mapped onto Cartesian grids, independently of the shape of the solid objects in the measurement domain. The use of Cartesian grids poses challenges for the determination of the surface pressure because the velocity gradients close to the object’s surface are not captured accurately. Therefore, an alternative surface pressure reconstruction scheme utilizing LPT data based on the arbitrary Lagrangian–Eulerian approach is proposed to mitigate the error propagation associated with the use of uniform grids. The introduced method provides an exact surface conformation utilizing boundary fitted coordinate systems and radial basis function based mesh deformations, which eliminates the need to use extrapolations to obtain surface pressure distributions. The introduced approach is assessed by means of a synthetic hill surface probing a three-dimensional analytical flow field; its practical applicability is demonstrated through an experimental characterization of turbulent boundary layer interactions with a steadily and unsteadily deforming elastic membrane.

Cationic tannins as aggregation agents in the flocculation on hematite–silica system

ABSTRACT This study aims to evaluate the use of commercial tannin derivatives, namely, tannin 1 (CT1), tannin 2 (CT2), tannin 3 (CT3), and extract of tannin produced from angico bark, as aggregation agent in hematite–silica systems. Hematite and quartz were used in aggregation tests at dosages of 1, 10, and 100 mg/L at pH values of 6–9. The zeta potential and Jar tests were conducted in the best conditions of aggregation tests. The condensed tannin content of the commercial reagents is approximately similar, and it exceeds the content found in the extract obtained from angico bark. CT3 demonstrated superior percentages of sedimented material for both minerals at a dosage of 10 mg/L and pH 7 (97.12% and 95.68% for hematite and quartz, respectively). The aggregation agent produced from the angico bark displayed good sedimentation results for hematite (>90%); however, the results for quartz were unsatisfactory. The isoelectric point shifts to pH 8 when each mineral was conditioned with CT3. The jar test revealed higher sedimentation of the compositions for the lowest velocity gradient (60 rpm) with low turbidity values in the supernatant; however, the lowest turbidity (24.71 NTU) is observed in the sample with a higher percentage of hematite.

Exploration of the dynamics of heated non-Newtonian Casson fluid within an annular region of eccentric cylinders subject to peristaltic motion

The flow of non-Newtonian fluids is widely observed in industry and biology, for example, enhanced oil recovery, chemical processes such as in distillation towers and fixed-bed reactors and in the applications of pumping fluids such as synthetic lubricants, colloidal fluids, liquid crystals, and biofluids (e.g., animal and human blood). Therefore, the present study delineates the heat transfer analysis of a Casson fluid within the annular region of eccentric cylinders subjected to peristaltic motion, considering the influence of thermal radiation. The outer cylinder remains rigid and moves at a constant speed, while the inner cylinder, featuring a sinusoidal wave along its wall, exhibits flexibility. The governing two-dimensional equations for the movement of the Casson fluid are reformulated under the assumption of the lubrication hypothesis. The perturbation scheme is used to find approximate results for velocity, temperature, and pressure gradient. A graphical representation is utilized to study the fluctuation of various flow fields with different imperative parameters. The results reveal that the liquid velocity declines as the Casson parameter increases, while the temperature decreases due to the amplified effect of thermal radiation. This study has applications in endoscopy, which is important for diagnosing problems in internal organs. Additionally, the variation of the pressure gradient helps maintain the flow rate, which is essential during the insertion of a catheter into an artery.

Inelastic fluid models with an objective stretch rate parameter

This paper presents an extension to the Generalized Newtonian Fluid (GNF) model, where the effects of different flow modes can be discerned. While existing GNF models have proven valuable in simulating processes like molding and extrusion, they often struggle to differentiate between distinct flow modes such as planar extension and simple shear. To address this challenge, we propose a modified GNF model that integrates an objective flow-type parameter, aiming to refine flow characterization. Emphasis is placed on defining the flow-type parameter to be able to transcend viscometric flows, remain frame-indifferent, quantify deformation magnitude, and differentiate between diverse flow modes. Inspired by the new advances in vortex identification in turbulent flow, we introduce a new stretch rate tensor and a new stretch rate parameter that are derived from the real Schur form of the objective velocity gradient tensor. These elements are embedded into the constitutive modeling of non-Newtonian fluid flow. The resulting model is employed to fit polymer melt data from the literature, demonstrating excellent fitting to combined shear and extension data. The basic model uses 5 to 6 parameters for data fitting, and further enhancement may be achieved by incorporating other extracted information of the stretch rate tensor.

Accretion versus core-filament collision. Implications for streamer formation in Per-emb-2

Recent millimetre and sub-millimetre observations have unveiled elongated and asymmetric structures around protostars. These structures, referred to as streamers, often exhibit coherent velocity gradients, seemingly indicating a directed gas flow towards the protostars. However, their origin and role in star formation remain uncertain. The protostellar core Per-emb-2, located in Barnard 1, has a relatively large streamer of $10^4$ au that is more prominent in emission from carbon-chain molecules. We aim to unveil the formation mechanism of this streamer. We conducted mapping observations towards Per-emb-2 using the Nobeyama 45 m telescope. We targeted carbon-chain molecular lines such as CCS, HC$_3$N, and HC$_5$N at 45 GHz. Using astrodendro we identified one protostellar and four starless cores, including three new detections, on the Herschel column density map. The starless and protostellar cores are more or less gravitationally bound. We discovered strong CCS and HC$_3$N emissions extending from the north to the south, appearing to bridge the gap between the protostellar core and the starless core to its north. This bridge spans $3 10^4$ au with velocities of 6.5 to 7.0 km $. The velocity gradient of the bridge is opposite that of the streamer. Thus, the streamer is unlikely to be connected to the bridge, suggesting that the former does not have an accretion origin. We propose that a collision between a spherical core and the filament has shaped the density structure in this region, consequently triggering star formation within the head-tail-shaped core. In this core-filament collision scenario, the collision appears to have fragmented the filament into two structures. The streamer is a bow structure, while the bridge is a remnant of the shock-compressed filament. Thus, we conclude that the Per-emb-2 streamer does not significantly contribute to the mass accumulation towards the protostar.

Molecular clouds as hubs in spiral galaxies: gas inflow and evolutionary sequence

ABSTRACT We decomposed the molecular gas in the spiral galaxy NGC 628 (M74) into multiscale hub-filament structures using the CO (2$-$1) line by the dendrogram algorithm. All leaf structures as potential hubs were classified into three categories, i.e. leaf-HFs-A, leaf-HFs-B and leaf-HFs-C. Leaf-HFs-A exhibit the best hub-filament morphology, which also have the highest density contrast, the largest mass and the lowest virial ratio. We employed the filfinder algorithm to identify and characterize filaments within 185 leaf-HFs-A structures, and fitted the velocity gradients around the intensity peaks. Measurements of velocity gradients provide evidence for gas inflow within these structures, which can serve as a kinematic evidence that these structures are hub-filament structures. The numbers of the associated 21 μm and H α structures and the peak intensities of 7.7 μm, 21 μm, and H α emissions decrease from leaf-HFs-A to leaf-HFs-C. The spatial separations between the intensity peaks of CO and 21 μm structures of leaf-HFs-A are larger than those of leaf-HFs-C. These evidence indicate that leaf-HFs-A are more evolved than leaf-HFs-C. There may be an evolutionary sequence from leaf-HFs-C to leaf-HFs-A. Currently, leaf-HFs-C lack a distinct gravitational collapse process that would result in a significant density contrast. The density contrast can effectively measure the extent of the gravitational collapse and the depth of the gravitational potential of the structure which, in turn, shapes the hub-filament morphology. Combined with the kinematic analysis presented in previous studies, a picture emerges that molecular gas in spiral galaxies is organized into network structures through the gravitational coupling of multiscale hub-filament structures. Molecular clouds, acting as knots within these networks, serve as hubs, which are local gravitational centres and the main sites of star formation.

Numerical Simulation of the Unsteady Airwake of the Liaoning Carrier Based on the DDES Model Coupled with Overset Grid

The wake behind an aircraft carrier under heavy wind condition is a key concern in ship design. The Chinese Liaoning ship’s upturned bow and the island on the deck could cause serious flow separation in the landing and take-off area. The flow separation induces strong velocity gradients and intense pulsations in the flow field. In addition, the sway of the aircraft carrier caused by waves could also intensify the flow separation. The complex flow field poses a significant risk to the shipboard aircraft take-off and landing operation. Therefore, accurately predicting the wake of an aircraft carrier during wave action motion is of great interest for design optimization and recovery aircraft control. In this research, the aerodynamic around an aircraft carrier (i.e., Liaoning) was analyzed using the computational fluid dynamics technique. The validity of two turbulence models was verified through comparison with the existing data from the literature. The upturned bow take-off deck and the right-hand island were the main areas where flow separation occurred. Delayed detached eddy simulation (DDES), which combines the advantages of LES and RANS, was adopted to capture the full-scale spatial and temporal flow information. The DDES was also coupled with the overset grid to calculate the flow field characteristics under the effect of hull sway. The downwash area at 15° starboard wind became shorter when the hull was stationary, while the upwash area and turbulence intensity increased. The respective characteristics of the wake flow field in the stationary and swaying state of the ship were investigated, and the flow separation showed a clear periodic when the ship was swaying. Comprehensive analysis of the time-dependent flow characteristic of the approach line for fixed-wing naval aircraft is also presented.

Viscosity of Asphalt Binder through Equilibrium and Non-Equilibrium Molecular Dynamics Simulations

Viscosity is a curial indicator for evaluating asphalt performance, representing its ability to resist deformation under external forces. The Green–Kubo integral in equilibrium molecular dynamics simulations and the Muller-Plathe algorithm in reverse non-equilibrium molecular dynamics simulations were used to calculate the asphalt viscosity. Meanwhile, the key parameters of both methods were rationalized. The results show that in equilibrium calculations, using a 1/t weighting for the viscosity integral curve results in a well-fitted curve that closely matches the original data. The isotropy of the asphalt model improves for atomic counts exceeding 260,000, rendering viscosity calculations more reasonable. When the viscosity did not converge, it increased linearly with the number of atoms. In non-equilibrium calculations, the number of region divisions had almost no effect on the viscosity value. A momentum exchange period of 20 timesteps exhibits a favorable linear trend in velocity gradients, and an ideal momentum exchange period was found to be between 10 and 20 timesteps. As the model size increased, the linear relationship with the shear rate became more pronounced, and the isotropy of the asphalt system improved. Using an orthogonal simulation box with a side length of 75 Å effectively meets the computational requirements.

IMPROVEMENT OF OPERATION AND RESEARCH METHODOLOGY OF THE HYDRAULIC FLAKE FORMATION CHAMBER FOR DRINKING WATER SUPPLY

Ukraine’s surface water sources are unsatisfactory due to pollution caused by industrial and agricultural activities and the Russian invasion. As the natural water quality deteriorates, the treatment plant’s efficiency in preparing drinking water for the population’s needs decreases. The hydraulic flake formation chamber allows for physicochemical processes that produce large and solid flakes of metal hydroxides with impurities that quickly settle and are then removed from the water. This study aims to develop a methodology for experimental research on the new design of a swirl-vortex flake formation chamber that intensifies the water purification process in the domestic and drinking water supply systems. The proposed design of the swirl-vortex chamber has dimensions of 0.75×2.0 m and a height of 0.65 m. Due to the installation in the first section of 4 fittings with nozzles, two pieces on each pipe, and in the second section, six fittings with nozzles, three pieces on each pipe with a diameter of 6–10 mm, it is possible to increase the effect of water illumination. The authors performed hydraulic modelling following the Reynolds criterion (Re) and the Froude criterion (Fr). We conducted experiments using artificial turbidity water. White-blue clay was used as a turbidant because it contains more small particles than the white-green one. We decided to model flake formation chambers according to the Froude criterion (Fr). Modelling according to the Reynolds criterion leads to such large velocity gradients that it simply does not make sense to talk about flake formation processes. We carried out the second series of experiments to obtain a qualitative assessment of the swirl-vortex chamber’s work in forming flakes by studying the deposition of flakes at different velocity gradients and angles of inclination of the nozzles. The best effect of lightening the water in the flake formation chamber occurs at a nozzle inclination angle of 45° to the bottom. The best effect of water clarification happens at a velocity gradient of about 60 s-1 and the water residence time in the flake formation chamber of 200–300 s. Keywords: water treatment, intensification, flake formation chamber, drinking water supply.

Scaling laws of velocity gradient moments of attached eddies

Scaling laws of velocity gradient moments of attached eddies

Improved elastic full‐waveform inversion of ocean bottom node data

AbstractElastic full‐waveform inversion enables the quantitative inversion of multiple subsurface parameters, significantly enhancing the interpretation of subsurface lithology. Simultaneously, with the ongoing advancements in ocean bottom node technology, the application of elastic full‐waveform inversion to marine ocean bottom node data is receiving increasing attention. This is attributed to the capability of ocean bottom node to acquire high‐quality four‐component data. However, elastic full‐waveform inversion of ocean bottom node data typically encounters two challenges: First, the presence of low S‐wave velocity layers in the seabed leads to weak energy of converted S‐waves, resulting in significantly poorer inversion results for S‐wave velocity compared to those for P‐wave velocity; second, the cross‐talk effect of multiple parameters further exacerbates the difficulty in inverting S‐wave velocity. To effectively recover the S‐wave velocity using ocean bottom node data, we modify the S‐wave velocity gradient in conventional elastic full‐waveform inversion to alleviate the impact of cross‐talk from multiple parameters on the inversion of S‐wave velocity. Furthermore, to invert for density parameters, we adopt a two‐stage inversion strategy. In the first stage, P‐wave and S‐wave velocities are updated simultaneously with a single‐step length. Because the initial density model is far from the true one, density is updated using an empirical relationship derived from well‐log data. In the second stage, velocities and density are updated simultaneously with multi‐step length to further refine the models obtained in the first stage. The high effectiveness of the improved elastic full‐waveform inversion is validated by numerical examples.

Analysis of the influence of the daily regulation of power stations on navigable flow conditions at river confluences using the LSTM model

The daily operations of large hydropower stations on rivers induce frequent variations in downstream water levels and flow velocities, resulting in unsteady and complex hydraulic characteristics at the confluence of the main stream and its tributaries, which adversely affect navigation safety. The continuity and momentum equations, along with the RNG k-ϵ turbulence model and the VOF model, were employed to simulate the river flow process at the confluence under unsteady flow conditions. The simulated results for water levels and velocity vector fields are in good agreement with experimental data. Variations in hydraulic characteristics, including water level, flow velocity, and longitudinal gradient at the confluence of the main stream and its tributaries, were analysed. The results indicated that the water level at the confluence decreases when the tributary merges with the main stream. As the confluence ratio increases, fluctuations in the water level at the confluence decrease. However, an increase in the staggered period results in greater fluctuations in the water level within this region. Moreover, a crescent-shaped high-speed flow region is formed at the confluence of the tributary and the main stream. As the unsteady flow discharge of the main stream increases, the relative area of this region correspondingly enlarges, reaching its maximum at peak discharge, and subsequently gradually diminishes as the discharge decreases. Based on these simulation data, a Long Short-Term Memory (LSTM) model was developed to effectively predict water levels and flow velocities, providing a more convenient and accurate method for obtaining real-time information on confluence areas than traditional mathematical and statistical approaches. This study provides novel insights into predicting flow characteristics in confluence areas, thereby offering a basis for formulating navigation safety plans.

The calculation method of blood flow pressure based on four-dimensional flow magnetic resonance imaging and deep learning

Utilizing artificial intelligence methods for blood flow pressure estimation can significantly enhance the computational speed of blood flow pressure. However, current related research can only calculate the blood flow pressure parameters of vessels with different geometric shapes under fixed boundary conditions, thus fail to achieve transient flow field calculation and consider the hemodynamic differences formed by patients' varying physiological and pathological conditions. In view of this, this study proposes a method for relative pressure estimation based on four-dimensional flow magnetic resonance imaging (4D flow MRI) of patient blood flow and deep learning. 4D flow MRI was used to obtain the patient's blood flow velocity gradient data, and feature engineering processing is performed on the sampled data. Then, a novel neural network was proposed to acquire the characteristic relationship between velocity gradient and pressure gradient in the vicinity of the point to be measured and within adjacent sampling time periods, thereby achieving the calculation of the relative pressure in the vicinity of the point to be measured. Statistical analysis was performed to evaluate the efficacy of the method, comparing it with computational fluid dynamics methods and catheter pressure measurement techniques. The accuracy of the proposed method exceeded 96%, while computational efficiency was improved by several tens of times, and no manual setting of physiological parameters was required. Furthermore, the results were compared with clinical catheter-measured pressure results, r2 = 0.9053, indicating a significant consistency between the two methods. Compared to previous research, the method proposed in this study can take the blood flow velocity conditions of different patients at different times as input features via 4D flow MRI, thus enabling the calculation of pressure in transient flow fields, which significantly improved computational efficiency and reduced costs while maintaining a high level of calculation accuracy. This provides new direction for future research on machine learning prediction of blood flow pressure.

Deep-learning optimization using the gradient of a custom objective function: A full-waveform inversion example study on the convolutional objective function

The integration of conventional high-performance full-waveform inversion (FWI) algorithms with deep-learning frameworks is an innovative and promising research direction with the potential to enhance and broaden the application prospects of this field significantly. Automatic differentiation with backpropagation techniques can derive the gradients of model parameters in an equivalent manner to that of adjoint methods; however, it requires a substantial amount of computer memory, particularly when considering the time-step layers. In addition, some excellent objective functions suitable for FWI are not available in deep-learning frameworks. In comparison, the adjoint method, based on effective boundary storage technology, offers greater practicality for calculating the gradients of various objective functions. Therefore, this paper develops a novel approach toward FWI that integrates deep-learning optimization with high-performance gradient computation. In particular, our method inputs model parameter gradients from a custom objective function into the deep-learning framework. Herein, we use the acoustic equation with variable density as an example to demonstrate how a convolutional objective function, along with its corresponding velocity and density gradients, can be used for optimized inversion, multiscale inversion, and deep network parameterization-based multiscale inversion within the deep-learning framework. This approach provides a paradigm for deep-learning-optimized FWI, which we apply to synthetic and field data scenarios.

Modified RNN for Solving Comprehensive Sylvester Equation With TDOA Application.

The augmented Sylvester equation, as a comprehensive equation, is of great significance and its special cases (e.g., Lyapunov equation, Sylvester equation, Stein equation) are frequently encountered in various fields. It is worth pointing out that the current research on simultaneously eliminating the lagging error and handling noises in the nonstationary complex-valued field is rather rare. Therefore, this article focuses on solving a nonstationary complex-valued augmented Sylvester equation (NCASE) in real time and proposes two modified recurrent neural network (RNN) models. The first proposed modified RNN model possesses gradient search and velocity compensation, termed as RNN-GV model. The superiority of the proposed RNN-GV model to traditional algorithms including the complex-valued gradient-based RNN (GRNN) model lies in completely eliminating the lagging error when employed in the nonstationary problem. The second model named complex-valued integration enhanced RNN-GV with the nonlinear acceleration (IERNN-GVN) model is proposed to adapt to a noisy environment and accelerate the convergence process. Besides, the convergence and robustness of these two proposed models are proved via theoretical analysis. Simulative results on an illustrative example and an application to the moving source localization coincide with the theoretical analysis and illustrate the excellent performance of the proposed models.

Fish-inspired tracking of underwater turbulent plumes

Autonomous ocean-exploring vehicles have begun to take advantage of onboard sensor measurements of water properties such as salinity and temperature to locate oceanic features in real time. Such targeted sampling strategies enable more rapid study of ocean environments by actively steering towards areas of high scientific value. Inspired by the ability of aquatic animals to navigate via flow sensing, this work investigates hydrodynamic cues for accomplishing targeted sampling using a palm-sized robotic swimmer. As proof-of-concept analogy for tracking hydrothermal vent plumes in the ocean, the robot is tasked with locating the center of turbulent jet flows in a 13,000-liter water tank using data from onboard pressure sensors. To learn a navigation strategy, we first implemented RL on a simulated version of the robot navigating in proximity to turbulent jets. After training, the RL algorithm discovered an effective strategy for locating the jets by following transverse velocity gradients sensed by pressure sensors located on opposite sides of the robot. When implemented on the physical robot, this gradient following strategy enabled the robot to successfully locate the turbulent plumes at more than twice the rate of random searching. Additionally, we found that navigation performance improved as the distance between the pressure sensors increased, which can inform the design of distributed flow sensors in ocean robots. Our results demonstrate the effectiveness and limits of flow-based navigation for autonomously locating hydrodynamic features of interest.

Molecular gas excitation in the circumgalactic medium of MACS1931–26

The evolution of galaxies is largely affected by exchanging material with their close environment, the circumgalactic medium (CGM). In this work, we investigate the CGM and the interstellar medium (ISM) of the bright central galaxy (BCG) of the galaxy cluster, MACS1931−26 at z ∼ 0.35. We detected [CI](2−1), 12CO(1−0), and 12CO(7−6) emission lines with the APEX 12-m and NRO 45-m telescopes. We complemented these single-dish observations with 12CO(1−0), 12CO(3−2), and 12CO(4−3) ALMA interferometric data and inferred the cold molecular hydrogen physical properties. Using a modified large velocity gradient (LVG) model, we modelled the CO and CI emission of the CGM and BCG to extract the gas thermodynamical properties, including the kinetic temperature, the density, and the virialisation factor. Our study shows that the gas in the BCG is highly excited, comparable to the gas in local ultra luminous infrared galaxies (ULIRGs), while the CGM is likely less excited, colder, less dense, and less bound compared to the ISM of the BCG. The molecular hydrogen mass of the whole system derived using [CI](2−1) is larger than the mass derived from 12CO(1−0) in literature, showing that part of the gas in this system is CO-poor. Additional spatially resolved CI observations in both transitions, [CI](1−0) and [CI](2−1), and the completion of the CO SLED with higher CO transitions are crucial to trace the different phases of the gas in such systems and constrain their properties.

Effect of hills on wind turbine flow and power efficiency: A large-eddy simulation study

This study investigates the influence of topography on wind turbine flow and power efficiency. Specifically, a standalone wind turbine is positioned at the top of idealized two-dimensional hills, and the effects of hill geometry and turbine position are systematically investigated. Various parameters are studied, including hill slope, distance between the leeward side of the hill and the turbine, turbine hub height, and hill size. Overall, it is observed that the turbine wake is consistently stronger in the hill cases compared to the flat case. This is attributed to two characteristics of hill flows: (1) the negative streamwise velocity gradients on the leeward side of the hills and (2) the reduced turbulence above the hilltops and hill wake regions. In addition, it is observed that the turbine induction factor is consistently increased in the hill cases compared to the flat case, while the turbine power and thrust coefficients are reduced. In practice, this means that turbines on the hills produce less power output than those on flat terrain for an equivalent wind potential, with the potential decrease in power output reaching more than 20% for certain cases. Altogether, the results offer new insights into the effect of topography on turbine power efficiency. In addition, the study identifies clear relationships between the turbine power coefficient, the induction factor, the overall maximum deficit, and the base flow pressure gradient. These relationships could potentially be used to predict the change in power efficiency based on the wake flow or the base flow. Overall, the results show a clear connection between the turbine power efficiency and the turbine wake development.

Comment on: "Anomalous reflection from a two-layered marine sediment" [J. Acoust. Soc. Am. 155, 1285-1296 (2024)] (L).

Buckingham [(2024). J. Acoust. Soc. Am. 155, 1285-1296] analyzed the dependence of the reflection coefficient on the grazing angle in two-layer marine sediment model. The upper layer in his model consists of a fine-grained material (mud), while seawater and the basement below the mud layer are treated as homogeneous halfspaces. Buckingham's analyses revealed several narrow spikes in this dependence that appeared only in the presence of a sound velocity gradient in the mud layer, a phenomenon he called acoustic glint. His derivation was accomplished for certain specific dependencies of the sound velocity on the depth. Surprisingly, the authors appear to reach the conclusion that for a slightly different vertical sound speed profile in the mud layer the spikes are no longer present in the dependence of the reflection coefficient on the grazing angle. More precisely, the same problem is examined in this letter for the case of an n2-linear layer (often called Airy medium). Acoustic glint effect is therefore very sensitive to the exact parametrization of the mud layer.