Three-dimensional Velocity Research Articles

3D mapping of the stiffness evolution of SAP concrete through elastic wave tomography

ABSTRACT Early-stage phenomena during concrete curing greatly influence its final mechanical properties, making hydration monitoring crucial. Non-destructive techniques have, therefore, gained great attention for early-age concrete assessment. This study examines the elastic wave velocity and stiffness development of hardening concrete cubes using elastic wave tomography (EWT) at different curing stages. Simultaneously, ultrasonic pulse velocity (UPV) measurements with a pseudorandom noise (PRN) pulse are performed and compared to a standardized UPV device. Monitoring begins 7 hours after mixing and continues until 70 hours. A three-dimensional (3D) velocity map compares conventional concrete with concrete containing superabsorbent polymers (SAPs), a shrinkage-reducing admixture. SAPs reduce the compressive strength of concrete by increasing the porosity, affecting the elastic wave velocity evolution. However, internal curing by SAPs promotes hydration product formation, partially offsetting strength loss. EWT provides global insights into SAP uniformity across specimens, contrasting with traditional single-path UPV measurements. Furthermore, early-age stiffness evolution, linked to UPV, is a good indicator of final mechanical properties. Results show that SAP concrete exhibits slower 3D stiffness development than conventional concrete but supports hydration over a longer period. Continuous wavelet transform (CWT) analysis of PRN signals shows prolonged signal transmission development, indicating a more thorough hydration evolution in SAP concrete.

Three-dimensional velocity fields measurement of bulge structure observed in a cavity via particle tracking velocimetry

Three-dimensional velocity fields measurement of bulge structure observed in a cavity via particle tracking velocimetry

Resolving three-dimensional wind velocity fields with sequential wind-Doppler LiDAR for wind energy in the complex terrain - Gotthard Pass, Switzerland

Background Understanding the effects of the complex terrain on wind turbines in alpine regions requires high-resolution computational modelling accompanied by detailed wind observations. In technologically advanced measurement campaigns, often multiple synchronised wind-Doppler LiDARs are deployed to overcome the limitation of these instruments to only measure line-of-sight velocity. Methods In this work, a novel deployment method, a sequential wind-Doppler LiDAR deployment is introduced. We present the example of a field campaign on the Gotthard Pass, a narrow north-south permutated high-mountain pass in the central Swiss Alps. We propose a matching algorithm that can robustly group wind profiles, enabling comparable scientific detail to study turbine efficiency as in synchronised triple LiDAR campaigns, whilst only requiring a single LiDAR instrument to be deployed. Results In the three-month study period in the summer of 2023, we successfully used turbulence kinetic energy, wind shear and veer, as well as wind channelling to explain turbine power production discrepancies observed in the five turbines erected on a mountain pass.

Simulation of dynamic response changes in curved river flow under landslide-induced surge wave influence

This article uses a three-dimensional loose rock landslide surge model test in shallow water areas under dynamic water conditions to study the dynamic response characteristics of river flow. Based on the observation of the changes in the flow field and morphology of the river surface before and after the landslide body enters the water using a large-scale surface flow field measurement system, the changes in the river flow conditions under the influence of landslide surges are divided into four main stages: normal water flow state, landslide inflow disturbance state, wave current coupling motion state, and accumulation body ejection state. According to the acoustic Doppler velocimeter flowmeter arranged at the intersection of the initial surge waveform centerline and the mainstream flow direction, the three-dimensional velocity time-domain process near the water surface is measured and analyzed. Based on different cross sections and measuring points in the landslide area and its upstream and downstream, a non-steady flow propeller flowmeter and an ultrasonic wave/water level acquisition analyzer were arranged to measure and reveal the longitudinal and transverse flow velocity distribution and water surface line variation of the river under the influence of landslide surge.

Analysis of the measurement uncertainty for a 3D wind lidar

Abstract. High-resolution three-dimensional (3D) wind velocity measurements are of major importance for the characterization of atmospheric turbulence. The use of a multi-beam wind lidar focusing on a measurement volume from different directions is a promising approach for obtaining such wind data. This paper provides a detailed study of the propagation of measurement uncertainty of a three-beam wind lidar designed for mounting on airborne platforms with geometrical constraints that lead to increased measurement uncertainties of the wind components transverse to the main axis of the system. The uncertainty analysis is based on synthetic wind data generated by an Ornstein–Uhlenbeck process as well as on experimental wind data from airborne and ground-based 3D ultrasonic anemometers. For typical atmospheric conditions, we show that the measurement uncertainty of the transverse components can be reduced by about 30 %–50 % by applying an appropriate post-processing algorithm. Optimized post-processing parameters can be determined in an actual experiment by characterizing measured data in terms of variance and correlation time of wind fluctuations, allowing for the optimized design of a multi-beam wind lidar with strong geometrical limitations.

Inferring in vivo murine cerebrospinal fluid flow using artificial intelligence velocimetry with moving boundaries and uncertainty quantification.

Cerebrospinal fluid (CSF) flow is crucial for clearing metabolic waste from the brain, a process whose dysregulation is linked to neurodegenerative diseases like Alzheimer's. Traditional approaches like particle tracking velocimetry (PTV) are limited by their reliance on single-plane two-dimensional measurements, which fail to capture the complex dynamics of CSF flow fully. To overcome these limitations, we employ artificial intelligence velocimetry (AIV) to reconstruct three-dimensional velocities, infer pressure and wall shear stress and quantify flow rates. Given the experimental nature of the data and inherent variability in biological systems, robust uncertainty quantification (UQ) is essential. Towards this end, we have modified the baseline AIV architecture to address aleatoric uncertainty caused by noisy experimental data, enhancing our measurement refinement capabilities. We also implement UQ for the model and epistemic uncertainties arising from the governing equations and network representation. Towards this end, we test multiple governing laws, representation models and initializations. Our approach not only advances the accuracy of CSF flow quantification but also can be adapted to other applications that use physics-informed machine learning to reconstruct fields from experimental data, providing a versatile tool for inverse problems.

Large-scale reorientation in cubic Rayleigh–Bénard convection measured with particle tracking velocimetry

Three-dimensional velocity fields of a large-scale reorientation in turbulent Rayleigh–Bénard convection at Ra = 2.5 ⋅ 10 9 in a 300 mm cubic water cell are measured using particle tracking velocimetry. Reorientations are rare events occurring about once every three days in our setup, involve the large-scale circulation switching between cell diagonals. The dominant flow structures of the reorientation are extracted from the measurement data using POD supported by symmetries of the cubic cell to mimic long time series of reorientation events. The decomposition reveals degenerate mode pairs. The first six modes of the decomposition account for about 70% of the total energy and contain the major coherent structures. Modes 1-3 reflect the orientation and dynamics of the large-scale circulation, and modes 4-6 provide the orientation and dynamics of the corner circulations. A pure Y roll structure is observed in the middle of the reorientation event.

Crust and uppermost mantle S-wave velocity structure of the Wudalianchi volcanic belt from direct surface-wave tomography

The Wudalianchi volcanic belt is located at the junction among the Greater Xing’an range, the Lesser Xing’an range, and the Songliao basin. Investigation of detailed crustal velocity structure under the Wudalianchi volcanic belt is of great significance to better understand the deep geodynamics of Northeast Asia. Applying the direct surface-wave tomography method to ambient noise records of our newly deployed dense WAVESArray stations from 2015 to 2019, we aim to determine a high-resolution three-dimensional (3-D) S-wave velocity (Vs) model of the crust and uppermost mantle down to 45 km depth beneath the Wudalianchi volcanic belt and surrounding areas. The WAVESArray stations have good azimuthal coverage around the Wudalianchi volcano. Our high-resolution tomographic model reveals low-Vs anomalies in the upper crust and the uppermost mantle beneath the Wudalianchi volcano and high-Vs anomalies in the mid-lower crust, indicating the presence of hot mantle upwelling and lower crust cooling solidification. This upwelling process is related to the complex dynamics of the big mantle wedge that has developed above the subducted Pacific slab that is stagnant in the mantle transition zone beneath East Asia. In addition, low-Vs anomalies are visible beneath the Erkeshan, Wudalianchi, Keluo, and Xunke volcanoes in the upper crust and they are connected with a low-Vs layer in the mid-lower crust, which provides a new piece of seismological evidence for the homology of these volcanoes, suggesting that there might be exchanges of material and energy between these volcanoes.

Turbulent flow structure around a single submerged angled spur dike under ice cover

Abstract This experimental study examines the velocity fields around the single submerged spur dike in a large-scale flume under three flow conditions: open channel, smooth ice-covered, and rough ice-covered. The effects of dike orientation were investigated for alignment angles of 90°, 120°, and 135°. Instantaneous three-dimensional velocity components were recorded using an acoustic Doppler velocimeter. Results show that the spur dikes generate distinct transverse flow regions in the streamwise, lateral, and vertical directions. Alignment angles greater than 90° reduced streamwise velocity near the dikes, while the frontal surface of the dike tip exhibited increased velocity magnitudes. Downstream, significant variations in Reynolds shear stress were observed, driven by flow separation and the formation of a recirculation wake zone. Quadrant analysis revealed that under ice-covered conditions, turbulent interactions near the dike tip were dominated by ejection and sweep events, whereas sweep events were more prevalent in open channel flows, influencing overall flow dynamics.

Reconstruction of unstable atmospheric surface layer streamwise turbulence based on multi-layer perceptron neural network architecture

The accurate simulation of sand-laden turbulence under different stratification stabilities remains a critical challenge in turbulence research. This study presents an innovative approach to reconstructing streamwise turbulence in an unstable atmospheric surface layer (ASL) using a multi-layer perceptron (MLP) neural network architecture. Leveraging high-resolution measurements of three-dimensional wind velocity and temperature from multiple observational sites, the study develops prediction models for streamwise wind velocity at varying heights in the unstable ASL. The predictive model integrates large-scale motions (LSMs) generated by the MLP, small-scale motions (SSMs) derived from the Kaimal spectrum, and mean wind velocity, providing a comprehensive representation of turbulence. The impact of sand content and stratification stability on model performance is analyzed, with discussion highlighting the model's strengths and limitations under weak instability conditions. Validation is conducted through cross-site comparison, statistical analysis, and power spectrum assessment, demonstrating the model's ability to capture the temporal and spectral characteristics of wind velocity in sand-laden, unstable ASL conditions. The study also reveals that, under weak instability, shear forces dominate the formation of coherent structures, while buoyancy effects enhance vertical mixing as instability increases. Compared to existing models, the proposed prediction model is applicable over a broader range of conditions, offering a valuable data source for the study of atmospheric sand-laden turbulence and serving as a reference for practical sand control projects.

Three-dimensional velocity structure of the MS 6.0 Luxian earthquake source region and adjacent areas based on a dense seismic array

On September 16, 2021, an MS 6.0 earthquake struck Luxian County in the Sichuan basin. To investigate the regional velocity structure and its relationship with seismic activity, we gathered seismic phase data from permanent stations for events occurring between January 2009 and April 2021 as well as data from a dense mobile seismic array that operated from April 2021 to July 2023. Utilizing Double-Difference tomography, we have determined well-constrained earthquake relocations and have derived a detailed 3D velocity structure. Many of the earthquakes exhibit linear clustering patterns, with an average depth of 4.3 km and a NE-SW orientation. Approximately 96 % of the seismic events occurred within a depth range of 0–7 km. The early aftershock sequence of the Luxian event also displayed a linear trend, with a length of 6 km but with an ESE orientation. The mainshock occurred at a depth of 6.2 km, located at the northwestern end of the aftershock sequence. The aftershock sequence along with other linear seismic clusters, predominantly occurred within regions characterized by high seismic velocities and low Poisson's ratios, both within the sedimentary cover above the crystalline basement. The heterogeneity of the velocity structure likely plays a significant role in controlling the occurrence of moderate-to-strong earthquakes in the deeper parts of the study region, which deepens the existing understanding from previous research: pre-existing faults, their scales, and their slip-tendencies under the present-day regional and reservoir-scale stress fields are also controlling factors for induced earthquakes, especially larger ones. We have identified five areas where moderate-to-strong earthquakes are speculated to have a higher likelihood of occurrence. These findings hold considerable importance for local seismic hazard assessments.

Characterizing the contact force of a high-speed rotating fluid on brush wire

Abstract To study the effect of coolant fluid on rotor-brush wire contact in high-speed conductive slip rings, the rotor-brush wire contact model is simplified to two cylindrical vertical contacts. The theoretical formula of the force on the near-wall surface of the brush wire is derived by combining the distribution of the characteristics of the cylindrical rotating fluid domain. A three-dimensional model of high-speed rotor-brush wire fluid-solid coupling is created. The initial preload and coolant disturbance on the near-wall surface of the brush wire is considered to analyze the force characteristics of the brush wire. The force characteristics of the near-wall surface and the three-dimensional surface velocity cloud diagram of the fluid domain are obtained. The results show that the growth rate of the fluid domain force on the wall surface of the brush wire increases with the increase of rotational speed. A change of only 0.5 mm near the wall leads to a change of nearly 40% in the speed.

Physics-informed data-driven reconstruction of turbulent wall-bounded flows from planar measurements

Obtaining accurate and dense three-dimensional estimates of turbulent wall-bounded flows is notoriously challenging, and this limitation negatively impacts geophysical and engineering applications, such as weather forecasting, climate predictions, air quality monitoring, and flow control. This study introduces a physics-informed variational autoencoder model that reconstructs realizable three-dimensional turbulent velocity fields from two-dimensional planar measurements thereof. Physics knowledge is introduced as soft and hard constraints in the loss term and network architecture, respectively, to enhance model robustness and leverage inductive biases alongside observational ones. The performance of the proposed framework is examined in a turbulent open-channel flow application at friction Reynolds number Reτ=250. The model excels in precisely reconstructing the dynamic flow patterns at any given time and location, including turbulent coherent structures, while also providing accurate time- and spatially-averaged flow statistics. The model outperforms state-of-the-art classical approaches for flow reconstruction such as the linear stochastic estimation method. Physical constraints provide a modest but discernible improvement in the prediction of small-scale flow structures and maintain better consistency with the fundamental equations governing the system when compared to a purely data-driven approach.

3d Mapping Of Stiffness Evolution Of Hardening Concrete With Saps Using Elastic Wave Tomography

Phenomena occurring during the delicate phase of concrete curing can have a strong influence on the final mechanical properties. Therefore, monitoring the changes during hydration can provide meaningful information on the material properties. Lately, non-destructive techniques have received great attention for monitoring earlyage concrete. This paper aims to assess the ultrasonic velocity and stiffness development of hardening concrete during various curing stages using the Elastic Wave Tomography (EWT) technique. The monitoring of the curing process starts as soon as seven hours after casting and lasts up to seventy hours. A three-dimensional (3D) wave velocity map is created, and conventional concrete is compared to concrete containing SuperAbsorbent Polymers (SAPs), a novel admixture used for shrinkage mitigation by providing internal curing in the cementitious matrix. However, SAPs have been proven to reduce compressive strength when added to concrete, due to the increased porosity they induce. This porosity may also result in the reduction of the wave velocity. However, the internal curing provided by the SAPs can promote the formation of new hydration products in the matrix and thus (partly) compensate for the strength loss making the uniformity of the internal curing another important point of concern. EWT can provide global information on the homogeneity of the influence of the SAPs in the cementitious matrix as opposed to the wave velocity of a single wave path that is usually examined in practice. In addition, the determination of the early-age stiffness evolution can be connected to the final mechanical properties of the material. The dynamic Young’s Modulus is calculated and compared to the static Young’s modulus at 28 days. Predictions towards the static Young’s modulus are also made, showing good agreement.

4D particle tracking velocimetry of an undular hydraulic jump

Undular hydraulic jumps are characterized by a three-dimensional flow field due to shock waves generated near the sidewalls. Basic flow properties have been described in the literature with experimental data, mostly gathered with classical sensors which provide local information only. A continuous description of the 3D flow field is still missing. In this study, instantaneous and three-dimensional velocity data in an undular jump were obtained between the inflow section and second wave crest using a volumetric particle tracking velocimetry method with high sample rates. A special feature of the tracking algorithm is its capability to process images with very high particle density yielding a highly resolved Lagrangian description of the flow. Velocity fields, turbulent kinetic energy, dissipation rates, Reynolds stresses and turbulent scales are presented for a volume of 10 cm width in cross-direction. Some differences were found when compared to data obtained with an intrusive acoustic Doppler velocimeter.

Distinguishing the XUV-induced Coulomb explosion dynamics of iodobenzene using covariance analysis

Abstract The primary and secondary fragmentation dynamics of iodobenzene following its ionization at 120 eV were determined using three-dimensional velocity map imaging and covariance analysis. Site-selective iodine 4d ionization was used to populate a range of excited polycationic parent states, which primarily broke apart at the carbon-iodine bond to produce I+ with phenyl or phenyl-like cations (CnHx + or CnHx 2+, with n = 1-6 and x = 1-5). The molecular products were produced with varying degrees of internal excitation and dehydrogenation, leading to stable and unstable outcomes. This further allowed the secondary dynamics of C6Hx 2+ intermediates to be distinguished using native-frame covariance analysis, which isolated these processes in their own centre-of-mass reference frames. The mass resolution of the imaging mass spectrometer used for these measurements enabled the primary and secondary reaction channels to be specified at the level of individual hydrogen atoms, demonstrating the ability of covariance analysis to comprehensively measure the competing fragmentation channels of aryl cations, including those involving intermediate steps.

Design of a Contactless Inductive Flow Tomography system for a large Rayleigh–Bénard convection cell with aspect ratio [formula omitted]

Contactless Inductive Flow Tomography (CIFT) is a flow measurement technique that is able to reconstruct the time-dependent three-dimensional velocity field in electrically conducting fluids, e.g., liquid metals, from magnetic field measurements. The paper describes the design of a specific CIFT measurement set-up for flow studies in liquid metal Rayleigh–Bénard convection (RBC) in a large cylinder of aspect ratio (diameter/height) of Γ=0.5 filled with the ternary alloy GaInSn as model fluid. An optimized configuration for the CIFT excitation system and magnetic field sensor layout under consideration of the specific requirements for the application in turbulent RBC is determined by numerical simulations. The new experimental CIFT-RBC system resulting from the design process is constructed and a preliminary experiment at a Rayleigh number of Ra=2.13×107 and a Prandtl number of Pr=0.03 is performed and evaluated.

Superresolution and analysis of three-dimensional velocity fields of underexpanded jets in different screech modes

Time-resolved (TR), three-dimensional (3D) velocity fields of screeching, underexpanded jets are estimated using non-time-resolved particle image velocimetry and simultaneous TR microphone measurements. Specifically, we aim to reconstruct TR 3D velocity fluctuation fields associated with the A2, B, and C modes of a screeching jet using a linear regression model and to analyze screech dynamics of these modes. The linear regression model is constructed on the basis of a linear relationship between the velocity and acoustic fields. Three nozzle pressure ratios (NPRs) of 2.30, 2.97, and 3.40 are employed. The dominant azimuthal modes for three cases are investigated using azimuthal Fourier coefficients of the acoustic data obtained by the azimuthal array of eight microphones placed near the nozzle exit. The dominant azimuthal modes at NPRs of 2.30, 2.97, and 3.40 are m=0, 1, and 1, respectively. The first two proper orthogonal decomposition (POD) modes in these azimuthal modes are dominant at all NPRs and are associated with screech. 3D velocity fluctuation fields associated with screech are reconstructed from these leading POD modes of the acoustic data. The reconstructed 3D velocity fluctuation fields at NPRs of 2.97 and 3.40 exhibit two helical structures with opposite rotation directions. The present results demonstrate that, in the B mode, the flapping structure exhibits random clockwise and counterclockwise rotations over an extended time domain, while maintaining a consistent direction within short time domains. In addition, in the C mode, two helical structures with opposite rotation directions, as well as the flapping structure, are observed. Published by the American Physical Society 2024

Flow field characteristic in a novel cyclone-granular bed coupled separator

The three-dimensional flow field in a novel cyclone-granular bed coupled separator was discussed experimentally with a five-hole probe system. The airflow behaviors in the annular space, separation space, and central outlet were addressed. Several significant phenomena (the squeezing effect, the top flow loop, and the rectification effect) were observed and analyzed. By comparing the three-dimensional velocity distribution in the coupled separator with different structure parameters (the coupling space index, rc=0.37/0.44), the combined effect between the two efficient gas purifiers was demonstrated and the importance of the tangential velocity was clarified. For this purpose, the equations for the tangential velocity at four circumferential positions were fitted using regression analysis with a wide array of experimental data and effectively characterized prior experimental outcomes.

Kinetic energy and speed powers vn of a heavy quark inside S wave and P wave heavy-light mesons

The average values of the powers of |q→|n¯≡qn and |v→|n¯≡vn are commonly used physical quantities, where q→ and v→ are the three-dimensional momentum and velocity of a quark inside a meson, respectively. For example, the average kinetic energy μπ2=q2 is an important quantity in the heavy quark effective theory, and the expansion of vn is commonly used in the nonrelativistic quantum chromodynamics. In this paper, based on the instantaneous Bethe-Salpeter equation method, we calculate the average values qn and vn (n=1, 2, 3, 4) of a heavy quark inside S wave and P wave heavy-light mesons. We obtain the kinetic energy μπ2=0.455 GeV2 for the B meson, which is consistent with the experimental result 0.464±0.076 GeV2. For the Bs, D, and Ds mesons, the μπ2 are 0.530, 0.317, and 0.369 GeV2, respectively, and v2=0.0185, 0.0215, 0.121, and 0.140 for B, Bs, D, and Ds, respectively. We obtain some relationships, for example, q0−n(mS)≈q1−n(mS), q0+n(mP)≈q1+′n(mP′)>q1+n(mP)≈q2+n(mP), and qn(mS)<qn(mP) (m=1, 2, 3), etc. Published by the American Physical Society 2024