Modeling of Lagrangian particles in turbulence boundary layer considering attached eddies: particle trajectories and concentration profiles

2021 ◽  
Author(s):  
Yu-Ying Huang ◽  
Christina W. Tsai
Keyword(s):  
Boundary Layer ◽  
Type A ◽  
Type B ◽  
Lagrangian Particle ◽  
Particle Trajectories ◽  
Particle Tracking Model ◽  
Proposed Model ◽  
Tracking Model ◽  
The Mean ◽  
Attached Eddies

<p>     Sediment particles in flow not only follow the mean drift, but also diffuse randomly due to turbulence. Owing to this property, Lagrangian particle trajectory is regarded as a stochastic process in this study. The proposed model based on Lagrangian methods will combine physical mechanisms and stochastic methods to simulate the particle motion, and uses the Brownian motion to describe the diffusion affected by turbulence. In turbulence boundary layer, there are eddies with different length and velocity scales. Eddies affect the motion of a particle, like the occurrences of ejection and sweep events. Among others, those extended to the wall, named attached eddies, are primarily responsible for most of the turbulent kinetic energy and Reynolds shear stresses. Perry & Marušić (1995) further divided the attached eddies into two types, those directly attached to the wall are called Type-A eddies while others not directly attached to the wall in the wake region are called Type-B eddies. The scales of Type-B eddies are affected by the distance away from the wall. Therefore, this study will combine the above-mentioned theory and the stochastic diffusion particle tracking model (SD-PTM) to simulate the Lagrangian sediment particles in turbulence boundary layer considering the effects of attached eddies.<br>     The SD-PTM which has been built on the Lagrangian scheme and derived from the Langevin equation has two main parts – the mean drift term and the turbulence term. The proposed model will separate the turbulence term into the effects by Type-A eddies and the effects by Type-B eddies, respectively. In the simulation results of sediment concentration in Tsai & Huang (2019), it can be found that when only Type-A eddies are considered, there were some discrepancies except for the near wall region within about 20% of the thickness of turbulence boundary layer. Hence, after taking into account for the effects of Type-B eddies in the proposed model, it can be expected that accuracy of the simulation results of Lagrangian particle trajectories and sediment concentrations can be improved throughout the whole boundary layer.</p><p>Keywords: Lagrangian methods, stochastic particle tracking model, attached eddies, Brownian motion, particle trajectories</p>

Transient Electrophoretic Motion of Charged Particles Through an L-Shaped Microchannel

2009 ◽  
Author(s):  
Ye Ai ◽  
Seungkyung Park ◽  
Junjie Zhu ◽  
Xiangchun Xuan ◽  
Ali Beskok ◽  
...  
Keyword(s):  
Particle Tracking ◽  
Particle Trajectory ◽  
Charged Particles ◽  
Quantitative Agreement ◽  
Uniform Electric Field ◽  
Lagrangian Particle Tracking ◽  
Lagrangian Particle ◽  
Outer Corner ◽  
Particle Tracking Model ◽  
Tracking Model

Direct current dielectrophoretic (DC-DEP) effects on the electrophoretic motion of charged polystyrene particles through an L-shaped microchannel were experimentally and numerically studied. In addition to the electrostatic and hydrodynamic forces, particles experience a negative DC-DEP force arising from the interaction between the dielectric particle and the induced spatially non-uniform electric field occurring around the corner of the L-shape microchannel. The latter force causes a cross-stream DEP motion so that the particle trajectory is shifted towards the outer corner of the turn. A two-dimensional (2D) Lagrangian particle tracking model taking into account the induced DC-DEP effect was used to predict the particle trajectory shift through the L-shaped channel, which achieves quantitative agreement with the experimental data.

The wind-induced bias of the Thies Laser Precipitation Monitor obtained using CFD and a Lagrangian particle tracking model

2021 ◽  
Author(s):  
Enrico Chinchella ◽  
Arianna Cauteruccio ◽  
Mattia Stagnaro ◽  
Luca G. Lanza
Keyword(s):  
Size Distribution ◽  
Particle Tracking ◽  
Drop Size ◽  
Shielding Effect ◽  
Lagrangian Particle Tracking ◽  
Measurement Instruments ◽  
Lagrangian Particle ◽  
Precipitation Measurement ◽  
Particle Tracking Model ◽  
Tracking Model

<p>Environmental sources of measurement biases affect the accuracy of non-catching (mostly contact-less) precipitation gauges (Lanza et al., 2021). Wind is among the most significant influencing variables, since instruments exposed to the wind generate strong airflow velocity gradients and turbulence near their sensing volume. Hydrometeor trajectories are diverted by the induced updraft/downdraft and acceleration near the instrument, affecting the measured particle size distribution, and leading to an over- or underestimation of the precipitation intensity. This bias is common to all precipitation measurement instruments, including traditional catching-type gauges, but is amplified in non-catching gauges due to their complex shapes and measuring principles. Wind also changes the velocity of the falling hydrometeors, introducing further potential biases since velocity is explicitly used by disdrometers (in combination with the hydrometeors size) to determine the type of precipitation and to discard outliers.</p><p>The present work focuses on the Thies laser precipitation monitor, which employs a laser beam to detect hydrometeors in fight. It has a complex, non-axisymmetric shape, due to the physical constraints of its measuring principle. To evaluate the effect of wind on liquid precipitation measurements, Computational Fluid Dynamics simulations were run, using OpenFOAM, together with a Lagrangian particle tracking model. The drag coefficient formulation validated by Cauteruccio et al. (2021) was implemented in the OpenFOAM package. Various drop diameters were considered (0.25, 0.5, 0.75 and from 1 to 8 mm in 1 mm increments), and for each drop size, the vertical and horizontal velocity components were set equal to the terminal velocity and the free-stream velocity, respectively. Nine angles of attack were considered, from 0° to 180°, in 22.5° increments. For each angle, five different wind speed values (2, 5, 10, 15 and 20 m/s) were simulated. Each combination was run twice, first using a constant velocity field (as if the instrument were transparent to the wind) to evaluate the sole shielding effect of the instrument body on the measurement section, and then using the effective velocity fields.</p><p>The data were then processed, using a suitable drop size distribution and for each velocity/angle/rainfall intensity combination the collection efficiency of the instrument was calculated. This work is funded as part of the activities of the EURAMET project 18NRM03 – “INCIPIT – Calibration and Accuracy of Non-Catching Instruments to measure liquid/solid atmospheric precipitation”.</p><p><strong>References:</strong></p><p>Lanza L.G., Merlone A., Cauteruccio A., Chinchella E., Stagnaro M., Dobre M., Garcia Izquierdo M.C., Nielsen J., Kjeldsen H., Roulet Y.A., Coppa G., Musacchio C., Bordianu C., 2021: Calibration of non-catching precipitation measurement instruments: a review. J. Meteorological Applications (submitted).</p><p>Cauteruccio A, Brambilla E, Stagnaro M, Lanza LG, Rocchi D, 2021: Wind tunnel validation of a particle tracking model to evaluate the wind-induced bias of precipitation measurements. Water Resour. Res., (conditionally accepted).</p>

Particle tracking model results suggest little lateral transport bias in inorganic and organic SST proxies in the Mediterranean Sea

2021 ◽  
Author(s):  
Addison Rice ◽  
Peter Nooteboom ◽  
Erik van Sebille ◽  
Francien Peterse ◽  
Martin Ziegler ◽  
...  
Keyword(s):  
Mediterranean Sea ◽  
Particle Tracking ◽  
Ocean Surface ◽  
Lateral Transport ◽  
Lagrangian Particle ◽  
Burial Site ◽  
Particle Tracking Model ◽  
Tracking Model ◽  
The Mediterranean ◽  
Paleoclimate Records

<p>Ocean currents can transport sinking particles hundreds of kilometers from their origin at the ocean surface to their burial location, resulting in an offset between sea surface temperatures (SSTs) above the burial site and the particle’s origin. Quantifying this offset in particles carrying molecules used in SST proxies can reduce uncertainty in paleoclimate reconstructions. In the Mediterranean Sea, where δ<sup>18</sup>O<sub>foraminifera</sub>, U<sup>K’</sup><sub>37</sub>- and TEX<sub>86</sub>-based SSTs can exhibit large offsets from surface conditions, understanding the possible contribution of lateral transport to proxy bias can provide additional insight when interpreting paleoclimate records.</p><p>In this study, Lagrangian particle tracking experiments are performed using the NEMO flow field to simulate transport and allow for a quantitative estimate of transport bias. The model determines the ocean surface origin locations of foraminifera and sedimentary particles that carry alkenones or GDGTs to compare with surface sediment datasets for δ<sup>18</sup>O<sub>foraminifera</sub>, U<sup>K’</sup><sub>37</sub> and TEX<sub>86</sub>, respectively. A range of sinking speeds appropriate for the export of organic matter (6, 12, 25, 50, 100, 250, and 500 m/d) is used in the model to represent different export modes (i.e., individual coccoliths, coccospheres, aggregates), where the three fastest sinking speeds can also represent sinking foraminifera. Results show that lateral transport bias is generally small within the Mediterranean Sea and cannot explain the large offsets in proxy-based SST reconstructions in this basin.</p>

scholarly journals Lagrangian Particle Dispersion Modeling of the Fumigation Process Using Large-Eddy Simulation

2005 ◽  
Vol 62 (6) ◽  
pp. 1932-1946 ◽  
Author(s):  
Si-Wan Kim ◽  
Chin-Hoh Moeng ◽  
Jeffrey C. Weil ◽  
Mary C. Barth
Keyword(s):  
Boundary Layer ◽  
Wind Speed ◽  
Convective Boundary Layer ◽  
Particle Dispersion ◽  
Lagrangian Particle ◽  
Convective Boundary ◽  
Eddy Simulation ◽  
Large Eddy ◽  
Entrainment Zone ◽  
The Mean

Abstract A Lagrangian particle dispersion model (LPDM) is used to study fumigation of pollutants in and above the entrainment zone into a growing convective boundary layer. Probability density functions of particle location with height and time are calculated from particle trajectories driven by the sum of the resolved-scale velocity from a large-eddy simulation (LES) model and the stochastic subgrid-scale (SGS) velocity. The crosswind-integrated concentration (CWIC) fields show good agreement with water tank experimental data. A comparison of the LPDM output with an Eulerian diffusion model output based on the same LES flow shows qualitative agreement with each other except that a greater overshoot maximum of the ground-level concentration occurs in the Eulerian model. The dimensionless CWICs near the surface for sources located above the entrainment zone collapse to a nearly universal curve provided that the profiles are time shifted, where the shift depends on the source heights. The dimensionless CWICs for sources located within the entrainment zone show a different behavior. Thus, fumigation from sources above the entrainment zone and within the entrainment zone should be treated separately. An examination of the application of Taylor’s translation hypothesis to the fumigation process showed the importance of using the mean boundary layer wind speed as a function of time rather than the initial mean boundary layer wind speed, because the mean boundary layer wind speed decreases as the simulation proceeds. The LPDM using LES is capable of accurately simulating fumigation of particles into the convective boundary layer. This technique provides more computationally efficient simulations than Eulerian models.

scholarly journals Repellent activities of dichloromethane extract of Allium sativum (garlic) (Liliaceae) against Hyalomma rufipes (Acari)

2016 ◽  
Vol 87 (1) ◽  
Author(s):  
Felix Nchu ◽  
Solomon R. Magano ◽  
Jacobus N. Eloff
Keyword(s):  
Avoidance Response ◽  
Allium Sativum ◽  
Type A ◽  
Test Solution ◽  
Hard Tick ◽  
Type B ◽  
Repellent Effect ◽  
The Mean ◽  
The Difference ◽  
Hyalomma Rufipes

Dichloromethane (DCM) extract of garlic (Allium sativum Linn.) bulbs was assessed for its repellent effect against the hard tick, Hyalomma rufipes (Acari: Ixodidae) using two tick behavioural bioassays; Type A and Type B repellency bioassays, under laboratory conditions. These bioassays exploit the questing behaviour of H. rufipes, a tick that in nature displays ambush strategy, seeking its host by climbing up on vegetation and attaching to a passing host. One hundred microlitres (100 µL) of the test solution containing DCM extract of garlic bulbs and DCM at concentrations of 0.35%, 0.7% or 1.4% w/v were evaluated. DCM only was used for control. Tick repellency increased significantly (R2 = 0.98) with increasing concentration (40.03% – 86.96%) yielding an EC50 of 0.45% w/v in Type B repellency bioassay. At concentration of 1.4% w/v, the DCM extract of garlic bulbs produced high repellency index of 87% (male ticks) and 87.5% (female ticks) in the Type A repellency bioassay. Only 4% avoidance of male ticks or female ticks was recorded in the Type B repellency bioassay. In the corresponding controls, the mean numbers of non-repelled male or female ticks were 80% and 41 males or 38 females of 50 ticks in the Type A and Type B repellency bioassays, respectively. The variations in the results could be attributed to the difference in tick repellent behaviours that were assessed by the two repellency bioassays; the Type A repellency bioassay assessed repellent effect of garlic extracts without discriminating between deterrence and avoidance whereas the Type B repellency bioassay only assessed avoidance response. Generally, DCM extract of garlic was repellent against H. rufipes, albeit weak tick repellency was obtained in the Type B repellency bioassay. Furthermore, this study established that the tick repellent activity of garlic extracts is predominantly by deterrence.

Computer Simulation of the Inclusion Removal Behavior in the Tundish and Model Evaluation

2014 ◽  
Vol 513-517 ◽  
pp. 4314-4318
Author(s):  
Yun Wang
Keyword(s):  
Computer Simulation ◽  
Random Walk ◽  
Particle Tracking ◽  
Random Walk Model ◽  
Motion Simulation ◽  
Lagrangian Particle Tracking ◽  
Lagrangian Particle ◽  
Inclusion Removal ◽  
Particle Tracking Model ◽  
Tracking Model

Computer simulation was applied to study the inclusion behavior in the tundish with Lagrangian particle tracking model including both the deterministic and random walk model. Comparing with the experiment result, the prediction result revealed that random walk model obtained more accuracy than the deterministic walk model by considering the effect of turbulence fluctuation on the inclusion movement. The accuracy of inclusion motion simulation was determined by the turbulence model and boundary condition.

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