arXiv subjects

Dan Liberzon

Publications and source records attributed to Dan Liberzon.

8 recordsLinked to original sources

arXiv2024

Dataset of polarimetric images of mechanically generated water surface waves coupled with surface elevation records by wave gauges linear array

Effective spatio-temporal measurements of water surface elevation (water waves) in laboratory experiments are essential for scientific and engineering research. Existing techniques are often cumbersome, computationally heavy and generally suffer from limited wavenumber/frequency response. To address these challenges a novel method was developed, using polarization filter equipped camera as the main sensor and Machine Learning (ML) algorithms for data processing [1,2]. The developed method training and evaluation was based on in-house made supervised dataset. Here we present this supervised dataset of polarimetric images of the water surface coupled with the water surface elevation measurements made by a linear array of resistance-type wave gauges (WG). The water waves were mechanically generated in a laboratory waves basin, and the polarimetric images were captured under an artificial light source. Meticulous camera and WGs calibration and instruments synchronization supported high spatio-temporal resolution. The data set covers several wavefield conditions, from simple monochromatic wave trains of various steepness, to irregular wavefield of JONSWAP prescribed spectral shape and several wave breaking scenarios. The dataset contains measurements repeated in several camera positions relative to the wave field propagation direction.

physics.ao-ph↗

arXiv2024

Wave (from) Polarized Light Learning (WPLL) method: high resolution spatio-temporal measurements of water surface waves in laboratory setups

Effective spatio-temporal measurements of water surface elevation (water waves) in laboratory experiments are crucial for scientific and engineering research. Existing techniques are often cumbersome, computationally heavy and generally suffer from limitations in wavenumber/frequency response. To address these challenges, we propose Wave (from) Polarized Light Learning (WPLL), a learning based remote sensing method for laboratory implementation, capable of inferring surface elevation and slope maps in high resolution. The method uses the polarization properties of light reflected from the water surface. The WPLL uses a deep neural network (DNN) model that approximates the water surface slopes from the polarized light intensities. Once trained on simple monochromatic wave trains, the WPLL is capable of producing high-resolution and accurate 2D reconstruction of the water surface slopes and elevation in a variety of irregular wave fields. The method's robustness is demonstrated by showcasing its high wavenumber/frequency response, its ability to reconstruct wave fields propagating at arbitrary angles relative to the camera optical axis, and its computational efficiency. This developed methodology is an accurate and cost-effective near-real time remote sensing tool for laboratory water surface waves measurements, setting the path for upscaling to open sea application for research, monitoring, and short-time forecasting.

physics.ao-ph↗

arXiv2023

Laboratory investigation of nominally two-dimensional anabatic flow on symmetric double slopes

We investigated the dynamics of highly turbulent thermally driven anabatic (upslope) flow on a physical model inside a large water tank using particle image velocimetry (PIV) and a thermocouple grid. The results showed that the flow exhibited pronounced variations in velocity and temperature and, importantly, could not be accurately modeled as a two-dimensional quasi-steady flow. Five significant findings are presented to underscore the three-dimensional nature of the flow. Namely, the B-shaped mean velocity profiles, B-shaped turbulent flux profiles, synthetic streaks that revealed particles flowing perpendicular to the laser sheet, average vorticity maps revealing helical structure splitting, and identified vortices shooting away from the boundary towards the apex plume. Collectively, these findings offer novel insights into the flow behavior patterns of thermally driven complex terrain flows, which influence local weather and microclimates and are responsible for scalar transport, e.g., pollution.

physics.flu-dyn↗

arXiv2023

Wave-by-wave forecasts in directional seas using nonlinear dispersion corrections

We develop a new methodology for the deterministic forecasting of directional ocean surface waves, based on nonlinear frequency corrections. These frequency corrections can be pre-computed based on measured energy density spectra, and therefore come at no additional computational cost compared to linear theory. The nonlinear forecasting methodology is tested on highly-nonlinear, synthetically generated seas with a variety of values of average steepness and directional spreading, and shown to consistently outperform a linear forecast.

physics.ao-ph↗

arXiv2021

Next generation combined sonic-hotfilm anemometer: wind alignment and automated calibration procedure using deep learning

The study of naturally occurring turbulent flows requires ability to collect empirical data down to the fine scales. While hotwire anemometry offers such ability, the open field studies are uncommon due to the cumbersome calibration procedure and operational requirements of hotwire anemometry, e.g., constant ambient properties and steady flow conditions. The combo probe-the combined sonic-hotfilm anemometer developed and tested over the last decade-has demonstrated its ability to overcome this hurdle. The old-er generation had a limited wind alignment range of 120 degrees and the in-situ calibration procedure was human decision based. This study presents the next generation of the combo probe design, and the new fully automated in-situ calibration procedure implementing deep learning. The elegant new design now enables measurements of the incoming wind flow in a 360-degree range. The improved calibration procedure is shown to have the robustness necessary for operation in everchanging open field flow and environmental conditions. This is especially useful with diurnally changing environments or non-stationary measuring stations, i.e., probes placed on moving platforms like boats, drones, and weather balloons. Together, the updated design and the new calibration procedure, allow for continuous field measurements with minimal to no human interaction, enabling near real-time monitoring of fine-scale turbulent fluctuations. Integration of these probes will contribute toward generation of a large pool of field data to be collected to unravel the intricacies of all scales of turbulent flows occurring in natural setups.

physics.flu-dyn↗

arXiv2020

Automated identification and characterization method of turbulent bursting from single-point records of the velocity field

A new automated method capable of accurately identifying bursting periods in single-point turbulent velocity field records is presented. Manual selection of the method sensitivity (tau*) and threshold (eT) are necessary for effective discrimination between burst periods and the background turbulent flow fluctuations (burst-free periods). The flow characteristic used for identification is the normalized 'instantaneous' TKE dissipation rate levels, calculated using sliding window averaging. Use of the record root mean square and average values for normalization eliminates the need for definition of a physics-based flow-specific threshold. Instead, the suitable sensitivity range and the threshold parameters are selected based on preliminary examination of the velocity records. This, potentially, makes the method applicable for use across various flow fields, especially as it does not require resolving the burst-generation mechanism. The method performance is examined using a field obtained dataset of buoyancy driven turbulent boundary layer flow. Here, the selection of a two-fold (eT=2) increase is used and the sensitivity of the method is examined. Spectral shapes of non-bursting periods show distinguished similarity to those of the Kolmogorov theory, while the bursting period spectral shapes vary significantly. Low resolution records of temperature fluctuations were observed to exhibit a significant decrease in temperature (scalar) dissipation rate during bursting periods. Based on this observation and additional processing, a statistical examination of temperature (scalar) dissipation rate is presented along with a normalization procedure. Future examination of additional scalar variations, i.e. particulate matter and/or gaseous pollutant concentrations, in connection with turbulent bursting periods can assist in further understanding of bursting generation and scalar transfer processes.

physics.flu-dyn↗

arXiv2013

Lagrangian kinematics of steep waves up to the inception of a spilling breaker

Horizontal Lagrangian velocities and accelerations at the surface of steep water-waves are studied by Particle Tracking Velocimetry (PTV) for gradually increasing crest heights up to the inception of a spilling breaker. Localized steep waves are excited using wavemaker-generated Peregrine breather-type wave trains. Actual crest and phase velocities are estimated from video recorded sequences of the instantaneous wave shape as well as from surface elevation measurements by wave gauges. Effects of nonlinearity and spectral width on phase velocity, as well as relation between the phase velocity and crest propagation speed are discussed. The inception of a spilling breaker is associated with the horizontal velocity of water particles at the crest attaining that of the crest, thus confirming the kinematic criterion for inception of breaking.

physics.flu-dyn↗

arXiv2011

Initial Stages of Wind-Waves Evolution, Temporal vs. Spatial Cases

The video describes initial stages of spatial and temporal evolution of wind generated waves. This fluid dynamics video was created at Tel Aviv University small scale wind-wave flume as a part of an ongoing experimental program aimed at gaining better understanding of complex processes governing the excitation of water waves and their evolution in the presence of wind. Despite many decades of intense research mechanisms governing water waves' generation by wind and their evolution in space and time are still not fully understood.

physics.flu-dyn↗