arXiv subjects

Avshalom Offner

Publications and source records attributed to Avshalom Offner.

3 recordsLinked to original sources

arXiv2025

'Mic drop': on estimating the size of sub-mm droplets using a simple condenser microphone

The size distribution of aerosol droplets is a key parameter in a myriad of processes, and it is typically measured with optical aids (e.g., lasers or cameras) that require sophisticated calibration, thus making the measurement cost intensive. We developed a new method to indirectly measure the size of small droplets using off-the-shelf <\$1 electret microphones. In this method we exploit the natural oscillations that small droplets undergo after impacting a flat surface: by allowing droplets to land directly on a microphone diaphragm, we record the impact force they exert onto it and calculate the complex resonant frequencies of oscillations, from which their size can be inferred. To test this method, we recorded the impact signals of droplets of varying sizes generated by a pipette and extracted the resonant frequencies that characterize each signal. Various sources of uncertainty in the experiments led to a range of frequencies that can characterize each droplet size, and hence a data-driven approach was taken to estimate the size from each set of measured frequencies. We employed a simple setting of neural network and trained it on the frequencies we measured from impact of droplets of prescribed radius. The network was then able to predict the droplet radius in the test group with an average error of 2.7\% and a maximum of 8.6\% relative to the pipette nominal values. These results, achieved with a data set of only 320 measurements, demonstrate the potential for reliable size-distribution measurements via a simple and inexpensive method.

physics.flu-dyn↗

arXiv2022

A probabilistic framework for uncertainty quantification in positron emission particle tracking

Positron Emission Particle Tracking (PEPT) is an imaging method for the visualization of fluid motion, capable of reconstructing three-dimensional trajectories of small tracer particles suspended in nearly any medium, including fluids that are opaque or contained within opaque vessels. The particles are labeled radioactively, and their positions are reconstructed from the detection of pairs of back-to-back photons emitted by positron annihilation. Current reconstruction algorithms are heuristic and typically based on minimizing the distance between the particles and the so-called lines of response (LoRs) joining the detection points, while accounting for spurious LoRs generated by scattering. Here we develop a probabilistic framework for the Bayesian inference and uncertainty quantification of particle positions from PEPT data. We formulate a likelihood by describing the emission of photons and their noisy detection as a Poisson process in the space of LoRs. We derive formulas for the corresponding Poisson rate in the case of cylindrical detectors, accounting for both undetected and scattered photons. We illustrate the formulation by quantifying the uncertainty in the reconstruction of the position of a single particle on a circular path from data generated by state-of-the-art Monte Carlo simulations. The results show how the observation time $\Delta t$ can be chosen optimally to balance the need for a large number of LoRs with the requirement of small particle displacement imposed by the assumption that the particle is static over $\Delta t$. We further show how this assumption can be relaxed by inferring jointly the position and velocity of the particle, with clear benefits for the accuracy of the reconstruction.

physics.ins-det↗

arXiv2021

Airborne lifetime of respiratory droplets

We formulate a model for the dynamics of respiratory droplets and use it to study their airborne lifetime in turbulent air representative of indoor settings. This lifetime is a common metric to assess the risk of respiratory transmission of infectious diseases, with longer lifetime correlating with higher risk. We consider a simple momentum balance to calculate the droplets spread, accounting for their size evolution as they undergo vaporization via mass and energy balances. The model shows how an increase in relative humidity leads to higher droplet settling velocity, which shortens the lifetime of droplets and can therefore reduce the risk of transmission. Emulating indoor air turbulence using a stochastic process, we numerically calculate probability distributions for the lifetime of droplets, showing how an increase in the air turbulent velocity significantly enhances the range of lifetimes. The distributions reveal non-negligible probabilities for very long lifetimes, which potentially increase the risk of transmission.

physics.med-ph↗