10 research outputs found

    Sound parameters on acoustics agglomeration.

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    <p>Effect of frequency, intensity and residence time on agglomeration efficiency. (Reproduced from Liu et al. [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0178851#pone.0178851.ref096" target="_blank">96</a>] for fly ash with bi-modal characteristics).</p

    Filtration efficiency of MERV 8 and 13 filters.

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    <p>Relationship between filter efficiency and particle size [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0178851#pone.0178851.ref033" target="_blank">33</a>], including the size distributions of virus [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0178851#pone.0178851.ref152" target="_blank">152</a>], bacteria [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0178851#pone.0178851.ref153" target="_blank">153</a>,<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0178851#pone.0178851.ref154" target="_blank">154</a>] and fungi [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0178851#pone.0178851.ref151" target="_blank">151</a>,<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0178851#pone.0178851.ref155" target="_blank">155</a>].</p

    Orthokinetic and hydrodynamic mechanisms.

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    <p>Due to differential fluid and inertia forces, particles become entrained at different amplitudes and phase in the oscillations of an acoustic field. Consequently, the relative motions between the different sized particles result in collisions.</p

    Summary of relevant experimental works in acoustic agglomeration with reported performances.

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    <p>Summary of relevant experimental works in acoustic agglomeration with reported performances.</p

    Forces acting on fine particles (PM<sub>2.5</sub>) in an acoustics field.

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    <p>Forces acting on fine particles (PM<sub>2.5</sub>) in an acoustics field.</p

    Experimental results on the filtration efficiencies of MERV 11 and 13 filters with and without acoustic agglomeration pre-conditioning.

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    <p>Filtration efficiency is expressed as the percentage drop in particle number concentration before the agglomeration zone and after the filter. With acoustic pre-conditioning, the filtration efficiency of the MERV 11 filter is increased by about 10%, bringing its filtration efficiency closer to that of the MERV 13 filter without acoustic pre-conditioning.</p

    Schematic of experimental set-up.

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    <p>Experimental set-up simulating travelling airborne PM in an open-loop, draw-through wind tunnel (resembling a ventilation duct) with acoustic agglomeration pre-conditioning prior to a test filter that is typically used in ACMV systems.</p

    Filter properties [157] and computed fan power to overcome filter pressure drop in Eq (2), assuming an overall fan efficiency of 0.15.

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    <p>Filter properties [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0178851#pone.0178851.ref157" target="_blank">157</a>] and computed fan power to overcome filter pressure drop in Eq (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0178851#pone.0178851.e002" target="_blank">2</a>), assuming an overall fan efficiency of 0.15.</p

    Experimental results on the effect of acoustic agglomeration on particle size concentration.

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    <p>In the smaller size range, number concentration of particles in the range of 0.4 μm to 0.5 μm in diameter is reduced by almost 16%. In the intermediate size range of around 1 μm to 2.5 μm, we observe another drop in number concentration of 10%.</p

    Numerical investigation of spatially nonhomogeneous acoustic agglomeration using sectional algorithm

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    <p>In the simulation of acoustic agglomeration, the conventional temporal model assumes spatial homogeneity in aerosol properties and sound field, which is often not the case in real applications. In this article, we investigated the effects of spatial nonhomogeneity of sound field on the acoustic agglomeration process through a one-dimensional spatial sectional model. The spatial sectional model is validated against existing experimental data and results indicate lower requirements on the number of sections and better accuracy. Two typical cases of spatial nonhomogeneous acoustic agglomeration are studied by the established model. The first case involves acoustic agglomeration in a standing wave field with spatial alternation of acoustic kernels from nodes to antinodes. The good agreement between the simulation and experiments demonstrates the predictive capability of the present spatial sectional model for the standing-conditioned agglomeration. The second case incorporates sound attenuation in the particulate medium into acoustic agglomeration. Results indicate that sound attenuation can influence acoustic agglomeration significantly, particularly at high frequencies, and neglecting the effects of sound attenuation can cause overprediction of agglomeration rates. The present investigation demonstrates that the spatial sectional method is capable of simulating the spatially nonhomogeneous acoustic agglomeration with high computation efficiency and numerical robustness and the coupling with flow dynamics will be the goal of future work.</p> <p>Copyright © 2018 American Association for Aerosol Research</p
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