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Geoscientific Instrumentation, Methods and Data Systems An interactive open-access journal of the European Geosciences Union

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Geosci. Instrum. Method. Data Syst., 6, 199-207, 2017
http://www.geosci-instrum-method-data-syst.net/6/199/2017/
doi:10.5194/gi-6-199-2017
© Author(s) 2017. This work is distributed
under the Creative Commons Attribution 3.0 License.
Research article
19 Apr 2017
A low-cost acoustic permeameter
Stephen A. Drake1, John S. Selker2, and Chad W. Higgins2 1CEOAS, Oregon State University, Corvallis, OR 97333, USA
2BEE, Oregon State University, Corvallis, OR 97333, USA
Abstract. Intrinsic permeability is an important parameter that regulates air exchange through porous media such as snow. Standard methods of measuring snow permeability are inconvenient to perform outdoors, are fraught with sampling errors, and require specialized equipment, while bringing intact samples back to the laboratory is also challenging. To address these issues, we designed, built, and tested a low-cost acoustic permeameter that allows computation of volume-averaged intrinsic permeability for a homogenous medium. In this paper, we validate acoustically derived permeability of homogenous, reticulated foam samples by comparison with results derived using a standard flow-through permeameter. Acoustic permeameter elements were designed for use in snow, but the measurement methods are not snow-specific. The electronic components – consisting of a signal generator, amplifier, speaker, microphone, and oscilloscope – are inexpensive and easily obtainable. The system is suitable for outdoor use when it is not precipitating, but the electrical components require protection from the elements in inclement weather. The permeameter can be operated with a microphone either internally mounted or buried a known depth in the medium. The calibration method depends on choice of microphone positioning. For an externally located microphone, calibration was based on a low-frequency approximation applied at 500 Hz that provided an estimate of both intrinsic permeability and tortuosity. The low-frequency approximation that we used is valid up to 2 kHz, but we chose 500 Hz because data reproducibility was maximized at this frequency. For an internally mounted microphone, calibration was based on attenuation at 50 Hz and returned only intrinsic permeability. We found that 50 Hz corresponded to a wavelength that minimized resonance frequencies in the acoustic tube and was also within the response limitations of the microphone. We used reticulated foam of known permeability (ranging from 2 × 10−7 to 3 × 10−9 m2) and estimated tortuosity of 1.05 to validate both methods. For the externally mounted microphone the mean normalized standard deviation was 6 % for permeability and 2 % for tortuosity. The mean relative error from known measurements was 17 % for permeability and 2 % for tortuosity. For the internally mounted microphone the mean normalized standard deviation for permeability was 10 % and the relative error was also 10 %. Permeability determination for an externally mounted microphone is less sensitive to environmental noise than is the internally mounted microphone and is therefore the recommended method. The approximation using the internally mounted microphone was developed as an alternative for circumstances in which placing the microphone in the medium was not feasible. Environmental noise degrades precision of both methods and is recognizable as increased scatter for replicate data points.

Citation: Drake, S. A., Selker, J. S., and Higgins, C. W.: A low-cost acoustic permeameter, Geosci. Instrum. Method. Data Syst., 6, 199-207, doi:10.5194/gi-6-199-2017, 2017.
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Short summary
Intrinsic permeability of snow is an important parameter that regulates snow–atmosphere exchange. Current permeability measurements require specialized equipment for acquisition in the field and have increased variability with increasing snow heterogeneity. To facilitate a field-based, volume-averaged measure of permeability, we designed and assembled an acoustic permeameter. When using reticulated foam samples of known permeability, the mean relative error from known values was less than 20 %.
Intrinsic permeability of snow is an important parameter that regulates snow–atmosphere...
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