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Last year we used an AUV (autonomous underwater vehicle) to collect bathymetry (depth) and sonar (bottom hardness and roughness) data for the lake.
Roughness data collected from SPS-5 experimental sites has a clustered longitudinal structure.
Rigorous assessments were employed to establish the form of the roughness data.
Comparison with surface roughness data from AFM showed a similar trend in roughness across the series of particles.
The estimation approach applies the Method of Moments to roughness data from several international field experiments and other published sources.
Roughness data were determined at different scales from 3D surfaces obtained using a stereoscopic reconstruction of SEM images.
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In the proposed method, the full three-dimensional contact geometry is reduced to a point contact in order to lower the computational cost and to reduce the amount of required input roughness-data.
In this article, we have presented a new approach to formulate a non-empirical scoring scale based on membrane roughness (Rrms) data obtained from atomic force microscopy.
The optimal smoothing model was achieved through adjusting the normalized smoothing factor, which is usually determined by using a trade-off value between model roughness and data misfit (Fig. 5a).
First, due to the lack of track beam road roughness test data, the simulation can only use the US road spectrum in the mean of grade A road roughness as ordinary excitation, it makes the measured values have certain discrepancy in the PC beam area compared with the simulation data, and it influences the superposition of acceleration at the finger-band area.
Channel width, velocity and roughness amplitude data were presented as mean ± SD.
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