We propose a primitive model of Janus ellipsoids that represents particles with an ellipsoidal core and two semisurfaces coded with dissimilar properties, for example, hydrophobicity and hydrophilicity, respectively. We investigate the effects of the aspect ratio on the self-assembly morphology and aggregation processes using Monte Carlo simulations. We also discuss certain differences between our results and those of earlier results for Janus spheres. In particular, we find that the size and structure of the aggregate can be controlled by the aspect ratio.
SUMMARY
Linear arrays are usually deployed for passive surface-wave investigations because of their high efficiency and convenience. In populated urban areas, it is almost impossible to set up a 2-D array in terms of the restriction from the existing infrastructures. The limited azimuthal coverage, however, lacks the ability to attenuate velocity overestimation caused by directional noise sources. We came up with a novel idea to compensate the azimuthal coverage by adding two more offline receivers to a conventional linear array, which is called pseudo-linear-array analysis of passive surface waves (PLAS). We used a beamforming algorithm to capture noise sources distribution and extract accurate dispersion curves. We used array response function to explain the superiority of the pseudo-linear array over the linear array and present the basic workflow of PLAS. Synthetic tests and field examples demonstrated the feasibility of PLAS to measure unbiased dispersion image. Comparison with mostly used passive surface wave methods (refraction microtremor, multichannel analysis of passive surface waves, spatial autocorrelation method, frequency–wavenumber analysis) suggested that PLAS can serve as an alternative passive surface wave method, especially in urban areas with restricted land accessibility and short-time acquisition demands.
Accurate understanding of near-surface structures of the solid Earth is challenging, especially in urban areas where active source seismic surveys are constrained and difficult to perform. The analysis of anthropogenic seismic noise provides an alternative way to image the shallow subsurface in urban environments. We present an application of using traffic noise with seismic interferometry to investigate near-surface structures in Hangzhou City, eastern China. Noise data were recorded by dense linear arrays with approximately 5 m spacing deployed along two crossing roads. We analyze the characteristics of traffic-induced noise using 36 hr continuous recordings. Coherent Rayleigh surface waves between 2 and 20 Hz are retrieved based on crosscorrelations within 1 hr time windows. Robust phase-velocity dispersion curves are extracted from virtual shot gathers using multichannel analysis of surface waves and coincide with the results from active seismic data, noise beamforming analysis, and measurements with the spatial autocorrelation method (SPAC). Shear-wave velocity profiles are derived for the top 100 m of the subsurface at the array locations. The estimated shear-wave velocities from traffic noise correspond to the velocities estimated from logging data. The 2D shear-wave velocity maps reveal different soil deposits and bedrock structures in the estuarine sedimentary area. The results demonstrate the accuracy and efficiency of delineating near-surface structures from traffic-induced noise, which has great potential for monitoring subsurface changes in urban areas.
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