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Principles and Basic Modes of Atomic Force Microscopy
Published in Cai Shen, Atomic Force Microscopy for Energy Research, 2022
Anyang Cui, Menghan Deng, Yan Ye, Xiang Wang, Zhigao Hu
In general, the vertical resolution of AFM is described as the minimum change of step height that can be measured on the surface. It is primarily restricted by noise floor of the AFM system, including vertical cantilever deflection noise, z scanner noise, seismic noise, and environmental acoustic. Being in a quiet environment and implementing appropriate seismic isolation can be helpful for reducing the environmental acoustic and seismic noise. As for the vertical deflection noise, it consists of the detector noise and the thermal noise of the deflection detection system. The source of these noises is statistically independent of each other, as shown below: δA≈δz=δzth2+δzdet2
Seismic measurements to recognize rock mass damaging induced by recurrent vibrations
Published in Vladimir Litvinenko, EUROCK2018: Geomechanics and Geodynamics of Rock Masses, 2018
Danilo D’ Angió, Roberto Iannucci, Luca Lenti, Salvatore Martino, Antonella Paciello
Rock-slides and rock-falls represent one of the most hazardous natural events because of the short time available for taking actions in case of exposed infrastructures due to their rapid evolution as well as their hardly detectable precursors. A recent approach devoted to risk prevention consists in performing ambient vibration studies on potentially unstable jointed rock masses (Got et al., 2010; Levy et al., 2010; Bottelin et al., 2013), in order to detect irreversible changes in vibrational behavior that can be related to microcracking, i.e. the generation of new joints at the rock mass scale (Eberhardt et al., 2004; Stead et al., 2006). Seismic noise is influenced by several factors, both natural (earthquakes, rainfalls, wind speed and direction, air and rock mass temperature) and anthropic (car traffic, quarry activities). In case of rock masses located close to railways or highways, an important contribution to ambient vibration is provided by recurrent and often frequent solicitations generated by trains transit.
Multidisciplinary monitoring of progressive failure processes in brittle rock slopes
Published in Xia-Ting Feng, Rock Mechanics and Engineering, 2017
Simon Loew, Valentin Gischig, Franziska Glueer, Reto Seifert, Jeffrey Moore
Ambient noise monitoring differs from the aforementioned methods that rely on seismic signal detection, because it focuses on the noise characteristics between signals. For this application, the wave field ideally is not recorded in a triggered but in continuous mode. It relies on the assumption that seismic noise mostly contains wave field components generated at large distances from the site, e.g. by oceanic wave-shore interaction, meteorological forcing, anthropogenic noise. These waves travel as plane waves vertically toward the ground surface if originating from large distances, and should produce similar noise characteristics at neighboring seismic stations unless the local rock mass conditions are the same. Hence, differences in these ambient noise characteristics may indicate local disturbances to the rock mass.
Seismic noise to public health signal: investigating the effects of pandemic guidance in Mexico
Published in Tapuya: Latin American Science, Technology and Society, 2022
Abril Saldaña-Tejeda, Xyoli Pérez-Campos, Elizabeth Reddy
Seismographs record ground motion. Seismologists are mainly interested in those vibrations generated by earthquakes; however, the seismic record contains vibrations from other origins, which are referred to as seismic “noise” – a term used to describe data that do not pertain to the “signals” related to ground motion that seismologists are often interested in studying. Possible sources for this “noise” include movement near instruments. This might include pedestrians, moving vehicles, or machinery in operation. To avoid collecting noise data along with the data about ground motion that they can put to use, seismologists often site instruments in places that can be somewhat isolated from human activity. However, this is not always possible. Data about the ground motion in cities (particularly in uniquely sensitive cities like Mexico City) might be unavailable to seismologists if they simply refuse to put instruments in highly populated areas. For this reason, many seismic networks include a few instruments in urban sites along with others thoroughly remote from human activity. Furthermore, The world changes around seismic stations, some once-remote instruments are now in populated places. These compromises and population changes make the seismic analysis presented here possible.
Development of empirical relationship between the observed and the estimated ground acceleration values of small to moderate earthquakes in northwest (Gujarat) and northeast (NE) regions of India
Published in Geomatics, Natural Hazards and Risk, 2022
Pallabee Choudhury, Ketan Singha Roy, Charu Kamra, Sumer Chopra
It is necessary to mention here that there might be uncertainties derived from observations as well as estimation that could give rise to bias to the results. We need to identify such error sources to achieve optimal quality control, data analysis, and interpretation. One such source could be clipped seismic waveforms. The seismic waveforms would be clipped when the amplitude exceeds the upper-limit dynamic range of the seismometer. Clipped waveforms are typically assumed not useful and need to be discarded as these will not present the actual amplitude. Either during quality check, we need to reject such waveforms, or the clipped seismic waveforms may be restored (Zhang et al. 2016). In addition, seismic signals are occasionally masked by seismic noise. One of the main issues in any study that involves seismic data is to ensure high signal-to-noise (SNR) ratio or to improve SNR by applying proper ways of data acquisition and processing (Bormann and Wielandt 2013). In particular, more attention on data from stations established on soft soils is needed, as those stations tend to be noisier. One of the sources of uncertainties in the estimation of the accelerations could be underestimation. Accelerograms have been computed from the seismograms by derivation, using the Fourier transformation and it may filter out the high frequency of the corresponding seismogram. Nevertheless, the recorded accelerograms may have a greater abundance of high frequency energy than the derived one. This is what we observe at TURA and GTK stations in NE India.