MEMS surface microgravimetry for geotechnical surveying

Author(s):  
Zhijun Du ◽  
Arif Mustafazade ◽  
Yaoguo Li ◽  
Adrian Topham ◽  
Jeremy Lofts ◽  
...  

<p>Microgravity measurements have enabled a variety of geophysical surveying and monitoring applications including advance warning of natural hazards, slope stability monitoring, discovery of buried tunnels, pipework, and other utilities, identification of sinkholes and other natural voids, buried aquifers and in monitoring groundwater hydrology. In the civil engineering context, microgravity measurements can provide valuable information for construction projects or intervention activities by locating buried utilities, hazards or other features of relevance.</p><p>Disruptive MEMS gravity sensor technologies are poised to provide entirely new approaches for microgravity measurements in the form of portable sensors that could ultimately be mounted on remotely operated vehicles or drones, integrated into land-based distributed sensor networks, or deployed in shallow borehole configurations. Instruments based on these sensors could enable vector gravity measurements as well as full tensor gravity gradiometry.</p><p>Trials are ongoing of a single-axis MEMS surface module with a noise floor of 50 µGal/rt-Hz and a resolution of < 10 µGal while allowing for measurement over the entire +/- 1g dynamic range. This paper discusses the background and context for gravity imaging in geotechnical applications, forward modelling of case studies of relevance, and ongoing developments in the construction of a unique portable surface gravimeter.</p>

2005 ◽  
Vol 1 (3-4) ◽  
pp. 345-354 ◽  
Author(s):  
Dibyendu Chakrabarti ◽  
Subhamoy Maitra ◽  
Bimal Roy

Key pre-distribution is an important area of research in Distributed Sensor Networks (DSN). Two sensor nodes are considered connected for secure communication if they share one or more common secret key(s). It is important to analyse the largest subset of nodes in a DSN where each node is connected to every other node in that subset (i.e., the largest clique). This parameter (largest clique size) is important in terms of resiliency and capability towards efficient distributed computing in a DSN. In this paper, we concentrate on the schemes where the key pre-distribution strategies are based on transversal design and study the largest clique sizes. We show that merging of blocks to construct a node provides larger clique sizes than considering a block itself as a node in a transversal design.


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