On the approach to modeling of the mechanical behavior of a fine grained material

2012 ◽  
Author(s):  
O. I. Bylya ◽  
K. Bhaskaran ◽  
P. V. Chistyakov ◽  
R. A. Vasin
Keyword(s):  
Mechanical Behavior ◽  
Fine Grained ◽  
Fine Grained Material

scholarly journals Potential Impacts of Future Climate Change Scenarios on Ground Subsidence

Water ◽  
2020 ◽  
Vol 12 (1) ◽  
pp. 219 ◽  
Author(s):  
Antonio-Juan Collados-Lara ◽  
David Pulido-Velazquez ◽  
Rosa María Mateos ◽  
Pablo Ezquerro
Keyword(s):  
Climate Change ◽  
Land Subsidence ◽  
Ground Subsidence ◽  
Lower Percentage ◽  
Future Climate Change ◽  
Climate Change Scenarios ◽  
Fine Grained ◽  
Fine Grained Material ◽  
The Impact

In this work, we developed a new method to assess the impact of climate change (CC) scenarios on land subsidence related to groundwater level depletion in detrital aquifers. The main goal of this work was to propose a parsimonious approach that could be applied for any case study. We also evaluated the methodology in a case study, the Vega de Granada aquifer (southern Spain). Historical subsidence rates were estimated using remote sensing techniques (differential interferometric synthetic aperture radar, DInSAR). Local CC scenarios were generated by applying a bias correction approach. An equifeasible ensemble of the generated projections from different climatic models was also proposed. A simple water balance approach was applied to assess CC impacts on lumped global drawdowns due to future potential rainfall recharge and pumping. CC impacts were propagated to drawdowns within piezometers by applying the global delta change observed with the lumped assessment. Regression models were employed to estimate the impacts of these drawdowns in terms of land subsidence, as well as to analyze the influence of the fine-grained material in the aquifer. The results showed that a more linear behavior was observed for the cases with lower percentage of fine-grained material. The mean increase of the maximum subsidence rates in the considered wells for the future horizon (2016–2045) and the Representative Concentration Pathway (RCP) scenario 8.5 was 54%. The main advantage of the proposed method is its applicability in cases with limited information. It is also appropriate for the study of wide areas to identify potential hot spots where more exhaustive analyses should be performed. The method will allow sustainable adaptation strategies in vulnerable areas during drought-critical periods to be assessed.

FG-LiquID

2021 ◽  
Vol 5 (3) ◽  
pp. 1-27
Author(s):  
Yumeng Liang ◽  
Anfu Zhou ◽  
Huanhuan Zhang ◽  
Xinzhe Wen ◽  
Huadong Ma
Keyword(s):  
Alcohol Concentration ◽  
Coarse Grained ◽  
Robust Identification ◽  
Fine Grained ◽  
Fresh Milk ◽  
Average Accuracy ◽  
Coarse Grained Material ◽  
Potential Applications ◽  
Fine Grained Material ◽  
The Difference

Contact-less liquid identification via wireless sensing has diverse potential applications in our daily life, such as identifying alcohol content in liquids, distinguishing spoiled and fresh milk, and even detecting water contamination. Recent works have verified the feasibility of utilizing mmWave radar to perform coarse-grained material identification, e.g., discriminating liquid and carpet. However, they do not fully exploit the sensing limits of mmWave in terms of fine-grained material classification. In this paper, we propose FG-LiquID, an accurate and robust system for fine-grained liquid identification. To achieve the desired fine granularity, FG-LiquID first focuses on the small but informative region of the mmWave spectrum, so as to extract the most discriminative features of liquids. Then we design a novel neural network, which uncovers and leverages the hidden signal patterns across multiple antennas on mmWave sensors. In this way, FG-LiquID learns to calibrate signals and finally eliminate the adverse effect of location interference caused by minor displacement/rotation of the liquid container, which ensures robust identification towards daily usage scenarios. Extensive experimental results using a custom-build prototype demonstrate that FG-LiquID can accurately distinguish 30 different liquids with an average accuracy of 97%, under 5 different scenarios. More importantly, it can discriminate quite similar liquids, such as liquors with the difference of only 1% alcohol concentration by volume.

Characterization of preserved primitive fine-grained material from the Jupiter family comet 81P/Wild 2 – A new link between comets and CP-IDPs

2014 ◽  
Vol 388 ◽  
pp. 367-373 ◽  
Author(s):  
Julien Stodolna ◽  
Zack Gainsforth ◽  
Anna L. Butterworth ◽  
Andrew J. Westphal
Keyword(s):  
Fine Grained ◽  
Fine Grained Material

Separation of fine-grained material from a pneumatic transport flow

1971 ◽  
Vol 7 (9) ◽  
pp. 678-681
Author(s):  
M. K. Pis'men ◽  
N. A. Kirichenko ◽  
V. G. Ermakov
Keyword(s):  
Pneumatic Transport ◽  
Fine Grained ◽  
Fine Grained Material ◽  
Transport Flow
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