Experimental study of thermophysical properties of coal gangue at initial stage of spontaneous combustion

2020 ◽  
Vol 400 ◽  
pp. 123251 ◽  
Author(s):  
Bei Li ◽  
Jia-Hua Wang ◽  
Ming-Shu Bi ◽  
Wei Gao ◽  
Chi-Min Shu
Keyword(s):  
Experimental Study ◽  
Thermophysical Properties ◽  
Spontaneous Combustion ◽  
Coal Gangue ◽  
Initial Stage

Experimental study of the effects of stacking modes on the spontaneous combustion of coal gangue

2019 ◽  
Vol 123 ◽  
pp. 39-47 ◽  
Author(s):  
Yuguo Wu ◽  
Xiaoyang Yu ◽  
Shengyong Hu ◽  
He Shao ◽  
Qi Liao ◽  
...  
Keyword(s):  
Experimental Study ◽  
Spontaneous Combustion ◽  
Coal Gangue ◽  
Spontaneous Combustion Of Coal

An Experimental Study of Thermophysical Properties for Quinary High-Entropy NiFeCoCrCu/Al Alloys

2016 ◽  
Vol 33 (11) ◽  
pp. 116102 ◽  
Author(s):  
Wei-Li Wang ◽  
Li-Jun Meng ◽  
Liu-Hui Li ◽  
Liang Hu ◽  
Kai Zhou ◽  
...  
Keyword(s):  
Experimental Study ◽  
Thermophysical Properties ◽  
Al Alloys ◽  
High Entropy

scholarly journals Simulating Heat Stress of Coal Gangue Spontaneous Combustion on Vegetation Using Alfalfa Leaf Water Content Spectral Features as Indicators

2021 ◽  
Vol 13 (13) ◽  
pp. 2634
Author(s):  
Qiyuan Wang ◽  
Yanling Zhao ◽  
Feifei Yang ◽  
Tao Liu ◽  
Wu Xiao ◽  
...  
Keyword(s):  
Heat Stress ◽  
Water Content ◽  
Spontaneous Combustion ◽  
Leaf Water ◽  
Coal Gangue ◽  
Leaf Water Content ◽  
Spectral Features ◽  
Lasso Regression ◽  
Stress Assessment ◽  
First Derivative

Vegetation heat-stress assessment in the reclamation areas of coal gangue dumps is of great significance in controlling spontaneous combustion; through a temperature gradient experiment, we collected leaf spectra and water content data on alfalfa. We then obtained the optimal spectral features of appropriate leaf water content indicators through time series analysis, correlation analysis, and Lasso regression analysis. A spectral feature-based long short-term memory (SF-LSTM) model is proposed to estimate alfalfa’s heat stress level; the live fuel moisture content (LFMC) varies significantly with time and has high regularity. Correlation analysis of the raw spectrum, first-derivative spectrum, spectral reflectance indices, and leaf water content data shows that LFMC and spectral data were the most strongly correlated. Combined with Lasso regression analysis, the optimal spectral features were the first-derivative spectral value at 1661 nm (abbreviated as FDS (1661)), RVI (1525,1771), DVI (1412,740), and NDVI (1447,1803). When the classification strategies were divided into three categories and the time sequence length of the spectral features was set to five consecutive monitoring dates, the SF-LSTM model had the highest accuracy in estimating the heat stress level in alfalfa; the results provide an important theoretical basis and technical support for vegetation heat-stress assessment in coal gangue dump reclamation areas.

scholarly journals Experimental study of the initial stage of oil spread on calm water.

1980 ◽  
Vol 13 (5) ◽  
pp. 417-419 ◽  
Author(s):  
TETSUO AKIYAMA ◽  
TAKAHIRO NISHIOKA ◽  
HIROMI BABA ◽  
SATORU MITSUMORI ◽  
Kozo KOIDE
Keyword(s):  
Experimental Study ◽  
Initial Stage ◽  
Calm Water
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