Mining Safety and Sustainability I

Safety and sustainability are becoming ever bigger challenges for the mining industry with the increasing depth of mining. It is of great significance to reduce the disaster risk of mining accidents, enhance the safety of mining operations, and improve the efficiency and sustainability of developmen...

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格式: Online
語言:英语
出版: MDPI - Multidisciplinary Digital Publishing Institute 2022
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AMD
SEM
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collection Directory of Open Access Books
description Safety and sustainability are becoming ever bigger challenges for the mining industry with the increasing depth of mining. It is of great significance to reduce the disaster risk of mining accidents, enhance the safety of mining operations, and improve the efficiency and sustainability of development of mineral resource. This book provides a platform to present new research and recent advances in the safety and sustainability of mining. More specifically, Mining Safety and Sustainability presents recent theoretical and experimental studies with a focus on safety mining, green mining, intelligent mining and mines, sustainable development, risk management of mines, ecological restoration of mines, mining methods and technologies, and damage monitoring and prediction. It will be further helpful to provide theoretical support and technical support for guiding the normative, green, safe, and sustainable development of the mining industry.
format Online
id doab-20.500.12854ir-93171
institution Directory of Open Access Books
language eng
publishDate 2022
publishDateRange 2022
publishDateSort 2022
publisher MDPI - Multidisciplinary Digital Publishing Institute
publisherStr MDPI - Multidisciplinary Digital Publishing Institute
record_format ojs
spelling doab-20.500.12854ir-931712024-04-09T23:15:59Z Mining Safety and Sustainability I Dong, Longjun Zhao, Yanlin Chen, Wenxue top-coal caving mining process parameters decision model BP neural network similaritysimulation test time-dependent cohesion traction force deep-sea sediment tracked miner rheology cemented paste backfill curing conditions mechanical properties mathematical strength model AMD phytoremediation sulfate hydroponic experiment wetland plants ecological pollution tailings dam safety factor quantitative evaluation dynamic weight comprehensivediagnosis of health : rock formations surface subsidence law surface subsidence process 3D test device 3Dlaser scanning mine ventilation network wind speed sensors distribution air volume reconstruction independent cut set surface subsidence probability integration loess donga superimposed calculation additional displacement of slope mining slip : mining water hazard microseismic monitoring intelligent recognition feature extraction support vector machine classification model freeze–thaw cycles tailings mechanical behavior SEM MIP thick aeolian sand shallow buried thick seam overburden failure ground damage numerical simulation rock mechanics cyclic impact chemical corrosion axial compression strength degradation pipe transportation system test pressure loss random forest algorithm filling-aided design vibration signals neural network drilling state identification algorithm drilling depth monitoring-while-drilling method   thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology Safety and sustainability are becoming ever bigger challenges for the mining industry with the increasing depth of mining. It is of great significance to reduce the disaster risk of mining accidents, enhance the safety of mining operations, and improve the efficiency and sustainability of development of mineral resource. This book provides a platform to present new research and recent advances in the safety and sustainability of mining. More specifically, Mining Safety and Sustainability presents recent theoretical and experimental studies with a focus on safety mining, green mining, intelligent mining and mines, sustainable development, risk management of mines, ecological restoration of mines, mining methods and technologies, and damage monitoring and prediction. It will be further helpful to provide theoretical support and technical support for guiding the normative, green, safe, and sustainable development of the mining industry. 2022-10-25T09:00:17Z 2022-10-25T09:00:17Z 2022 book ONIX_20221025_9783036546872_25 9783036546872 9783036546889 https://directory.doabooks.org/handle/20.500.12854/93171 eng application/octet-stream Attribution 4.0 International https://mdpi.com/books/pdfview/topic/6067 https://mdpi.com/books/pdfview/topic/6067 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-0365-4688-9 10.3390/books978-3-0365-4688-9 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783036546872 9783036546889 348 open access
spellingShingle top-coal caving mining
process parameters
decision model
BP neural network
similaritysimulation test
time-dependent cohesion
traction force
deep-sea sediment
tracked miner
rheology
cemented paste backfill
curing conditions
mechanical properties
mathematical strength model
AMD
phytoremediation
sulfate
hydroponic experiment
wetland plants
ecological pollution
tailings dam
safety factor
quantitative evaluation
dynamic weight
comprehensivediagnosis of health
: rock formations
surface subsidence law
surface subsidence process
3D test device
3Dlaser scanning
mine ventilation network
wind speed sensors distribution
air volume reconstruction
independent cut set
surface subsidence
probability integration
loess donga
superimposed calculation
additional displacement of slope mining slip
: mining water hazard
microseismic monitoring
intelligent recognition
feature extraction
support vector machine
classification model
freeze–thaw cycles
tailings
mechanical behavior
SEM
MIP
thick aeolian sand
shallow buried thick seam
overburden failure
ground damage
numerical simulation
rock mechanics
cyclic impact
chemical corrosion
axial compression
strength degradation
pipe transportation system test
pressure loss
random forest algorithm
filling-aided design
vibration signals
neural network
drilling state identification algorithm
drilling depth
monitoring-while-drilling method
 
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
Mining Safety and Sustainability I
title Mining Safety and Sustainability I
title_full Mining Safety and Sustainability I
title_fullStr Mining Safety and Sustainability I
title_full_unstemmed Mining Safety and Sustainability I
title_short Mining Safety and Sustainability I
title_sort mining safety and sustainability i
topic top-coal caving mining
process parameters
decision model
BP neural network
similaritysimulation test
time-dependent cohesion
traction force
deep-sea sediment
tracked miner
rheology
cemented paste backfill
curing conditions
mechanical properties
mathematical strength model
AMD
phytoremediation
sulfate
hydroponic experiment
wetland plants
ecological pollution
tailings dam
safety factor
quantitative evaluation
dynamic weight
comprehensivediagnosis of health
: rock formations
surface subsidence law
surface subsidence process
3D test device
3Dlaser scanning
mine ventilation network
wind speed sensors distribution
air volume reconstruction
independent cut set
surface subsidence
probability integration
loess donga
superimposed calculation
additional displacement of slope mining slip
: mining water hazard
microseismic monitoring
intelligent recognition
feature extraction
support vector machine
classification model
freeze–thaw cycles
tailings
mechanical behavior
SEM
MIP
thick aeolian sand
shallow buried thick seam
overburden failure
ground damage
numerical simulation
rock mechanics
cyclic impact
chemical corrosion
axial compression
strength degradation
pipe transportation system test
pressure loss
random forest algorithm
filling-aided design
vibration signals
neural network
drilling state identification algorithm
drilling depth
monitoring-while-drilling method
 
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
topic_facet top-coal caving mining
process parameters
decision model
BP neural network
similaritysimulation test
time-dependent cohesion
traction force
deep-sea sediment
tracked miner
rheology
cemented paste backfill
curing conditions
mechanical properties
mathematical strength model
AMD
phytoremediation
sulfate
hydroponic experiment
wetland plants
ecological pollution
tailings dam
safety factor
quantitative evaluation
dynamic weight
comprehensivediagnosis of health
: rock formations
surface subsidence law
surface subsidence process
3D test device
3Dlaser scanning
mine ventilation network
wind speed sensors distribution
air volume reconstruction
independent cut set
surface subsidence
probability integration
loess donga
superimposed calculation
additional displacement of slope mining slip
: mining water hazard
microseismic monitoring
intelligent recognition
feature extraction
support vector machine
classification model
freeze–thaw cycles
tailings
mechanical behavior
SEM
MIP
thick aeolian sand
shallow buried thick seam
overburden failure
ground damage
numerical simulation
rock mechanics
cyclic impact
chemical corrosion
axial compression
strength degradation
pipe transportation system test
pressure loss
random forest algorithm
filling-aided design
vibration signals
neural network
drilling state identification algorithm
drilling depth
monitoring-while-drilling method
 
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
url ONIX_20221025_9783036546872_25